[A multi-measure analysis of the similarity, attraction, and compromise effects in multi-attribute decision making].

Science.gov (United States)

Tsuzuki, Takashi; Matsui, Hiroshi; Kikuchi, Manabu

2012-12-01

In multi-attribute decision making, the similarity, attraction, and compromise effects warrant specific investigation as they cause violations of principles in rational choice. In order to investigate these three effects simultaneously, we assigned 145 undergraduates to three context effect conditions. We requested them to solve the same 20 hypothetical purchase problems, each of which had three alternatives described along two attributes. We measured their choices, confidence ratings, and response times. We found that manipulating the third alternative had significant context effects for choice proportions and confidence ratings in all three conditions. Furthermore, the attraction effect was the most prominent with regard to choice proportions. In the compromise effect condition, although the choice proportion of the third alternative was high, the confidence rating was low and the response time was long. These results indicate that the relationship between choice proportions and confidence ratings requires further theoretical investigation. They also suggest that a combination of experimental and modeling studies is imperative to reveal the mechanisms underlying the context effects in multi-attribute, multi-alternative decision making.

A generalized measurement model to quantify health: the multi-attribute preference response model.

Science.gov (United States)

Krabbe, Paul F M

2013-01-01

After 40 years of deriving metric values for health status or health-related quality of life, the effective quantification of subjective health outcomes is still a challenge. Here, two of the best measurement tools, the discrete choice and the Rasch model, are combined to create a new model for deriving health values. First, existing techniques to value health states are briefly discussed followed by a reflection on the recent revival of interest in patients' experience with regard to their possible role in health measurement. Subsequently, three basic principles for valid health measurement are reviewed, namely unidimensionality, interval level, and invariance. In the main section, the basic operation of measurement is then discussed in the framework of probabilistic discrete choice analysis (random utility model) and the psychometric Rasch model. It is then shown how combining the main features of these two models yields an integrated measurement model, called the multi-attribute preference response (MAPR) model, which is introduced here. This new model transforms subjective individual rank data into a metric scale using responses from patients who have experienced certain health states. Its measurement mechanism largely prevents biases such as adaptation and coping. Several extensions of the MAPR model are presented. The MAPR model can be applied to a wide range of research problems. If extended with the self-selection of relevant health domains for the individual patient, this model will be more valid than existing valuation techniques.

Multi-person and multi-attribute design evaluations using evidential reasoning based on subjective safety and cost analyses

International Nuclear Information System (INIS)

Wang, J.; Yang, J.B.; Sen, P.

1996-01-01

This paper presents an approach for ranking proposed design options based on subjective safety and cost analyses. Hierarchical system safety analysis is carried out using fuzzy sets and evidential reasoning. This involves safety modelling by fuzzy sets at the bottom level of a hierarchy and safety synthesis by evidential reasoning at higher levels. Fuzzy sets are also used to model the cost incurred for each design option. An evidential reasoning approach is then employed to synthesise the estimates of safety and cost, which are made by multiple designers. The developed approach is capable of dealing with problems of multiple designers, multiple attributes and multiple design options to select the best design. Finally, a practical engineering example is presented to demonstrate the proposed multi-person and multi-attribute design selection approach

Efficiently Multi-User Searchable Encryption Scheme with Attribute Revocation and Grant for Cloud Storage.

Science.gov (United States)

Wang, Shangping; Zhang, Xiaoxue; Zhang, Yaling

2016-01-01

Cipher-policy attribute-based encryption (CP-ABE) focus on the problem of access control, and keyword-based searchable encryption scheme focus on the problem of finding the files that the user interested in the cloud storage quickly. To design a searchable and attribute-based encryption scheme is a new challenge. In this paper, we propose an efficiently multi-user searchable attribute-based encryption scheme with attribute revocation and grant for cloud storage. In the new scheme the attribute revocation and grant processes of users are delegated to proxy server. Our scheme supports multi attribute are revoked and granted simultaneously. Moreover, the keyword searchable function is achieved in our proposed scheme. The security of our proposed scheme is reduced to the bilinear Diffie-Hellman (BDH) assumption. Furthermore, the scheme is proven to be secure under the security model of indistinguishability against selective ciphertext-policy and chosen plaintext attack (IND-sCP-CPA). And our scheme is also of semantic security under indistinguishability against chosen keyword attack (IND-CKA) in the random oracle model.

Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection

Science.gov (United States)

Lin, Hui; Wang, Zhou-Jing

2017-01-01

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice. PMID:28926985

Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection.

Science.gov (United States)

Lin, Hui; Wang, Zhou-Jing

2017-09-17

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice.

Fuzzy Linguistic Optimization on Multi-Attribute Machining

Directory of Open Access Journals (Sweden)

Tian-Syung Lan

2010-06-01

Full Text Available Most existing multi-attribute optimization researches for the modern CNC (computer numerical control turning industry were either accomplished within certain manufacturing circumstances, or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme proposed is deemed to be necessary for the industry. In this paper, four parameters (cutting depth, feed rate, speed, tool nose runoff with three levels (low, medium, high are considered to optimize the multi-attribute (surface roughness, tool wear, and material removal rate finish turning. Through FAHP (Fuzzy Analytic Hierarchy Process with eighty intervals for each attribute, the weight of each attribute is evaluated from the paired comparison matrix constructed by the expert judgment. Additionally, twenty-seven fuzzy control rules using trapezoid membership function with respective to seventeen linguistic grades for each attribute are constructed. Considering thirty input and eighty output intervals, the defuzzifierion using center of gravity is thus completed. The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution is moreover utilized to integrate and evaluate the multiple machining attributes for the Taguchi experiment, and thus the optimum general deduction parameters can then be received. The confirmation experiment for optimum general deduction parameters is furthermore performed on an ECOCA-3807 CNC lathe. It is shown that the attributes from the fuzzy linguistic optimization parameters are all significantly advanced comparing to those from benchmark. This paper not only proposes a general deduction optimization scheme using orthogonal array, but also contributes the satisfactory fuzzy linguistic approach for multiple CNC turning attributes with profound insight.

A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes

Science.gov (United States)

Lu, Hongwei; Ren, Lixia; Chen, Yizhong; Tian, Peipei; Liu, Jia

2017-12-01

Due to the uncertainty (i.e., fuzziness, stochasticity and imprecision) existed simultaneously during the process for groundwater remediation, the accuracy of ranking results obtained by the traditional methods has been limited. This paper proposes a cloud model based multi-attribute decision making framework (CM-MADM) with Monte Carlo for the contaminated-groundwater remediation strategies selection. The cloud model is used to handle imprecise numerical quantities, which can describe the fuzziness and stochasticity of the information fully and precisely. In the proposed approach, the contaminated concentrations are aggregated via the backward cloud generator and the weights of attributes are calculated by employing the weight cloud module. A case study on the remedial alternative selection for a contaminated site suffering from a 1,1,1-trichloroethylene leakage problem in Shanghai, China is conducted to illustrate the efficiency and applicability of the developed approach. Totally, an attribute system which consists of ten attributes were used for evaluating each alternative through the developed method under uncertainty, including daily total pumping rate, total cost and cloud model based health risk. Results indicated that A14 was evaluated to be the most preferred alternative for the 5-year, A5 for the 10-year, A4 for the 15-year and A6 for the 20-year remediation.

Multi-Attribute Vickrey Auctions when Utility Functions are Unknown

NARCIS (Netherlands)

Máhr, T.; De Weerdt, M.M.

2006-01-01

Multi-attribute auctions allow negotiations over multiple attributes besides price. For example in task allocation, service providers can define their service by means of multiple attributes, such as quality of service, deadlines, or delay penalties. Auction mechanisms assume that the players have

Using qualitative methods for attribute development for discrete choice experiments: issues and recommendations.

Science.gov (United States)

Coast, Joanna; Al-Janabi, Hareth; Sutton, Eileen J; Horrocks, Susan A; Vosper, A Jane; Swancutt, Dawn R; Flynn, Terry N

2012-06-01

Attribute generation for discrete choice experiments (DCEs) is often poorly reported, and it is unclear whether this element of research is conducted rigorously. This paper explores issues associated with developing attributes for DCEs and contrasts different qualitative approaches. The paper draws on eight studies, four developed attributes for measures, and four developed attributes for more ad hoc policy questions. Issues that have become apparent through these studies include the following: the theoretical framework for random utility theory and the need for attributes that are neither too close to the latent construct nor too intrinsic to people's personality; the need to think about attribute development as a two-stage process involving conceptual development followed by refinement of language to convey the intended meaning; and the difficulty in resolving tensions inherent in the reductiveness of condensing complex and nuanced qualitative findings into precise terms. The comparison of alternative qualitative approaches suggests that the nature of data collection will depend both on the characteristics of the question (its sensitivity, for example) and the availability of existing qualitative information. An iterative, constant comparative approach to analysis is recommended. Finally, the paper provides a series of recommendations for improving the reporting of this element of DCE studies. Copyright © 2011 John Wiley & Sons, Ltd.

Methodology for assessing the effectiveness of countermeasures in rural settlements in the long term after the Chernobyl accident on the multi-attribute analysis basis

Energy Technology Data Exchange (ETDEWEB)

Panov, A.V.; Alexakhin, R.M. [Russian Institute of Agricultural Radiology and Agroecology, Obninsk (Russian Federation); Fesenko, S.V. [International Atomic Energy Agency (IAEA), Lab. (Austria)

2006-07-01

A methodology has been developed for the assessment of the effectiveness of countermeasures in agriculture based on a multi-attribute analysis of quantitative (radiological, economic, regulatory) and qualitative (social, psychological, technological) indicators characterizing their application. The method makes use of weight coefficients established for the countermeasures parameters with their subsequent comparison adjusted to a single scale. The method is realized with the P.R.I.M.E. Decision support system adapted for the task of countermeasures planning. The multi-attribute analysis of countermeasures effectiveness was made depending on the aspect of rehabilitation works considered: dose, financial or social. Presented are results from the analysis of effectiveness of individual countermeasures and most effective countermeasures and their combinations. Based on the multi attribute analysis data, rating of the most effective countermeasures and their combinations was performed. (authors)

Methodology for assessing the effectiveness of countermeasures in rural settlements in the long term after the Chernobyl accident on the multi-attribute analysis basis

International Nuclear Information System (INIS)

Panov, A.V.; Alexakhin, R.M.; Fesenko, S.V.

2006-01-01

A methodology has been developed for the assessment of the effectiveness of countermeasures in agriculture based on a multi-attribute analysis of quantitative (radiological, economic, regulatory) and qualitative (social, psychological, technological) indicators characterizing their application. The method makes use of weight coefficients established for the countermeasures parameters with their subsequent comparison adjusted to a single scale. The method is realized with the P.R.I.M.E. Decision support system adapted for the task of countermeasures planning. The multi-attribute analysis of countermeasures effectiveness was made depending on the aspect of rehabilitation works considered: dose, financial or social. Presented are results from the analysis of effectiveness of individual countermeasures and most effective countermeasures and their combinations. Based on the multi attribute analysis data, rating of the most effective countermeasures and their combinations was performed. (authors)

Multi-attribute Reverse Auction Design Based on Fuzzy Data Envelopment Analysis Approach

Directory of Open Access Journals (Sweden)

Deyan Chen

2017-08-01

Full Text Available Multi-attribute reverse auction is widely used for the procurements of enterprises or governments. To overcome the difficulty of identifying bidding attribute weight and score function of the buyer, the multi-round auction and bidding models with multiple winners are established based on fuzzy data envelopment analysis. The winner determination model of the buyer considers the integrated input-output efficiency of k winners. The bidding strategy of seller is divided into two parts: the first one estimates the weight of the ideal supplier that is thought to be the buyer’s preference; the second one is to calculate the weight of the test supplier which reflects the change trend of current weights and the seller’s weakness. The final predicted weight is the weighted sum of both. On the basis of known weight, the test supplier can improve his efficiency to increase the winning chance in the next round auction. Our models comprise crisp numbers and fuzzy numbers. Finally, a numerical example verifies the validity of the proposed models.

Visualizing multifactorial and multi-attribute effect sizes in linear mixed models with a view towards sensometrics

DEFF Research Database (Denmark)

and straightforward idea is to interpret effects relative to the residual error and to choose the proper effect size measure. For multi-attribute bar plots of F-statistics this amounts, in balanced settings, to a simple transformation of the bar heights to get them transformed into depicting what can be seen...... on a multifactorial sensory profile data set and compared to actual d-prime calculations based on ordinal regression modelling through the ordinal package. A generic ``plug-in'' implementation of the method is given in the SensMixed package, which again depends on the lmerTest package. We discuss and clarify the bias...

Multi-Attribute Decision-Making Based on Prioritized Aggregation Operator under Hesitant Intuitionistic Fuzzy Linguistic Environment

Directory of Open Access Journals (Sweden)

Peide Liu

2017-11-01

Full Text Available A hesitant intuitionistic fuzzy linguistic set (HIFLS that integrates both qualitative and quantitative evaluations is an extension of the linguistic set, intuitionistic fuzzy set (IFS, hesitant fuzzy set (HFS and hesitant intuitionistic fuzzy set (HIFS. It can describe the qualitative evaluation information given by the decision-makers (DMs and reflect their uncertainty. In this article, we defined some new operational laws and comparative method for HIFLSs. Then, based on these operations, we propose two prioritized aggregation (PA operators for HIFLSs: prioritized weighted averaging operator for HIFLSs (HIFLPWA and prioritized weighted geometric operator for HIFLSs (HIFLPWG. Based on these aggregation operators, an approach for multi-attribute decision-making (MADM is developed under the environment of HIFLSs. Finally, a practical example is given to show the practicality and effectiveness of the developed approach by comparing with the other representative methods.

An approach to multi-attribute utility analysis under parametric uncertainty

International Nuclear Information System (INIS)

Kelly, M.; Thorne, M.C.

2001-01-01

The techniques of cost-benefit analysis and multi-attribute analysis provide a useful basis for informing decisions in situations where a number of potentially conflicting opinions or interests need to be considered, and where there are a number of possible decisions that could be adopted. When the input data to such decision-making processes are uniquely specified, cost-benefit analysis and multi-attribute utility analysis provide unambiguous guidance on the preferred decision option. However, when the data are not uniquely specified, application and interpretation of these techniques is more complex. Herein, an approach to multi-attribute utility analysis (and hence, as a special case, cost-benefit analysis) when input data are subject to parametric uncertainty is presented. The approach is based on the use of a Monte Carlo technique, and has recently been applied to options for the remediation of former uranium mining liabilities in a number of Central and Eastern European States

Methods and Model Dependency of Extreme Event Attribution: The 2015 European Drought

Science.gov (United States)

Hauser, Mathias; Gudmundsson, Lukas; Orth, René; Jézéquel, Aglaé; Haustein, Karsten; Vautard, Robert; van Oldenborgh, Geert J.; Wilcox, Laura; Seneviratne, Sonia I.

2017-10-01

Science on the role of anthropogenic influence on extreme weather events, such as heatwaves or droughts, has evolved rapidly in the past years. The approach of "event attribution" compares the occurrence-probability of an event in the present, factual climate with its probability in a hypothetical, counterfactual climate without human-induced climate change. Several methods can be used for event attribution, based on climate model simulations and observations, and usually researchers only assess a subset of methods and data sources. Here, we explore the role of methodological choices for the attribution of the 2015 meteorological summer drought in Europe. We present contradicting conclusions on the relevance of human influence as a function of the chosen data source and event attribution methodology. Assessments using the maximum number of models and counterfactual climates with pre-industrial greenhouse gas concentrations point to an enhanced drought risk in Europe. However, other evaluations show contradictory evidence. These results highlight the need for a multi-model and multi-method framework in event attribution research, especially for events with a low signal-to-noise ratio and high model dependency such as regional droughts.

On multi-fingerprint detection and attribution of greenhouse gas- and aerosol forced climate change

Energy Technology Data Exchange (ETDEWEB)

Hegerl, G C [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Hasselmann, K [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Cubasch, U [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany); Mitchell, J F.B. [Hadley Centre for Climate Prediction and Research, Bracknell (United Kingdom). Meteorological Office; Roeckner, E [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Voss, R [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany); Waszkewitz, J [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany)

1996-07-01

A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single fingerprint, as applied in a previous paper by Hegerl et al. (1996), is optimal for detecting a significant climate change, the simultaneous use of several fingerprints allows one to investigate additionally the consistency between observations and model predicted climate change signals for competing candidate forcing mechanisms. Thus the multi-fingerprint method is a particularly useful technique for attributing an observed climate change to a proposed cause. Different model-predicted climate change signals are derived from three global warming simulations for the period 1880 to 2049. In one simulation, the forcing was by greenhouse gases only, while in the remaining two simulations the influence of aerosols was also included. The two dominant climate change signals derived from these simulations are optimized statistically by weighting the model-predicted climate change pattern towards low-noise directions. These optimized fingerprints are then applied to observed near surface temperature trends. The space-time structure of natural climate variability (needed to determine the signal-to-noise ratio) is estimated from several multi-century control simulations with different CGCMs and from instrumental data over the last 134 years. (orig.)

INTEGRATING VISUALIZATION AND MULTI-ATTRIBUTE UTILITY THEORY FOR ONLINE PRODUCT SELECTION

OpenAIRE

CHUREE THEETRANONT; PETER HADDAWY; DONYAPRUETH KRAIRIT

2007-01-01

Effectively selling products online is a challenging task. Today's product domains often contain a dizzying variety of brands and models with highly complex sets of characteristics. This paper addresses the problem of supporting product search and selection in domains containing large numbers of alternatives with complex sets of features. A number of online shopping websites provide product choice assistance by making direct use of Multi-Attribute Utility Theory (MAUT). While the MAUT approac...

Graduate Attribute Attainment in a Multi-Level Undergraduate Geography Course

Science.gov (United States)

Mager, Sarah; Spronken-Smith, Rachel

2014-01-01

We investigated students' perceptions of graduate attributes in a multi-level (second and third year) geography course. A case study with mixed methodology was employed, with data collected through focus groups and a survey. We found that undergraduate geography students can identify the skills, knowledge and attributes that are developed through…

On the choice of an optimal value-set of qualitative attributes for information retrieval in databases

International Nuclear Information System (INIS)

Ryjov, A.; Loginov, D.

1994-01-01

The problem of choosing an optimal set of significances of qualitative attributes for information retrieval in databases is addressed. Given a particular database, a set of significances is called optimal if it results in the minimization of losses of information and information noise for information retrieval in the data base. Obviously, such a set of significances depends on the statistical parameters of the data base. The software, which enables to calculate on the basis of the statistical parameters of the given data base, the losses of information and the information noise for arbitrary sets of significances of qualitative attributes, is described. The software also permits to compare various sets of significances of qualitative attributes and to choose the optimal set of significances

Cognitive Development Masks Support for Attributional Style Models of Depression in Children and Adolescents

Science.gov (United States)

Weitlauf, Amy S.; Cole, David A.

2012-01-01

Attributional style models of depression in adults (Abramson et al. 1989, 1978) have been adapted for use with children; however, most applications do not consider that children's understanding of causal relations may be qualitatively different from that of adults. If children's causal attributions depend on children's level of cognitive…

Direct estimation of patient attributes from anatomical MRI based on multi-atlas voting

Directory of Open Access Journals (Sweden)

Dan Wu

2016-01-01

Full Text Available MRI brain atlases are widely used for automated image segmentation, and in particular, recent developments in multi-atlas techniques have shown highly accurate segmentation results. In this study, we extended the role of the atlas library from mere anatomical reference to a comprehensive knowledge database with various patient attributes, such as demographic, functional, and diagnostic information. In addition to using the selected (heavily-weighted atlases to achieve high segmentation accuracy, we tested whether the non-anatomical attributes of the selected atlases could be used to estimate patient attributes. This can be considered a context-based image retrieval (CBIR approach, embedded in the multi-atlas framework. We first developed an image similarity measurement to weigh the atlases on a structure-by-structure basis, and then, the attributes of the multiple atlases were weighted to estimate the patient attributes. We tested this concept first by estimating age in a normal population; we then performed functional and diagnostic estimations in Alzheimer's disease patients. The accuracy of the estimated patient attributes was measured against the actual clinical data, and the performance was compared to conventional volumetric analysis. The proposed CBIR framework by multi-atlas voting would be the first step toward a knowledge-based support system for quantitative radiological image reading and diagnosis.

Direct estimation of patient attributes from anatomical MRI based on multi-atlas voting.

Science.gov (United States)

Wu, Dan; Ceritoglu, Can; Miller, Michael I; Mori, Susumu

MRI brain atlases are widely used for automated image segmentation, and in particular, recent developments in multi-atlas techniques have shown highly accurate segmentation results. In this study, we extended the role of the atlas library from mere anatomical reference to a comprehensive knowledge database with various patient attributes, such as demographic, functional, and diagnostic information. In addition to using the selected (heavily-weighted) atlases to achieve high segmentation accuracy, we tested whether the non-anatomical attributes of the selected atlases could be used to estimate patient attributes. This can be considered a context-based image retrieval (CBIR) approach, embedded in the multi-atlas framework. We first developed an image similarity measurement to weigh the atlases on a structure-by-structure basis, and then, the attributes of the multiple atlases were weighted to estimate the patient attributes. We tested this concept first by estimating age in a normal population; we then performed functional and diagnostic estimations in Alzheimer's disease patients. The accuracy of the estimated patient attributes was measured against the actual clinical data, and the performance was compared to conventional volumetric analysis. The proposed CBIR framework by multi-atlas voting would be the first step toward a knowledge-based support system for quantitative radiological image reading and diagnosis.

Temporal Drivers of Liking Based on Functional Data Analysis and Non-Additive Models for Multi-Attribute Time-Intensity Data of Fruit Chews.

Science.gov (United States)

Kuesten, Carla; Bi, Jian

2018-06-03

Conventional drivers of liking analysis was extended with a time dimension into temporal drivers of liking (TDOL) based on functional data analysis methodology and non-additive models for multiple-attribute time-intensity (MATI) data. The non-additive models, which consider both direct effects and interaction effects of attributes to consumer overall liking, include Choquet integral and fuzzy measure in the multi-criteria decision-making, and linear regression based on variance decomposition. Dynamics of TDOL, i.e., the derivatives of the relative importance functional curves were also explored. Well-established R packages 'fda', 'kappalab' and 'relaimpo' were used in the paper for developing TDOL. Applied use of these methods shows that the relative importance of MATI curves offers insights for understanding the temporal aspects of consumer liking for fruit chews.

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

Science.gov (United States)

Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin

2017-08-10

Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.

Gluon attributes

International Nuclear Information System (INIS)

Weiler, T.

1981-01-01

An overview is presented of the attributes of gluons, deducible from experimental data. Particular attention is given to the photon-gluon fusion model of charm leptoproduction. The agreement with QCD and theoretical prejudice is qualitatively good

An Evaluation Model of Quantitative and Qualitative Fuzzy Multi-Criteria Decision-Making Approach for Location Selection of Transshipment Ports

Directory of Open Access Journals (Sweden)

Ji-Feng Ding

2013-01-01

Full Text Available The role of container logistics centre as home bases for merchandise transportation has become increasingly important. The container carriers need to select a suitable centre location of transshipment port to meet the requirements of container shipping logistics. In the light of this, the main purpose of this paper is to develop a fuzzy multi-criteria decision-making (MCDM model to evaluate the best selection of transshipment ports for container carriers. At first, some concepts and methods used to develop the proposed model are briefly introduced. The performance values of quantitative and qualitative subcriteria are discussed to evaluate the fuzzy ratings. Then, the ideal and anti-ideal concepts and the modified distance measure method are used in the proposed model. Finally, a step-by-step example is illustrated to study the computational process of the quantitative and qualitative fuzzy MCDM model. The proposed approach has successfully accomplished our goal. In addition, the proposed fuzzy MCDM model can be empirically employed to select the best location of transshipment port for container carriers in the future study.

A multi-attribute decision model for portfolio selection aiming to replace technologies in industrial motor systems

International Nuclear Information System (INIS)

Vanderley Herrero Sola, Antonio; Mota, Caroline Maria de Miranda

2012-01-01

Highlights: ► We propose a multicriteria decision model for technology replacement. ► We prioritize induction motors in order to improve the energy efficiency. ► The best portfolio of options is selected based on decision maker’s utilities. ► The model contribute to surpass some organizational barriers. - Abstract: The energy efficient technologies offered by the market are in constant evolution, but their insertion in the productive sector comes up against organizational barriers, which obstruct decision making in firms. This paper proposes a multicriteria decision model in order to replace technologies in industrial energy systems, regarding organizational barriers for energy efficiency. The proposed model is applied in industrial motor systems, using Multi-Attribute Utility Theory (MAUT), in order to select the best portfolio of options based on the decision maker’s utilities. Portfolios of options from the prioritized set of motors compiled by the operational area of the studied industry are analyzed, including diverse suppliers and different classes of motors. The results show that it is essential to structure the proposed model in two steps, beginning with the operational level, to ensure that important technologies for the production system are prioritized, thus preserving the interests of the organization and improving the efficiency of industrial energy systems.

Case-based reasoning diagnostic technique based on multi-attribute similarity

Energy Technology Data Exchange (ETDEWEB)

Makoto, Takahashi [Tohoku University, Miyagi (Japan); Akio, Gofuku [Okayama University, Okayamaa (Japan)

2014-08-15

Case-based diagnostic technique has been developed based on the multi-attribute similarity. Specific feature of the developed system is to use multiple attributes of process signals for similarity evaluation to retrieve a similar case stored in a case base. The present technique has been applied to the measurement data from Monju with some simulated anomalies. The results of numerical experiments showed that the present technique can be utilizes as one of the methods for a hybrid-type diagnosis system.

Complex Event Detection via Multi Source Video Attributes (Open Access)

Science.gov (United States)

2013-10-03

Complex Event Detection via Multi-Source Video Attributes Zhigang Ma† Yi Yang‡ Zhongwen Xu‡§ Shuicheng Yan Nicu Sebe† Alexander G. Hauptmann...under its International Research Centre @ Singapore Fund- ing Initiative and administered by the IDM Programme Of- fice, and the Intelligence Advanced

An unprecedented multi attribute decision making using graph theory matrix approach

Directory of Open Access Journals (Sweden)

N.K. Geetha

2018-02-01

Full Text Available A frame work for investigating the best combination of functioning parameters on a variable compression ratio diesel engine is proposed in the present study using a multi attribute optimization methodology, Graph Theory Matrix Approach. The functioning parameters, attributes, sub attributes and functioning variables of sub attributes are chosen based on expert’s opinion and literature review. The directed graphs are developed for attributes and sub attributes. The ‘Parameter Index’ was calculated for all trials to choose the best trial. The experimental results are verified with the theoretical data. Functioning parameters with combination of compression ratio of 17, fuel injection pressure of 20 N/mm2 and fuel injection pressure of 21°bTDC was found to be best. The proposed method allows the decision maker to systematically and logically find the best combination of functioning parameters.

m2-ABKS: Attribute-Based Multi-Keyword Search over Encrypted Personal Health Records in Multi-Owner Setting.

Science.gov (United States)

Miao, Yinbin; Ma, Jianfeng; Liu, Ximeng; Wei, Fushan; Liu, Zhiquan; Wang, Xu An

2016-11-01

Online personal health record (PHR) is more inclined to shift data storage and search operations to cloud server so as to enjoy the elastic resources and lessen computational burden in cloud storage. As multiple patients' data is always stored in the cloud server simultaneously, it is a challenge to guarantee the confidentiality of PHR data and allow data users to search encrypted data in an efficient and privacy-preserving way. To this end, we design a secure cryptographic primitive called as attribute-based multi-keyword search over encrypted personal health records in multi-owner setting to support both fine-grained access control and multi-keyword search via Ciphertext-Policy Attribute-Based Encryption. Formal security analysis proves our scheme is selectively secure against chosen-keyword attack. As a further contribution, we conduct empirical experiments over real-world dataset to show its feasibility and practicality in a broad range of actual scenarios without incurring additional computational burden.

A multi-attribute approach to choosing adaptation strategies: Application to sea-level rise

International Nuclear Information System (INIS)

Smith, A.E.; Chu, H.Q.

1994-01-01

Selecting good adaptation strategies in anticipation of climate change is gaining increasing attention as it becomes increasingly clear that much of the likely change is already committed, and could not be avoided even with aggressive and immediate emissions reductions. Adaptation decision making will place special requirements on regional and local planners in the US and other countries, especially developing countries. Approaches, tools, and guidance will be useful to assist in an effective response to the challenge. This paper describes the value of using a multi-attribute approach for evaluating adaptation strategies and its implementation as a decision-support software tool to help planners understand and execute this approach. The multi-attribute approach described here explicitly addresses the fact that many aspects of the decision cannot be easily quantified, that future conditions are highly uncertain, and that there are issues of equity, flexibility, and coordination that may be as important to the decision as costs and benefits. The approach suggested also avoids trying to collapse information on all of the attributes to a single metric. Such metrics can obliterate insights about the nature of the trade-offs that must be made in choosing among very dissimilar types of responses to the anticipated threat of climate change. Implementation of such an approach requires management of much information, and an ability to easily manipulate its presentation while seeking acceptable trade-offs. The Adaptation Strategy Evaluator (ASE) was developed under funding from the US Environmental Protection Agency to provide user-friendly, PC-based guidance through the major steps of a multi-attribute evaluation. The initial application of ASE, and the focus of this paper, is adaptation to sea level rise. However, the approach can be easily adapted to any multi-attribute choice problem, including the range of other adaptation planning needs

The spruce budworm and forest: a qualitative comparison of ODE and Boolean models

Directory of Open Access Journals (Sweden)

Raina Robeva

2016-01-01

Full Text Available Boolean and polynomial models of biological systems have emerged recently as viable companions to differential equations models. It is not immediately clear however whether such models are capable of capturing the multi-stable behaviour of certain biological systems: this behaviour is often sensitive to changes in the values of the model parameters, while Boolean and polynomial models are qualitative in nature. In the past few years, Boolean models of gene regulatory systems have been shown to capture multi-stability at the molecular level, confirming that such models can be used to obtain information about the system’s qualitative dynamics when precise information regarding its parameters may not be available. In this paper, we examine Boolean approximations of a classical ODE model of budworm outbreaks in a forest and show that these models exhibit a qualitative behaviour consistent with that derived from the ODE models. In particular, we demonstrate that these models can capture the bistable nature of insect population outbreaks, thus showing that Boolean models can be successfully utilized beyond the molecular level.

Secure Data Access Control for Fog Computing Based on Multi-Authority Attribute-Based Signcryption with Computation Outsourcing and Attribute Revocation.

Science.gov (United States)

Xu, Qian; Tan, Chengxiang; Fan, Zhijie; Zhu, Wenye; Xiao, Ya; Cheng, Fujia

2018-05-17

Nowadays, fog computing provides computation, storage, and application services to end users in the Internet of Things. One of the major concerns in fog computing systems is how fine-grained access control can be imposed. As a logical combination of attribute-based encryption and attribute-based signature, Attribute-based Signcryption (ABSC) can provide confidentiality and anonymous authentication for sensitive data and is more efficient than traditional "encrypt-then-sign" or "sign-then-encrypt" strategy. Thus, ABSC is suitable for fine-grained access control in a semi-trusted cloud environment and is gaining more and more attention recently. However, in many existing ABSC systems, the computation cost required for the end users in signcryption and designcryption is linear with the complexity of signing and encryption access policy. Moreover, only a single authority that is responsible for attribute management and key generation exists in the previous proposed ABSC schemes, whereas in reality, mostly, different authorities monitor different attributes of the user. In this paper, we propose OMDAC-ABSC, a novel data access control scheme based on Ciphertext-Policy ABSC, to provide data confidentiality, fine-grained control, and anonymous authentication in a multi-authority fog computing system. The signcryption and designcryption overhead for the user is significantly reduced by outsourcing the undesirable computation operations to fog nodes. The proposed scheme is proven to be secure in the standard model and can provide attribute revocation and public verifiability. The security analysis, asymptotic complexity comparison, and implementation results indicate that our construction can balance the security goals with practical efficiency in computation.

An Agent Architecture for Multi-Attribute Negotiation Using Incomplete Preference Information

NARCIS (Netherlands)

Jonker, C.M.; Robu, V.; Treur, J.

2007-01-01

A component-based generic agent architecture for multi-attribute (integrative) negotiation is introduced and its application is described in a prototype system for negotiation about cars, developed in cooperation with, among others, Dutch Telecom KPN. The approach can be characterized as cooperative

Schizophrenia: multi-attribute utility theory approach to selection of atypical antipsychotics.

Science.gov (United States)

Bettinger, Tawny L; Shuler, Garyn; Jones, Donnamaria R; Wilson, James P

2007-02-01

Current guidelines/algorithms recommend atypical antipsychotics as first-line agents for the treatment of schizophrenia. Because there are extensive healthcare costs associated with the treatment of schizophrenia, many institutions and health systems are faced with making restrictive formulary decisions regarding the use of atypical antipsychotics. Often, medication acquisition costs are the driving force behind formulary decisions, while other treatment factors are not considered. To apply a multi-attribute utility theory (MAUT) analysis to aid in the selection of a preferred agent among the atypical antipsychotics for the treatment of schizophrenia. Five atypical antipsychotics (risperidone, olanzapine, quetiapine, ziprasidone, aripiprazole) were selected as the alternative agents to be included in the MAUT analysis. The attributes identified for inclusion in the analysis were efficacy, adverse effects, cost, and adherence, with relative weights of 35%, 35%, 20%, and 10%, respectively. For each agent, attribute scores were calculated, weighted, and then summed to generate a total utility score. The agent with the highest total utility score was considered the preferred agent. Aripiprazole, with a total utility score of 75.8, was the alternative agent with the highest total utility score in this model. This was followed by ziprasidone, risperidone, and quetiapine, with total utility scores of 71.8, 69.0, and 65.9, respectively. Olanzapine received the lowest total utility score. A sensitivity analysis was performed and failed to displace aripiprazole as the agent with the highest total utility score. This model suggests that aripiprazole should be considered a preferred agent for the treatment of schizophrenia unless found to be otherwise inappropriate.

Decision Support for Personalized Cloud Service Selection through Multi-Attribute Trustworthiness Evaluation

Science.gov (United States)

Ding, Shuai; Xia, Chen-Yi; Zhou, Kai-Le; Yang, Shan-Lin; Shang, Jennifer S.

2014-01-01

Facing a customer market with rising demands for cloud service dependability and security, trustworthiness evaluation techniques are becoming essential to cloud service selection. But these methods are out of the reach to most customers as they require considerable expertise. Additionally, since the cloud service evaluation is often a costly and time-consuming process, it is not practical to measure trustworthy attributes of all candidates for each customer. Many existing models cannot easily deal with cloud services which have very few historical records. In this paper, we propose a novel service selection approach in which the missing value prediction and the multi-attribute trustworthiness evaluation are commonly taken into account. By simply collecting limited historical records, the current approach is able to support the personalized trustworthy service selection. The experimental results also show that our approach performs much better than other competing ones with respect to the customer preference and expectation in trustworthiness assessment. PMID:24972237

A multi-attribute approach to the rationalization of radiation protection options

International Nuclear Information System (INIS)

Lombard, J.; Oudiz, A.

1979-01-01

Application of the ALARA principle requires the use of quantitative methods such as cost-benefit, cost-effectiveness, multi-attribute and other analyses. An example is presented of the application of a multi-attribute analysis in connection with the determination of ALARA levels for the light-water fuel cycle. Thirty-nine processing options for waste from different fuel cycle facilities have been identified. These are categorized on the basis of cost, of performance in terms of reduction of collective and individual detriment and, finally, of a subjective index of data reliability. Multi-attribute analysis can be used for classifying options on the basis of these four criteria. In particular, a method known as ''total outclassing analysis'' can be used for initial classification of options independently of the ''implicit value of human life''. The value of total outclassing analysis lies in the fact that it can be used for a classification of options which takes collective and individual detriment simultaneously into account. It thus represents a satisfactory synthesis of the individual approach (critical groups) and the collective approach. A finer classification can be obtained by carrying out a non-total outclassing analysis (ELECTRE method). At this stage the weighting of criteria becomes a necessity. The results, however, are fairly insensitive to modification of the ''implicit value of human life''. Generally, the study shows traditional radiation protection options to be justified, especially where the trapping of iodine in reactors is concerned, and stresses the value of retaining noble gases in reprocessing plants

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

Science.gov (United States)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land

Exemplar-based inference in multi-attribute decision making

Directory of Open Access Journals (Sweden)

Linnea Karlsson

2008-03-01

Full Text Available Several studies propose that exemplar retrieval contributes to multi-attribute decisions. The authors have proposed a process theory enabling a priori predictions of what cognitive representations people use as input to their judgment process (extit{Sigma}, for ``summation''; P. Juslin, L. Karlsson, and H. Olsson, 2008. According to Sigma, exemplar retrieval is a back-up system when the task does not allow for additive and linear abstraction and integration of cue-criterion knowledge (e.g., when the task is non-additive. An important question is to what extent such shifts occur spontaneously as part of automatic procedures, such as error-minimization with the Delta rule, or if they are controlled extit{strategy} shifts contingent on the ability to identify a sufficiently successful judgment strategy. In this article data are reviewed that demonstrate a shift between exemplar memory and cue abstraction, as well as data where the expected shift does extit{not} occur. In contrast to a common assumption of previous models, these results suggest a controlled and contingent strategy shift.

Development of the Attributed Dignity Scale.

Science.gov (United States)

Jacelon, Cynthia S; Dixon, Jane; Knafl, Kathleen A

2009-07-01

A sequential, multi-method approach to instrument development beginning with concept analysis, followed by (a) item generation from qualitative data, (b) review of items by expert and lay person panels, (c) cognitive appraisal interviews, (d) pilot testing, and (e) evaluating construct validity was used to develop a measure of attributed dignity in older adults. The resulting positively scored, 23-item scale has three dimensions: Self-Value, Behavioral Respect-Self, and Behavioral Respect-Others. Item-total correlations in the pilot study ranged from 0.39 to 0.85. Correlations between the Attributed Dignity Scale (ADS) and both Rosenberg's Self-Esteem Scale (0.17) and Crowne and Marlowe's Social Desirability Scale (0.36) were modest and in the expected direction, indicating attributed dignity is a related but independent concept. Next steps include testing the ADS with a larger sample to complete factor analysis, test-retest stability, and further study of the relationships between attributed dignity and other concepts.

How to Be Both Rich and Happy: Combining Quantitative and Qualitative Strategic Reasoning about Multi-Player Games

DEFF Research Database (Denmark)

Bulling, Nils; Goranko, Valentin

2013-01-01

We propose a logical framework combining a game-theoretic study of abilities of agents to achieve quantitative objectives in multi-player games by optimizing payoffs or preferences on outcomes with a logical analysis of the abilities of players for achieving qualitative objectives of players, i.......e., reaching or maintaining game states with desired properties. We enrich concurrent game models with payoffs for the normal form games associated with the states of the model and propose a quantitative extension of the logic ATL* enabling the combination of quantitative and qualitative reasoning....

A qualitative evaluation of the crucial attributes of contextual information necessary in EHR design to support patient-centered medical home care.

Science.gov (United States)

Weir, Charlene R; Staggers, Nancy; Gibson, Bryan; Doing-Harris, Kristina; Barrus, Robyn; Dunlea, Robert

2015-04-16

Effective implementation of a Primary Care Medical Home model of care (PCMH) requires integration of patients' contextual information (physical, mental, social and financial status) into an easily retrievable information source for the healthcare team and clinical decision-making. This project explored clinicians' perceptions about important attributes of contextual information for clinical decision-making, how contextual information is expressed in CPRS clinical documentation as well as how clinicians in a highly computerized environment manage information flow related to these areas. A qualitative design using Cognitive Task Analyses and a modified Critical Incident Technique were used. The study was conducted in a large VA with a fully implemented EHR located in the western United States. Seventeen providers working in a PCMH model of care in Primary Care, Home Based Care and Geriatrics reported on a recent difficult transition requiring contextual information for decision-making. The transcribed interviews were qualitatively analyzed for thematic development related to contextual information using an iterative process and multiple reviewers with ATLAS@ti software. Six overarching themes emerged as attributes of contextual information: Informativeness, goal language, temporality, source attribution, retrieval effort, and information quality. These results indicate that specific attributes are needed to in order for contextual information to fully support clinical decision-making in a Medical Home care delivery environment. Improved EHR designs are needed for ease of contextual information access, displaying linkages across time and settings, and explicit linkages to both clinician and patient goals. Implications relevant to providers' information needs, team functioning and EHR design are discussed.

Variable precision rough set for multiple decision attribute analysis

Institute of Scientific and Technical Information of China (English)

Lai; Kin; Keung

2008-01-01

A variable precision rough set (VPRS) model is used to solve the multi-attribute decision analysis (MADA) problem with multiple conflicting decision attributes and multiple condition attributes. By introducing confidence measures and a β-reduct, the VPRS model can rationally solve the conflicting decision analysis problem with multiple decision attributes and multiple condition attributes. For illustration, a medical diagnosis example is utilized to show the feasibility of the VPRS model in solving the MADA...

On the universality of the attribution-affect model of helping.

Science.gov (United States)

Reisenzein, Rainer

2015-08-01

Although Pilati et al.'s (2014) findings question the strong quantitative universality of the attribution-affect model of helping, they are consistent with a weak form of quantitative universality, as well as with the qualitative universality of the theory. However, universality is put into question by previous studies revealing significant and sizeable between-study differences in the strength of the causal paths postulated by the theory. These differences may in part reflect differences in the type of helping situations studied. © 2015 International Union of Psychological Science.

A formulation of multidimensional growth models for the assessment and forecast of technology attributes

Science.gov (United States)

Danner, Travis W.

modeling technique begins to diminish. With the introduction of multiple objectives, researchers often abandon technology growth models for scoring models and technology frontiers. While both approaches possess advantages over current growth models for the assessment of multi-objective technologies, each lacks a necessary dimension for comprehensive technology assessment. By collapsing multiple system metrics into a single, non-intuitive technology measure, scoring models provide a succinct framework for multi-objective technology assessment and forecasting. Yet, with no consideration of physical limits, scoring models provide no insight as to the feasibility of a particular combination of system capabilities. They only indicate that a given combination of system capabilities yields a particular score. Conversely, technology frontiers are constructed with the distinct objective of providing insight into the feasibility of system capability combinations. Yet again, upper limits to overall system performance are ignored. Furthermore, the data required to forecast subsequent technology frontiers is often inhibitive. In an attempt to reincorporate the fundamental nature of technology advancement as bound by physical principles, researchers have sought to normalize multi-objective systems whereby the variability of a single system objective is eliminated as a result of changes in the remaining objectives. This drastically limits the applicability of the resulting technology model because it is only applicable for a single setting of all other system attributes. Attempts to maintain the interaction between the growth curves of each technical objective of a complex system have thus far been limited to qualitative and subjective consideration. This research proposes the formulation of multidimensional growth models as an approach to simulating the advancement of multi-objective technologies towards their upper limits. Multidimensional growth models were formulated by noticing and

A qualitative study on the attributes of nurses' workplace social capital in Japan.

Science.gov (United States)

Norikoshi, Kensuke; Kobayashi, Toshio; Tabuchi, Keiji

2018-01-01

To identify attributes of nurses' workplace social capital in Japan. Much attention has been paid to nurses' workplace social capital to improve the quality of the work environment; however, few studies are available on the attributes of nurses' workplace social capital. Semi-structured interviews were conducted with 32 nurses at seven hospitals. Nurses reported on the attributes of workplace social capital, such as characteristics facilitating individual positive action in an organisation, which were qualitatively analysed using the Kawakita Jiro method. The attributes of nurses' workplace social capital were organised into six groups: affirmation; exchange of appreciation; unrestricted information sharing; ability to trust; access to the strength; and altruistic reciprocity. The attributes of nurses' workplace social capital included a social structure that allowed nurses to make full use of their abilities both vertically and horizontally and were supported by a sense of security. In particular, newly emerged exchange of appreciation and altruistic reciprocity were important for nurses in Japan in building cooperative relationships with others. Managing human relationships, such as exchange of appreciation and altruistic reciprocity, in clinical settings based on nurses' workplace social capital may promote positive emotions in the organisation, positive ideas among staff and cooperative teamwork, which may lead to high-quality patient care. © 2017 John Wiley & Sons Ltd.

Qualitative analysis of patient-centered decision attributes associated with initiating hepatitis C treatment.

Science.gov (United States)

Zuchowski, Jessica L; Hamilton, Alison B; Pyne, Jeffrey M; Clark, Jack A; Naik, Aanand D; Smith, Donna L; Kanwal, Fasiha

2015-10-01

In this era of a constantly changing landscape of antiviral treatment options for chronic viral hepatitis C (CHC), shared clinical decision-making addresses the need to engage patients in complex treatment decisions. However, little is known about the decision attributes that CHC patients consider when making treatment decisions. We identify key patient-centered decision attributes, and explore relationships among these attributes, to help inform the development of a future CHC shared decision-making aid. Semi-structured qualitative interviews with CHC patients at four Veterans Health Administration (VHA) hospitals, in three comparison groups: contemplating CHC treatment at the time of data collection (Group 1), recently declined CHC treatment (Group 2), or recently started CHC treatment (Group 3). Participant descriptions of decision attributes were analyzed for the entire sample as well as by patient group and by gender. Twenty-nine Veteran patients participated (21 males, eight females): 12 were contemplating treatment, nine had recently declined treatment, and eight had recently started treatment. Patients on average described eight (range 5-13) decision attributes. The attributes most frequently reported overall were: physical side effects (83%); treatment efficacy (79%), new treatment drugs in development (55%); psychological side effects (55%); and condition of the liver (52%), with some variation based on group and gender. Personal life circumstance attributes (such as availability of family support and the burden of financial responsibilities) influencing treatment decisions were also noted by all participants. Multiple decision attributes were interrelated in highly complex ways. Participants considered numerous attributes in their CHC treatment decisions. A better understanding of these attributes that influence patient decision-making is crucial in order to inform patient-centered clinical approaches to care (such as shared decision-making augmented

Stakeholder-driven multi-attribute analysis for energy project selection under uncertainty

International Nuclear Information System (INIS)

Read, Laura; Madani, Kaveh; Mokhtari, Soroush; Hanks, Catherine

2017-01-01

In practice, selecting an energy project for development requires balancing criteria and competing stakeholder priorities to identify the best alternative. Energy source selection can be modeled as multi-criteria decision-maker problems to provide quantitative support to reconcile technical, economic, environmental, social, and political factors with respect to the stakeholders' interests. Decision making among these complex interactions should also account for the uncertainty present in the input data. In response, this work develops a stochastic decision analysis framework to evaluate alternatives by involving stakeholders to identify both quantitative and qualitative selection criteria and performance metrics which carry uncertainties. The developed framework is illustrated using a case study from Fairbanks, Alaska, where decision makers and residents must decide on a new source of energy for heating and electricity. We approach this problem in a five step methodology: (1) engaging experts (role players) to develop criteria of project performance; (2) collecting a range of quantitative and qualitative input information to determine the performance of each proposed solution according to the selected criteria; (3) performing a Monte-Carlo analysis to capture uncertainties given in the inputs; (4) applying multi-criteria decision-making, social choice (voting), and fallback bargaining methods to account for three different levels of cooperation among the stakeholders; and (5) computing an aggregate performance index (API) score for each alternative based on its performance across criteria and cooperation levels. API scores communicate relative performance between alternatives. In this way, our methodology maps uncertainty from the input data to reflect risk in the decision and incorporates varying degrees of cooperation into the analysis to identify an optimal and practical alternative. - Highlights: • We develop an applicable stakeholder-driven framework for

Multi-Model Prediction for Demand Forecast in Water Distribution Networks

Directory of Open Access Journals (Sweden)

Rodrigo Lopez Farias

2018-03-01

Full Text Available This paper presents a multi-model predictor called Qualitative Multi-Model Predictor Plus (QMMP+ for demand forecast in water distribution networks. QMMP+ is based on the decomposition of the quantitative and qualitative information of the time-series. The quantitative component (i.e., the daily consumption prediction is forecasted and the pattern mode estimated using a Nearest Neighbor (NN classifier and a Calendar. The patterns are updated via a simple Moving Average scheme. The NN classifier and the Calendar are executed simultaneously every period and the most suited model for prediction is selected using a probabilistic approach. The proposed solution for water demand forecast is compared against Radial Basis Function Artificial Neural Networks (RBF-ANN, the statistical Autoregressive Integrated Moving Average (ARIMA, and Double Seasonal Holt-Winters (DSHW approaches, providing the best results when applied to real demand of the Barcelona Water Distribution Network. QMMP+ has demonstrated that the special modelling treatment of water consumption patterns improves the forecasting accuracy.

Using linguistic descriptions with multi-criteria decision aid approaches in urban energy systems

OpenAIRE

Afsordegan, Arayeh; Sánchez Soler, Monica; Agell Jané, Núria; Gamboa Jimenez, Gonzalo; Cremades Oliver, Lázaro Vicente

2015-01-01

Multi-Criteria Decision Aid (MCDA) methods include various collections of mathematical techniques related to decision support systems in non-deterministic environments to support such applications as facility management, disaster management and urban planning. This paper applies MCDA approaches based on qualitative reasoning techniques with linguistic labels assessment. The aim of this method is ranking multi-attribute alternatives in group decision-making with qualitative labels. Finally ...

Global Qualitative Flow-Path Modeling for Local State Determination in Simulation and Analysis

Science.gov (United States)

Malin, Jane T. (Inventor); Fleming, Land D. (Inventor)

1998-01-01

For qualitative modeling and analysis, a general qualitative abstraction of power transmission variables (flow and effort) for elements of flow paths includes information on resistance, net flow, permissible directions of flow, and qualitative potential is discussed. Each type of component model has flow-related variables and an associated internal flow map, connected into an overall flow network of the system. For storage devices, the implicit power transfer to the environment is represented by "virtual" circuits that include an environmental junction. A heterogeneous aggregation method simplifies the path structure. A method determines global flow-path changes during dynamic simulation and analysis, and identifies corresponding local flow state changes that are effects of global configuration changes. Flow-path determination is triggered by any change in a flow-related device variable in a simulation or analysis. Components (path elements) that may be affected are identified, and flow-related attributes favoring flow in the two possible directions are collected for each of them. Next, flow-related attributes are determined for each affected path element, based on possibly conflicting indications of flow direction. Spurious qualitative ambiguities are minimized by using relative magnitudes and permissible directions of flow, and by favoring flow sources over effort sources when comparing flow tendencies. The results are output to local flow states of affected components.

MULTI-ATTRIBUTE SEISMIC/ROCK PHYSICS APPROACH TO CHARACTERIZING FRACTURED RESERVOIRS

Energy Technology Data Exchange (ETDEWEB)

Gary Mavko

2000-10-01

This project consists of three key interrelated Phases, each focusing on the central issue of imaging and quantifying fractured reservoirs, through improved integration of the principles of rock physics, geology, and seismic wave propagation. This report summarizes the results of Phase I of the project. The key to successful development of low permeability reservoirs lies in reliably characterizing fractures. Fractures play a crucial role in controlling almost all of the fluid transport in tight reservoirs. Current seismic methods to characterize fractures depend on various anisotropic wave propagation signatures that can arise from aligned fractures. We are pursuing an integrated study that relates to high-resolution seismic images of natural fractures to the rock parameters that control the storage and mobility of fluids. Our goal is to go beyond the current state-of-the art to develop and demonstrate next generation methodologies for detecting and quantitatively characterizing fracture zones using seismic measurements. Our study incorporates 3 key elements: (1) Theoretical rock physics studies of the anisotropic viscoelastic signatures of fractured rocks, including up scaling analysis and rock-fluid interactions to define the factors relating fractures in the lab and in the field. (2) Modeling of optimal seismic attributes, including offset and azimuth dependence of travel time, amplitude, impedance and spectral signatures of anisotropic fractured rocks. We will quantify the information content of combinations of seismic attributes, and the impact of multi-attribute analyses in reducing uncertainty in fracture interpretations. (3) Integration and interpretation of seismic, well log, and laboratory data, incorporating field geologic fracture characterization and the theoretical results of items 1 and 2 above. The focal point for this project is the demonstration of these methodologies in the Marathon Oil Company Yates Field in West Texas.

How to Be Both Rich and Happy: Combining Quantitative and Qualitative Strategic Reasoning about Multi-Player Games (Extended Abstract

Directory of Open Access Journals (Sweden)

Nils Bulling

2013-03-01

Full Text Available We propose a logical framework combining a game-theoretic study of abilities of agents to achieve quantitative objectives in multi-player games by optimizing payoffs or preferences on outcomes with a logical analysis of the abilities of players for achieving qualitative objectives of players, i.e., reaching or maintaining game states with desired properties. We enrich concurrent game models with payoffs for the normal form games associated with the states of the model and propose a quantitative extension of the logic ATL* enabling the combination of quantitative and qualitative reasoning.

A Checklist for Reporting Valuation Studies of Multi-Attribute Utility-Based Instruments (CREATE)

NARCIS (Netherlands)

Xie, Feng; Pickard, A. Simon; Krabbe, Paul F. M.; Revicki, Dennis; Viney, Rosalie; Devlin, Nancy; Feeny, David

Multi-attribute utility-based instruments (MAUIs) assess health status and provide an index score on the full health-dead scale, and are widely used to support reimbursement decisions for new healthcare interventions worldwide. A valuation study is a key part of the development of MAUIs, with the

The Systems Biology Markup Language (SBML) Level 3 Package: Qualitative Models, Version 1, Release 1.

Science.gov (United States)

Chaouiya, Claudine; Keating, Sarah M; Berenguier, Duncan; Naldi, Aurélien; Thieffry, Denis; van Iersel, Martijn P; Le Novère, Nicolas; Helikar, Tomáš

2015-09-04

Quantitative methods for modelling biological networks require an in-depth knowledge of the biochemical reactions and their stoichiometric and kinetic parameters. In many practical cases, this knowledge is missing. This has led to the development of several qualitative modelling methods using information such as, for example, gene expression data coming from functional genomic experiments. The SBML Level 3 Version 1 Core specification does not provide a mechanism for explicitly encoding qualitative models, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The SBML Qualitative Models package for SBML Level 3 adds features so that qualitative models can be directly and explicitly encoded. The approach taken in this package is essentially based on the definition of regulatory or influence graphs. The SBML Qualitative Models package defines the structure and syntax necessary to describe qualitative models that associate discrete levels of activities with entity pools and the transitions between states that describe the processes involved. This is particularly suited to logical models (Boolean or multi-valued) and some classes of Petri net models can be encoded with the approach.

The application of the lake ecosystem index in multi-attribute decision analysis in radioecology

International Nuclear Information System (INIS)

Haakanson, Lars; Gallego, Eduardo; Rios-Insua, Sixto

2000-01-01

This work gives a summary of multi-attribute analysis (MAA) and its use in decision support systems for radiological and environmental contamination problems and presents a modification of the lake ecosystem index (LEI) as a tool to give an holistic account for the environmental (and not just radiological) consequences of chemical remedial measures (lake and wet land liming, potash treatment and lake fertilisation) carried out to reduce radionuclide levels in water, sediments and biota. The first step in determining a LEI-value is to set normal or initial values of two important limnological state variables, pH and total-P. The second step involves predicting state indices describing the abundance of key functional groups (the fish yield and biomasses of phytoplankton and bottom fauna). The next step concerns the definition of a lake ecosystem index based on the state indices. The final step is the derivation of the utility function to be used in the multi-attribute analysis to compare environmental, economical and social attributes of different dimensions (ECU, kg, Bq/kg, etc.). The ecosystem index characterises the entire lake over longer periods of time (months), and not specific sites in lakes or specific sampling events

Experience of insomnia, symptom attribution and treatment preferences in individuals with moderate to severe COPD: a qualitative study

Directory of Open Access Journals (Sweden)

Kauffman KS

2014-12-01

Full Text Available Karen S Kauffman,1 Megan Doede,1 Montserrat Diaz-Abad,2 Steven M Scharf,2,3 Wanda Bell-Farrell,2 Valerie E Rogers,1 Jeanne Geiger-Brown1 1Department of Family and Community Health, University of Maryland School of Nursing, Baltimore, MD, USA; 2Division of Pulmonary and Critical Care, University of Maryland School of Medicine, Baltimore, MD, USA; 3The University of Maryland Sleep Disorders Center, Baltimore, MD, USA Abstract: Persons with chronic obstructive pulmonary disease (COPD are known to have poor sleep quality. Acceptance of and adherence to therapies for sleep problems may depend on how the person with COPD regards the source of his sleep problem, yet little is known about their attribution as to the cause of these sleep symptoms. The objective of this study was to describe the subjective sleep complaints of individuals with COPD along with their attributions as to the cause of these symptoms, and their treatment preferences for insomnia. Three focus groups were conducted (N=18 with participants who have moderate to severe COPD. Focus group data were transcribed, compared and contrasted to identify themes of attribution. Participants reported difficulty falling asleep, staying asleep, and daytime sleepiness. They attributed their sleep problems primarily to their pulmonary symptoms, but also poor air quality (thick humid air and death anxiety when awake during the night. There was no clear preference for type of treatment to remedy this problem (medication, cognitive therapy, although they indicated that traveling to the clinic was difficult and should be avoided as much as possible. These data suggest that environmental manipulation to improve air quality (eg, air conditioning and modifications to reduce death anxiety could be beneficial to persons with COPD. In-person multi-session therapy may not be acceptable to persons with moderate to severe COPD, however internet-based therapy might make treatment more accessible. Keywords

A multi-level qualitative analysis of Telehomecare in Ontario: challenges and opportunities

OpenAIRE

Hunting, Gemma; Shahid, Nida; Sahakyan, Yeva; Fan, Iris; Moneypenny, Crystal R.; Stanimirovic, Aleksandra; North, Taylor; Petrosyan, Yelena; Krahn, Murray D.; Rac, Valeria E.

2015-01-01

Background Despite research demonstrating the potential effectiveness of Telehomecare for people with Chronic Obstructive Pulmonary Disease and Heart Failure, broad-scale comprehensive evaluations are lacking. This article discusses the qualitative component of a mixed-method program evaluation of Telehomecare in Ontario, Canada. The objective of the qualitative component was to explore the multi-level factors and processes which facilitate or impede the implementation and adoption of the pro...

On the benefits of multi-attribute risk analysis in nuclear emergency management

International Nuclear Information System (INIS)

Haemaelaeinen, R.P.; Lindstedt, M.

1999-01-01

The radiation protection authorities have seen a need to apply multi-attribute risk analysis in the nuclear emergency management and planning processes to deal with the conflicting objectives, different parties involved and uncertainties. This type of an approach is expected to help in at least the following three areas; to ensure that all the relevant attributes are considered in the decision making, to enhance communication between concerned parties including the population, and to provide a method for including risk analysis explicitly in the process. A MAUT analysis was used to select a strategy for protecting the population after a simulated nuclear accident. A value-focused approach and the use of a neutral facilitator were seen as very useful

On the benefits of multi-attribute risk analysis in nuclear emergency management

Energy Technology Data Exchange (ETDEWEB)

Haemaelaeinen, R.P.; Lindstedt, M. [Helsinki Univ. of Technology (Finland). Systems Analysis Lab.; Sinkko, K. [The Radiation and Nuclear Safety Authority, Helsinki (Finland)

1999-12-01

The radiation protection authorities have seen a need to apply multi-attribute risk analysis in the nuclear emergency management and planning processes to deal with the conflicting objectives, different parties involved and uncertainties. This type of an approach is expected to help in at least the following three areas; to ensure that all the relevant attributes are considered in the decision making, to enhance communication between concerned parties including the population, and to provide a method for including risk analysis explicitly in the process. A MAUT analysis was used to select a strategy for protecting the population after a simulated nuclear accident. A value-focused approach and the use of a neutral facilitator were seen as very useful.

PLANE: A Platform for Negotiation of Multi-attribute Multimedia Objects

Directory of Open Access Journals (Sweden)

Rharon M. Guedes

2013-12-01

Full Text Available This work proposes the definition of a system to negotiate products in an e-commerce scenario. This negotiation system is defined as PLANE – Platform to Assist Negotiation – and it is carried in a semi-automatic way, using multi-attributes functions, based on attributes of the negotiated content. It also presents an architecture to interconnect the participant through an inter-network in the television broadcasters context. Each participant of the inter-network applies policies for its own contents, and all of them must comply these policies. If a participant needs a content not covered by the policies, it is possible to start a negotiation process for this specific content. Experiments present a simulation scenario where PLANE assists the negotiation between three sellers and one buyer with predefined negotiation profiles. Results demonstrated the success of the system in approximate the negotiator after some few interactions, reducing time and cost.

The Multi-Attribute Group Decision-Making Method Based on Interval Grey Trapezoid Fuzzy Linguistic Variables.

Science.gov (United States)

Yin, Kedong; Wang, Pengyu; Li, Xuemei

2017-12-13

With respect to multi-attribute group decision-making (MAGDM) problems, where attribute values take the form of interval grey trapezoid fuzzy linguistic variables (IGTFLVs) and the weights (including expert and attribute weight) are unknown, improved grey relational MAGDM methods are proposed. First, the concept of IGTFLV, the operational rules, the distance between IGTFLVs, and the projection formula between the two IGTFLV vectors are defined. Second, the expert weights are determined by using the maximum proximity method based on the projection values between the IGTFLV vectors. The attribute weights are determined by the maximum deviation method and the priorities of alternatives are determined by improved grey relational analysis. Finally, an example is given to prove the effectiveness of the proposed method and the flexibility of IGTFLV.

Plenty of Blame to Go Around: A Qualitative Approach to Attribution of Moral Responsibility

National Research Council Canada - National Science Library

Tomai, Emmett; Forbus, Ken

2007-01-01

We present a computational model of blame attribution. Recently Mao and Gratch, following Attribution theory, created a computational model that assigned blame to an agent for a negative occurrence...

New agrophysics divisions: application of GIS and fuzzy multi attributive comparison of alternatives (review)

Science.gov (United States)

This review paper is devoted to review the new scientific divisions that emerged in agrophysics in the last 10-15 years. Among them are the following: 1) application of Geographic Information Systems, 2) development and application of fuzzy multi attributive comparison of alternatives. In recent yea...

Energy-dissipation-model for metallurgical multi-phase-systems

Energy Technology Data Exchange (ETDEWEB)

Mavrommatis, K.T. [Rheinisch-Westfaelische Technische Hochschule Aachen, Aachen (Germany)

1996-12-31

Entropy production in real processes is directly associated with the dissipation of energy. Both are potential measures for the proceed of irreversible processes taking place in metallurgical systems. Many of these processes in multi-phase-systems could then be modelled on the basis of the energy-dissipation associated with. As this entity can often be estimated using very simple assumptions from first principles, the evolution of an overall measure of systems behaviour can be studied constructing an energy-dissipation -based model of the system. In this work a formulation of this concept, the Energy-Dissipation-Model (EDM), for metallurgical multi-phase-systems is given. Special examples are studied to illustrate the concept, and benefits as well as the range of validity are shown. This concept might be understood as complement to usual CFD-modelling of complex systems on a more abstract level but reproducing essential attributes of complex metallurgical systems. (author)

Energy-dissipation-model for metallurgical multi-phase-systems

Energy Technology Data Exchange (ETDEWEB)

Mavrommatis, K T [Rheinisch-Westfaelische Technische Hochschule Aachen, Aachen (Germany)

1997-12-31

Entropy production in real processes is directly associated with the dissipation of energy. Both are potential measures for the proceed of irreversible processes taking place in metallurgical systems. Many of these processes in multi-phase-systems could then be modelled on the basis of the energy-dissipation associated with. As this entity can often be estimated using very simple assumptions from first principles, the evolution of an overall measure of systems behaviour can be studied constructing an energy-dissipation -based model of the system. In this work a formulation of this concept, the Energy-Dissipation-Model (EDM), for metallurgical multi-phase-systems is given. Special examples are studied to illustrate the concept, and benefits as well as the range of validity are shown. This concept might be understood as complement to usual CFD-modelling of complex systems on a more abstract level but reproducing essential attributes of complex metallurgical systems. (author)

The Multi-Attribute Group Decision-Making Method Based on Interval Grey Trapezoid Fuzzy Linguistic Variables

Directory of Open Access Journals (Sweden)

Kedong Yin

2017-12-01

Full Text Available With respect to multi-attribute group decision-making (MAGDM problems, where attribute values take the form of interval grey trapezoid fuzzy linguistic variables (IGTFLVs and the weights (including expert and attribute weight are unknown, improved grey relational MAGDM methods are proposed. First, the concept of IGTFLV, the operational rules, the distance between IGTFLVs, and the projection formula between the two IGTFLV vectors are defined. Second, the expert weights are determined by using the maximum proximity method based on the projection values between the IGTFLV vectors. The attribute weights are determined by the maximum deviation method and the priorities of alternatives are determined by improved grey relational analysis. Finally, an example is given to prove the effectiveness of the proposed method and the flexibility of IGTFLV.

Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings

Energy Technology Data Exchange (ETDEWEB)

ALwaer, H. [The University of Dundee, School of Architecture, Matthew Building, 13 Perth Road, Dundee DD1 4HT (United Kingdom); Clements-Croome, D.J. [School of Construction Management and Engineering, The University of Reading, Whiteknights, PO Box 219, Reading RG6 6AW (United Kingdom)

2010-04-15

The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a 'tool' for 'comparative' rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers

Attributional Models of Depression and Marital Distress.

Science.gov (United States)

Horneffer, Karen J.; Fincham, Frank D.

1996-01-01

Compares attributional models presented in depression and marital literatures by examining simultaneously their prediction of depressive symptoms and marital distress with 150 married couples. Findings show that a model including paths from depressogenic and distress-maintaining marital attributions to both depressive symptoms and marital distress…

Qualitative models for space system engineering

Science.gov (United States)

Forbus, Kenneth D.

1990-01-01

The objectives of this project were: (1) to investigate the implications of qualitative modeling techniques for problems arising in the monitoring, diagnosis, and design of Space Station subsystems and procedures; (2) to identify the issues involved in using qualitative models to enhance and automate engineering functions. These issues include representing operational criteria, fault models, alternate ontologies, and modeling continuous signals at a functional level of description; and (3) to develop a prototype collection of qualitative models for fluid and thermal systems commonly found in Space Station subsystems. Potential applications of qualitative modeling to space-systems engineering, including the notion of intelligent computer-aided engineering are summarized. Emphasis is given to determining which systems of the proposed Space Station provide the most leverage for study, given the current state of the art. Progress on using qualitative models, including development of the molecular collection ontology for reasoning about fluids, the interaction of qualitative and quantitative knowledge in analyzing thermodynamic cycles, and an experiment on building a natural language interface to qualitative reasoning is reported. Finally, some recommendations are made for future research.

Computational modelling of multi-cell migration in a multi-signalling substrate

International Nuclear Information System (INIS)

Mousavi, Seyed Jamaleddin; Doblaré, Manuel; Doweidar, Mohamed Hamdy

2014-01-01

Cell migration is a vital process in many biological phenomena ranging from wound healing to tissue regeneration. Over the past few years, it has been proven that in addition to cell–cell and cell-substrate mechanical interactions (mechanotaxis), cells can be driven by thermal, chemical and/or electrical stimuli. A numerical model was recently presented by the authors to analyse single cell migration in a multi-signalling substrate. That work is here extended to include multi-cell migration due to cell–cell interaction in a multi-signalling substrate under different conditions. This model is based on balancing the forces that act on the cell population in the presence of different guiding cues. Several numerical experiments are presented to illustrate the effect of different stimuli on the trajectory and final location of the cell population within a 3D heterogeneous multi-signalling substrate. Our findings indicate that although multi-cell migration is relatively similar to single cell migration in some aspects, the associated behaviour is very different. For instance, cell–cell interaction may delay single cell migration towards effective cues while increasing the magnitude of the average net cell traction force as well as the local velocity. Besides, the random movement of a cell within a cell population is slightly greater than that of single cell migration. Moreover, higher electrical field strength causes the cell slug to flatten near the cathode. On the other hand, as with single cell migration, the existence of electrotaxis dominates mechanotaxis, moving the cells to the cathode or anode pole located at the free surface. The numerical results here obtained are qualitatively consistent with related experimental works. (paper)

Multi-attribute Evaluation of Website Quality in E-business Using an Integrated Fuzzy AHPTOPSIS Methodology

Directory of Open Access Journals (Sweden)

Tolga Kaya

2010-09-01

Full Text Available Success of an e-business company is strongly associated with the relative quality of its website compared to that of its competitors. The purpose of this study is to propose a multi-attribute e-business website quality evaluation methodology based on a modified fuzzy TOPSIS approach. In the proposed methodology, weights of the evaluation criteria are generated by a fuzzy AHP procedure. In performance evaluation problems, the judgments of the experts may usually be vague in form. As fuzzy logic can successfully deal with this kind of uncertainty in human preferences, both classical TOPSIS and classical AHP procedures are implemented under fuzzy environment. The proposed TOPSIS-AHP methodology has successfully been applied to a multi-attribute website quality evaluation problem in Turkish e-business market. Nine sub-criteria under four main categories are used in the evaluation of the most popular e-business websites of Turkey. A sensitivity analysis is also provided.

Selection of key terrain attributes for SOC model

DEFF Research Database (Denmark)

Greve, Mogens Humlekrog; Adhikari, Kabindra; Chellasamy, Menaka

As an important component of the global carbon pool, soil organic carbon (SOC) plays an important role in the global carbon cycle. SOC pool is the basic information to carry out global warming research, and needs to sustainable use of land resources. Digital terrain attributes are often use...... was selected, total 2,514,820 data mining models were constructed by 71 differences grid from 12m to 2304m and 22 attributes, 21 attributes derived by DTM and the original elevation. Relative importance and usage of each attributes in every model were calculated. Comprehensive impact rates of each attribute...

Selection methodology for LWR safety R and D programs and proposals. Volume III. User's manual for the multi-attribute utility package (MAUP)

International Nuclear Information System (INIS)

Hale, M.; Turnage, J.J.; Husseiny, A.A.; Ritzman, R.L.

1981-02-01

The computer program which was developed to apply the multi-attribute utility (MAU) methodology to the selection of LWR safety R and D programs and proposals is described. An overview of the MAU method is presented, followed by a description of the steps incorporated in developing individual modules for use in the multi-attribute utility package (MAUP). Each module is described complete with usage information and an example of computer output

Multi-attribute evaluation and choice of alternatives for surplus weapons-usable plutonium disposition at uncertainty

International Nuclear Information System (INIS)

Kosterev, V.V.; Bolyatko, V.V.; Khajretdinov, S.I.; Averkin, A.N.

2014-01-01

The problem of surplus weapons-usable plutonium disposition is formalized as a multi-attribute problem of a choice of alternatives from a set of possible alternatives under fuzzy conditions. Evaluation and ordering of alternatives for the surplus weapons-usable plutonium disposition and sensitivity analysis are carried out at uncertainty [ru

A multi-level qualitative analysis of Telehomecare in Ontario: challenges and opportunities.

Science.gov (United States)

Hunting, Gemma; Shahid, Nida; Sahakyan, Yeva; Fan, Iris; Moneypenny, Crystal R; Stanimirovic, Aleksandra; North, Taylor; Petrosyan, Yelena; Krahn, Murray D; Rac, Valeria E

2015-12-09

Despite research demonstrating the potential effectiveness of Telehomecare for people with Chronic Obstructive Pulmonary Disease and Heart Failure, broad-scale comprehensive evaluations are lacking. This article discusses the qualitative component of a mixed-method program evaluation of Telehomecare in Ontario, Canada. The objective of the qualitative component was to explore the multi-level factors and processes which facilitate or impede the implementation and adoption of the program across three regions where it was first implemented. The study employs a multi-level framework as a conceptual guide to explore the facilitators and barriers to Telehomecare implementation and adoption across five levels: technology, patients, providers, organizations, and structures. In-depth semi-structured interviews and ethnographic observations with program stakeholders, as well as a Telehomecare document review were used to elicit key themes. Study participants (n = 89) included patients and/or informal caregivers (n = 39), health care providers (n = 23), technicians (n = 2), administrators (n = 12), and decision makers (n = 13) across three different Local Health Integration Networks in Ontario. Key facilitators to Telehomecare implementation and adoption at each level of the multi-level framework included: user-friendliness of Telehomecare technology, patient motivation to participate in the program, support for Telehomecare providers, the integration of Telehomecare into broader health service provision, and comprehensive program evaluation. Key barriers included: access-related issues to using the technology, patient language (if not English or French), Telehomecare provider time limitations, gaps in health care provision for patients, and structural barriers to patient participation related to geography and social location. Though Telehomecare has the potential to positively impact patient lives and strengthen models of health care provision, a

Multi-attribute criteria applied to electric generation energy system analysis LDRD.

Energy Technology Data Exchange (ETDEWEB)

Kuswa, Glenn W.; Tsao, Jeffrey Yeenien; Drennen, Thomas E.; Zuffranieri, Jason V.; Paananen, Orman Henrie; Jones, Scott A.; Ortner, Juergen G. (DLR, German Aerospace, Cologne); Brewer, Jeffrey D.; Valdez, Maximo M.

2005-10-01

This report began with a Laboratory-Directed Research and Development (LDRD) project to improve Sandia National Laboratories multidisciplinary capabilities in energy systems analysis. The aim is to understand how various electricity generating options can best serve needs in the United States. The initial product is documented in a series of white papers that span a broad range of topics, including the successes and failures of past modeling studies, sustainability, oil dependence, energy security, and nuclear power. Summaries of these projects are included here. These projects have provided a background and discussion framework for the Energy Systems Analysis LDRD team to carry out an inter-comparison of many of the commonly available electric power sources in present use, comparisons of those options, and efforts needed to realize progress towards those options. A computer aid has been developed to compare various options based on cost and other attributes such as technological, social, and policy constraints. The Energy Systems Analysis team has developed a multi-criteria framework that will allow comparison of energy options with a set of metrics that can be used across all technologies. This report discusses several evaluation techniques and introduces the set of criteria developed for this LDRD.

Acknowleding attributes that enable the career academic nurse to thrive in the tertiary education sector: A qualitative systematic review.

Science.gov (United States)

Wyllie, Aileen; DiGiacomo, Michelle; Jackson, Debra; Davidson, Patricia; Phillips, Jane

2016-10-01

To optimise the career development in early career academic nurses by providing an overview of the attributes necessary for success. Evidence of early prospective career planning is necessary to optimise success in the tertiary sector. This is particularly important for nurse academics given the profession's later entry into academia, the ageing nursing workforce and the continuing global shortage of nurses. A qualitative systematic review. Academic Search Complete, CINAHL, Medline, ERIC, Professional Development Collection and Google Scholar databases were searched; resulting in the inclusion of nine qualitative nurse-only focussed studies published between 2004 and 2014. The studies were critically appraised and the data thematically analysed. Three abilities were identified as important to the early career academic nurse: a willingness to adapt to change, an intention to pursue support and embodying resilience. These abilities give rise to attributes that are recommended as key to successful academic career development for those employed on a continuing academic basis. The capacity to rely on one's own capabilities is becoming seen as increasingly important. It is proposed that recognition of these attributes, their skilful application and monitoring outlined in the review are recommended for a successful career in academia. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Use of a multi-attribute utility theory for evaluating the best coolant material in transmutation reactors

International Nuclear Information System (INIS)

Yu, Dong Han; Han, Suk Joong; Kim, Do Hyung; Park, Won Suk

1998-12-01

In order to develop and design a good transmutation system, it is necessary first to select the best available coolant material for a reactor coolant system. Choosing the best coolant material may not be easy since there are several criteria associated with thermal performance, safety problem, cost problem, neutronic aspects. etc. The best option should be chosen based on the maximization of our needs in this situation. It is a challenging task. Decision theory can be employed to solve this type of problem. This report presents the feasibility study for evaluating the best coolant material in transmutation reactors based on the multi=attribute utility theory. The main problem presented here is how to logically evaluate candidate coolant materials under multiple criteria such as thermal performance, safety problem, cost problem, cost problem, neutronic aspects, etc. Since the current problem involves multiple criteria or attributes, first of all, the multi-attribute utility theory (MAUT) such as SMART and AHP has been extensively reviewed. Then, many candidate coolant material for transmutation reactors have been identified. The next step is to construct a value tree that express to reflect the relative importance of the attributes for overall evaluation. Finally, given these assignments, the final goal were obtained by manipulating these ranks through the value tree. The proposed approach is intended to help people be rational and logical in making decisions such complex tasks. (author). 8 refs., 7 tabs., 22 figs

A multi-attribute vertical handoff scheme for heterogeneous wireless networks

Directory of Open Access Journals (Sweden)

JI Xiaolong

2014-04-01

Full Text Available In order to meet the user demand for different services as well as to mitigate the Ping-pong effect caused by vertical handoff for wireless network,a multi-attribute vertical handoff scheme for heterogeneous wireless network is proposed.In the algorithm,a fuzzy logic method is used to make pre-decision.The optimal handoff target network is selected by a cost function of network which uses an Analytic Hierarchy Process to calculate the weights of SNR,delay,cost and user preference in different business scenarios.Simulation is performed in the environment which is overlapped by WiMAX and UMTS networks.Results show that the proposed approach can effectively reduce the number of handoff and power consumption in a condition to satisfy the user needs.

Predictive user modeling with actionable attributes

NARCIS (Netherlands)

Zliobaite, I.; Pechenizkiy, M.

2013-01-01

Different machine learning techniques have been proposed and used for modeling individual and group user needs, interests and preferences. In the traditional predictive modeling instances are described by observable variables, called attributes. The goal is to learn a model for predicting the target

Multi-Attribute Decision Making Based on Several Trigonometric Hamming Similarity Measures under Interval Rough Neutrosophic Environment

Directory of Open Access Journals (Sweden)

Surapati Pramanik

2018-03-01

Full Text Available In this paper, the sine, cosine and cotangent similarity measures of interval rough neutrosophic sets is proposed. Some properties of the proposed measures are discussed. We have proposed multi attribute decision making approaches based on proposed similarity measures. To demonstrate the applicability, a numerical example is solved.

Analysis of the Usage of Magnetic Force-directed Approach and Visual Techniques for Interactive Context-based Drawing of Multi-attributed Graphs

Directory of Open Access Journals (Sweden)

Zabiniako Vitaly

2014-12-01

Full Text Available In this article, the authors perform an analysis in order to assess adaptation of magnetic force-directed algorithms for context-based information extraction from multi-attributed graphs during visualization sessions. Theoretic standings behind magnetic force-directed approach are stated together with review on how particular features of respective algorithms in combination with appropriate visual techniques are especially suitable for improved processing and presenting of knowledge that is captured in form of graphs. The complexity of retrieving multi-attributed information within the proposed approach is handled with dedicated tools, such as selective attraction of nodes to MFE (Magnetic Force Emitter based on search criteria, localization of POI (Point of Interest regions, graph node anchoring, etc. Implicit compatibility of aforementioned tools with interactive nature of data exploration is distinguished. Description of case study, based on bibliometric network analysis is given, which is followed by the review of existing related works in this field. Conclusions are made and further studies in the field of visualization of multi-attributed graphs are defined.

Renewable energy selection Matrix based on multi-attribute analysis for fish preservation

International Nuclear Information System (INIS)

Vega-Clavijo, Lili Tatiana; Prías-Caicedo, Omar Fredy; Sierra-Vargas, Fabio Emiro

2016-01-01

The article presents the application of the methodology of multi attribute utility theory validated by a matrix system established by researchers, to identify the best alternative of energy supply to 10 kwe in the generation of ice for preservation of fish in coastal and rural areas of the Chocó. The comparison between the potentials of different renewable energy sources and diesel, natural gas and propane fuels took place, based on economic, technological, environmental and social criteria, being validated by experts and the community on field work. It was concluded that the best alternative is diesel followed by biomass. (author)

Qualitative and quantitative comparison of geostatistical techniques of porosity prediction from the seismic and logging data: a case study from the Blackfoot Field, Alberta, Canada

Science.gov (United States)

Maurya, S. P.; Singh, K. H.; Singh, N. P.

2018-05-01

In present study, three recently developed geostatistical methods, single attribute analysis, multi-attribute analysis and probabilistic neural network algorithm have been used to predict porosity in inter well region for Blackfoot field, Alberta, Canada, an offshore oil field. These techniques make use of seismic attributes, generated by model based inversion and colored inversion techniques. The principle objective of the study is to find the suitable combination of seismic inversion and geostatistical techniques to predict porosity and identification of prospective zones in 3D seismic volume. The porosity estimated from these geostatistical approaches is corroborated with the well log porosity. The results suggest that all the three implemented geostatistical methods are efficient and reliable to predict the porosity but the multi-attribute and probabilistic neural network analysis provide more accurate and high resolution porosity sections. A low impedance (6000-8000 m/s g/cc) and high porosity (> 15%) zone is interpreted from inverted impedance and porosity sections respectively between 1060 and 1075 ms time interval and is characterized as reservoir. The qualitative and quantitative results demonstrate that of all the employed geostatistical methods, the probabilistic neural network along with model based inversion is the most efficient method for predicting porosity in inter well region.

A Qualitative Multi-Site Case Study: Examining Principals' Leadership Styles and School Performance

Science.gov (United States)

Preyear, Loukisha

2015-01-01

The purpose of this qualitative multi-site case study was to explore the impact of principals' leadership styles on student academic achievement in a high-poverty low-performing school district in Louisiana. A total of 17 participants, principals and teachers, from this school district were used in this study. Data source triangulation of…

Helping boys at-risk of criminal activity: qualitative results of a multi-component intervention

Directory of Open Access Journals (Sweden)

Brennan Erin

2011-05-01

Full Text Available Abstract Background This qualitative study examines parent and child experiences of participation in a multi-component community-based program aimed at reducing offending behaviour, and increasing social competence in boys 6 to 11 years old in Hamilton, Ontario, Canada. The program builds on the concept of crime prevention through social development, and includes structured groups for the identified boy, parents, and siblings. Methods A sample of 35 families participating in the multi-component program took part in the qualitative study. Individual interviews with the boys, parents and siblings asked about changes in themselves, relationships with family and peers, and school after the group. Interviews were taped, transcribed and content analysis was used to code and interpret the data. Results Parents reported improvement in parenting skills and attainment of more effective communication skills, particularly with their children. Parents also found the relationships they formed with other parents in the program and the advice that they gained to be beneficial. Boys who participated in the program also benefited, with both parents and boys reporting improvements in boys' anger management skills, social skills, impulse control, and ability to recognize potentially volatile situations. Both parents and boys described overall improvement in family relationships and school-related success. Conclusions The qualitative data revealed that parents and boys participating in the multi-component program perceived improvements in a number of specific areas, including social competence of the boys. This has not been demonstrated as clearly in other evaluations of the program.

Assessing the empirical validity of alternative multi-attribute utility measures in the maternity context

Directory of Open Access Journals (Sweden)

Morrell Jane

2009-05-01

Full Text Available Abstract Background Multi-attribute utility measures are preference-based health-related quality of life measures that have been developed to inform economic evaluations of health care interventions. The objective of this study was to compare the empirical validity of two multi-attribute utility measures (EQ-5D and SF-6D based on hypothetical preferences in a large maternity population in England. Methods Women who participated in a randomised controlled trial of additional postnatal support provided by trained community support workers represented the study population for this investigation. The women were asked to complete the EQ-5D descriptive system (which defines health-related quality of life in terms of five dimensions: mobility, self care, usual activities, pain/discomfort and anxiety/depression and the SF-36 (which defines health-related quality of life, using 36 items, across eight dimensions: physical functioning, role limitations (physical, social functioning, bodily pain, general health, mental health, vitality and role limitations (emotional at six months postpartum. Their responses were converted into utility scores using the York A1 tariff set and the SF-6D utility algorithm, respectively. One-way analysis of variance was used to test the hypothetically-constructed preference rule that each set of utility scores differs significantly by self-reported health status (categorised as excellent, very good, good, fair or poor. The degree to which EQ-5D and SF-6D utility scores reflected alternative dichotomous configurations of self-reported health status and the Edinburgh Postnatal Depression Scale score was tested using the relative efficiency statistic and receiver operating characteristic (ROC curves. Results The mean utility score for the EQ-5D was 0.861 (95% CI: 0.844, 0.877, whilst the mean utility score for the SF-6D was 0.809 (95% CI: 0.796, 0.822, representing a mean difference in utility score of 0.052 (95% CI: 0.040, 0

Using the framework method for the analysis of qualitative data in multi-disciplinary health research.

Science.gov (United States)

Gale, Nicola K; Heath, Gemma; Cameron, Elaine; Rashid, Sabina; Redwood, Sabi

2013-09-18

The Framework Method is becoming an increasingly popular approach to the management and analysis of qualitative data in health research. However, there is confusion about its potential application and limitations. The article discusses when it is appropriate to adopt the Framework Method and explains the procedure for using it in multi-disciplinary health research teams, or those that involve clinicians, patients and lay people. The stages of the method are illustrated using examples from a published study. Used effectively, with the leadership of an experienced qualitative researcher, the Framework Method is a systematic and flexible approach to analysing qualitative data and is appropriate for use in research teams even where not all members have previous experience of conducting qualitative research.

Development of slim-maud: a multi-attribute utility approach to human reliability evaluation

International Nuclear Information System (INIS)

Embrey, D.E.

1984-01-01

This paper describes further work on the Success Likelihood Index Methodology (SLIM), a procedure for quantitatively evaluating human reliability in nuclear power plants and other systems. SLIM was originally developed by Human Reliability Associates during an earlier contract with Brookhaven National Laboratory (BNL). A further development of SLIM, SLIM-MAUD (Multi-Attribute Utility Decomposition) is also described. This is an extension of the original approach using an interactive, computer-based system. All of the work described in this report was supported by the Human Factors and Safeguards Branch of the US Nuclear Regulatory Commission

How leadership attributes influence employee loyalty in the aerospace industry: An exploratory qualitative inquiry

Science.gov (United States)

Harrison, Marriel

The influence leaders have on employee loyalty in the aerospace industry was examined through exploratory, qualitative inquiry. In-depth, semi-structured interviews were conducted to ascertain the influence of six leadership attributes on loyalty. These specific leadership attributes were addressed based on key themes from the scholarly leadership research and included communication, trust, accountability, understanding, compassion, and recognition. Data were analyzed to identify common themes and patterns among the 21 study participants. Based on the study findings, the majority of participants expressed that they want leaders to communicate--and to do so often and concisely. Participants also voiced that communication was a central component in resolving many of the problems associated with loyalty, such as clarity of direction or sense of inclusion in the organization. The central themes derived from the research include the following: (a) employee loyalty no longer exists when organizational leadership fails to challenge or empower employees or create an opportunity for growth, (b) effective leaders inspire employees by sharing the vision of an organization and including employees in the decision-making process, and (c) organizational culture, values, and effective leadership play an integral role in employee loyalty and long-term commitment to the organization.

Merging information from multi-model flood projections in a hierarchical Bayesian framework

Science.gov (United States)

Le Vine, Nataliya

2016-04-01

Multi-model ensembles are becoming widely accepted for flood frequency change analysis. The use of multiple models results in large uncertainty around estimates of flood magnitudes, due to both uncertainty in model selection and natural variability of river flow. The challenge is therefore to extract the most meaningful signal from the multi-model predictions, accounting for both model quality and uncertainties in individual model estimates. The study demonstrates the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach facilitates explicit treatment of shared multi-model discrepancy as well as the probabilistic nature of the flood estimates, by treating the available models as a sample from a hypothetical complete (but unobserved) set of models. The advantages of the approach are: 1) to insure an adequate 'baseline' conditions with which to compare future changes; 2) to reduce flood estimate uncertainty; 3) to maximize use of statistical information in circumstances where multiple weak predictions individually lack power, but collectively provide meaningful information; 4) to adjust multi-model consistency criteria when model biases are large; and 5) to explicitly consider the influence of the (model performance) stationarity assumption. Moreover, the analysis indicates that reducing shared model discrepancy is the key to further reduction of uncertainty in the flood frequency analysis. The findings are of value regarding how conclusions about changing exposure to flooding are drawn, and to flood frequency change attribution studies.

A General Attribute and Rule Based Role-Based Access Control Model

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Growing numbers of users and many access control policies which involve many different resource attributes in service-oriented environments bring various problems in protecting resource. This paper analyzes the relationships of resource attributes to user attributes in all policies, and propose a general attribute and rule based role-based access control(GAR-RBAC) model to meet the security needs. The model can dynamically assign users to roles via rules to meet the need of growing numbers of users. These rules use different attribute expression and permission as a part of authorization constraints, and are defined by analyzing relations of resource attributes to user attributes in many access policies that are defined by the enterprise. The model is a general access control model, and can support many access control policies, and also can be used to wider application for service. The paper also describes how to use the GAR-RBAC model in Web service environments.

Modelling innovation performance of European regions using multi-output neural networks.

Science.gov (United States)

Hajek, Petr; Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

Modelling innovation performance of European regions using multi-output neural networks.

Directory of Open Access Journals (Sweden)

Petr Hajek

Full Text Available Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

A Quadrupole Dalton-based multi-attribute method for product characterization, process development, and quality control of therapeutic proteins.

Science.gov (United States)

Xu, Weichen; Jimenez, Rod Brian; Mowery, Rachel; Luo, Haibin; Cao, Mingyan; Agarwal, Nitin; Ramos, Irina; Wang, Xiangyang; Wang, Jihong

2017-10-01

During manufacturing and storage process, therapeutic proteins are subject to various post-translational modifications (PTMs), such as isomerization, deamidation, oxidation, disulfide bond modifications and glycosylation. Certain PTMs may affect bioactivity, stability or pharmacokinetics and pharmacodynamics profile and are therefore classified as potential critical quality attributes (pCQAs). Identifying, monitoring and controlling these PTMs are usually key elements of the Quality by Design (QbD) approach. Traditionally, multiple analytical methods are utilized for these purposes, which is time consuming and costly. In recent years, multi-attribute monitoring methods have been developed in the biopharmaceutical industry. However, these methods combine high-end mass spectrometry with complicated data analysis software, which could pose difficulty when implementing in a quality control (QC) environment. Here we report a multi-attribute method (MAM) using a Quadrupole Dalton (QDa) mass detector to selectively monitor and quantitate PTMs in a therapeutic monoclonal antibody. The result output from the QDa-based MAM is straightforward and automatic. Evaluation results indicate this method provides comparable results to the traditional assays. To ensure future application in the QC environment, this method was qualified according to the International Conference on Harmonization (ICH) guideline and applied in the characterization of drug substance and stability samples. The QDa-based MAM is shown to be an extremely useful tool for product and process characterization studies that facilitates facile understanding of process impact on multiple quality attributes, while being QC friendly and cost-effective.

Modeling Multi-Level Systems

CERN Document Server

Iordache, Octavian

2011-01-01

This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale sy...

Modeling and Event-Driven Simulation of Coordinated Multi-Point in LTE-Advanced with Constrained Backhaul

DEFF Research Database (Denmark)

Artuso, Matteo; Christiansen, Henrik Lehrmann

2014-01-01

multi-point joint transmission (CoMP JT). Field tests are generally considered impractical and costly for CoMP JT, therefore the need to provide a comprehensive and high-fidelity computer model to understand the impact of different design attributes and the applicability use cases. This paper presents...

Multiplicative Attribute Graph Model of Real-World Networks

Energy Technology Data Exchange (ETDEWEB)

Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)

2010-10-20

Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.

Advanced GPR imaging of sedimentary features: integrated attribute analysis applied to sand dunes

Science.gov (United States)

Zhao, Wenke; Forte, Emanuele; Fontolan, Giorgio; Pipan, Michele

2018-04-01

We evaluate the applicability and the effectiveness of integrated GPR attribute analysis to image the internal sedimentary features of the Piscinas Dunes, SW Sardinia, Italy. The main objective is to explore the limits of GPR techniques to study sediment-bodies geometry and to provide a non-invasive high-resolution characterization of the different subsurface domains of dune architecture. On such purpose, we exploit the high-quality Piscinas data-set to extract and test different attributes of the GPR trace. Composite displays of multi-attributes related to amplitude, frequency, similarity and textural features are displayed with overlays and RGB mixed models. A multi-attribute comparative analysis is used to characterize different radar facies to better understand the characteristics of internal reflection patterns. The results demonstrate that the proposed integrated GPR attribute analysis can provide enhanced information about the spatial distribution of sediment bodies, allowing an enhanced and more constrained data interpretation.

Multi-valley effective mass theory for device-level modeling of open quantum dynamics

Science.gov (United States)

Jacobson, N. Tobias; Baczewski, Andrew D.; Frees, Adam; Gamble, John King; Montano, Ines; Moussa, Jonathan E.; Muller, Richard P.; Nielsen, Erik

2015-03-01

Simple models for semiconductor-based quantum information processors can provide useful qualitative descriptions of device behavior. However, as experimental implementations have matured, more specific guidance from theory has become necessary, particularly in the form of quantitatively reliable yet computationally efficient modeling. Besides modeling static device properties, improved characterization of noisy gate operations requires a more sophisticated description of device dynamics. Making use of recent developments in multi-valley effective mass theory, we discuss device-level simulations of the open system quantum dynamics of a qubit interacting with phonons and other noise sources. Sandia is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy National Nuclear Security Administration under Contract No. DE-AC04-94AL85000.

Clustered iterative stochastic ensemble method for multi-modal calibration of subsurface flow models

KAUST Repository

Elsheikh, Ahmed H.

2013-05-01

A novel multi-modal parameter estimation algorithm is introduced. Parameter estimation is an ill-posed inverse problem that might admit many different solutions. This is attributed to the limited amount of measured data used to constrain the inverse problem. The proposed multi-modal model calibration algorithm uses an iterative stochastic ensemble method (ISEM) for parameter estimation. ISEM employs an ensemble of directional derivatives within a Gauss-Newton iteration for nonlinear parameter estimation. ISEM is augmented with a clustering step based on k-means algorithm to form sub-ensembles. These sub-ensembles are used to explore different parts of the search space. Clusters are updated at regular intervals of the algorithm to allow merging of close clusters approaching the same local minima. Numerical testing demonstrates the potential of the proposed algorithm in dealing with multi-modal nonlinear parameter estimation for subsurface flow models. © 2013 Elsevier B.V.

A Literature Review and Compilation of Nuclear Waste Management System Attributes for Use in Multi-Objective System Evaluations.

Energy Technology Data Exchange (ETDEWEB)

Kalinina, Elena Arkadievna [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Samsa, Michael [Argonne National Lab. (ANL), Argonne, IL (United States)

2015-11-01

The purpose of this work was to compile a comprehensive initial set of potential nuclear waste management system attributes. This initial set of attributes is intended to serve as a starting point for additional consideration by system analysts and planners to facilitate the development of a waste management system multi-objective evaluation framework based on the principles and methodology of multi-attribute utility analysis. The compilation is primarily based on a review of reports issued by the Canadian Nuclear Waste Management Organization (NWMO) and the Blue Ribbon Commission on America's Nuclear Future (BRC), but also an extensive review of the available literature for similar and past efforts as well. Numerous system attributes found in different sources were combined into a single objectives-oriented hierarchical structure. This study provides a discussion of the data sources and the descriptions of the hierarchical structure. A particular focus of this study was on collecting and compiling inputs from past studies that involved the participation of various external stakeholders. However, while the important role of stakeholder input in a country's waste management decision process is recognized in the referenced sources, there are only a limited number of in-depth studies of the stakeholders' differing perspectives. Compiling a comprehensive hierarchical listing of attributes is a complex task since stakeholders have multiple and often conflicting interests. The BRC worked for two years (January 2010 to January 2012) to "ensure it has heard from as many points of view as possible." The Canadian NWMO study took four years and ample resources, involving national and regional stakeholders' dialogs, internet-based dialogs, information and discussion sessions, open houses, workshops, round tables, public attitude research, website, and topic reports. The current compilation effort benefited from the distillation of these many varied inputs

A Literature Review and Compilation of Nuclear Waste Management System Attributes for Use in Multi-Objective System Evaluations

International Nuclear Information System (INIS)

Kalinina, Elena Arkadievna; Samsa, Michael

2015-01-01

The purpose of this work was to compile a comprehensive initial set of potential nuclear waste management system attributes. This initial set of attributes is intended to serve as a starting point for additional consideration by system analysts and planners to facilitate the development of a waste management system multi-objective evaluation framework based on the principles and methodology of multi-attribute utility analysis. The compilation is primarily based on a review of reports issued by the Canadian Nuclear Waste Management Organization (NWMO) and the Blue Ribbon Commission on America's Nuclear Future (BRC), but also an extensive review of the available literature for similar and past efforts as well. Numerous system attributes found in different sources were combined into a single objectives-oriented hierarchical structure. This study provides a discussion of the data sources and the descriptions of the hierarchical structure. A particular focus of this study was on collecting and compiling inputs from past studies that involved the participation of various external stakeholders. However, while the important role of stakeholder input in a country's waste management decision process is recognized in the referenced sources, there are only a limited number of in-depth studies of the stakeholders' differing perspectives. Compiling a comprehensive hierarchical listing of attributes is a complex task since stakeholders have multiple and often conflicting interests. The BRC worked for two years (January 2010 to January 2012) to 'ensure it has heard from as many points of view as possible.' The Canadian NWMO study took four years and ample resources, involving national and regional stakeholders' dialogs, internet-based dialogs, information and discussion sessions, open houses, workshops, round tables, public attitude research, website, and topic reports. The current compilation effort benefited from the distillation of these many varied inputs conducted by the

New paradigms for Salmonella source attribution based on microbial subtyping.

Science.gov (United States)

Mughini-Gras, Lapo; Franz, Eelco; van Pelt, Wilfrid

2018-05-01

Microbial subtyping is the most common approach for Salmonella source attribution. Typically, attributions are computed using frequency-matching models like the Dutch and Danish models based on phenotyping data (serotyping, phage-typing, and antimicrobial resistance profiling). Herewith, we critically review three major paradigms facing Salmonella source attribution today: (i) the use of genotyping data, particularly Multi-Locus Variable Number of Tandem Repeats Analysis (MLVA), which is replacing traditional Salmonella phenotyping beyond serotyping; (ii) the integration of case-control data into source attribution to improve risk factor identification/characterization; (iii) the investigation of non-food sources, as attributions tend to focus on foods of animal origin only. Population genetics models or simplified MLVA schemes may provide feasible options for source attribution, although there is a strong need to explore novel modelling options as we move towards whole-genome sequencing as the standard. Classical case-control studies are enhanced by incorporating source attribution results, as individuals acquiring salmonellosis from different sources have different associated risk factors. Thus, the more such analyses are performed the better Salmonella epidemiology will be understood. Reparametrizing current models allows for inclusion of sources like reptiles, the study of which improves our understanding of Salmonella epidemiology beyond food to tackle the pathogen in a more holistic way. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling

Science.gov (United States)

Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.

2016-11-01

A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is

Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

KAUST Repository

Xu, Zhiqiang

2017-02-16

Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

KAUST Repository

Xu, Zhiqiang; Cheng, James; Xiao, Xiaokui; Fujimaki, Ryohei; Muraoka, Yusuke

2017-01-01

Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

[Comparative study on promoting blood effects of Danshen-Honghua herb pair with different preparations based on chemometrics and multi-attribute comprehensive index methods].

Science.gov (United States)

Qu, Cheng; Tang, Yu-Ping; Shi, Xu-Qin; Zhou, Gui-Sheng; Shang, Er-Xin; Shang, Li-Li; Guo, Jian-Ming; Liu, Pei; Zhao, Jing; Zhao, Bu-Chang; Duan, Jin-Ao

2017-08-01

To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(DH) herb pair with different preparations (alcohol, 50% alcohol and water) on blood rheology and coagulation functions in acute blood stasis rats, and optimize the best preparation method of DH based on principal component analysis(PCA), hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods. Ice water bath and subcutaneous injection of adrenaline were both used to establish the acute blood stasis rat model. Then the blood stasis rats were administrated intragastrically with DH (alcohol, 50% alcohol and water) extracts. The whole blood viscosity(WBV), plasma viscosity(PV), erythrocyte sedimentation rate(ESR) and haematocrit(HCT) were tested to observe the effects of DH herb pair with different preparations and doses on hemorheology of blood stasis rats; the activated partial thromboplastin time(APTT), thrombin time(TT), prothrombin time(PT), and plasma fibrinogen(FIB) were tested to observe the effects of DH herb pair with different preparations on blood coagulation function and platelet aggregation of blood stasis rats. Then PCA, hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods were all used to comprehensively evaluate the total promoting blood circulation and removing blood stasis effects of DH herb pair with different preparations. The hemorheological indexes and coagulation parameters of model group had significant differences with normal blank group. As compared with the model group, the DH herb pair with different preparations at low, middle and high doses could improve the blood hemorheology indexes and coagulation parameters in acute blood stasis rats with dose-effect relation. Based on the PCA, hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods, the high dose group of 50% alcohol extract had the best effect of promoting blood circulation and removing blood

Attributing foodborne salmonellosis in humans to animal reservoirs in the European Union using a multi-country stochastic model

DEFF Research Database (Denmark)

de Knegt, Leonardo; Pires, Sara Monteiro; Hald, Tine

2015-01-01

A Bayesian modelling approach comparing the occurrence of Salmonella serovars in animals and humans was used to attribute salmonellosis cases to broilers, turkeys, pigs, laying hens, travel and outbreaks in 24 European Union countries. Salmonella data for animals and humans, covering the period f......, highlighting differences in the epidemiology of Salmonella, surveillance focus and eating habits across the European Union....

Multi-criteria decision making with linguistic labels: a comparison of two methodologies applied to energy planning

OpenAIRE

Afsordegan, Arayeh; Sánchez Soler, Monica; Agell Jané, Núria; Cremades Oliver, Lázaro Vicente; Zahedi, Siamak

2014-01-01

This paper compares two multi-criteria decision making (MCDM) approaches based on linguistic label assessment. The first approach consists of a modified fuzzy TOPSIS methodology introduced by Kaya and Kahraman in 2011. The second approach, introduced by Agell et al. in 2012, is based on qualitative reasoning techniques for ranking multi-attribute alternatives in group decision-making with linguistic labels. Both approaches are applied to a case of assessment and selection of the most suita...

Assessing the Impact of Urban Improvement on Housing Values: A Hedonic Pricing and Multi-Attribute Analysis Model for the Historic Centre of Venice

Directory of Open Access Journals (Sweden)

Paolo Rosato

2017-11-01

Full Text Available The Hedonic Pricing Method is one of the principal assessment methods for evaluating services and resources not normally exchanged on the market. However, the method is often unable to account for the great variety of qualities in an urban context and faces scarce and heterogeneous market data. This paper presents a model for the valuation of benefits generated by environmental and urban improvement investments adopting a mixed hedonic-multi-attribute procedure for modeling a value function of urban real estate values. The peculiarity of the model is that the independent variables are aggregated indicators, which synthetize more detailed characteristics. Using the expertise of real estate agents, all relevant variables influencing real estate values were weighted and synthetized in a set of cardinal indicators. Next, market prices were used to calibrate a hedonic function that transforms the cardinal indicators into real estate values. The valuation model was integrated into a GIS for mapping the housing value, and its variation induced by urban investment. The proposed model pointed out plausible and robust results, in particular, the possibility to use any available information, such as location, position, technical and economic characteristics of buildings, and organize it in a flexible and transparent way, and to keep evident the role of each characteristic through the hierarchical structure of the model. The model was applied to the real estate market of Venice to test the effects of the MOSE project (Electromechanical Experimental Module for the protection of Venice from high tides. The results of the application showed a relevant increase in real estate values in the center of Venice, especially related to property in ground floor units, of about 1.4 billion €.

Cross Entropy Measures of Bipolar and Interval Bipolar Neutrosophic Sets and Their Application for Multi-Attribute Decision-Making

Directory of Open Access Journals (Sweden)

Surapati Pramanik

2018-03-01

Full Text Available The bipolar neutrosophic set is an important extension of the bipolar fuzzy set. The bipolar neutrosophic set is a hybridization of the bipolar fuzzy set and neutrosophic set. Every element of a bipolar neutrosophic set consists of three independent positive membership functions and three independent negative membership functions. In this paper, we develop cross entropy measures of bipolar neutrosophic sets and prove their basic properties. We also define cross entropy measures of interval bipolar neutrosophic sets and prove their basic properties. Thereafter, we develop two novel multi-attribute decision-making strategies based on the proposed cross entropy measures. In the decision-making framework, we calculate the weighted cross entropy measures between each alternative and the ideal alternative to rank the alternatives and choose the best one. We solve two illustrative examples of multi-attribute decision-making problems and compare the obtained result with the results of other existing strategies to show the applicability and effectiveness of the developed strategies. At the end, the main conclusion and future scope of research are summarized.

[Attributes and features of a community health model from the perspective of practitioners].

Science.gov (United States)

Dois, Angelina; Bravo, Paulina; Soto, Gabriela

2017-07-01

The Family and Community Health Model is based on three essential principles: user-centered care, comprehensive care and continuity of care. To describe the attributes and characteristics of the guiding principles of the Family and Community Health Model (FHM) from the perspective of primary care experts. This was a qualitative study. An electronic Delphi was conducted with 29 national experts on primary care. The experts agree that user centered care must be based on a psycho-social model integrating the multiple factors that influence health problems. It also must integrate patients' individual features, family and environmental issues. The proposed actions promote shared decision making. To promote integral care, anticipatory guidelines should be expanded and health care of patients with chronic conditions should be improved. Continuity of care should be promoted increasing working hours of medical centers and easing access to integrated electronic medical records, thereby generating efficient links between the different care levels. The results of the study can guide the clinical and administrative management of health teams, allowing the strengthening of primary health care according to the local realities.

A multi attribute decision making method for selection of optimal assembly line

Directory of Open Access Journals (Sweden)

B. Vijaya Ramnath

2011-01-01

Full Text Available With globalization, sweeping technological development, and increasing competition, customers are placing greater demands on manufacturers to increase quality, flexibility, on time delivery of product and less cost. Therefore, manufacturers must develop and maintain a high degree of coherence among competitive priorities, order winning criteria and improvement activities. Thus, the production managers are making an attempt to transform their organization by adopting familiar and beneficial management philosophies like cellular manufacturing (CM, lean manufacturing (LM, green manufacturing (GM, total quality management (TQM, agile manufacturing (AM, and just in time manufacturing (JIT. The main objective of this paper is to propose an optimal assembly method for an engine manufacturer’s assembly line in India. Currently, the Indian manufacturer is following traditional assembly method where the raw materials for assembly are kept along the sideways of conveyor line. It consumes more floor space, more work in process inventory, more operator's walking time and more operator's walking distance per day. In order to reduce the above mentioned wastes, lean kitting assembly is suggested by some managers. Another group of managers suggest JIT assembly as it consumes very less inventory cost compared to other types of assembly processes. Hence, a Multi-attribute decision making model namely analytical hierarchy process (AHP is applied to analyse the alternative assembly methods based on various important factors.

Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

Directory of Open Access Journals (Sweden)

Željko Stević

2017-11-01

Full Text Available Supply chain presents a very complex field involving a large number of participants. The aim of the complete supply chain is finding an optimum from the aspect of all participants, which is a rather complex task. In order to ensure optimum satisfaction for all participants, it is necessary that the beginning phase consists of correct evaluations and supplier selection. In this study, the supplier selection was performed in the construction company, on the basis of a new approach in the field of multi-criteria model. Weight coefficients were obtained by DEMATEL (Decision Making Trial and Evaluation Laboratory method, based on the rough numbers. Evaluation and the supplier selection were made on the basis of a new Rough EDAS (Evaluation based on Distance from Average Solution method, which presents one of the latest methods in this field. In order to determine the stability of the model and the applicability of the proposed Rough EDAS method, an extension of the COPRAS and MULTIMOORA method by rough numbers was also performed in this study, and the findings of the comparative analysis were presented. Besides the new approaches based on the extension by rough numbers, the results are also compared with the Rough MABAC (MultiAttributive Border Approximation area Comparison and Rough MAIRCA (MultiAttributive Ideal-Real Comparative Analysis. In addition, in the sensitivity analysis, 18 different scenarios were formed, the ones in which criteria change their original values. At the end of the sensitivity analysis, SCC (Spearman Correlation Coefficient of the obtained ranges was carried out, confirming the applicability of the proposed approaches.

Decision-making in irrigation networks: Selecting appropriate canal structures using multi-attribute decision analysis.

Science.gov (United States)

Hosseinzade, Zeinab; Pagsuyoin, Sheree A; Ponnambalam, Kumaraswamy; Monem, Mohammad J

2017-12-01

The stiff competition for water between agriculture and non-agricultural production sectors makes it necessary to have effective management of irrigation networks in farms. However, the process of selecting flow control structures in irrigation networks is highly complex and involves different levels of decision makers. In this paper, we apply multi-attribute decision making (MADM) methodology to develop a decision analysis (DA) framework for evaluating, ranking and selecting check and intake structures for irrigation canals. The DA framework consists of identifying relevant attributes for canal structures, developing a robust scoring system for alternatives, identifying a procedure for data quality control, and identifying a MADM model for the decision analysis. An application is illustrated through an analysis for automation purposes of the Qazvin irrigation network, one of the oldest and most complex irrigation networks in Iran. A survey questionnaire designed based on the decision framework was distributed to experts, managers, and operators of the Qazvin network and to experts from the Ministry of Power in Iran. Five check structures and four intake structures were evaluated. A decision matrix was generated from the average scores collected from the survey, and was subsequently solved using TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. To identify the most critical structure attributes for the selection process, optimal attribute weights were calculated using Entropy method. For check structures, results show that the duckbill weir is the preferred structure while the pivot weir is the least preferred. Use of the duckbill weir can potentially address the problem with existing Amil gates where manual intervention is required to regulate water levels during periods of flow extremes. For intake structures, the Neyrpic® gate and constant head orifice are the most and least preferred alternatives, respectively. Some advantages

Decision making in goverment tenders: A formalized qualitative model

Directory of Open Access Journals (Sweden)

Štěpán Veselý

2012-01-01

Full Text Available The paper presents a simple formalized qualitative model of government tenders (GTs. Qualitative models use just three values: Positive/Increasing, Zero/Constant and Negative/Decreasing. Such quantifiers of trends are the least information intensive. Qualitative models can be useful, since GT evaluation often includes such goals as e.g. efficiency of public purchasing, and variables as e.g. availability of relevant information or subjectivity of judgment, that are difficult to quantify. Hence, a significant fraction of available information about GTs is not of numerical nature, e.g. if availability of relevant information is decreasing then efficiency of public purchasing is decreasing as well. Such equationless relations are studied in this paper. A qualitative model of the function F(Goals, Variables is developed. The model has four goal functions, eight variables, and 39 equationless relations. The model is solved and seven solutions, i.e. scenarios are obtained. All qualitative states, including first and second qualitative derivatives with respect to time, of all variables are specified for each scenario. Any unsteady state behavior of the GT model is described by its transitional oriented graph. There are eight possible transitions among seven scenarios. No a priori knowledge of qualitative modeling is required on the reader’s part.

Application to Determination of Scholarship Worthiness Using Simple Multi Attribute Rating Technique and Merkle Hellman Method

Directory of Open Access Journals (Sweden)

Dicky Nofriansyah

2017-10-01

Full Text Available This research was focused on explaining how the concept of simple multi attribute rating technique method in a decision support system based on desktop programming to solve multi-criteria selection problem, especially Scholarship. The Merkle Hellman method is used for securing the results of choices made by the Smart process. The determination of PPA and BBP-PPA scholarship recipients on STMIK Triguna Dharma becomes a problem because it takes a long time in determining the decision. By adopting the SMART method, the application can make decisions quickly and precisely. The expected result of this research is the application can facilitate in overcoming the problems that occur concerning the determination of PPA and BBP-PPA scholarship recipients as well as assisting Student Affairs STMIK Triguna Dharma in making decisions quickly and accurately

Crucial contextual attributes of nursing leadership towards a care ethics.

Science.gov (United States)

Gustafsson, Lena-Karin; Stenberg, Maja

2017-06-01

It is of importance to understand and communicate caring ethics as a ground for qualitative caring environments. Research is needed on nursing attributes that are visible in nursing leadership since it may give bases for reflections related to the patterns of specific contexts. The aim of this study was to illuminate the meaning of crucial attributes in nursing leadership toward an ethical care of patients in psychiatric in-patient settings. The design of the study was descriptive and qualitative with a phenomenological hermeneutical approach. Participants and research context: The study comprised focus group interviews with nurses working in indoor psychiatric care who participated after giving informed consent. Ethical considerations: Since the topic and informants are not labeled as sensitive and subject to ethical approval, it is not covered by the ethics committee's aim and purpose according to Swedish law. However, careful procedures have been followed according to ethics expressed in the Declaration of Helsinki. When identifying the thematic structures, analysis resulted in three major themes: To supply, including the following aspects: to supply evidence, to supply common space, and to supply good structures; To support, including the following aspects: to be a role model, to show appreciation and care, and to harbor; To shield, including the following aspects: to advocate, to emit non-tolerance of unethical behavior, and to reprove. Leadership is challenging for nurses and plays an important role in ethical qualitative care. These findings should not be understood as a description about nurse manager's role, which probably has different attributes and more focus on an organizational level. Making the understanding about crucial attributes explicit, the nurse may receive confirmation and recognition of crucial attributes for ethical care in order to move toward an ethical care.

To eat and not be eaten: modelling resources and safety in multi-species animal groups.

Directory of Open Access Journals (Sweden)

Umesh Srinivasan

Full Text Available Using mixed-species bird flocks as an example, we model the payoffs for two types of species from participating in multi-species animal groups. Salliers feed on mobile prey, are good sentinels and do not affect prey capture rates of gleaners; gleaners feed on prey on substrates and can enhance the prey capture rate of salliers by flushing prey, but are poor sentinels. These functional types are known from various animal taxa that form multi-species associations. We model costs and benefits of joining groups for a wide range of group compositions under varying abundances of two types of prey-prey on substrates and mobile prey. Our model predicts that gleaners and salliers show a conflict of interest in multi-species groups, because gleaners benefit from increasing numbers of salliers in the group, whereas salliers benefit from increasing gleaner numbers. The model also predicts that the limits to size and variability in composition of multi-species groups are driven by the relative abundance of different types of prey, independent of predation pressure. Our model emphasises resources as a primary driver of temporal and spatial group dynamics, rather than reproductive activity or predation per se, which have hitherto been thought to explain patterns of multi-species group formation and cohesion. The qualitative predictions of the model are supported by empirical patterns from both terrestrial and marine multi-species groups, suggesting that similar mechanisms might underlie group dynamics in a range of taxa. The model also makes novel predictions about group dynamics that can be tested using variation across space and time.

PAM: Particle automata model in simulation of Fusarium graminearum pathogen expansion.

Science.gov (United States)

Wcisło, Rafał; Miller, S Shea; Dzwinel, Witold

2016-01-21

The multi-scale nature and inherent complexity of biological systems are a great challenge for computer modeling and classical modeling paradigms. We present a novel particle automata modeling metaphor in the context of developing a 3D model of Fusarium graminearum infection in wheat. The system consisting of the host plant and Fusarium pathogen cells can be represented by an ensemble of discrete particles defined by a set of attributes. The cells-particles can interact with each other mimicking mechanical resistance of the cell walls and cell coalescence. The particles can move, while some of their attributes can be changed according to prescribed rules. The rules can represent cellular scales of a complex system, while the integrated particle automata model (PAM) simulates its overall multi-scale behavior. We show that due to the ability of mimicking mechanical interactions of Fusarium tip cells with the host tissue, the model is able to simulate realistic penetration properties of the colonization process reproducing both vertical and lateral Fusarium invasion scenarios. The comparison of simulation results with micrographs from laboratory experiments shows encouraging qualitative agreement between the two. Copyright © 2015 Elsevier Ltd. All rights reserved.

Attributing Asymmetric Productivity Responses to Internal Ecosystem Dynamics and External Drivers Using Probabilistic Models

Science.gov (United States)

Parolari, A.; Goulden, M.

2017-12-01

A major challenge to interpreting asymmetric changes in ecosystem productivity is the attribution of these changes to external climate forcing or to internal ecophysiological processes that respond to these drivers (e.g., photosynthesis response to drying soil). For example, positive asymmetry in productivity can result from either positive skewness in the distribution of annual rainfall amount or from negative curvature in the productivity response to annual rainfall. To analyze the relative influences of climate and ecosystem dynamics on both positive and negative asymmetry in multi-year ANPP experiments, we use a multi-scale coupled ecosystem water-carbon model to interpret field experimental results that span gradients of rainfall skewness and ANPP response curvature. The model integrates rainfall variability, soil moisture dynamics, and net carbon assimilation from the daily to inter-annual scales. From the underlying physical basis of the model, we compute the joint probability distribution of the minimum and maximum ANPP for an annual ANPP experiment of N years. The distribution is used to estimate the likelihood that either positive or negative asymmetry will be observed in an experiment, given the annual rainfall distribution and the ANPP response curve. We estimate the total asymmetry as the mode of this joint distribution and the relative contribution attributable to rainfall skewness as the mode for a linear ANPP response curve. Applied to data from several long-term ANPP experiments, we find that there is a wide range of observed ANPP asymmetry (positive and negative) and a spectrum of contributions from internal and external factors. We identify the soil water holding capacity relative to the mean rain event depth as a critical ecosystem characteristic that controls the non-linearity of the ANPP response and positive curvature at high rainfall. Further, the seasonal distribution of rainfall is shown to control the presence or absence of negative

Attributes of ethical employees in Malaysian public sector ...

African Journals Online (AJOL)

This study aims to explore the attributes of ethical employees in public sector and to pattern match the attributes with human behavior, social and ethics theories. A qualitative research is used by focusing on first-order attributes (through interviews) and second-order concepts (using theories to explain the facts). This study ...

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

Directory of Open Access Journals (Sweden)

Kaveh Khalili-Damghani

2017-07-01

Full Text Available In this paper a multi-period multi-product multi-objective aggregate production planning (APP model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.

The comparison of alternatives for nuclear spent fuel management using multi-attribute utility function

International Nuclear Information System (INIS)

Yang, J. W.; Kang, C. S.

1999-01-01

It is necessary to find a solution immediately to nuclear spent fuel management that is temporarily stored in on-site spent fuel storage before the saturation of the storage. However the choice of alternative for nuclear spent fuel management consists of complex process that are affected by economic, technical and social factors. And it is not easy to quantify these factors; public opinion, probability of diplomatic problem and contribution to development of nuclear technology. Therefore the analysis of the affecting factors and assessment of alternatives are required. This study performed the comparison of the alternatives for nuclear spent fuel management using MAU (Multi-Attribute Utility Function) and AHP(Analytic Hierarchy Process)

Multi-objective optimization for generating a weighted multi-model ensemble

Science.gov (United States)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic

Information networks in the stock market based on the distance of the multi-attribute dimensions between listed companies

Science.gov (United States)

Liu, Qian; Li, Huajiao; Liu, Xueyong; Jiang, Meihui

2018-04-01

In the stock market, there are widespread information connections between economic agents. Listed companies can obtain mutual information about investment decisions from common shareholders, and the extent of sharing information often determines the relationships between listed companies. Because different shareholder compositions and investment shares lead to different formations of the company's governance mechanisms, we map the investment relationships between shareholders to the multi-attribute dimensional spaces of the listed companies (each shareholder investment in a company is a company dimension). Then, we construct the listed company's information network based on co-shareholder relationships. The weights for the edges in the information network are measured with the Euclidean distance between the listed companies in the multi-attribute dimension space. We define two indices to analyze the information network's features. We conduct an empirical study that analyzes Chinese listed companies' information networks. The results from the analysis show that with the diversification and decentralization of shareholder investments, almost all Chinese listed companies exchanged information through common shareholder relationships, and there is a gradual reduction in information sharing capacity between listed companies that have common shareholders. This network analysis has benefits for risk management and portfolio investments.

Generalized modeling of multi-component vaporization/condensation phenomena for multi-phase-flow analysis

International Nuclear Information System (INIS)

Morita, K.; Fukuda, K.; Tobita, Y.; Kondo, Sa.; Suzuki, T.; Maschek, W.

2003-01-01

A new multi-component vaporization/condensation (V/C) model was developed to provide a generalized model for safety analysis codes of liquid metal cooled reactors (LMRs). These codes simulate thermal-hydraulic phenomena of multi-phase, multi-component flows, which is essential to investigate core disruptive accidents of LMRs such as fast breeder reactors and accelerator driven systems. The developed model characterizes the V/C processes associated with phase transition by employing heat transfer and mass-diffusion limited models for analyses of relatively short-time-scale multi-phase, multi-component hydraulic problems, among which vaporization and condensation, or simultaneous heat and mass transfer, play an important role. The heat transfer limited model describes the non-equilibrium phase transition processes occurring at interfaces, while the mass-diffusion limited model is employed to represent effects of non-condensable gases and multi-component mixture on V/C processes. Verification of the model and method employed in the multi-component V/C model of a multi-phase flow code was performed successfully by analyzing a series of multi-bubble condensation experiments. The applicability of the model to the accident analysis of LMRs is also discussed by comparison between steam and metallic vapor systems. (orig.)

Causal attribution of mental illness in South-Eastern Nigeria.

Science.gov (United States)

Ikwuka, Ugo; Galbraith, Niall; Nyatanga, Lovemore

2014-05-01

Understanding of mental illness in sub-Saharan Africa has remained under-researched in spite of the high and increasing neuropsychiatric burden of disease in the region. This study investigated the causal beliefs that the Igbo people of south-eastern Nigeria hold about schizophrenia, with a view to establishing the extent to which the population makes psychosocial, biological and supernatural attributions. Multi-stage sampling was used to select participants (N = 200) to which questionnaires were administered. Mean comparison of the three causal models revealed a significant endorsement of supernatural causation. Logistic regressions revealed significant contributions of old age and female gender to supernatural attribution; old age, high education and Catholic religious denomination to psychosocial attributions; and high education to biological attributions. It is hoped that the findings would enlighten, augment literature and enhance mental health care service delivery.

Phenomenology and Meaning Attribution

African Journals Online (AJOL)

John Paley. (2017). Phenomenology as Qualitative Research: A Critical Analysis of Meaning Attribution. ... basic philosophical nature of phenomenological meaning and inquiry, and that he not ... In keeping with the title of my book, Researching. Lived Experience ...... a quantitative social science that can make generalizing.

Quantifying multi-dimensional attributes of human activities at various geographic scales based on smartphone tracking.

Science.gov (United States)

Zhou, Xiaolu; Li, Dongying

2018-05-09

Advancement in location-aware technologies, and information and communication technology in the past decades has furthered our knowledge of the interaction between human activities and the built environment. An increasing number of studies have collected data regarding individual activities to better understand how the environment shapes human behavior. Despite this growing interest, some challenges exist in collecting and processing individual's activity data, e.g., capturing people's precise environmental contexts and analyzing data at multiple spatial scales. In this study, we propose and implement an innovative system that integrates smartphone-based step tracking with an app and the sequential tile scan techniques to collect and process activity data. We apply the OpenStreetMap tile system to aggregate positioning points at various scales. We also propose duration, step and probability surfaces to quantify the multi-dimensional attributes of activities. Results show that, by running the app in the background, smartphones can measure multi-dimensional attributes of human activities, including space, duration, step, and location uncertainty at various spatial scales. By coordinating Global Positioning System (GPS) sensor with accelerometer sensor, this app can save battery which otherwise would be drained by GPS sensor quickly. Based on a test dataset, we were able to detect the recreational center and sports center as the space where the user was most active, among other places visited. The methods provide techniques to address key issues in analyzing human activity data. The system can support future studies on behavioral and health consequences related to individual's environmental exposure.

Attribute Synthetic Evaluation Model for the CBM Recoverability and Its Application

Directory of Open Access Journals (Sweden)

Xiao-gang Xia

2015-01-01

Full Text Available The coal-bed methane (CBM recoverability is the basic premise of CBM development practice; in order to effectively evaluate the CBM recoverability, the attribute synthetic evaluation model is established based on the theory and method of attribute mathematics. Firstly, five indexes are chosen to evaluate the recoverability through analyzing the influence factors of CBM, including seam thickness, gas saturation, permeability, reservoir pressure gradient, and hydrogeological conditions. Secondly, the attribute measurement functions of each index are constructed based on the attribute mathematics theory, and the calculation methods of the single index attribute measurement and the synthetic attribute measurement also are provided. Meanwhile, the weight of each index is given with the method of similar number and similar weight; the evaluation results also are determined by the confidence criterion reliability code. At last, according to the application results of the model in some coal target area of Fuxin and Hancheng mine, the evaluation results are basically consistent with the actual situation, which proves that the evaluation model can be used in the CBM recoverability prediction, and an effective method of the CBM recoverability evaluation is also provided.

How Qualitative Methods Can be Used to Inform Model Development.

Science.gov (United States)

Husbands, Samantha; Jowett, Susan; Barton, Pelham; Coast, Joanna

2017-06-01

Decision-analytic models play a key role in informing healthcare resource allocation decisions. However, there are ongoing concerns with the credibility of models. Modelling methods guidance can encourage good practice within model development, but its value is dependent on its ability to address the areas that modellers find most challenging. Further, it is important that modelling methods and related guidance are continually updated in light of any new approaches that could potentially enhance model credibility. The objective of this article was to highlight the ways in which qualitative methods have been used and recommended to inform decision-analytic model development and enhance modelling practices. With reference to the literature, the article discusses two key ways in which qualitative methods can be, and have been, applied. The first approach involves using qualitative methods to understand and inform general and future processes of model development, and the second, using qualitative techniques to directly inform the development of individual models. The literature suggests that qualitative methods can improve the validity and credibility of modelling processes by providing a means to understand existing modelling approaches that identifies where problems are occurring and further guidance is needed. It can also be applied within model development to facilitate the input of experts to structural development. We recommend that current and future model development would benefit from the greater integration of qualitative methods, specifically by studying 'real' modelling processes, and by developing recommendations around how qualitative methods can be adopted within everyday modelling practice.

Qualitative and Quantitative Integrated Modeling for Stochastic Simulation and Optimization

Directory of Open Access Journals (Sweden)

Xuefeng Yan

2013-01-01

Full Text Available The simulation and optimization of an actual physics system are usually constructed based on the stochastic models, which have both qualitative and quantitative characteristics inherently. Most modeling specifications and frameworks find it difficult to describe the qualitative model directly. In order to deal with the expert knowledge, uncertain reasoning, and other qualitative information, a qualitative and quantitative combined modeling specification was proposed based on a hierarchical model structure framework. The new modeling approach is based on a hierarchical model structure which includes the meta-meta model, the meta-model and the high-level model. A description logic system is defined for formal definition and verification of the new modeling specification. A stochastic defense simulation was developed to illustrate how to model the system and optimize the result. The result shows that the proposed method can describe the complex system more comprehensively, and the survival probability of the target is higher by introducing qualitative models into quantitative simulation.

Experiences from a pilot study on how to conduct a qualitative multi-country research project regarding use of antibiotics in Southeast Europe

DEFF Research Database (Denmark)

Kaae, Susanne; Sporrong, Sofia Kälvemark; Traulsen, Janine Morgall

2016-01-01

regarding how to conduct these types of research projects by evaluating a pilot study of the project. METHODS: Local data collectors conducted the study according to a developed protocol and evaluated the study with the responsible researcher-team from University of Copenhagen. The pilot study focused......BACKGROUND: In 2014, a qualitative multi-country research project was launched to study the reasons behind the high use of antibiotics in regions of Southeast Europe by using previously untrained national interviewers (who were engaged in other antibiotic microbial resistance-related investigations......) to conduct qualitative interviews with local patients, physicians and pharmacists. Little knowledge exists about how to implement qualitative multi-country research collaborations involving previously untrained local data collectors. The aim of this paper was therefore to contribute to the knowledge...

Using synchronization in multi-model ensembles to improve prediction

Science.gov (United States)

Hiemstra, P.; Selten, F.

2012-04-01

In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of

Controller Synthesis using Qualitative Models and Constraints

OpenAIRE

Ramamoorthy, Subramanian; Kuipers, Benjamin J

2004-01-01

Many engineering systems require the synthesis of global behaviors in nonlinear dynamical systems. Multiple model approaches to control design make it possible to synthesize robust and optimal versions of such global behaviors. We propose a methodology called Qualitative Heterogeneous Control that enables this type of control design. This methodology is based on a separation of concerns between qualitative correctness and quantitative optimization. Qualitative sufficient conditions are derive...

Numerical modeling of macrodispersion in heterogeneous media: a comparison of multi-Gaussian and non-multi-Gaussian models

Science.gov (United States)

Wen, Xian-Huan; Gómez-Hernández, J. Jaime

1998-03-01

The macrodispersion of an inert solute in a 2-D heterogeneous porous media is estimated numerically in a series of fields of varying heterogeneity. Four different random function (RF) models are used to model log-transmissivity (ln T) spatial variability, and for each of these models, ln T variance is varied from 0.1 to 2.0. The four RF models share the same univariate Gaussian histogram and the same isotropic covariance, but differ from one another in terms of the spatial connectivity patterns at extreme transmissivity values. More specifically, model A is a multivariate Gaussian model for which, by definition, extreme values (both high and low) are spatially uncorrelated. The other three models are non-multi-Gaussian: model B with high connectivity of high extreme values, model C with high connectivity of low extreme values, and model D with high connectivities of both high and low extreme values. Residence time distributions (RTDs) and macrodispersivities (longitudinal and transverse) are computed on ln T fields corresponding to the different RF models, for two different flow directions and at several scales. They are compared with each other, as well as with predicted values based on first-order analytical results. Numerically derived RTDs and macrodispersivities for the multi-Gaussian model are in good agreement with analytically derived values using first-order theories for log-transmissivity variance up to 2.0. The results from the non-multi-Gaussian models differ from each other and deviate largely from the multi-Gaussian results even when ln T variance is small. RTDs in non-multi-Gaussian realizations with high connectivity at high extreme values display earlier breakthrough than in multi-Gaussian realizations, whereas later breakthrough and longer tails are observed for RTDs from non-multi-Gaussian realizations with high connectivity at low extreme values. Longitudinal macrodispersivities in the non-multi-Gaussian realizations are, in general, larger than

Supporting ALARP decision-making by cost benefit analysis and multi-attribute utility theory

International Nuclear Information System (INIS)

French, Simon; Bedford, Tim; Atherton, Elizabeth

2001-01-01

Current regulation in the UK and elsewhere specify upper and target risk limits for the operation of nuclear plant in terms of frequencies of various kinds of accidents and accidental releases per annum. 'As low as reasonably practicable' (ALARP) arguments are used to justify the acceptance or rejection of policies that lead to risk changes between these limits. We assess the suitability of cost-benefit analysis (CBA) and multi-attribute utility theory (MAUT) for performing ALARP ('as low as reasonably possible') assessments, in particular within the nuclear industry. Four problems stand out in current CBA applications to ALARP, concerning the determination of prices of safety gains or detriments, the valuation of group and individual risk, calculations using 'disproportionality', and the use of discounting to trade off risks through time. This last point has received less attention in the past but is important because of the growing interest in risk-informed regulation in which policies extend over several timeframes and distribute the risk unevenly over these, or in policies that lead to a non-uniform risk within a single timeframe (such as maintenance policies). We discuss the problems associated with giving quantitative support to such decisions. We argue that multi-attribute utility methods (MAUT) provide an alternative methodology to CBA which enable the four problems described above to be addressed in a more satisfactory way. Through sensitivity analysis MAUT can address the perceptions of all stakeholder groups, facilitating constructive discussion and elucidating the key points of disagreement. We also argue that by being explicitly subjective it provides an open, auditable and clear analysis in contrast to the illusory objectivity of CBA. CBA seeks to justify a decision by using a common basis for weights (prices), while MAUT recognizes that different parties may want to give different valuations. It then allows the analyst to explore the ways in which

Methodology for assessing the effectiveness of countermeasures in rural settlements in the long term after the Chernobyl accident on the multi-attribute analysis basis

International Nuclear Information System (INIS)

Panov, A.V.; Fesenko, S.V.; Aleksakhin, R.M.

2005-01-01

The effectiveness of countermeasures in rural settlements affected by the Chernobyl accident was assessed based on a multi-attribute approach, using radiological, economic and socio-psychological parameters. (authors)

Technical attributes, health attribute, consumer attributes and their roles in adoption intention of healthcare wearable technology.

Science.gov (United States)

Zhang, Min; Luo, Meifen; Nie, Rui; Zhang, Yan

2017-12-01

This paper aims to explore factors influencing the healthcare wearable technology adoption intention from perspectives of technical attributes (perceived convenience, perceived irreplaceability, perceived credibility and perceived usefulness), health attribute (health belief) and consumer attributes (consumer innovativeness, conspicuous consumption, informational reference group influence and gender difference). By integrating technology acceptance model, health belief model, snob effect and conformity and reference group theory, hypotheses and research model are proposed. The empirical investigation (N=436) collects research data through questionnaire. Results show that the adoption intention of healthcare wearable technology is influenced by technical attributes, health attribute and consumer attributes simultaneously. For technical attributes, perceived convenience and perceived credibility both positively affect perceived usefulness, and perceived usefulness influences adoption intention. The relation between perceived irreplaceability and perceived usefulness is only supported by males. For health attribute, health belief affects perceived usefulness for females. For consumer attributes, conspicuous consumption and informational reference group influence can significantly moderate the relation between perceived usefulness and adoption intention and the relation between consumer innovativeness and adoption intention respectively. What's more, consumer innovativeness significantly affects adoption intention for males. This paper aims to discuss technical attributes, health attribute and consumer attributes and their roles in the adoption intention of healthcare wearable technology. Findings may provide enlightenment to differentiate product developing and marketing strategies and provide some implications for clinical medicine. Copyright © 2017 Elsevier B.V. All rights reserved.

Selection of hybrid vehicle for green environment using multi-attributive border approximation area comparison method

Directory of Open Access Journals (Sweden)

Tapas Kumar Biswas

2018-02-01

Full Text Available The mobility sector including all kinds of transportation systems are facing global challenges in re-spect of green environmental issues. There has been a paradigm shift in the concept of design and manufacturing of automotive vehicles keeping in mind the scarcity of fossil fuel and the impact of emission on environment due to burning of it. The addition of hybrid and electric vehicles in pas-senger car segment has got significant momentum to address the global challenges. This research investigates the performance of a group of hybrid vehicles from customers’ perspective. Among the different brands that are available in the hybrid vehicle market, smart customers have given pri-ority to vehicle cost, mileage, tail pipe emission, comfortness and high tank size volume for long drive. Considering these attributes, selection strategy for hybrid vehicles has been developed using entropy based multi-attributive border approximation area comparison (MABAC method. This research highlights the best hybrid vehicle which reduces air pollution in cities with other significant environmental benefits, reduces dependence on foreign energy imports and minimizes the annual fuel cost.

Multi-population genomic prediction using a multi-task Bayesian learning model.

Science.gov (United States)

Chen, Liuhong; Li, Changxi; Miller, Stephen; Schenkel, Flavio

2014-05-03

Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to develop a multi-task Bayesian learning model for multi-population genomic prediction with a strategy to effectively share information across populations. Simulation studies and real data from Holstein and Ayrshire dairy breeds with phenotypes on five milk production traits were used to evaluate the proposed multi-task Bayesian learning model and compare with a single-task model and a simple data pooling method. A multi-task Bayesian learning model was proposed for multi-population genomic prediction. Information was shared across populations through a common set of latent indicator variables while SNP effects were allowed to vary in different populations. Both simulation studies and real data analysis showed the effectiveness of the multi-task model in improving genomic prediction accuracy for the smaller Ayshire breed. Simulation studies suggested that the multi-task model was most effective when the number of QTL was small (n = 20), with an increase of accuracy by up to 0.09 when QTL effects were lowly correlated between two populations (ρ = 0.2), and up to 0.16 when QTL effects were highly correlated (ρ = 0.8). When QTL genotypes were included for training and validation, the improvements were 0.16 and 0.22, respectively, for scenarios of the low and high correlation of QTL effects between two populations. When the number of QTL was large (n = 200), improvement was small with a maximum of 0.02 when QTL genotypes were not included for genomic prediction. Reduction in accuracy was observed for the simple pooling method when the number of QTL was small and correlation of QTL effects between the two populations was low. For the real data, the multi-task model achieved an

Multi-Model Ensemble Wake Vortex Prediction

Science.gov (United States)

Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

2015-01-01

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Involving mental health service users in suicide-related research: a qualitative inquiry model.

Science.gov (United States)

Lees, David; Procter, Nicholas; Fassett, Denise; Handley, Christine

2016-03-01

To describe the research model developed and successfully deployed as part of a multi-method qualitative study investigating suicidal service-users' experiences of mental health nursing care. Quality mental health care is essential to limiting the occurrence and burden of suicide, however there is a lack of relevant research informing practice in this context. Research utilising first-person accounts of suicidality is of particular importance to expanding the existing evidence base. However, conducting ethical research to support this imperative is challenging. The model discussed here illustrates specific and more generally applicable principles for qualitative research regarding sensitive topics and involving potentially vulnerable service-users. Researching into mental health service users with first-person experience of suicidality requires stakeholder and institutional support, researcher competency, and participant recruitment, consent, confidentiality, support and protection. Research with service users into their experiences of sensitive issues such as suicidality can result in rich and valuable data, and may also provide positive experiences of collaboration and inclusivity. If challenges are not met, objectification and marginalisation of service-users may be reinforced, and limitations in the evidence base and service provision may be perpetuated.

Multi-Attribute Task Battery - Applications in pilot workload and strategic behavior research

Science.gov (United States)

Arnegard, Ruth J.; Comstock, J. R., Jr.

1991-01-01

The Multi-Attribute Task (MAT) Battery provides a benchmark set of tasks for use in a wide range of lab studies of operator performance and workload. The battery incorporates tasks analogous to activities that aircraft crewmembers perform in flight, while providing a high degree of experimenter control, performance data on each subtask, and freedom to nonpilot test subjects. Features not found in existing computer based tasks include an auditory communication task (to simulate Air Traffic Control communication), a resource management task permitting many avenues or strategies of maintaining target performance, a scheduling window which gives the operator information about future task demands, and the option of manual or automated control of tasks. Performance data are generated for each subtask. In addition, the task battery may be paused and onscreen workload rating scales presented to the subject. The MAT Battery requires a desktop computer with color graphics. The communication task requires a serial link to a second desktop computer with a voice synthesizer or digitizer card.

Sources of multi-decadal variability in Arctic sea ice extent

International Nuclear Information System (INIS)

Day, J J; Hargreaves, J C; Annan, J D; Abe-Ouchi, A

2012-01-01

The observed dramatic decrease in September sea ice extent (SIE) has been widely discussed in the scientific literature. Though there is qualitative agreement between observations and ensemble members of the Third Coupled Model Intercomparison Project (CMIP3), it is concerning that the observed trend (1979–2010) is not captured by any ensemble member. The potential sources of this discrepancy include: observational uncertainty, physical model limitations and vigorous natural climate variability. The latter has received less attention and is difficult to assess using the relatively short observational sea ice records. In this study multi-centennial pre-industrial control simulations with five CMIP3 climate models are used to investigate the role that the Arctic oscillation (AO), the Atlantic multi-decadal oscillation (AMO) and the Atlantic meridional overturning circulation (AMOC) play in decadal sea ice variability. Further, we use the models to determine the impact that these sources of variability have had on SIE over both the era of satellite observation (1979–2010) and an extended observational record (1953–2010). There is little evidence of a relationship between the AO and SIE in the models. However, we find that both the AMO and AMOC indices are significantly correlated with SIE in all the models considered. Using sensitivity statistics derived from the models, assuming a linear relationship, we attribute 0.5–3.1%/decade of the 10.1%/decade decline in September SIE (1979–2010) to AMO driven variability. (letter)

TWO-DIMENSIONAL CORE-COLLAPSE SUPERNOVA MODELS WITH MULTI-DIMENSIONAL TRANSPORT

International Nuclear Information System (INIS)

Dolence, Joshua C.; Burrows, Adam; Zhang, Weiqun

2015-01-01

We present new two-dimensional (2D) axisymmetric neutrino radiation/hydrodynamic models of core-collapse supernova (CCSN) cores. We use the CASTRO code, which incorporates truly multi-dimensional, multi-group, flux-limited diffusion (MGFLD) neutrino transport, including all relevant O(v/c) terms. Our main motivation for carrying out this study is to compare with recent 2D models produced by other groups who have obtained explosions for some progenitor stars and with recent 2D VULCAN results that did not incorporate O(v/c) terms. We follow the evolution of 12, 15, 20, and 25 solar-mass progenitors to approximately 600 ms after bounce and do not obtain an explosion in any of these models. Though the reason for the qualitative disagreement among the groups engaged in CCSN modeling remains unclear, we speculate that the simplifying ''ray-by-ray'' approach employed by all other groups may be compromising their results. We show that ''ray-by-ray'' calculations greatly exaggerate the angular and temporal variations of the neutrino fluxes, which we argue are better captured by our multi-dimensional MGFLD approach. On the other hand, our 2D models also make approximations, making it difficult to draw definitive conclusions concerning the root of the differences between groups. We discuss some of the diagnostics often employed in the analyses of CCSN simulations and highlight the intimate relationship between the various explosion conditions that have been proposed. Finally, we explore the ingredients that may be missing in current calculations that may be important in reproducing the properties of the average CCSNe, should the delayed neutrino-heating mechanism be the correct mechanism of explosion

Multi-Domain Modeling Based on Modelica

Directory of Open Access Journals (Sweden)

Liu Jun

2016-01-01

Full Text Available With the application of simulation technology in large-scale and multi-field problems, multi-domain unified modeling become an effective way to solve these problems. This paper introduces several basic methods and advantages of the multidisciplinary model, and focuses on the simulation based on Modelica language. The Modelica/Mworks is a newly developed simulation software with features of an object-oriented and non-casual language for modeling of the large, multi-domain system, which makes the model easier to grasp, develop and maintain.It This article shows the single degree of freedom mechanical vibration system based on Modelica language special connection mechanism in Mworks. This method that multi-domain modeling has simple and feasible, high reusability. it closer to the physical system, and many other advantages.

Quality Model Based on Cots Quality Attributes

OpenAIRE

Jawad Alkhateeb; Khaled Musa

2013-01-01

The quality of software is essential to corporations in making their commercial software. Good or poorquality to software plays an important role to some systems such as embedded systems, real-time systems,and control systems that play an important aspect in human life. Software products or commercial off theshelf software are usually programmed based on a software quality model. In the software engineeringfield, each quality model contains a set of attributes or characteristics that drives i...

PENERAPAN FUZZY ANALYTIC HIERARCHY PROCESS DALAM METODE MULTI ATTRIBUTE FAILURE MODE ANALYSIS UNTUK MENGIDENTIFIKASI PENYEBAB KEGAGALAN POTENSIAL PADA PROSES PRODUKSI

OpenAIRE

Dorina Hetharia

2012-01-01

Banyak metode dalam Total Quality Management (TQM) yang dapat digunakan untuk melakukan perbaikan kualitas produk dan jasa. Salah satunya adalah Multi Attribute Failure Mode Analysis (MAFMA), yang dapat digunakan untuk mengeliminasi atau mengurangi kemungkinan terjadinya kegagalan bila dilihat dari faktor penyebabnya, sehingga dapat mencegah terulang kembali kegagalan tersebut. MAFMA merupakan pengembangan dari Failure Mode and Effect Analysis (FMEA), yang mengintegrasikan atribut severity, o...

Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.

Science.gov (United States)

Kirschner, Denise E; Hunt, C Anthony; Marino, Simeone; Fallahi-Sichani, Mohammad; Linderman, Jennifer J

2014-01-01

The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. © 2014 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

A multi-attribute analysis of radiation protection choices. A methodological approach in the case of radioactive releases from US nuclear plants

International Nuclear Information System (INIS)

Lombard, Jacques; Oudiz, Andre.

1981-02-01

In the field of PWR fuel cycle the authors use of multi-attribute analysis to optimize radiation protection. This study proceeds from a methodological point of view and data have been taken from a US Environmental Protection Agency study. The multi-attribute analysis, called ELECTRE 1, includes two distinct phases. The first one gives a segmentation of the 39 effluent control options, which may be applied in the fuel cycle plants, in six sub-groups or kernels. Such a classification allows for a first reduction of the decision problem and gives a ranking of the sub-groups. In order to separate between the options of a sub-group another procedure is used. This second phase introduces weight of the criteria. The adopted criteria are: option's cost, avoided collective risk, avoided individual risk, and a data relative uncertainty indicator. Following this second step we are able to select from the 39 options 19 leading to ALARA levels. The final ranking suggests the synthetic character of the method used which permits to refer simultaneously to the individual approach and the collective one [fr

Research on Multi - Person Parallel Modeling Method Based on Integrated Model Persistent Storage

Science.gov (United States)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

2018-03-01

This paper mainly studies the multi-person parallel modeling method based on the integrated model persistence storage. The integrated model refers to a set of MDDT modeling graphics system, which can carry out multi-angle, multi-level and multi-stage description of aerospace general embedded software. Persistent storage refers to converting the data model in memory into a storage model and converting the storage model into a data model in memory, where the data model refers to the object model and the storage model is a binary stream. And multi-person parallel modeling refers to the need for multi-person collaboration, the role of separation, and even real-time remote synchronization modeling.

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

Science.gov (United States)

Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

2017-01-01

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780

Qualitative phase space reconstruction analysis of supply-chain inventor time series

Directory of Open Access Journals (Sweden)

Jinliang Wu

2010-10-01

Full Text Available The economy systems are usually too complex to be analysed, but some advanced methods have been developed in order to do so, such as system dynamics modelling, multi-agent modelling, complex adaptive system modelling and qualitative modelling. In this paper, we considered a supply-chain (SC system including several kinds of products. Using historic suppliers’ demand data, we firstly applied the phase space analysis method and then used qualitative analysis to improve the complex system’s performance. Quantitative methods can forecast the quantitative SC demands, but they cannot indicate the qualitative aspects of SC, so when we apply quantitative methods to a SC system we get only numerous data of demand. By contrast, qualitative methods can show the qualitative change and trend of the SC demand. We therefore used qualitative methods to improve the quantitative forecasting results. Comparing the quantitative only method and the combined method used in this paper, we found that the combined method is far more accurate. Not only is the inventory cost lower, but the forecasting accuracy is also better.

Investigation of reflood models by coupling REFLA-1D and multi-loop system model

International Nuclear Information System (INIS)

Sugimoto, Jun; Murao, Yoshio

1983-09-01

A system analysis code REFLA-1DS was developed by coupling reflood analysis code REFLA-1D and a multi-loop primary system model. The reflood models in the code were investigated for the development of the integral system analysis code. The REFLA-1D, which was developed with the small scale reflood experiment at JAERI, consists of one-dimensional core model and a primary system model with a constant loop resistance. The multi-loop primary system model was developed with the Cylindrical Core Test Facility of JAERI's large scale reflood tests. The components modeled in the code are the upper plenum, the steam generator, the coolant pump, the ECC injection port, the downcomer and the broken cold leg nozzle. The coupling between the two models in REFLA-1DS is accomplished by applying the equivalent flow resistance calculated with the multiloop model to the REFLA-1D. The characteristics of the code is its simplicity of the system model and the solution method which enables the fast running and the easy reflood analysis for the further model development. A fairly good agreement was obtained with the results of the Cylindrical Core Test Facility for the calculated water levels in the downcomer, the core and the upper plenum. A qualitatively good agreement was obtained concerning the parametric effects of the system pressure, the ECC flow rate and the initial clad temperature. Needs for further code improvements of the models, however, were pointed out. These include the problem concerning the generation rate of the steam and water droplets in the core in an early period, the effect of the flow oscillation on the core cooling, the heat release from the downcomer wall, and the stable system calculation. (author)

Statistical post-processing of seasonal multi-model forecasts: Why is it so hard to beat the multi-model mean?

Science.gov (United States)

Siegert, Stefan

2017-04-01

Initialised climate forecasts on seasonal time scales, run several months or even years ahead, are now an integral part of the battery of products offered by climate services world-wide. The availability of seasonal climate forecasts from various modeling centres gives rise to multi-model ensemble forecasts. Post-processing such seasonal-to-decadal multi-model forecasts is challenging 1) because the cross-correlation structure between multiple models and observations can be complicated, 2) because the amount of training data to fit the post-processing parameters is very limited, and 3) because the forecast skill of numerical models tends to be low on seasonal time scales. In this talk I will review new statistical post-processing frameworks for multi-model ensembles. I will focus particularly on Bayesian hierarchical modelling approaches, which are flexible enough to capture commonly made assumptions about collective and model-specific biases of multi-model ensembles. Despite the advances in statistical methodology, it turns out to be very difficult to out-perform the simplest post-processing method, which just recalibrates the multi-model ensemble mean by linear regression. I will discuss reasons for this, which are closely linked to the specific characteristics of seasonal multi-model forecasts. I explore possible directions for improvements, for example using informative priors on the post-processing parameters, and jointly modelling forecasts and observations.

Qualitative models of global warming amplifiers

NARCIS (Netherlands)

Milošević, U.; Bredeweg, B.; de Kleer, J.; Forbus, K.D.

2010-01-01

There is growing interest from ecological experts to create qualitative models of phenomena for which numerical information is sparse or missing. We present a number of successful models in the field of environmental science, namely, the domain of global warming. The motivation behind the effort is

The Validity of Attribute-Importance Measurement: A Review

NARCIS (Netherlands)

Ittersum, van K.; Pennings, J.M.E.; Wansink, B.; Trijp, van J.C.M.

2007-01-01

A critical review of the literature demonstrates a lack of validity among the ten most common methods for measuring the importance of attributes in behavioral sciences. The authors argue that one of the key determinants of this lack of validity is the multi-dimensionality of attribute importance.

PEMILIHAN STRATEGI BISNIS DENGAN MENGGUNAKAN QSPM (QUANTITATIVE STRATEGIC PLANNING MATRIX DAN MODEL MAUT (MULTI ATTRIBUTE UTILITY THEORY (STUDI KASUS PADA SENTRA INDUSTRI GERABAH KASONGAN, BANTUL, YOGYAKARTA

Directory of Open Access Journals (Sweden)

Nia Budi Puspitasari

2013-09-01

Full Text Available Industri Kecil Menengah (IKM gerabah yang terletak di kecamatan Kasongan, kabupaten Bantul, Yogyakarta ini merupakan salah satu sentra industri gerabah Indonesia yang sedang berkembang untuk pasar domestik dan luar negeri.Menurut data statistik Provinsi Daerah Istimewa Yogyakarta (DIY, IKM mempunyai daya serap pekerja yang cukup banyak.Perkembangan tersebut perlu diiringi dengan adanya sistem pemasaran yang baik dalam IKM tersebut.Adanya penurunan penjulaan pada beberapa tahun terakhir dan kurang baiknya metode strategi pemasaran merupakan penyebab munculnya masalah –masalah dalam hal penjualan di Industri IKM Gerabah Kasongan, Yogyakarta.Analisis lingkungan eksternal dan lingkungan internal dapat dijadikan acuan utama untuk melakukan perbaikan strategi pemasaran.Analisis lingkungan ekternal dan internal tersebut digabungkan dengan analisis SWOT, kemudian dilakukan penetapan prioritas strategi dari hasil analisis SWOT dengan matriks QSPM (Quantitative Strategic Planning Matrix. Model MAUT (Multi Attribute Utility Theory juga digunakan untuk membandingakan prioritas strategi bisnis dengan melihat segi infrastruktur, waktu, cost dan pendapat pengusaha dalam penelitian ini. Dari hasil penelitian bahwa ini Industri IKM dapat melakukan strategi  pengembangan produk dan penetrasi pasar. Selain itu membuat desa Kasongan lebih menarik dengan mengembangkan desa menjadi daerah wisata yang memang menarik untuk dikunjungi. Kesiapan ini juga diiringi dengan adanya kesiaapan oleh masyarakat dan para pengusaha dengan lebih mengembangkan produknya dengan melakukan diversifikasi produk dengan bahan baku yang sama yaitu tanah tersebut. Kata Kunci : strategi bisnis, SWOT, QSPM, model MAUT Abstract The Gerabah Small and Mid-sized Industrial Firm (IKM placed in Kasongan, Bantul, Yogyakarta is one of the central industry of Indonesian gerabah, which is now currently develop into domestic and international market.According to the statistical data from the Local

Use of the sensitivity analysis for multi-attributes decision models for oil exploration and production systems; Uso da analise de sensibilidade em modelos de decisao multiatributos para sistemas de exploracao e producao de petroleo

Energy Technology Data Exchange (ETDEWEB)

Furtado, Ricardo

2000-07-01

Today, oil companies must be able to survive in a hostile and competitive environment. Such environment involves volatility of oil prices, the narrow margins of profitability, and ever increasing environmental restrictions. In order to survive, firms must have the appropriate tools to consider the tradeoffs involving the financial, environmental, technological and of market parameters which are the key elements within the investment decision-making process. The aim of the present work is to analyze the behavior of the weights (relative importance) of the attributes int the multi-criteria decision model through a high dimension sensitivity analysis. Among the benefits of such method are: provide the analyst (decision-maker) with a better characterization and control of the weights of the attributes, providing the user with a clear view of the entire decision process. The methodology suggested in this dissertation was applied in two oil exploration and production case studies. The first case involved the selection of an exploratory target among three options. In this case, there is interaction of the objectives of the company, where financial, technological and of market parameters interact. In the second case, a hypothetical production project is suggested. For this second study, the decision-maker has the option of using one of the following production systems: a FPSO (Floating, Production, Storage and Offloading); a TLP (Tension Leg Platform); or a SS (Semi Submersible). The attributes for each one of the production systems are financial, technological and environmental. In this second case, the model makes it possible to simulate several options, providing the manager with the choice of the most appropriate production system to this objectives and preferences. (author)

Language Learner Beliefs from an Attributional Perspective

OpenAIRE

Gabillon, Zehra

2013-01-01

International audience; This qualitative study, aimed to analyze eight French-speaking learners' beliefs about English and English language learning. The data were obtained via semi-structured interviews. The study drew on Weiner's attribution theory of achievement motivation and Bandura's self-efficacy theory. The novelty about this research is the employment of an attributional analysis framework to study and explain the learners' stated beliefs about English and English language learning.

Experiences from a pilot study on how to conduct a qualitative multi-country research project regarding use of antibiotics in Southeast Europe.

Science.gov (United States)

Kaae, Susanne; Sporrong, Sofia Kälvemark; Traulsen, Janine Morgall; Wallach Kildemoes, Helle; Nørgaard, Lotte Stig; Jakupi, Arianit; Raka, Denis; Gürpinar, Emre Umut; Alkan, Ali; Hoxha, Iris; Malaj, Admir; Cantarero, Lourdes Arevalo

2016-01-01

In 2014, a qualitative multi-country research project was launched to study the reasons behind the high use of antibiotics in regions of Southeast Europe by using previously untrained national interviewers (who were engaged in other antibiotic microbial resistance-related investigations) to conduct qualitative interviews with local patients, physicians and pharmacists. Little knowledge exists about how to implement qualitative multi-country research collaborations involving previously untrained local data collectors. The aim of this paper was therefore to contribute to the knowledge regarding how to conduct these types of research projects by evaluating a pilot study of the project. Local data collectors conducted the study according to a developed protocol and evaluated the study with the responsible researcher-team from University of Copenhagen. The pilot study focused on 'local ownership', 'research quality' and 'feasibility' with regard to successful implementation and evaluation. The evaluation was achieved by interpreting 'Skype' and 'face to face' meetings and email correspondence by applying 'critical common sense'. Local data collectors achieved a sense of joint ownership. Overall, the protocol worked well. Several minor challenges pertaining to research quality and feasibility were identified, in particular obtaining narratives when conducting interviews and recruiting patients for the study. Furthermore, local data collectors found it difficult to allocate sufficient time to the project. Solutions were discussed and added to the protocol. Despite the challenges, it was possible to achieve an acceptable scientific level of research when conducting qualitative multi-country research collaboration under the given circumstances. Specific recommendations to achieve this are provided by the authors.

Environmental Consequences of Wildlife Tourism: The Use of Formalised Qualitative Models

Directory of Open Access Journals (Sweden)

Veselý Štěpán

2015-09-01

Full Text Available The paper presents a simple qualitative model of environmental consequences of wildlife tourism. Qualitative models use just three values: Positive/Increasing, Zero/Constant and Negative/Decreasing. Such quantifiers of trends are the least information intensive. Qualitative models can be useful, since models of wildlife tourism include such variables as, for example, Biodiversity (BIO, Animals’ habituation to tourists (HAB or Plant composition change (PLA that are sometimes difficult or costly to quantify. Hence, a significant fraction of available information about wildlife tourism and its consequences is not of numerical nature, for example, if HAB is increasing then BIO is decreasing. Such equationless relations are studied in this paper. The model has 10 variables and 20 equationless pairwise interrelations among them. The model is solved and 15 solutions, that is, scenarios are obtained. All qualitative states, including the first and second qualitative derivatives with respect to time, of all variables are specified for each scenario.

Primitive-path statistics of entangled polymers: mapping multi-chain simulations onto single-chain mean-field models

International Nuclear Information System (INIS)

Steenbakkers, Rudi J A; Schieber, Jay D; Tzoumanekas, Christos; Li, Ying; Liu, Wing Kam; Kröger, Martin

2014-01-01

We present a method to map the full equilibrium distribution of the primitive-path (PP) length, obtained from multi-chain simulations of polymer melts, onto a single-chain mean-field ‘target’ model. Most previous works used the Doi–Edwards tube model as a target. However, the average number of monomers per PP segment, obtained from multi-chain PP networks, has consistently shown a discrepancy of a factor of two with respect to tube-model estimates. Part of the problem is that the tube model neglects fluctuations in the lengths of PP segments, the number of entanglements per chain and the distribution of monomers among PP segments, while all these fluctuations are observed in multi-chain simulations. Here we use a recently proposed slip-link model, which includes fluctuations in all these variables as well as in the spatial positions of the entanglements. This turns out to be essential to obtain qualitative and quantitative agreement with the equilibrium PP-length distribution obtained from multi-chain simulations. By fitting this distribution, we are able to determine two of the three parameters of the model, which govern its equilibrium properties. This mapping is executed for four different linear polymers and for different molecular weights. The two parameters are found to depend on chemistry, but not on molecular weight. The model predicts a constant plateau modulus minus a correction inversely proportional to molecular weight. The value for well-entangled chains, with the parameters determined ab initio, lies in the range of experimental data for the materials investigated. (paper)

Informing vaccine decision-making: A strategic multi-attribute ranking tool for vaccines-SMART Vaccines 2.0.

Science.gov (United States)

Knobler, Stacey; Bok, Karin; Gellin, Bruce

2017-01-20

SMART Vaccines 2.0 software is being developed to support decision-making among multiple stakeholders in the process of prioritizing investments to optimize the outcomes of vaccine development and deployment. Vaccines and associated vaccination programs are one of the most successful and effective public health interventions to prevent communicable diseases and vaccine researchers are continually working towards expanding targets for communicable and non-communicable diseases through preventive and therapeutic modes. A growing body of evidence on emerging vaccine technologies, trends in disease burden, costs associated with vaccine development and deployment, and benefits derived from disease prevention through vaccination and a range of other factors can inform decision-making and investment in new and improved vaccines and targeted utilization of already existing vaccines. Recognizing that an array of inputs influences these decisions, the strategic multi-attribute ranking method for vaccines (SMART Vaccines 2.0) is in development as a web-based tool-modified from a U.S. Institute of Medicine Committee effort (IOM, 2015)-to highlight data needs and create transparency to facilitate dialogue and information-sharing among decision-makers and to optimize the investment of resources leading to improved health outcomes. Current development efforts of the SMART Vaccines 2.0 framework seek to generate a weighted recommendation on vaccine development or vaccination priorities based on population, disease, economic, and vaccine-specific data in combination with individual preference and weights of user-selected attributes incorporating valuations of health, economics, demographics, public concern, scientific and business, programmatic, and political considerations. Further development of the design and utility of the tool is being carried out by the National Vaccine Program Office of the Department of Health and Human Services and the Fogarty International Center of the

Attribute And-Or Grammar for Joint Parsing of Human Pose, Parts and Attributes.

Science.gov (United States)

Park, Seyoung; Nie, Xiaohan; Zhu, Song-Chun

2017-07-25

This paper presents an attribute and-or grammar (A-AOG) model for jointly inferring human body pose and human attributes in a parse graph with attributes augmented to nodes in the hierarchical representation. In contrast to other popular methods in the current literature that train separate classifiers for poses and individual attributes, our method explicitly represents the decomposition and articulation of body parts, and account for the correlations between poses and attributes. The A-AOG model is an amalgamation of three traditional grammar formulations: (i)Phrase structure grammar representing the hierarchical decomposition of the human body from whole to parts; (ii)Dependency grammar modeling the geometric articulation by a kinematic graph of the body pose; and (iii)Attribute grammar accounting for the compatibility relations between different parts in the hierarchy so that their appearances follow a consistent style. The parse graph outputs human detection, pose estimation, and attribute prediction simultaneously, which are intuitive and interpretable. We conduct experiments on two tasks on two datasets, and experimental results demonstrate the advantage of joint modeling in comparison with computing poses and attributes independently. Furthermore, our model obtains better performance over existing methods for both pose estimation and attribute prediction tasks.

Multi-model analysis in hydrological prediction

Science.gov (United States)

Lanthier, M.; Arsenault, R.; Brissette, F.

2017-12-01

Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

Application of the fuzzy topsis multi-attribute decision making method to determine scholarship recipients

Science.gov (United States)

Irvanizam, I.

2018-03-01

Some scholarships have been routinely offered by Ministry of Research, Technology and Higher Education of the Republic of Indonesia for students at Syiah Kuala University. In reality, the scholarship selection process is becoming subjective and highly complex problem. Multi-Attribute Decision Making (MADM) techniques can be a solution in order to solve scholarship selection problem. In this study, we demonstrated the application of a fuzzy TOPSIS as an MADM technique by using a numerical example in order to calculate a triangular fuzzy number for the fuzzy data onto a normalized weight. We then use this normalized value to construct the normalized fuzzy decision matrix. We finally use the fuzzy TOPSIS to rank alternatives in descending order based on the relative closeness to the ideal solution. The result in terms of final ranking shows slightly different from the previous work.

Integrated multi-scale modelling and simulation of nuclear fuels

International Nuclear Information System (INIS)

Valot, C.; Bertolus, M.; Masson, R.; Malerba, L.; Rachid, J.; Besmann, T.; Phillpot, S.; Stan, M.

2015-01-01

This chapter aims at discussing the objectives, implementation and integration of multi-scale modelling approaches applied to nuclear fuel materials. We will first show why the multi-scale modelling approach is required, due to the nature of the materials and by the phenomena involved under irradiation. We will then present the multiple facets of multi-scale modelling approach, while giving some recommendations with regard to its application. We will also show that multi-scale modelling must be coupled with appropriate multi-scale experiments and characterisation. Finally, we will demonstrate how multi-scale modelling can contribute to solving technology issues. (authors)

The interactive attribution of school success in multi-ethnic schools

NARCIS (Netherlands)

de Haan, M.; Wissink, I.

2013-01-01

The study shows how explanations for school success are expressed and dialogically constructed during teacher-parent conferences at school. Attribution theory is used to conceptualize the various explanations for school success that were expressed. However, instead of only looking at attributions as

Common attributes in retired professional cricketers that may enhance or hinder quality of life after retirement: a qualitative study.

Science.gov (United States)

Filbay, Stephanie R; Bishop, Felicity; Peirce, Nicholas; Jones, Mary E; Arden, Nigel K

2017-07-26

Retired professional cricketers shared unique experiences and may possess specific psychological attributes with potential to influence quality of life (QOL). Additionally, pain and osteoarthritis can be common in retired athletes which may negatively impact QOL. However, QOL in retired athletes is poorly understood. This study explores the following questions from the personal perspective of retired cricketers: How do retired cricketers perceive and experience musculoskeletal pain and function in daily life? Are there any psychological attributes that might enhance or hinder retired cricketers' QOL? A qualitative study using semistructured interviews, which were subject to inductive, thematic analysis. A data-driven, iterative approach to data coding was employed. All participants had lived and played professional cricket in the UK and were living in the UK or abroad at the time of interview. Eighteen male participants, aged a mean 57±11 (range 34-77) years had played professional cricket for a mean 12±7 seasons and had been retired from professional cricket on average 23±9 years. Fifteen participants reported pain or joint difficulties and all but one was satisfied with their QOL. Most retired cricketers reflected on experiences during their cricket career that may be associated with the psychological attributes that these individuals shared, including resilience and a positive attitude. Additional attributes included a high sense of body awareness, an ability to self-manage pain and adapt lifestyle choices to accommodate physical limitations. Participants felt fortunate and proud to have played professional cricket, which may have further contributed to the high QOL in this group of retired cricketers. Most retired cricketers in this study were living with pain or joint difficulties. Despite this, all but one was satisfied or very satisfied with their QOL. This may be partly explained by the positive psychological attributes that these retired cricketers

Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

Science.gov (United States)

Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.

2016-03-01

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

On the Nirex MADA [Multi-Attribute Decision Analysis]. Proof of evidence

International Nuclear Information System (INIS)

Stirling, A.

1996-01-01

Proof of Evidence is given by an expert witness on behalf of Greenpeace Ltd as part of their submission to a Planning Inquiry in 1995 hearing the application of UK Nirex Ltd for permission to construct an underground Rock Characterisation Facility (RCF) at a site near Sellafield. The RCF is part of an investigation by Nirex into a suitable site for the disposal of radioactive waste. The evidence concerns the use by Nirex of a technique known as Multi-Attribute Decision Analysis (MADA) in support of their decision to concentrate their studies on the Sellafield site. Potentially, MADA offers a highly effective methodology for making difficult political decisions involving a mixture of technical, social and economic considerations. Its proper use, however, relies on: drawing an explicit distinction between relatively technical ''performance scores'' and wholly subjective ''importance weightings''; a clearly expressed and agreed scope for the analysis; the inclusion of a wide range of perspectives; systematic and comprehensive sensitivity testing of the implications of varying data, assumptions and value judgements; optimising the choice of option under each perspective; presenting explicit data, assumptions, transparent methodologies and accessible procedures for critical evaluation and public peer review. It is concluded that Nirex's MADA seems to be seriously deficient in relation to many of these principles. (9 references). (UK)

Qualitative simulation in formal process modelling

International Nuclear Information System (INIS)

Sivertsen, Elin R.

1999-01-01

In relation to several different research activities at the OECD Halden Reactor Project, the usefulness of formal process models has been identified. Being represented in some appropriate representation language, the purpose of these models is to model process plants and plant automatics in a unified way to allow verification and computer aided design of control strategies. The present report discusses qualitative simulation and the tool QSIM as one approach to formal process models. In particular, the report aims at investigating how recent improvements of the tool facilitate the use of the approach in areas like process system analysis, procedure verification, and control software safety analysis. An important long term goal is to provide a basis for using qualitative reasoning in combination with other techniques to facilitate the treatment of embedded programmable systems in Probabilistic Safety Analysis (PSA). This is motivated from the potential of such a combination in safety analysis based on models comprising both software, hardware, and operator. It is anticipated that the research results from this activity will benefit V and V in a wide variety of applications where formal process models can be utilized. Examples are operator procedures, intelligent decision support systems, and common model repositories (author) (ml)

Microphysics in Multi-scale Modeling System with Unified Physics

Science.gov (United States)

Tao, Wei-Kuo

2012-01-01

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

The Goddard multi-scale modeling system with unified physics

Directory of Open Access Journals (Sweden)

W.-K. Tao

2009-08-01

Full Text Available Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1 a cloud-resolving model (CRM, (2 a regional-scale model, the NASA unified Weather Research and Forecasting Model (WRF, and (3 a coupled CRM-GCM (general circulation model, known as the Goddard Multi-scale Modeling Framework or MMF. The same cloud-microphysical processes, long- and short-wave radiative transfer and land-surface processes are applied in all of the models to study explicit cloud-radiation and cloud-surface interactive processes in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator for comparison and validation with NASA high-resolution satellite data.

This paper reviews the development and presents some applications of the multi-scale modeling system, including results from using the multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols. In addition, use of the multi-satellite simulator to identify the strengths and weaknesses of the model-simulated precipitation processes will be discussed as well as future model developments and applications.

Model Stirrer Based on a Multi-Material Turntable for Microwave Processing Materials

Directory of Open Access Journals (Sweden)

Jinghua Ye

2017-01-01

Full Text Available Microwaves have been widely used in the treatment of materials, such as heating, drying, and sterilization. However, the heating in the commonly used microwave applicators is usually uneven. In this paper, a novel multi-material turntable structure is creatively proposed to improve the temperature uniformity in microwave ovens. Three customized turntables consisting of polyethylene (PE and alumina, PE and aluminum, and alumina and aluminum are, respectively, utilized in a domestic microwave oven in simulation. During the heating process, the processed material is placed on a fixed Teflon bracket which covers the constantly rotating turntable. Experiments are conducted to measure the surface and point temperatures using an infrared thermal imaging camera and optical fibers. Simulated results are compared qualitatively with the measured ones, which verifies the simulated models. Compared with the turntables consisting of a single material, a 26%–47% increase in temperature uniformity from adapting the multi-material turntable can be observed for the microwave-processed materials.

The Interactive Attribution of School Success in Multi-Ethnic Schools

Science.gov (United States)

de Haan, Mariette; Wissink, Inge

2013-01-01

The study shows how explanations for school success are expressed and dialogically constructed during teacher-parent conferences at school. Attribution theory is used to conceptualize the various explanations for school success that were expressed. However, instead of only looking at attributions as beliefs which individuals or groups "have", the…

Modeling Aquatic Macroinvertebrate Richness Using Landscape Attributes

Directory of Open Access Journals (Sweden)

Marcia S. Meixler

2015-01-01

Full Text Available We used a rapid, repeatable, and inexpensive geographic information system (GIS approach to predict aquatic macroinvertebrate family richness using the landscape attributes stream gradient, riparian forest cover, and water quality. Stream segments in the Allegheny River basin were classified into eight habitat classes using these three landscape attributes. Biological databases linking macroinvertebrate families with habitat classes were developed using life habits, feeding guilds, and water quality preferences and tolerances for each family. The biological databases provided a link between fauna and habitat enabling estimation of family composition in each habitat class and hence richness predictions for each stream segment. No difference was detected between field collected and modeled predictions of macroinvertebrate families in a paired t-test. Further, predicted stream gradient, riparian forest cover, and total phosphorus, total nitrogen, and suspended sediment classifications matched observed classifications much more often than by chance alone. High gradient streams with forested riparian zones and good water quality were predicted to have the greatest macroinvertebrate family richness and changes in water quality were predicted to have the greatest impact on richness. Our findings indicate that our model can provide meaningful landscape scale macroinvertebrate family richness predictions from widely available data for use in focusing conservation planning efforts.

Attribution models and the Cooperative Game Theory

OpenAIRE

Cano Berlanga, Sebastian; Vilella, Cori

2017-01-01

The current paper studies the attribution model used by Google Analytics. Precisely, we use the Cooperative Game Theory to propose a fair distribution of the revenues among the considered channels, in order to facilitate the cooperation and to guarantee stability. We define a transferable utility convex cooperative game from the observed frequencies and we use the Shapley value to allocate the revenues among the di erent channels. Furthermore, we evaluate the impact of an advertising...

Attributional style and depression in multiple sclerosis: the learned helplessness model.

Science.gov (United States)

Vargas, Gray A; Arnett, Peter A

2013-01-01

Several etiologic theories have been proposed to explain depression in the general population. Studying these models and modifying them for use in the multiple sclerosis (MS) population may allow us to better understand depression in MS. According to the reformulated learned helplessness (LH) theory, individuals who attribute negative events to internal, stable, and global causes are more vulnerable to depression. This study differentiated attributional style that was or was not related to MS in 52 patients with MS to test the LH theory in this population and to determine possible differences between illness-related and non-illness-related attributions. Patients were administered measures of attributional style, daily stressors, disability, and depressive symptoms. Participants were more likely to list non-MS-related than MS-related causes of negative events on the Attributional Style Questionnaire (ASQ), and more-disabled participants listed significantly more MS-related causes than did less-disabled individuals. Non-MS-related attributional style correlated with stress and depressive symptoms, but MS-related attributional style did not correlate with disability or depressive symptoms. Stress mediated the effect of non-MS-related attributional style on depressive symptoms. These results suggest that, although attributional style appears to be an important construct in MS, it does not seem to be related directly to depressive symptoms; rather, it is related to more perceived stress, which in turn is related to increased depressive symptoms.

Application fuzzy multi-attribute decision analysis method to prioritize project success criteria

Science.gov (United States)

Phong, Nguyen Thanh; Quyen, Nguyen Le Hoang Thuy To

2017-11-01

Project success is a foundation for project owner to manage and control not only for the current project but also for future potential projects in construction companies. However, identifying the key success criteria for evaluating a particular project in real practice is a challenging task. Normally, it depends on a lot of factors, such as the expectation of the project owner and stakeholders, triple constraints of the project (cost, time, quality), and company's mission, vision, and objectives. Traditional decision-making methods for measuring the project success are usually based on subjective opinions of panel experts, resulting in irrational and inappropriate decisions. Therefore, this paper introduces a multi-attribute decision analysis method (MADAM) for weighting project success criteria by using fuzzy Analytical Hierarchy Process approach. It is found that this method is useful when dealing with imprecise and uncertain human judgments in evaluating project success criteria. Moreover, this research also suggests that although cost, time, and quality are three project success criteria projects, the satisfaction of project owner and acceptance of project stakeholders with the completed project criteria is the most important criteria for project success evaluation in Vietnam.

SDG and qualitative trend based model multiple scale validation

Science.gov (United States)

Gao, Dong; Xu, Xin; Yin, Jianjin; Zhang, Hongyu; Zhang, Beike

2017-09-01

Verification, Validation and Accreditation (VV&A) is key technology of simulation and modelling. For the traditional model validation methods, the completeness is weak; it is carried out in one scale; it depends on human experience. The SDG (Signed Directed Graph) and qualitative trend based multiple scale validation is proposed. First the SDG model is built and qualitative trends are added to the model. And then complete testing scenarios are produced by positive inference. The multiple scale validation is carried out by comparing the testing scenarios with outputs of simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.

A repertoire of leadership attributes: an international study of deans of nursing.

Science.gov (United States)

Wilkes, Lesley; Cross, Wendy; Jackson, Debra; Daly, John

2015-04-01

To determine which characteristics of academic leadership are perceived to be necessary for nursing deans to be successful. Effective leadership is essential for the continued growth of the discipline. A qualitative study using semi-structured interviews with 30 deans (academics in universities who headed a nursing faculty and degree programmes) was conducted in three countries--Canada, England and Australia. The conversations were analysed for leadership attributes. Sixty personal and positional attributes were nominated by the participants. Of these, the most frequent attribute was 'having vision'. Personal attributes included: passion, patience, courage, facilitating, sharing and being supportive. Positional attributes included: communication, faculty development, role modelling, good management and promoting nursing. Both positional and personal aspects of academic leadership are important to assist in developing a succession plan and education for new deans. It is important that talented people are recognised as potential leaders of the future. These future leaders should be given every chance to grow and develop through exposure to opportunities to develop skills and the attributes necessary for effective deanship. Strategic mentoring could prove to be useful in developing and supporting the growth of future deans of nursing. © 2013 John Wiley & Sons Ltd.

Modeling with Young Students--Quantitative and Qualitative.

Science.gov (United States)

Bliss, Joan; Ogborn, Jon; Boohan, Richard; Brosnan, Tim; Mellar, Harvey; Sakonidis, Babis

1999-01-01

A project created tasks and tools to investigate quality and nature of 11- to 14-year-old pupils' reasoning with quantitative and qualitative computer-based modeling tools. Tasks and tools were used in two innovative modes of learning: expressive, where pupils created their own models, and exploratory, where pupils investigated an expert's model.…

Towards a Computational Model of the Self-attribution of Agency

NARCIS (Netherlands)

Hindriks, K.V.; Wiggers, P.; Jonker, C.M.; Haselager, W.F.G.; Mehrotra, K.G.; Mohan, C.K.; Oh, J.C.; Varshney, P.K.; Ali, M.

2011-01-01

In this paper, a first step towards a computational model of the self-attribution of agency is presented, based on Wegner’s theory of apparent mental causation. A model to compute a feeling of doing based on first-order Bayesian network theory is introduced that incorporates the main contributing

Towards a computational model of the self-attribution of agency

NARCIS (Netherlands)

Hindriks, K.V.; Wiggers, P.; Jonker, C.M.; Haselager, W.F.G.; Olivier, P.; Kray, C.

2007-01-01

In this paper, a first step towards a computational model of the self-attribution of agency is presented, based on Wegner’s theory of apparent mental causation. A model to compute a feeling of doing based on first-order Bayesian network theory is introduced that incorporates the main contributing

A Qualitative Multi-Case Study of the Influence of Personal and Professional Ethics on the Leadership of Public School Superintendents

Science.gov (United States)

McDermott, Brian J.

2010-01-01

The purpose of this study is to examine the influence of personal and professional ethics on the leadership of public school superintendents. A multi-case, qualitative research design was used to gather data from four practicing public school superintendents. Transformational leadership theory and the three pillars of ethics of leadership…

Model-Based Analysis for Qualitative Data: An Application in Drosophila Germline Stem Cell Regulation

Science.gov (United States)

Pargett, Michael; Rundell, Ann E.; Buzzard, Gregery T.; Umulis, David M.

2014-01-01

Discovery in developmental biology is often driven by intuition that relies on the integration of multiple types of data such as fluorescent images, phenotypes, and the outcomes of biochemical assays. Mathematical modeling helps elucidate the biological mechanisms at play as the networks become increasingly large and complex. However, the available data is frequently under-utilized due to incompatibility with quantitative model tuning techniques. This is the case for stem cell regulation mechanisms explored in the Drosophila germarium through fluorescent immunohistochemistry. To enable better integration of biological data with modeling in this and similar situations, we have developed a general parameter estimation process to quantitatively optimize models with qualitative data. The process employs a modified version of the Optimal Scaling method from social and behavioral sciences, and multi-objective optimization to evaluate the trade-off between fitting different datasets (e.g. wild type vs. mutant). Using only published imaging data in the germarium, we first evaluated support for a published intracellular regulatory network by considering alternative connections of the same regulatory players. Simply screening networks against wild type data identified hundreds of feasible alternatives. Of these, five parsimonious variants were found and compared by multi-objective analysis including mutant data and dynamic constraints. With these data, the current model is supported over the alternatives, but support for a biochemically observed feedback element is weak (i.e. these data do not measure the feedback effect well). When also comparing new hypothetical models, the available data do not discriminate. To begin addressing the limitations in data, we performed a model-based experiment design and provide recommendations for experiments to refine model parameters and discriminate increasingly complex hypotheses. PMID:24626201

Intrusion detection model using fusion of chi-square feature selection and multi class SVM

Directory of Open Access Journals (Sweden)

Ikram Sumaiya Thaseen

2017-10-01

Full Text Available Intrusion detection is a promising area of research in the domain of security with the rapid development of internet in everyday life. Many intrusion detection systems (IDS employ a sole classifier algorithm for classifying network traffic as normal or abnormal. Due to the large amount of data, these sole classifier models fail to achieve a high attack detection rate with reduced false alarm rate. However by applying dimensionality reduction, data can be efficiently reduced to an optimal set of attributes without loss of information and then classified accurately using a multi class modeling technique for identifying the different network attacks. In this paper, we propose an intrusion detection model using chi-square feature selection and multi class support vector machine (SVM. A parameter tuning technique is adopted for optimization of Radial Basis Function kernel parameter namely gamma represented by ‘ϒ’ and over fitting constant ‘C’. These are the two important parameters required for the SVM model. The main idea behind this model is to construct a multi class SVM which has not been adopted for IDS so far to decrease the training and testing time and increase the individual classification accuracy of the network attacks. The investigational results on NSL-KDD dataset which is an enhanced version of KDDCup 1999 dataset shows that our proposed approach results in a better detection rate and reduced false alarm rate. An experimentation on the computational time required for training and testing is also carried out for usage in time critical applications.

Generalised linear models for correlated pseudo-observations, with applications to multi-state models

DEFF Research Database (Denmark)

Andersen, Per Kragh; Klein, John P.; Rosthøj, Susanne

2003-01-01

Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model......Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model...

Multiple attribute decision making model and application to food safety risk evaluation.

Science.gov (United States)

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Exploration of Scholars’ Attributions of Instructional Barriers in the Context of Pedagogical-Epistemological Belief Systems

Directory of Open Access Journals (Sweden)

Yılmaz SOYSAL

2017-08-01

Full Text Available In this study, two academics’ who have been employed in a private university teaching barriers and accompanied attributional reasoning were examined in the context of their belief systems with regards to learning, teaching and knowledge. This study was conducted with a basic qualitative perspective. By means of qualitative data gathering and analysis, it was aimed at estimating how the relation between teaching barriers and attributional reasoning was influenced by pedagogical-epistemological belief systems of scholars. Qualitative data was collected through two different semi-structured interview protocols and gathered data was analyzed with an inductive and interpretivist manner. The scholars’ beliefs systems’ divergences (teacher-centered vs. learner-centered allowed to explore the presumable relation of barrier-attribution in the context of pedagogical-epistemological belief systems. It was found out that the scholar who has adopted the more learner-centered modes of teaching favors more internally-oriented, controllable and non-stable attributional styles in illustrating her barrier-attribution relation. In contrast, it was also detected that the scholar who has held more teacher-centered teaching beliefs is liable to make attributions to overly external, non-controllable and stable factors in illuminating her barrier-attribution relation. Major outcomes of the study are evaluated by means of psychological (i.e., attribution theory and instructional (pedagogical-epistemological beliefs lenses and suggestions are offered in the context of higher education.

A research on applications of qualitative reasoning techniques in Human Acts Simulation Program

International Nuclear Information System (INIS)

Far, B.H.

1992-04-01

Human Acts Simulation Program (HASP) is a ten-year research project of the Computing and Information Systems Center of JAERI. In HASP the goal is developing programs for an advanced intelligent robot to accomplish multiple instructions (for instance, related to surveillance, inspection and maintenance) in nuclear power plants. Some recent artificial intelligence techniques can contribute to this project. This report introduces some original contributions concerning application of Qualitative Reasoning (QR) techniques in HASP. The focus is on the knowledge-intensive tasks, including model-based reasoning, analytic learning, fault diagnosis and functional reasoning. The multi-level extended qualitative modeling for the Skill-Rule-Knowledge (S-R-K) based reasoning, that included the coordination and timing of events, Qualitative Sensitivity analysis (Q S A), Subjective Qualitative Fault Diagnosis (S Q F D) and Qualitative Function Formation (Q F F ) techniques are introduced. (author) 123 refs

Multi-Agent Modeling in Managing Six Sigma Projects

Directory of Open Access Journals (Sweden)

K. Y. Chau

2009-10-01

Full Text Available In this paper, a multi-agent model is proposed for considering the human resources factor in decision making in relation to the six sigma project. The proposed multi-agent system is expected to increase the acccuracy of project prioritization and to stabilize the human resources service level. A simulation of the proposed multiagent model is conducted. The results show that a multi-agent model which takes into consideration human resources when making decisions about project selection and project team formation is important in enabling efficient and effective project management. The multi-agent modeling approach provides an alternative approach for improving communication and the autonomy of six sigma projects in business organizations.

Security of statistical data bases: invasion of privacy through attribute correlational modeling

Energy Technology Data Exchange (ETDEWEB)

Palley, M.A.

1985-01-01

This study develops, defines, and applies a statistical technique for the compromise of confidential information in a statistical data base. Attribute Correlational Modeling (ACM) recognizes that the information contained in a statistical data base represents real world statistical phenomena. As such, ACM assumes correlational behavior among the database attributes. ACM proceeds to compromise confidential information through creation of a regression model, where the confidential attribute is treated as the dependent variable. The typical statistical data base may preclude the direct application of regression. In this scenario, the research introduces the notion of a synthetic data base, created through legitimate queries of the actual data base, and through proportional random variation of responses to these queries. The synthetic data base is constructed to resemble the actual data base as closely as possible in a statistical sense. ACM then applies regression analysis to the synthetic data base, and utilizes the derived model to estimate confidential information in the actual database.

FAT-miner: mining frequent attribute trees

NARCIS (Netherlands)

Knijf, de J.; Cho, Y.; Wainwright, R.L.; Haddad, H.; Shin, S.Y.; Koo, Y.W.

2007-01-01

Data that can conceptually be viewed as tree structures abounds in domains such as bio-informatics, web logs, XML databases and multi-relational databases. Besides structural information such as nodes and edges, tree structured data also often contains attributes, that represent properties of nodes.

Multiple attribute decision making model and application to food safety risk evaluation.

Directory of Open Access Journals (Sweden)

Lihua Ma

Full Text Available Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Development of the promoting teacher attribution model for promoting science teachers' moral and ethical characteristics

Science.gov (United States)

Chanprathak, Anusorn; Worakham, Paisan; Suikraduang, Arun

2018-01-01

The promotion science teacher attribution model to develop the moral and ethical characteristics was to analyze, synthesis, and develop the guidelines of the scoping study into concepts, theories and research related about the moral and ethics of characteristically teachers from the resources, including research papers, research articles related research, and interviews with luminaries of 9 members. Using interviews and document analysis, data analysis, content analysis, and present an essay was built. The promoting attributes a teacher, moral principles, concepts and theories involved and guidance of a qualified were developed. The Multiple-Attribute Consensus Reaching (MACR) from 12 educational experts were checked the suitability and feasibility of the model, the possibility of the manual with the research instruments consisted of the promotion model attributes the moral and ethics teacher's characteristics were evaluated, to guide the promotion attributes' model forms were assessed, the first edition of the manual data analysis, information obtained from the evaluation of the suitability and feasibility analysis model and guide for the average were administered. The results have found that; the promoting moral teacher attribute data to their moral and ethical characteristics was divided into two groups, priests and scholars. In both groups, the promotion attributes, focusing on teacher's groups is moral in nature to modify the idea to a change of attitude within the organism. Students got down to real experience; an analysis and synthesis face learning environments that cause cognitive skills to act as a self-realization possibly. The promotion model, moral principles, including the importance of the activities, objectives and evaluation methods were attributed. These core concepts learning theory and social cognitive theory, and integrated learning experience were comprised in five stages and four processes, namely; the intended, memory storage process, the

Attributional Style and Depression in Multiple Sclerosis: The Learned Helplessness Model

OpenAIRE

Vargas, Gray A.; Arnett, Peter A.

2013-01-01

Several etiologic theories have been proposed to explain depression in the general population. Studying these models and modifying them for use in the multiple sclerosis (MS) population may allow us to better understand depression in MS. According to the reformulated learned helplessness (LH) theory, individuals who attribute negative events to internal, stable, and global causes are more vulnerable to depression. This study differentiated attributional style that was or was not related to MS...

Reference Models for Multi-Layer Tissue Structures

Science.gov (United States)

2016-09-01

function of multi-layer tissues (etiology and management of pressure ulcers ). What was the impact on other disciplines? As part of the project, a data...simplification to develop cost -effective models of surface manipulation of multi-layer tissues. Deliverables. Specimen- (or subject) and region-specific...simplification to develop cost -effective models of surgical manipulation. Deliverables. Specimen-specific surrogate models of upper legs confirmed against data

Extending Attribution Theory: Considering Students' Perceived Control of the Attribution Process

Science.gov (United States)

Fishman, Evan J.; Husman, Jenefer

2017-01-01

Research in attribution theory has shown that students' causal thinking profoundly affects their learning and motivational outcomes. Very few studies, however, have explored how students' attribution-related beliefs influence the causal thought process. The present study used the perceived control of the attribution process (PCAP) model to examine…

A model to Estimate the Implicit Values of Housing Attributes by Applying the Hedonic Pricing Method

Directory of Open Access Journals (Sweden)

TD Randeniya

2017-05-01

Full Text Available Many scholars focused on the location based attributes rather than the non-location factors in decision making on land prices. Further, new research studies have identified the importance of the non-location attributes with the location factors. Many studies suggest that, many attributes exist which affects the housing price. Since the attributes involved and dominant for a particular case differs from one situation to the other, there cannot be an exact list of attributes. Yet, identification of factors that determine housing price and their relationships and the level of influence have poorly understood in planning and property development in the context of Sri Lanka. This study attempts to address what make householders to decide on housing price and application of hedonic pricing approach to estimate the implicit price of housing attributes in context of Sri Lanka. A sample study of selected fifty (50 single house transactions in Maharagama urban neighborhood area has been utilized to illustrate the applicability of the hedonic pricing model. As a methodology, correlation analysis has been carried out to study the degree of relationship between the housing price and the independent variables. The attributes which correlate with housing prices, the study identified the most significant attributes. A model was developed to estimate the future house price by applying the pricing model which is incorporated with these attributes. A hedonic house price model derived from multiple liner regression analysis was developed for the purpose. The findings reveal that six attributes as design type of the house, distance to the local road, quality of Infrastructure, garden size, number of the bed rooms and property age are contributed to estimate the implicit value of Housing property. The model developed would be used to identify implicit values of houses located in urban neighborhood area of Sri Lanka.

A Multi-Session Attribution Modification Program for Children with Aggressive Behaviour: Changes in Attributions, Emotional Reaction Estimates, and Self-Reported Aggression.

Science.gov (United States)

Vassilopoulos, Stephanos P; Brouzos, Andreas; Andreou, Eleni

2015-09-01

Research suggests that aggressive children are prone to over-attribute hostile intentions to peers. The current study investigated whether this attributional style can be altered using a Cognitive Bias Modification of Interpretations (CBM-I) procedure. A sample of 10-12-year-olds selected for displaying aggressive behaviours was trained over three sessions to endorse benign rather than hostile attributions in response to ambiguous social scenarios. Compared to a test-retest control group (n = 18), children receiving CBM-I (n = 16) were less likely to endorse hostile attributions and more likely to endorse benign attributions in response to a new set of ambiguous social situations. Furthermore, aggressive behaviour scores reduced more in the trained group than in the untrained controls. Children who received attribution training also reported less perceived anger and showed a trend to report more self-control than those in the control group. Implications of these findings are discussed.

A Multi-Model Approach for System Diagnosis

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad; Bækgaard, Mikkel Ask Buur

2007-01-01

A multi-model approach for system diagnosis is presented in this paper. The relation with fault diagnosis as well as performance validation is considered. The approach is based on testing a number of pre-described models and find which one is the best. It is based on an active approach......,i.e. an auxiliary input to the system is applied. The multi-model approach is applied on a wind turbine system....

SCOPE – An Integrated Framework for Multi-Attribute Decision Making

DEFF Research Database (Denmark)

Leleur, Steen

2004-01-01

that are supported by a methodology of both a systemic and a systematic type. Specific use is made of operational research methods such as critical systems heuristics, scenario technique, stakeholder analysis and multi‐attribute decision making (MADM). To deal with issues of complexity and ambiguity, planning......This article presents an integrated framework for multi‐attribute decision making named SCOPE (System for Combined Planning and Evaluation) that was developed to assess infrastructure policy initiatives—in complex decision environments. The framework comprises scanning as well as assessment issues...

Multi-time, multi-scale correlation functions in turbulence and in turbulent models

NARCIS (Netherlands)

Biferale, L.; Boffetta, G.; Celani, A.; Toschi, F.

1999-01-01

A multifractal-like representation for multi-time, multi-scale velocity correlation in turbulence and dynamical turbulent models is proposed. The importance of subleading contributions to time correlations is highlighted. The fulfillment of the dynamical constraints due to the equations of motion is

Learning about Ecological Systems by Constructing Qualitative Models with DynaLearn

Science.gov (United States)

Leiba, Moshe; Zuzovsky, Ruth; Mioduser, David; Benayahu, Yehuda; Nachmias, Rafi

2012-01-01

A qualitative model of a system is an abstraction that captures ordinal knowledge and predicts the set of qualitatively possible behaviours of the system, given a qualitative description of its structure and initial state. This paper examines an innovative approach to science education using an interactive learning environment that supports…

Empirical analyses of a choice model that captures ordering among attribute values

DEFF Research Database (Denmark)

Mabit, Stefan Lindhard

2017-01-01

an alternative additionally because it has the highest price. In this paper, we specify a discrete choice model that takes into account the ordering of attribute values across alternatives. This model is used to investigate the effect of attribute value ordering in three case studies related to alternative-fuel...... vehicles, mode choice, and route choice. In our application to choices among alternative-fuel vehicles, we see that especially the price coefficient is sensitive to changes in ordering. The ordering effect is also found in the applications to mode and route choice data where both travel time and cost...

Multi-issue Agent Negotiation Based on Fairness

Science.gov (United States)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

A comparative review of multi-risk modelling methodologies for climate change adaptation in mountain regions

Science.gov (United States)

Terzi, Stefano; Torresan, Silvia; Schneiderbauer, Stefan

2017-04-01

Keywords: Climate change, mountain regions, multi-risk assessment, climate change adaptation. Climate change has already led to a wide range of impacts on the environment, the economy and society. Adaptation actions are needed to cope with the impacts that have already occurred (e.g. storms, glaciers melting, floods, droughts) and to prepare for future scenarios of climate change. Mountain environment is particularly vulnerable to the climate changes due to its exposure to recent climate warming (e.g. water regime changes, thawing of permafrost) and due to the high degree of specialization of both natural and human systems (e.g. alpine species, valley population density, tourism-based economy). As a consequence, the mountain local governments are encouraged to undertake territorial governance policies to climate change, considering multi-risks and opportunities for the mountain economy and identifying the best portfolio of adaptation strategies. This study aims to provide a literature review of available qualitative and quantitative tools, methodological guidelines and best practices to conduct multi-risk assessments in the mountain environment within the context of climate change. We analyzed multi-risk modelling and assessment methods applied in alpine regions (e.g. event trees, Bayesian Networks, Agent Based Models) in order to identify key concepts (exposure, resilience, vulnerability, risk, adaptive capacity), climatic drivers, cause-effect relationships and socio-ecological systems to be integrated in a comprehensive framework. The main outcomes of the review, including a comparison of existing techniques based on different criteria (e.g. scale of analysis, targeted questions, level of complexity) and a snapshot of the developed multi-risk framework for climate change adaptation will be here presented and discussed.

Multi-Level Model

Directory of Open Access Journals (Sweden)

Constanta Nicoleta BODEA

2008-01-01

Full Text Available Is an original paper, which contains a hierarchical model with three levels, for determining the linearized non-homogeneous and homogeneous credibility premiums at company level, at sector level and at contract level, founded on the relevant covariance relations between the risk premium, the observations and the weighted averages. We give a rather explicit description of the input data for the multi- level hierarchical model used, only to show that in practical situations, there will always be enough data to apply credibility theory to a real insurance portfolio.

Climatological attribution of wind power ramp events in East Japan and their probabilistic forecast based on multi-model ensembles downscaled by analog ensemble using self-organizing maps

Science.gov (United States)

Ohba, Masamichi; Nohara, Daisuke; Kadokura, Shinji

2016-04-01

Severe storms or other extreme weather events can interrupt the spin of wind turbines in large scale that cause unexpected "wind ramp events". In this study, we present an application of self-organizing maps (SOMs) for climatological attribution of the wind ramp events and their probabilistic prediction. The SOM is an automatic data-mining clustering technique, which allows us to summarize a high-dimensional data space in terms of a set of reference vectors. The SOM is applied to analyze and connect the relationship between atmospheric patterns over Japan and wind power generation. SOM is employed on sea level pressure derived from the JRA55 reanalysis over the target area (Tohoku region in Japan), whereby a two-dimensional lattice of weather patterns (WPs) classified during the 1977-2013 period is obtained. To compare with the atmospheric data, the long-term wind power generation is reconstructed by using a high-resolution surface observation network AMeDAS (Automated Meteorological Data Acquisition System) in Japan. Our analysis extracts seven typical WPs, which are linked to frequent occurrences of wind ramp events. Probabilistic forecasts to wind power generation and ramps are conducted by using the obtained SOM. The probability are derived from the multiple SOM lattices based on the matching of output from TIGGE multi-model global forecast to the WPs on the lattices. Since this method effectively takes care of the empirical uncertainties from the historical data, wind power generation and ramp is probabilistically forecasted from the forecasts of global models. The predictability skill of the forecasts for the wind power generation and ramp events show the relatively good skill score under the downscaling technique. It is expected that the results of this study provides better guidance to the user community and contribute to future development of system operation model for the transmission grid operator.

Testing the multi-configuration time-dependent Hartree-Fock method

International Nuclear Information System (INIS)

Zanghellini, Juergen; Kitzler, Markus; Brabec, Thomas; Scrinzi, Armin

2004-01-01

We test the multi-configuration time-dependent Hartree-Fock method as a new approach towards the numerical calculation of dynamical processes in multi-electron systems using the harmonic quantum dot and one-dimensional helium in strong laser pulses as models. We find rapid convergence for quantities such as ground-state population, correlation coefficient and single ionization towards the exact results. The method converges, where the time-dependent Hartree-Fock method fails qualitatively

Multi-Attribute Seismic/Rock Physics Approach to Characterizing Fractured Reservoirs

Energy Technology Data Exchange (ETDEWEB)

Gary Mavko

2004-11-30

fracturing is likely to be more intense near faults--sometimes referred to as the damaged zone. Yet another constraint, based on world-wide observations, is that the maximum likely fracture density increases with depth in a well-defined way. Defining these prior constrains has several benefits: they lead to a priori probability distributions of fractures, that are important for objective statistical integration; they limit the number of geologic hypotheses that need to be theoretically modeled; they provide plausible models for fracture distributions below the seismic resolution. The second element was theoretical rock physics modeling of optimal seismic attributes, including offset and azimuth dependence of traveltime, amplitude, and impedance signatures of anisotropic fractured rocks. The suggested workflow is to begin with an elastic earth model, based on well logs, theoretically add fractures to the likely facies as defined by the geologic prior information, and then compute synthetic seismic traces and attributes, including variations in P and S-wave velocities, Poisson's ratio, reflectivity, travel time, attenuation, and anisotropies of these parameters. This workflow is done in a Monte-Carlo fashion, yielding ranges of expected fracture signatures, and allowing realistic assessments of uncertainty to be honored. The third element was statistical integration of the geophysical data and prior constraints to map fracture intensity and orientations, along with uncertainties. A Bayesian framework was developed that allowed systematic integration of the prior constraints, the theoretical relations between fractures and their seismic signatures, and the various observed seismic observations. The integration scheme was successfully applied on an East Texas field site. The primary benefit from the study was the optimization and refinement of practical workflows for improved geophysical characterization of natural fractures and for quantifying the uncertainty of these

Mathematical model comparing of the multi-level economics systems

Science.gov (United States)

Brykalov, S. M.; Kryanev, A. V.

2017-12-01

The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.

Renormalization group study of the multi-layer sine-gordon model

International Nuclear Information System (INIS)

Nandori, I.

2005-01-01

Complete text of publication follows. We analyze the phase structure of the system of coupled sine-Gordon (SG) type field theoric models. The 'pure,' SG model is periodic in the internal space spanned by the field variable. The central subjects of investigation is the multi-layer sine-Gordon (LSG) model, where the periodicity is broken partially by the coupling terms between the layers each of which is described by a scalar field, where the second term on the r.h.s. describes the interaction of the layers. Here, we dis- cuss the generalization of the results obtained for the two-layer sine-Gordon model found in the previous study. Besides the obvious field theoretical interest, the LSG model has been used to describe the vortex properties of high transition temperature superconductors, and the extension of the previous analysis to a general N-layer model is necessary for a description of the critical behaviour of vortices in realistic multi-layer systems. The couplings between the layers can be considered as mass terms. Since the periodicity of the LSG model has been broken only partially, the N-layer model has always a single zero mass eigenvalue. The presence of this single zero mass eigenvalue is found to be decisive with respect to the phase structure of the N-layer models. By a suitable rotation of the field variables, we identify the periodic mode (which corresponds to the zero mass eigenvalue) and N - 1 non-periodic modes (with explicit mass terms). The N - 1 non-periodic modes have a trivial IR scaling which holds independently of β which has been proven consistently using (i) the non-perturbative renormalization group study of the rotated model, (ii) the Gaussian integration about the vanishing-field saddle point. Due to the presence of the periodic mode the model undergoes a Kosterlitz-Thouless type phase transition which occurs at a coupling parameter β c 2 = 8Nπ, where N is the number of layers. The critical value β c 2 corresponds to the critical

Multi-fluid modelling of pulsed discharges for flow control applications

Science.gov (United States)

Poggie, J.

2015-02-01

Experimental evidence suggests that short-pulse dielectric barrier discharge actuators are effective for speeds corresponding to take-off and approach of large aircraft, and thus are a fruitful direction for flow control technology development. Large-eddy simulations have reproduced some of the main fluid dynamic effects. The plasma models used in such simulations are semi-empirical, however, and need to be tuned for each flowfield under consideration. In this paper, the discharge physics is examined in more detail with multi-fluid modelling, comparing a five-moment model (continuity, momentum, and energy equations) to a two-moment model (continuity and energy equations). A steady-state, one-dimensional discharge was considered first, and the five-moment model was found to predict significantly lower ionisation rates and number densities than the two-moment model. A two-dimensional, transient discharge problem with an elliptical cathode was studied next. Relative to the two-moment model, the five-moment model predicted a slower response to the activation of the cathode, and lower electron velocities and temperatures as the simulation approached steady-state. The primary reason for the differences in the predictions of the two models can be attributed to the effects of particle inertia, particularly electron inertia in the cathode layer. The computational cost of the five-moment model is only about twice that of the simpler variant, suggesting that it may be feasible to use the more sophisticated model in practical calculations for flow control actuator design.

A multi-country approach for attributing human salmonellosis to animal reservoirs

DEFF Research Database (Denmark)

de Knegt, Leonardo

in order to extrapolate results to countries with less data availability, as a first step to perform source attribution of Salmonella in a more global perspective. Cases of foodborne salmonellosis in humans were attributed to travel, outbreaks and four animal reservoirs, namely pigs, broilers, turkeys...... here on referred to as “travel information”), human cases originating from outbreaks with and without a confirmed source and amounts of the meat or eggs of each animal reservoir originating from each country and available for consumption in each country. Thus, special data management, analysis...... with the lack of good-quality data for such studies. The project has also achieved results that may lay the groundwork for future attempts to develop Salmonella source attribution estimates in a more global perspective....

International study of perceived neighbourhood environmental attributes and Body Mass Index

DEFF Research Database (Denmark)

De Bourdeaudhuij, Ilse; Van Dyck, Delfien; Salvo, Deborah

2015-01-01

environmentally and culturally diverse countries. METHODS: A multi-site cross-sectional study was conducted in 17 cities (study sites) across 12 countries (Australia, Belgium, Brazil, China, Colombia, Czech Republic, Denmark, Mexico, New Zealand, Spain, the UK and USA). Participants (n = 14222, 18-66 years) self...... reason for these mixed results is the limited variability in built environments in these single-country studies. Therefore, the aim of this study was to examine associations between perceived neighbourhood built environmental attributes and BMI/weight status in a multi-country study including 12......-reported perceived neighbourhood environmental attributes. Height and weight were self-reported in eight countries, and measured in person in four countries. RESULTS: Three environmental attributes were associated with BMI or weight status in pooled data from 12 countries. Safety from traffic was the most robust...

QML-AiNet: An immune network approach to learning qualitative differential equation models.

Science.gov (United States)

Pang, Wei; Coghill, George M

2015-02-01

In this paper, we explore the application of Opt-AiNet, an immune network approach for search and optimisation problems, to learning qualitative models in the form of qualitative differential equations. The Opt-AiNet algorithm is adapted to qualitative model learning problems, resulting in the proposed system QML-AiNet. The potential of QML-AiNet to address the scalability and multimodal search space issues of qualitative model learning has been investigated. More importantly, to further improve the efficiency of QML-AiNet, we also modify the mutation operator according to the features of discrete qualitative model space. Experimental results show that the performance of QML-AiNet is comparable to QML-CLONALG, a QML system using the clonal selection algorithm (CLONALG). More importantly, QML-AiNet with the modified mutation operator can significantly improve the scalability of QML and is much more efficient than QML-CLONALG.

Modeling arson - An exercise in qualitative model building

Science.gov (United States)

Heineke, J. M.

1975-01-01

A detailed example is given of the role of von Neumann and Morgenstern's 1944 'expected utility theorem' (in the theory of games and economic behavior) in qualitative model building. Specifically, an arsonist's decision as to the amount of time to allocate to arson and related activities is modeled, and the responsiveness of this time allocation to changes in various policy parameters is examined. Both the activity modeled and the method of presentation are intended to provide an introduction to the scope and power of the expected utility theorem in modeling situations of 'choice under uncertainty'. The robustness of such a model is shown to vary inversely with the number of preference restrictions used in the analysis. The fewer the restrictions, the wider is the class of agents to which the model is applicable, and accordingly more confidence is put in the derived results. A methodological discussion on modeling human behavior is included.

Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making

Directory of Open Access Journals (Sweden)

Sen Liu

2015-01-01

Full Text Available Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.

Loop equations for multi-cut matrix models

International Nuclear Information System (INIS)

Akemann, G.

1995-03-01

The loop equation for the complex one-matrix model with a multi-cut structure is derived and solved in the planar limit. An iterative scheme for higher genus contributions to the free energy and the multi-loop correlators is presented for the two-cut model, where explicit results are given up to and including genus two. The double-scaling limit is analyzed and the relation to the one-cut solution of the hermitian and complex one-matrix model is discussed. (orig.)

Multi-Sensor Documentation of Metric and Qualitative Information of Historic Stone Structures

Science.gov (United States)

Adamopoulos, E.; Tsilimantou, E.; Keramidas, V.; Apostolopoulou, M.; Karoglou, M.; Tapinaki, S.; Ioannidis, C.; Georgopoulos, A.; Moropoulou, A.

2017-08-01

This paper focuses on the integration of multi-sensor techniques regarding the acquisition, processing, visualisation and management of data regarding historic stone structures. The interdisciplinary methodology that is carried out here comprises of two parts. In the first part, the acquisition of qualitative and quantitative data concerning the geometry, the materials and the degradation of the tangible heritage asset each time, is discussed. The second part, refers to the analysis, management and visualization of the interrelated data by using spatial information technologies. Through the paradigm of the surveying of the ancient temple of Pythian Apollo at Acropolis of Rhodes, Rhodes Island, Greece, it is aimed to highlight the issues deriving from the separate application of documentation procedures and how the fusion of these methods can contribute effectively to ensure the completeness of the measurements for complex structures. The surveying results are further processed to be compatible and integrated with GIS. Also, the geometric documentation derivatives are combined with environmental data and the results of the application of non-destructive testing and evaluation techniques in situ and analytical techniques in lab after sampling. GIS operations are utilized to document the building materials but also to model and to analyse the decay extent and patterns. Detailed surface measurements and geo-processing analysis are executed. This integrated approach, helps the assessment of past interventions on the monument, identify main causes of damage and decay, and finally assist the decision making on the most compatible materials and techniques for protection and restoration works.

MULTI-SENSOR DOCUMENTATION OF METRIC AND QUALITATIVE INFORMATION OF HISTORIC STONE STRUCTURES

Directory of Open Access Journals (Sweden)

E. Adamopoulos

2017-08-01

Full Text Available This paper focuses on the integration of multi-sensor techniques regarding the acquisition, processing, visualisation and management of data regarding historic stone structures. The interdisciplinary methodology that is carried out here comprises of two parts. In the first part, the acquisition of qualitative and quantitative data concerning the geometry, the materials and the degradation of the tangible heritage asset each time, is discussed. The second part, refers to the analysis, management and visualization of the interrelated data by using spatial information technologies. Through the paradigm of the surveying of the ancient temple of Pythian Apollo at Acropolis of Rhodes, Rhodes Island, Greece, it is aimed to highlight the issues deriving from the separate application of documentation procedures and how the fusion of these methods can contribute effectively to ensure the completeness of the measurements for complex structures. The surveying results are further processed to be compatible and integrated with GIS. Also, the geometric documentation derivatives are combined with environmental data and the results of the application of non-destructive testing and evaluation techniques in situ and analytical techniques in lab after sampling. GIS operations are utilized to document the building materials but also to model and to analyse the decay extent and patterns. Detailed surface measurements and geo-processing analysis are executed. This integrated approach, helps the assessment of past interventions on the monument, identify main causes of damage and decay, and finally assist the decision making on the most compatible materials and techniques for protection and restoration works.

Multi-level decision making models, methods and applications

CERN Document Server

Zhang, Guangquan; Gao, Ya

2015-01-01

This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.  

PENERAPAN FUZZY ANALYTIC HIERARCHY PROCESS DALAM METODE MULTI ATTRIBUTE FAILURE MODE ANALYSIS UNTUK MENGIDENTIFIKASI PENYEBAB KEGAGALAN POTENSIAL PADA PROSES PRODUKSI

Directory of Open Access Journals (Sweden)

Dorina Hetharia

2012-02-01

Full Text Available Banyak metode dalam Total Quality Management (TQM yang dapat digunakan untuk melakukan perbaikan kualitas produk dan jasa. Salah satunya adalah Multi Attribute Failure Mode Analysis (MAFMA, yang dapat digunakan untuk mengeliminasi atau mengurangi kemungkinan terjadinya kegagalan bila dilihat dari faktor penyebabnya, sehingga dapat mencegah terulang kembali kegagalan tersebut. MAFMA merupakan pengembangan dari Failure Mode and Effect Analysis (FMEA, yang mengintegrasikan atribut severity, occurance, dan detectability dengan aspek ekonomi yakni expected cost. Pada FMEA, penentuan penyebab kegagalan potensial suatu produk dilakukan dengan memberikan nilai (score pada atribut severity, occurance, dan detectability, yang dilanjutkan dengan menghitung nilai Risk Priority Number (RPN tertinggi. Sedangkan pada MAFMA, penentuan penyebab kegagalan potensial dilakukan dengan pemberian bobot pada ke-empat atribut. Pemberian bobot tersebut menggunakan Analytic Hierarchy Process (AHP dengan logika fuzy. Atribut severity, occurance, detectability dan expected cost pada MAFMA dimasukkan sebagai level kriteria dalam struktur hirarkhi AHP, sedangkan penyebab-penyebab kegagalan akan menjadi level alternatif pada struktur hirarkhi tersebut. Studi kasus pada PT Pelita Cengkareng Paper & Co. menunjukkan bahwa bobot  kriteria severity sebesar 0.3461, kriteria occurance sebesar 0.0848, kriteria detectability sebesar 0.1741 dan kriteria expected cost sebesar 0.3950.Sedangkan penyebab kegagalan potensial adalah penggumpalan chemical dengan bobot tertinggi sebesar 0.210. Kata kunci: AHP, logika fuzzy, MAFMA     There are several methods of Total Quality Management (TQM that can be used to improve quality of product and service. One of those is Multi Attribute Failure Mode Analysis (MAFMA, which can be used to eliminate or minimize the failure probability based on its causal factor, so we can prevent the same failure in the future. MAFMA is development of Failure Mode

MELA: Modelling in Ecology with Location Attributes

Directory of Open Access Journals (Sweden)

Ludovica Luisa Vissat

2016-10-01

Full Text Available Ecology studies the interactions between individuals, species and the environment. The ability to predict the dynamics of ecological systems would support the design and monitoring of control strategies and would help to address pressing global environmental issues. It is also important to plan for efficient use of natural resources and maintenance of critical ecosystem services. The mathematical modelling of ecological systems often includes nontrivial specifications of processes that influence the birth, death, development and movement of individuals in the environment, that take into account both biotic and abiotic interactions. To assist in the specification of such models, we introduce MELA, a process algebra for Modelling in Ecology with Location Attributes. Process algebras allow the modeller to describe concurrent systems in a high-level language. A key feature of concurrent systems is that they are composed of agents that can progress simultaneously but also interact - a good match to ecological systems. MELA aims to provide ecologists with a straightforward yet flexible tool for modelling ecological systems, with particular emphasis on the description of space and the environment. Here we present four example MELA models, illustrating the different spatial arrangements which can be accommodated and demonstrating the use of MELA in epidemiological and predator-prey scenarios.

Teachers' and Parental Attribution for School Performance of Ethnic Majority and Minority Children

Science.gov (United States)

Wissink, Inge B.; de Haan, Mariette

2013-01-01

This study examines whether teachers' and parental attributions for children's school performance differ depending on the ethnic background of the child. Using both quantitative and qualitative methods, real-life attributions within 54 teacher-parent conversations (15 ethnic majority; 39 minority) were examined. The results indicated that,…

Robust multi-model predictive control of multi-zone thermal plate system

Directory of Open Access Journals (Sweden)

Poom Jatunitanon

2018-02-01

Full Text Available A modern controller was designed by using the mathematical model of a multi–zone thermal plate system. An important requirement for this type of controller is that it must be able to keep the temperature set-point of each thermal zone. The mathematical model used in the design was determined through a system identification process. The results showed that when the operating condition is changed, the performance of the controller may be reduced as a result of the system parameter uncertainties. This paper proposes a weighting technique of combining the robust model predictive controller for each operating condition into a single robust multi-model predictive control. Simulation and experimental results showed that the proposed method performed better than the conventional multi-model predictive control in rise time of transient response, when used in a system designed to work over a wide range of operating conditions.

Multi baryons with flavors in the Skyrme model

Energy Technology Data Exchange (ETDEWEB)

Schat, Carlos L. [Centro Brasileiro de Pesquisas Fisicas (CBPF), Rio de Janeiro, RJ (Brazil); Scoccola, Norberto N. [Comision Nacional de Energia Atomica, Buenos Aires (Argentina). Dept. of Physics

1999-07-01

We investigate the possible existence of multi baryons with heavy flavor quantum numbers using the bound state approach to the topological soliton model and the recently proposed approximation for multi skyrmion fields based on rational maps. We use an effective interaction Lagrangian which consistently incorporates both chiral symmetry and the heavy quark symmetry including the corrections up to order {omicron}(1/m{sub Q}). The model predicts some narrow heavy flavored multi baryon states with baryon number four and seven. (author)

Multi baryons with flavors in the Skyrme model

International Nuclear Information System (INIS)

Schat, Carlos L.; Scoccola, Norberto N.

1999-07-01

We investigate the possible existence of multi baryons with heavy flavor quantum numbers using the bound state approach to the topological soliton model and the recently proposed approximation for multi skyrmion fields based on rational maps. We use an effective interaction Lagrangian which consistently incorporates both chiral symmetry and the heavy quark symmetry including the corrections up to order ο(1/m Q ). The model predicts some narrow heavy flavored multi baryon states with baryon number four and seven. (author)

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model - Part 1: Assessing the influence of constrained multi-generational ageing

Science.gov (United States)

Jathar, S. H.; Cappa, C. D.; Wexler, A. S.; Seinfeld, J. H.; Kleeman, M. J.

2016-02-01

tested. Consequently, the use of low and high NOx yields perturbs SOA concentrations by a factor of two and are probably a much stronger determinant in 3-D models than multi-generational oxidation. While total predicted SOA mass is similar for the SOM and two-product models, the SOM model predicts increased SOA contributions from anthropogenic (alkane, aromatic) and sesquiterpenes and decreased SOA contributions from isoprene and monoterpene relative to the two-product model calculations. The SOA predicted by SOM has a much lower volatility than that predicted by the traditional model, resulting in better qualitative agreement with volatility measurements of ambient OA. On account of its lower-volatility, the SOA mass produced by SOM does not appear to be as strongly influenced by the inclusion of oligomerization reactions, whereas the two-product model relies heavily on oligomerization to form low-volatility SOA products. Finally, an unconstrained contemporary hybrid scheme to model multi-generational oxidation within the framework of a two-product model in which ageing reactions are added on top of the existing two-product parameterization is considered. This hybrid scheme formed at least 3 times more SOA than the SOM during regional simulations as a result of excessive transformation of semi-volatile vapors into lower volatility material that strongly partitions to the particle phase. This finding suggests that these hybrid multi-generational schemes should be used with great caution in regional models.

Qualitative Analysis of the Impact of SOA Patterns on Quality Attributes

NARCIS (Netherlands)

Galster, Matthias; Avgeriou, Paris; Tang, A; Muccini, H

2012-01-01

Software architecture patterns are proven and reusable solutions to common architecture design problems. One characteristic of architecture patterns is that they affect quality attributes (e.g., performance, reliability). Over the past years, architecture patterns for service-based systems have been

Multi-model-based Access Control in Construction Projects

Directory of Open Access Journals (Sweden)

Frank Hilbert

2012-04-01

Full Text Available During the execution of large scale construction projects performed by Virtual Organizations (VO, relatively complex technical models have to be exchanged between the VO members. For linking the trade and transfer of these models, a so-called multi-model container format was developed. Considering the different skills and tasks of the involved partners, it is not necessary for them to know all the models in every technical detailing. Furthermore, the model size can lead to a delay in communication. In this paper an approach is presented for defining model cut-outs according to the current project context. Dynamic dependencies to the project context as well as static dependencies on the organizational structure are mapped in a context-sensitive rule. As a result, an approach for dynamic filtering of multi-models is obtained which ensures, together with a filtering service, that the involved VO members get a simplified view of complex multi-models as well as sufficient permissions depending on their tasks.

Preliminary Multi-Variable Parametric Cost Model for Space Telescopes

Science.gov (United States)

Stahl, H. Philip; Hendrichs, Todd

2010-01-01

This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.

Multi-compartment Fire Modeling for Switchgear Room using CFAST

International Nuclear Information System (INIS)

Han, Kiyoon; Kang, Dae Il; Lim, Ho Gon

2015-01-01

In this study, multi-compartment fire modeling for fire propagation scenario from SWGR A to SWGR B is performed using CFAST. New fire PSA method (NUREG/CR-6850) requires that the severity factor is to be calculated by fire modeling. If fire modeling is not performed, the severity factor should be estimated as one conservatively. Also, the possibility of the damages of components and cables located at adjacent compartments should be considered. Detailed fire modeling of multi-compartment fires refers to the evaluation of fire-generated conditions in one compartment that spread to adjacent ones. In general, the severity factor for multi-compartment fire scenario is smaller than that of single compartment scenario. Preliminary quantification of Hanul Unit 3 fire PSA was performed without fire modeling. As a result of quantification, multi-compartment scenario, fire propagation scenario from switchgear room (SWGR) A to SWGR B, is one of significant contributor to the CDF. In this study, fire modeling of multi-compartment was performed by Consolidated Fire Growth and Smoke Transport (CFAST) to identify the possibility of fire propagation. As a result of fire simulation, it is identified that fire propagation has little influences

Multi-compartment Fire Modeling for Switchgear Room using CFAST

Energy Technology Data Exchange (ETDEWEB)

Han, Kiyoon; Kang, Dae Il; Lim, Ho Gon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-10-15

In this study, multi-compartment fire modeling for fire propagation scenario from SWGR A to SWGR B is performed using CFAST. New fire PSA method (NUREG/CR-6850) requires that the severity factor is to be calculated by fire modeling. If fire modeling is not performed, the severity factor should be estimated as one conservatively. Also, the possibility of the damages of components and cables located at adjacent compartments should be considered. Detailed fire modeling of multi-compartment fires refers to the evaluation of fire-generated conditions in one compartment that spread to adjacent ones. In general, the severity factor for multi-compartment fire scenario is smaller than that of single compartment scenario. Preliminary quantification of Hanul Unit 3 fire PSA was performed without fire modeling. As a result of quantification, multi-compartment scenario, fire propagation scenario from switchgear room (SWGR) A to SWGR B, is one of significant contributor to the CDF. In this study, fire modeling of multi-compartment was performed by Consolidated Fire Growth and Smoke Transport (CFAST) to identify the possibility of fire propagation. As a result of fire simulation, it is identified that fire propagation has little influences.

MISTRAL: A game-theoretical model to allocate security measures in a multi-modal chemical transportation network with adaptive adversaries

International Nuclear Information System (INIS)

Talarico, Luca; Reniers, Genserik; Sörensen, Kenneth; Springael, Johan

2015-01-01

In this paper we present a multi-modal security-transportation model to allocate security resources within a chemical supply chain which is characterized by the use of different transport modes, each having their own security features. We consider security-related risks so as to take measures against terrorist acts which could target critical transportation systems. The idea of addressing security-related issues, by supporting decisions for preventing or mitigating intentional acts on transportation infrastructure, has gained attention in academic research only recently. The decision model presented in this paper is based on game theory and it can be employed to organize intelligence capabilities aimed at securing chemical supply chains. It enables detection and warning against impending attacks on transportation infrastructures and the subsequent adoption of security countermeasures. This is of extreme importance for preventing terrorist attacks and for avoiding (possibly huge) human and economic losses. In our work we also provide data sources and numerical simulations by applying the proposed model to a illustrative multi-modal chemical supply chain. - Highlights: • A model to increase the security in a multimodal chemical supply chain is proposed. • The model considers adaptive opponents having multi-attribute utility functions. • The model is based on game theory using an attacker–defender schema. • The model provides recommendations about where to allocate security measures. • Numerical simulations on a sample multimodal chemical supply chain are shown

Multi-cut solutions in Chern-Simons matrix models

Science.gov (United States)

Morita, Takeshi; Sugiyama, Kento

2018-04-01

We elaborate the Chern-Simons (CS) matrix models at large N. The saddle point equations of these matrix models have a curious structure which cannot be seen in the ordinary one matrix models. Thanks to this structure, an infinite number of multi-cut solutions exist in the CS matrix models. Particularly we exactly derive the two-cut solutions at finite 't Hooft coupling in the pure CS matrix model. In the ABJM matrix model, we argue that some of multi-cut solutions might be interpreted as a condensation of the D2-brane instantons.

A Multi-Actor Dynamic Integrated Assessment Model (MADIAM)

OpenAIRE

Weber, Michael

2004-01-01

The interactions between climate and the socio-economic system are investigated with a Multi-Actor Dynamic Integrated Assessment Model (MADIAM) obtained by coupling a nonlinear impulse response model of the climate sub-system (NICCS) to a multi-actor dynamic economic model (MADEM). The main goal is to initiate a model development that is able to treat the dynamics of the coupled climate socio-economic system, including endogenous technological change, in a non-equilibrium situation, thereby o...

The Multi-Attribute Task Battery II (MATB-II) Software for Human Performance and Workload Research: A User's Guide

Science.gov (United States)

Santiago-Espada, Yamira; Myer, Robert R.; Latorella, Kara A.; Comstock, James R., Jr.

2011-01-01

The Multi-Attribute Task Battery (MAT Battery). is a computer-based task designed to evaluate operator performance and workload, has been redeveloped to operate in Windows XP Service Pack 3, Windows Vista and Windows 7 operating systems.MATB-II includes essentially the same tasks as the original MAT Battery, plus new configuration options including a graphical user interface for controlling modes of operation. MATB-II can be executed either in training or testing mode, as defined by the MATB-II configuration file. The configuration file also allows set up of the default timeouts for the tasks, the flow rates of the pumps and tank levels of the Resource Management (RESMAN) task. MATB-II comes with a default event file that an experimenter can modify and adapt

A multi-attribute utility decision analysis for treatment alternatives for the DOE/SR aluminum-based spent nuclear fuel

International Nuclear Information System (INIS)

Davis, Freddie J.; Weiner, Ruth Fleischman; Wheeler, Timothy A.; Sorenson, Ken B.; Kuzio, Kenneth A.

2000-01-01

A multi-attribute utility analysis is applied to a decision process to select a treatment method for the management of aluminum-based spent nuclear fuel (Al-SNF) owned by the US Department of Energy (DOE). DOE will receive, treat, and temporarily store Al-SNF, most of which is composed of highly enriched uranium, at its Savannah River Site in South Carolina. DOE intends ultimately to send the treated Al-SNF to a geologic repository for permanent disposal. DOE initially considered ten treatment alternatives for the management of Al-SNF, and has narrowed the choice to two of these: the direct disposal and melt and dilute alternatives. The decision analysis presented in this document focuses on a formal decision process used to evaluate these two remaining alternatives

An equilibrium pricing model for weather derivatives in a multi-commodity setting

International Nuclear Information System (INIS)

Lee, Yongheon; Oren, Shmuel S.

2009-01-01

Many industries are exposed to weather risk. Weather derivatives can play a key role in hedging and diversifying such risk because the uncertainty in a company's profit function can be correlated to weather condition which affects diverse industry sectors differently. Unfortunately the weather derivatives market is a classical example of an incomplete market that is not amenable to standard methodologies used for derivative pricing in complete markets. In this paper, we develop an equilibrium pricing model for weather derivatives in a multi-commodity setting. The model is constructed in the context of a stylized economy where agents optimize their hedging portfolios which include weather derivatives that are issued in a fixed quantity by a financial underwriter. The supply and demand resulting from hedging activities and the supply by the underwriter are combined in an equilibrium pricing model under the assumption that all agents maximize some risk averse utility function. We analyze the gains due to the inclusion of weather derivatives in hedging portfolios and examine the components of that gain attributable to hedging and to risk sharing. (author)

TOWARDS A CONCEPTUAL FRAMEWORK OF ISLAMIC LEADERSHIP SUCCESSOR'S ATTRIBUTES MODEL AND GOOD GOVERNANCE

Directory of Open Access Journals (Sweden)

Naji Zuhair Alsarhi

2015-12-01

Full Text Available The purpose of this paper is to propose a conceptual model that explains the relationship between Islamic leadership successionpersonalityattributes and good governance. The paper sources information from an extensive search of literature to design a conceptual model of Islamic leadership succession (personal attributes & governmental characteristics of Succession and good governance. The model will provide an integration of relationships that will add valuable insights into improved leadership succession theory in the related literature. The paper may assist particularly policy makers and strategists to focus on new possibilities of leadership successors attributes that will lead to improved governance as well as government performance in the world in general, and the Palestine community, in particular.

A Brief Review on the Baer-Nunziato type Multi-pressure Multi-fluid Models

International Nuclear Information System (INIS)

Lee, Sang Yong; Park, Chan Eok; Lee, Gyu Cheon

2010-01-01

Single pressure two-fluid flow equations have complex characteristics. This causes ill-posedness problem. Even though some authors show that the numerical solutions are well behaved if the number of mesh points is sufficiently small, the stability of the solution is always challenged. There have been several attempts to overcome these problems. Multi-pressure multi-fluid models are one of them. Among them, Baer and Nunziato (BN) derived an interesting two-fluid model. BN model has independent phase pressures. It is closed by inserting volume fraction evolution equation. In this paper, several aspects of the BN type model will be reviewed and some suggestion for the future study will be made

Using multi-attribute decision-making approaches in the selection of a hospital management system.

Science.gov (United States)

Arasteh, Mohammad Ali; Shamshirband, Shahaboddin; Yee, Por Lip

2018-01-01

The most appropriate organizational software is always a real challenge for managers, especially, the IT directors. The illustration of the term "enterprise software selection", is to purchase, create, or order a software that; first, is best adapted to require of the organization; and second, has suitable price and technical support. Specifying selection criteria and ranking them, is the primary prerequisite for this action. This article provides a method to evaluate, rank, and compare the available enterprise software for choosing the apt one. The prior mentioned method is constituted of three-stage processes. First, the method identifies the organizational requires and assesses them. Second, it selects the best method throughout three possibilities; indoor-production, buying software, and ordering special software for the native use. Third, the method evaluates, compares and ranks the alternative software. The third process uses different methods of multi attribute decision making (MADM), and compares the consequent results. Based on different characteristics of the problem; several methods had been tested, namely, Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Elimination and Choice Expressing Reality (ELECTURE), and easy weight method. After all, we propose the most practical method for same problems.

An integrated multi attribute decision model for energy efficiency processes in petrochemical industry applying fuzzy set theory

International Nuclear Information System (INIS)

Taylan, Osman; Kaya, Durmus; Demirbas, Ayhan

2016-01-01

Graphical abstract: Evaluation of compressors by comparing the different cost parameters. - Highlights: • Fuzzy sets and systems are used for decision making in MCDM problems. • An integrated Fuzzy AHP and fuzzy TOPSIS approaches are employed for compressor selection. • Compressor selection is a highly complex and non-linear process. • This approach increases the efficiency, reliability of alternative scenarios, and reduces the pay-back period. - Abstract: Energy efficient technologies offered by the market increases productivity. However, decision making for these technologies is usually obstructed in the firms and comes up with organizational barriers. Compressor selection in petrochemical industry requires assessment of several criteria such as ‘reliability, energy consumption, initial investment, capacity, pressure, and maintenance cost.’ Therefore, air compressor selection is a multi-attribute decision making (MADM) problem. The aim of this study is to select the most eligible compressor(s) so as to avoid the high energy consumption due to the capacity and maintenance costs. It is also aimed to avoid failures due to the reliability problems and high pressure. MADM usually takes place in a vague and imprecise environment. Soft computing techniques such as fuzzy sets and system can be used for decision making where vague and imprecise knowledge is available. In this study, an integrated fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) methodologies are employed for the compressor selection. Fuzzy AHP was used to determine the weights of criteria and fuzzy TOPSIS was employed to order the scenarios according to their superiority. The total effect of all criteria was determined for all alternative scenarios to make an optimal decision. Moreover, the types of compressor, carbon emission, waste heat recovery and their capacities were analyzed and compared by statistical

The benefits of global scaling in multi-criteria decision analysis

Directory of Open Access Journals (Sweden)

Jamie P. Monat

2009-10-01

Full Text Available When there are multiple competing objectives in a decision-making process, Multi-Attribute Choice scoring models are excellent tools, permitting the incorporation of both subjective and objective attributes. However, their accuracy depends upon the subjective techniques used to construct the attribute scales and their concomitant weights. Conventional techniques using local scales tend to overemphasize small differences in attribute measures, which may yield erroneous conclusions. The Range Sensitivity Principle (RSP is often invoked to adjust attribute weights when local scales are used. In practice, however, decision makers often do not follow the prescriptions of the Range Sensitivity Principle and under-adjust the weights, resulting in potentially poor decisions. Examples are discussed as is a proposed solution: the use of global scales instead of local scales.

Graphical means for inspecting qualitative models of system behaviour

NARCIS (Netherlands)

Bouwer, A.; Bredeweg, B.

2010-01-01

This article presents the design and evaluation of a tool for inspecting conceptual models of system behaviour. The basis for this research is the Garp framework for qualitative simulation. This framework includes modelling primitives, such as entities, quantities and causal dependencies, which are

The design of multi-core DSP parallel model based on message passing and multi-level pipeline

Science.gov (United States)

Niu, Jingyu; Hu, Jian; He, Wenjing; Meng, Fanrong; Li, Chuanrong

2017-10-01

Currently, the design of embedded signal processing system is often based on a specific application, but this idea is not conducive to the rapid development of signal processing technology. In this paper, a parallel processing model architecture based on multi-core DSP platform is designed, and it is mainly suitable for the complex algorithms which are composed of different modules. This model combines the ideas of multi-level pipeline parallelism and message passing, and summarizes the advantages of the mainstream model of multi-core DSP (the Master-Slave model and the Data Flow model), so that it has better performance. This paper uses three-dimensional image generation algorithm to validate the efficiency of the proposed model by comparing with the effectiveness of the Master-Slave and the Data Flow model.

Wave Model Development in Multi-Ion Plasmas

Directory of Open Access Journals (Sweden)

Sung-Hee Song

1999-06-01

Full Text Available Near-earth space is composed of plasmas which embed a number of plasma waves. Space plasmas consist of electrons and multi-ion that determine local wave propagation characteristics. In multi-ion plasmas, it is di cult to find out analytic solution from the dispersion relation in general. In this work, we have developed a model with an arbitrary magnetic field and density as well as multi-ion plasmas. This model allows us to investigate how plasma waves behave when they propagate along realistic magnetic field lines, which are assumed by IGRF(International Geomagnetic Reference Field. The results are found to be useful for the analysis of the in situ observational data in space. For instance, if waves are assumed to propagate into the polar region, from the equatorial region, our model quantitatively shows how polarization is altered along earth travel path.

Determinant attributes in the purchase decision: a study on street food establishments

OpenAIRE

Loriato, Hannah Nicchio; Pelissari, Anderson Soncini

2017-01-01

Abstract The importance of the attributes of a product can vary greatly according to the different consumers, thus we start from the idea that there are different degrees of importance in relation to the attributes and that this importance influences the buying decision. The purpose of this study is to identify which attributes are key in the buying decision-making process for consumers in making buying decisions in establishments that sell street food. It is a study of both qualitative and q...

A View on the Importance of "Multi-Attribute Method" for Measuring Purity of Biopharmaceuticals and Improving Overall Control Strategy.

Science.gov (United States)

Rogers, Richard S; Abernathy, Michael; Richardson, Douglas D; Rouse, Jason C; Sperry, Justin B; Swann, Patrick; Wypych, Jette; Yu, Christopher; Zang, Li; Deshpande, Rohini

2017-11-30

Today, we are experiencing unprecedented growth and innovation within the pharmaceutical industry. Established protein therapeutic modalities, such as recombinant human proteins, monoclonal antibodies (mAbs), and fusion proteins, are being used to treat previously unmet medical needs. Novel therapies such as bispecific T cell engagers (BiTEs), chimeric antigen T cell receptors (CARTs), siRNA, and gene therapies are paving the path towards increasingly personalized medicine. This advancement of new indications and therapeutic modalities is paralleled by development of new analytical technologies and methods that provide enhanced information content in a more efficient manner. Recently, a liquid chromatography-mass spectrometry (LC-MS) multi-attribute method (MAM) has been developed and designed for improved simultaneous detection, identification, quantitation, and quality control (monitoring) of molecular attributes (Rogers et al. MAbs 7(5):881-90, 2015). Based on peptide mapping principles, this powerful tool represents a true advancement in testing methodology that can be utilized not only during product characterization, formulation development, stability testing, and development of the manufacturing process, but also as a platform quality control method in dispositioning clinical materials for both innovative biotherapeutics and biosimilars.

Response Surface Approximation for Fatigue Life Prediction and Its Application to Multi-Criteria Optimization With a Priori Preference Information

International Nuclear Information System (INIS)

Baek, Seok Heum; Joo, Won Sik; Cho, Seok Swoo

2009-01-01

In this paper, a versatile multi-criteria optimization concept for fatigue life prediction is introduced. Multi-criteria decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability

Choice attributes in restaurant services: An exploratory study

Directory of Open Access Journals (Sweden)

Derli Luís Angnes

2013-08-01

Full Text Available There are about one million of bars and restaurants that generate around six millions of jobs in Brazil. Among the most important reasons to choose a restaurant are the service attributes. Attributes are judgments the client makes about the performance and quality of the service provided. The identification of restaurant choice attributes is important in order to propose a higher value to services and to make marketing strategies. This article aims to identify the choice attributes of service quality in restaurants. The methodology employed was a qualitative exploratory study based on interviews made using the critical incident technique. It was used a sample of 72 restaurant customers. The content analysis technique was used to treat and analyze the critical incidents obtained in the interviews. The result obtained was a relation of 615 critical incidents, which after being analyzed generated a list of 27 attributes that influence customer’s choice and customer’s evaluation of service quality provided in restaurants. The identified attributes can subsidize and contribute to improvement of future research and studies in the academic environment, besides contributing for the management of restaurants business.

Multi-scale MHD analysis of heliotron plasma in change of background field

International Nuclear Information System (INIS)

Ichiguchi, K.; Sakakibara, S.; Ohdachi, S.; Carreras, B.A.

2012-11-01

A partial collapse observed in the Large Helical Device (LHD) experiments shifting the magnetic axis inwardly with a real time control of the background field is analyzed with a magnetohydrodynamics (MHD) numerical simulation. The simulation is carried out with a multi-scale simulation scheme. In the simulation, the equilibrium also evolves including the change of the pressure and the rotational transform due to the perturbation dynamics. The simulation result agrees with the experiments qualitatively, which shows that the mechanism is attributed to the destabilization of an infernal-like mode. The destabilization is caused by the change of the background field through the enhancement of the magnetic hill. (author)

Using multi-state markov models to identify credit card risk

Directory of Open Access Journals (Sweden)

Daniel Evangelista Régis

2016-06-01

Full Text Available Abstract The main interest of this work is to analyze the application of multi-state Markov models to evaluate credit card risk by investigating the characteristics of different state transitions in client-institution relationships over time, thereby generating score models for various purposes. We also used logistic regression models to compare the results with those obtained using multi-state Markov models. The models were applied to an actual database of a Brazilian financial institution. In this application, multi-state Markov models performed better than logistic regression models in predicting default risk, and logistic regression models performed better in predicting cancellation risk.

Multi-Index Attribution of Beijing's 2013 "Airpocalypse"

Science.gov (United States)

Callahan, C.; Diffenbaugh, N. S.; Horton, D. E.

2017-12-01

Poor air quality causes 2 to 4 million premature deaths per year globally. Individual high-impact events, like Beijing's January 2013 "airpocalypse," have drawn significant attention, as they have demonstrated that short-lived air quality events can have outsized effects on public health and economic vitality. Poor air quality events are the result of emission of pollutants and the meteorological conditions favorable to their accumulation in the near-surface environment. Accumulation occurs when pollutants are not dispersed or scavenged from the atmosphere. The most important meteorological precursors of these conditions include lack of precipitation, low wind speeds, and vertical temperature inversions. Recent reports of extreme air quality, in conjunction with projected future changes in some meteorological air quality indices, raise the question: have the meteorological conditions that shape air quality changed in frequency, intensity, or duration over the observational era? Here we assess whether anthropogenic climate change has altered meteorological conditions conducive to poor air quality. To gain a more complete picture of the effect of anthropogenic change on air quality, we use three indices that quantify poor air quality: the Pollution Potential Index (Zou et al, 2017), which measures temperature inversions and surface wind speeds, the Haze Weather Index (Cai et al, 2017), which measures temperature inversions and mid-level wind speeds, and the Air Stagnation Index (Horton et al, 2014), which measures precipitation, surface wind speeds, and mid-level wind speeds. Drawing on the attribution methods of Diffenbaugh et al (2017), we assess the contribution of observed meteorological trends to the magnitude of air quality events, the return interval of events in the observational record, historical simulated climate, and pre-industrial simulated climate, and the probability of the observed trend in historical and pre-industrial simulated climates. Particular

Qualitative mechanism models and the rationalization of procedures

Science.gov (United States)

Farley, Arthur M.

1989-01-01

A qualitative, cluster-based approach to the representation of hydraulic systems is described and its potential for generating and explaining procedures is demonstrated. Many ideas are formalized and implemented as part of an interactive, computer-based system. The system allows for designing, displaying, and reasoning about hydraulic systems. The interactive system has an interface consisting of three windows: a design/control window, a cluster window, and a diagnosis/plan window. A qualitative mechanism model for the ORS (Orbital Refueling System) is presented to coordinate with ongoing research on this system being conducted at NASA Ames Research Center.

Investigating attribute non-attendance and its consequences in choice experiments with latent class models.

Science.gov (United States)

Lagarde, Mylene

2013-05-01

A growing literature, mainly from transport and environment economics, has started to explore whether respondents violate some of the axioms about individuals' preferences in Discrete Choice Experiments (DCEs) and use simple strategies to make their choices. One of these strategies, termed attribute non-attendance (ANA), consists in ignoring one or more attributes. Using data from a DCE administered to healthcare providers in Ghana to evaluate their potential resistance to changes in clinical guidelines, this study illustrates how latent class models can be used in a step-wise approach to account for all possible ANA strategies used by respondents and explore the consequences of such behaviours. Results show that less than 3% of respondents considered all attributes when choosing between the two hypothetical scenarios proposed, with a majority looking at only one or two attributes. Accounting for ANA strategies improved the goodness-of-fit of the model and affected the magnitude of some of the coefficient and willingness-to-pay estimates. However, there was no difference in the predicted probabilities of the model taking into account ANA and the standard approach. Although the latter result is reassuring about the ability of DCEs to produce unbiased policy guidance, it should be confirmed by other studies. Copyright © 2012 John Wiley & Sons, Ltd.

Direct Visual Editing of Node Attributes in Graphs

Directory of Open Access Journals (Sweden)

Christian Eichner

2016-10-01

Full Text Available There are many expressive visualization techniques for analyzing graphs. Yet, there is only little research on how existing visual representations can be employed to support data editing. An increasingly relevant task when working with graphs is the editing of node attributes. We propose an integrated visualize-and-edit approach to editing attribute values via direct interaction with the visual representation. The visualize part is based on node-link diagrams paired with attribute-dependent layouts. The edit part is as easy as moving nodes via drag-and-drop gestures. We present dedicated interaction techniques for editing quantitative as well as qualitative attribute data values. The benefit of our novel integrated approach is that one can directly edit the data while the visualization constantly provides feedback on the implications of the data modifications. Preliminary user feedback indicates that our integrated approach can be a useful complement to standard non-visual editing via external tools.

Multi-state modeling of biomolecules.

Directory of Open Access Journals (Sweden)

Melanie I Stefan

2014-09-01

Full Text Available Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behavior of biological molecules or complexes that can adopt a large number of possible functional states. Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: the problem of how to describe and specify a multi-state system (the "specification problem" and the problem of how to use a computer to simulate the progress of the system over time (the "computation problem". To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus, BioNetGen, the Allosteric Network Compiler, and others. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators fall into two further categories: nonspatial simulators, such as StochSim, DYNSTOC, RuleMonkey, and the Network-Free Stochastic Simulator (NFSim, and spatial simulators, including Meredys, SRSim, and MCell. Modelers can thus choose from a variety of tools, the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future.

Cellular Automaton Modeling of Dendritic Growth Using a Multi-grid Method

International Nuclear Information System (INIS)

Natsume, Y; Ohsasa, K

2015-01-01

A two-dimensional cellular automaton model with a multi-grid method was developed to simulate dendritic growth. In the present model, we used a triple-grid system for temperature, solute concentration and solid fraction fields as a new approach of the multi-grid method. In order to evaluate the validity of the present model, we carried out simulations of single dendritic growth, secondary dendrite arm growth, multi-columnar dendritic growth and multi-equiaxed dendritic growth. From the results of the grid dependency from the simulation of single dendritic growth, we confirmed that the larger grid can be used in the simulation and that the computational time can be reduced dramatically. In the simulation of secondary dendrite arm growth, the results from the present model were in good agreement with the experimental data and the simulated results from a phase-field model. Thus, the present model can quantitatively simulate dendritic growth. From the simulated results of multi-columnar and multi-equiaxed dendrites, we confirmed that the present model can perform simulations under practical solidification conditions. (paper)

ADMIT: a toolbox for guaranteed model invalidation, estimation and qualitative-quantitative modeling.

Science.gov (United States)

Streif, Stefan; Savchenko, Anton; Rumschinski, Philipp; Borchers, Steffen; Findeisen, Rolf

2012-05-01

Often competing hypotheses for biochemical networks exist in the form of different mathematical models with unknown parameters. Considering available experimental data, it is then desired to reject model hypotheses that are inconsistent with the data, or to estimate the unknown parameters. However, these tasks are complicated because experimental data are typically sparse, uncertain, and are frequently only available in form of qualitative if-then observations. ADMIT (Analysis, Design and Model Invalidation Toolbox) is a MatLab(TM)-based tool for guaranteed model invalidation, state and parameter estimation. The toolbox allows the integration of quantitative measurement data, a priori knowledge of parameters and states, and qualitative information on the dynamic or steady-state behavior. A constraint satisfaction problem is automatically generated and algorithms are implemented for solving the desired estimation, invalidation or analysis tasks. The implemented methods built on convex relaxation and optimization and therefore provide guaranteed estimation results and certificates for invalidity. ADMIT, tutorials and illustrative examples are available free of charge for non-commercial use at http://ifatwww.et.uni-magdeburg.de/syst/ADMIT/

Searchable attribute-based encryption scheme with attribute revocation in cloud storage.

Science.gov (United States)

Wang, Shangping; Zhao, Duqiao; Zhang, Yaling

2017-01-01

Attribute based encryption (ABE) is a good way to achieve flexible and secure access control to data, and attribute revocation is the extension of the attribute-based encryption, and the keyword search is an indispensable part for cloud storage. The combination of both has an important application in the cloud storage. In this paper, we construct a searchable attribute-based encryption scheme with attribute revocation in cloud storage, the keyword search in our scheme is attribute based with access control, when the search succeeds, the cloud server returns the corresponding cipher text to user and the user can decrypt the cipher text definitely. Besides, our scheme supports multiple keywords search, which makes the scheme more practical. Under the assumption of decisional bilinear Diffie-Hellman exponent (q-BDHE) and decisional Diffie-Hellman (DDH) in the selective security model, we prove that our scheme is secure.

A qualitative evaluation approach for energy system modelling frameworks

DEFF Research Database (Denmark)

Wiese, Frauke; Hilpert, Simon; Kaldemeyer, Cord

2018-01-01

properties define how useful it is in regard to the existing challenges. For energy system models, evaluation methods exist, but we argue that many decisions upon properties are rather made on the model generator or framework level. Thus, this paper presents a qualitative approach to evaluate frameworks...

Probability of Detection (POD) as a statistical model for the validation of qualitative methods.

Science.gov (United States)

Wehling, Paul; LaBudde, Robert A; Brunelle, Sharon L; Nelson, Maria T

2011-01-01

A statistical model is presented for use in validation of qualitative methods. This model, termed Probability of Detection (POD), harmonizes the statistical concepts and parameters between quantitative and qualitative method validation. POD characterizes method response with respect to concentration as a continuous variable. The POD model provides a tool for graphical representation of response curves for qualitative methods. In addition, the model allows comparisons between candidate and reference methods, and provides calculations of repeatability, reproducibility, and laboratory effects from collaborative study data. Single laboratory study and collaborative study examples are given.

Basilar membrane and reticular lamina motion in a multi-scale finite element model of the mouse cochlea

Science.gov (United States)

Soons, Joris; Dirckx, Joris; Steele, Charles; Puria, Sunil

2015-12-01

A multi-scale finite element (FE) model of the mouse cochlea, based on its anatomy and material properties is presented. The important feature in the model is a lattice of 400 Y-shaped structures in the longitudinal direction, each formed by Deiters cells, phalangeal processes and outer hair cells (OHC). OHC somatic motility is modeled by an expansion force proportional to the shear on the stereocilia, which in turn is proportional to the pressure difference between the scala vestibule and scala tympani. Basilar membrane (BM) and reticular lamina (RL) velocity compare qualitatively very well with recent in vivo measurements in guinea pig [2]. Compared to the BM, the RL is shown to have higher amplification and a shift to higher frequencies. This comes naturally from the realistic Y-shaped cell organization without tectorial membrane tuning.

Multi Stakeholders' Attitudes toward Bt rice in Southwest, Iran: Application of TPB and Multi Attribute Models.

Science.gov (United States)

Ghoochani, Omid M; Ghanian, Mansour; Baradaran, Masoud; Azadi, Hossein

2017-03-01

Organisms that have been genetically engineered and modified (GM) are referred to as genetically modified organisms (GMOs). Bt crops are plants that have been genetically modified to produce certain proteins from the soil bacteria Bacillus thuringiensis (Bt), which makes these plants resistant to certain lepidopteran and coleopteran species. Genetically Modified (GM) rice was produced in 2006 by Iranian researchers from Tarom Mowla'ii and has since been called 'Bt rice'. As rice is an important source of food for over 3 billion inhabitants on Earth, this study aims to use a correlational survey in order to shed light on the predicting factors relating to the extent of stakeholders' behavioral intentions towards Bt rice. It is assumed and the results confirm that "attitudes toward GM crops" can be used as a bridge in the Attitude Model and the Behavioral Intention Model in order to establish an integrated model. To this end, a case study was made of the Southwest part of Iran in order to verify this research model. This study also revealed that as a part of the integrated research framework in the Behavior Intention Model both constructs of attitude and the subjective norm of the respondents serve as the predicting factors of stakeholders' intentions of working with Bt rice. In addition, the Attitude Model, as the other part of the integrated research framework, showed that the stakeholders' attitudes toward Bt rice can only be determined by the perceived benefits (e.g. positive outcomes) of Bt rice.

A multi-species multi-fleet bioeconomic simulation model for the English Channel artisanal fisheries

DEFF Research Database (Denmark)

Ulrich, Clara; Le Gallic, B.; Dunn, M.R.

2002-01-01

Considering the large number of technical interactions between various fishing activities, the English Channel (ICES divisions VIId and VIIe) fisheries may be regarded as one large and diverse multi-country, multi-gear and multi-species artisanal fishery, although rarely studied as such. A whole...... of the model is to study the long-term consequences of various management alternatives on the economic situation of the English and French fleets fishing in the area and on exploited resources. The model describes this feature through the links between three entities on the one hand (stocks, fleets...... and "metiers", i.e. gear x target species x fishing area), and three modules on the other hand (activity, biological production and economics). The model is described and some simulation results are presented. An example simulating a decrease of one fleet segment effort illustrates these technical interactions...

Computationally Efficient Transient Stability Modeling of multi-terminal VSC-HVDC

DEFF Research Database (Denmark)

van der Meer, Arjen A; Rueda-Torres, José; Silva, Filipe Miguel Faria da

2016-01-01

This paper studies the inclusion of averaged VSC-based grid interfaces and HVDC networks into stability type simulations, and compares the accuracy and speed of three multi-terminal DC dynamic models: 1) a state-space based model, 2) a multi-rate improved model, and 3) a reduced-order model...

Attributional processes in the learned helplessness paradigm: behavioral effects of global attributions.

Science.gov (United States)

Mikulincer, M

1986-12-01

Following the learned helplessness paradigm, I assessed in this study the effects of global and specific attributions for failure on the generalization of performance deficits in a dissimilar situation. Helplessness training consisted of experience with noncontingent failures on four cognitive discrimination problems attributed to either global or specific causes. Experiment 1 found that performance in a dissimilar situation was impaired following exposure to globally attributed failure. Experiment 2 examined the behavioral effects of the interaction between stable and global attributions of failure. Exposure to unsolvable problems resulted in reduced performance in a dissimilar situation only when failure was attributed to global and stable causes. Finally, Experiment 3 found that learned helplessness deficits were a product of the interaction of global and internal attribution. Performance deficits following unsolvable problems were recorded when failure was attributed to global and internal causes. Results were discussed in terms of the reformulated learned helplessness model.

A qualitative model construction method of nuclear power plants for effective diagnostic knowledge generation

International Nuclear Information System (INIS)

Yoshikawa, Shinji; Endou, Akira; Kitamura, Yoshinobu; Sasajima, Munehiko; Ikeda, Mitsuru; Mizoguchi, Riichiro.

1994-01-01

This paper discusses a method to construct a qualitative model of a nuclear power plant, in order to generate effective diagnostic knowledge. The proposed method is to prepare deep knowledge to be provided to a knowledge compiler based upon qualitative reasoning (QR). Necessity of knowledge compilation for nuclear plant diagnosis will be explained first, and conventionally-experienced problems in qualitative reasoning and a proposed method to overcome this problem is shown next, then a sample procedure to build a qualitative nuclear plant model is demonstrated. (author)

CONFIG - Adapting qualitative modeling and discrete event simulation for design of fault management systems

Science.gov (United States)

Malin, Jane T.; Basham, Bryan D.

1989-01-01

CONFIG is a modeling and simulation tool prototype for analyzing the normal and faulty qualitative behaviors of engineered systems. Qualitative modeling and discrete-event simulation have been adapted and integrated, to support early development, during system design, of software and procedures for management of failures, especially in diagnostic expert systems. Qualitative component models are defined in terms of normal and faulty modes and processes, which are defined by invocation statements and effect statements with time delays. System models are constructed graphically by using instances of components and relations from object-oriented hierarchical model libraries. Extension and reuse of CONFIG models and analysis capabilities in hybrid rule- and model-based expert fault-management support systems are discussed.

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 1: Assessing the influence of constrained multi-generational ageing

Directory of Open Access Journals (Sweden)

S. H. Jathar

2016-02-01

the conditions tested. Consequently, the use of low and high NOx yields perturbs SOA concentrations by a factor of two and are probably a much stronger determinant in 3-D models than multi-generational oxidation. While total predicted SOA mass is similar for the SOM and two-product models, the SOM model predicts increased SOA contributions from anthropogenic (alkane, aromatic and sesquiterpenes and decreased SOA contributions from isoprene and monoterpene relative to the two-product model calculations. The SOA predicted by SOM has a much lower volatility than that predicted by the traditional model, resulting in better qualitative agreement with volatility measurements of ambient OA. On account of its lower-volatility, the SOA mass produced by SOM does not appear to be as strongly influenced by the inclusion of oligomerization reactions, whereas the two-product model relies heavily on oligomerization to form low-volatility SOA products. Finally, an unconstrained contemporary hybrid scheme to model multi-generational oxidation within the framework of a two-product model in which ageing reactions are added on top of the existing two-product parameterization is considered. This hybrid scheme formed at least 3 times more SOA than the SOM during regional simulations as a result of excessive transformation of semi-volatile vapors into lower volatility material that strongly partitions to the particle phase. This finding suggests that these hybrid multi-generational schemes should be used with great caution in regional models.

A Qualitative Acceleration Model Based on Intervals

Directory of Open Access Journals (Sweden)

Ester MARTINEZ-MARTIN

2013-08-01

Full Text Available On the way to autonomous service robots, spatial reasoning plays a main role since it properly deals with problems involving uncertainty. In particular, we are interested in knowing people's pose to avoid collisions. With that aim, in this paper, we present a qualitative acceleration model for robotic applications including representation, reasoning and a practical application.

An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing.

Science.gov (United States)

Wu, Zujian; Pang, Wei; Coghill, George M

2015-01-01

Both qualitative and quantitative model learning frameworks for biochemical systems have been studied in computational systems biology. In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems. In the proposed framework, interactions between reactants in the candidate models for a target biochemical system are evolved and eventually identified by the application of a qualitative model learning approach with an evolution strategy. Kinetic rates of the models generated from qualitative model learning are then further optimised by employing a quantitative approach with simulated annealing. Experimental results indicate that our proposed integrative framework is feasible to learn the relationships between biochemical reactants qualitatively and to make the model replicate the behaviours of the target system by optimising the kinetic rates quantitatively. Moreover, potential reactants of a target biochemical system can be discovered by hypothesising complex reactants in the synthetic models. Based on the biochemical models learned from the proposed framework, biologists can further perform experimental study in wet laboratory. In this way, natural biochemical systems can be better understood.

Summary of multi-core hardware and programming model investigations

Energy Technology Data Exchange (ETDEWEB)

Kelly, Suzanne Marie; Pedretti, Kevin Thomas Tauke; Levenhagen, Michael J.

2008-05-01

This report summarizes our investigations into multi-core processors and programming models for parallel scientific applications. The motivation for this study was to better understand the landscape of multi-core hardware, future trends, and the implications on system software for capability supercomputers. The results of this study are being used as input into the design of a new open-source light-weight kernel operating system being targeted at future capability supercomputers made up of multi-core processors. A goal of this effort is to create an agile system that is able to adapt to and efficiently support whatever multi-core hardware and programming models gain acceptance by the community.

What attributions do Australian high-performing general practices make for their success? Applying the clinical microsystems framework: a qualitative study.

Science.gov (United States)

Dunham, Annette H; Dunbar, James A; Johnson, Julie K; Fuller, Jeff; Morgan, Mark; Ford, Dale

2018-04-10

To identify the success attributions of high-performing Australian general practices and the enablers and barriers they envisage for practices wishing to emulate them. Qualitative study using semi-structured interviews and content analysis of the data. Responses were recorded, transcribed verbatim and coded according to success characteristics of high-performing clinical microsystems. Primary healthcare with the participating general practices representing all Australian states and territories, and representing metropolitan and rural locations. Twenty-two general practices identified as high performing via a number of success criteria. The 52 participants were 19 general practitioners, 18 practice managers and 15 practice nurses. Participants most frequently attributed success to the interdependence of the team members, patient-focused care and leadership of the practice. They most often signalled practice leadership, team interdependence and staff focus as enablers that other organisations would need to emulate their success. They most frequently identified barriers that might be encountered in the form of potential deficits or limitations in practice leadership, staff focus and mesosystem support. Practice leaders need to empower their teams to take action through providing inclusive leadership that facilitates team interdependence. Mesosystem support for quality improvement in general practice should focus on enabling this leadership and team building, thereby ensuring improvement efforts are converted into effective healthcare provision. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Predictive modeling of coupled multi-physics systems: I. Theory

International Nuclear Information System (INIS)

Cacuci, Dan Gabriel

2014-01-01

Highlights: • We developed “predictive modeling of coupled multi-physics systems (PMCMPS)”. • PMCMPS reduces predicted uncertainties in predicted model responses and parameters. • PMCMPS treats efficiently very large coupled systems. - Abstract: This work presents an innovative mathematical methodology for “predictive modeling of coupled multi-physics systems (PMCMPS).” This methodology takes into account fully the coupling terms between the systems but requires only the computational resources that would be needed to perform predictive modeling on each system separately. The PMCMPS methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution based on a priori known mean values and uncertainties characterizing the parameters and responses for both multi-physics models. This “maximum entropy”-approximate a priori distribution is combined, using Bayes’ theorem, with the “likelihood” provided by the multi-physics simulation models. Subsequently, the posterior distribution thus obtained is evaluated using the saddle-point method to obtain analytical expressions for the optimally predicted values for the multi-physics models parameters and responses along with corresponding reduced uncertainties. Noteworthy, the predictive modeling methodology for the coupled systems is constructed such that the systems can be considered sequentially rather than simultaneously, while preserving exactly the same results as if the systems were treated simultaneously. Consequently, very large coupled systems, which could perhaps exceed available computational resources if treated simultaneously, can be treated with the PMCMPS methodology presented in this work sequentially and without any loss of generality or information, requiring just the resources that would be needed if the systems were treated sequentially

Attributable risk of Capillaria species in domestic pigeons (Columba livia domestica

Directory of Open Access Journals (Sweden)

M.F. Qamar

Full Text Available ABSTRACT Fecal samples were collected from 120 domestic pigeons to determine the Attributable risk of Capillaria spp. The Capillaria spp. was observed in 64 out of 120 (51% pigeons (70 males and 50 females under this study. A total of 64 (39 males and 25 females were found naturally infected with Capillaria spp. with infection percentage of 51% and 50% in males and females respectively. Qualitative examinations include the direct microscopy and faecal floatation while quantitative examination includes McMaster technique (worms load was calculated per gram of the faeces. Month wise Attributable risk showed that eggs of the worms were found to be abundant in the month of July during the present study (60% to 73% because of high humidity. Very high and very low temperature is not suitable for the proper development of the eggs. Qualitative and quantitative examination revealed that Capillaria spp. was more prevalent in males (51% than females (50% but overall there was no significant difference (P>0.05 in the male and female because both individuals invest equal amount of energy in search of food and incubating the eggs. Different breeds of pigeons gave different Attributable risk in different months during the study. Groups of pigeons from different locations showed different variable Attributable risk. Areas with high humidity were more suitable for the development of eggs, which is the reason why higher Attributable risk was observed in Shahdara (75% area of Lahore, Pakistan.

Bi-dimension decomposed hidden Markov models for multi-person activity recognition

Institute of Scientific and Technical Information of China (English)

Wei-dong ZHANG; Feng CHEN; Wen-li XU

2009-01-01

We present a novel model for recognizing long-term complex activities involving multiple persons. The proposed model, named 'decomposed hidden Markov model' (DHMM), combines spatial decomposition and hierarchical abstraction to capture multi-modal, long-term dependent and multi-scale characteristics of activities. Decomposition in space and time offers conceptual advantages of compaction and clarity, and greatly reduces the size of state space as well as the number of parameters.DHMMs are efficient even when the number of persons is variable. We also introduce an efficient approximation algorithm for inference and parameter estimation. Experiments on multi-person activities and multi-modal individual activities demonstrate that DHMMs are more efficient and reliable than familiar models, such as coupled HMMs, hierarchical HMMs, and multi-observation HMMs.

A methodology for acquiring qualitative knowledge for probabilistic graphical models

DEFF Research Database (Denmark)

Kjærulff, Uffe Bro; Madsen, Anders L.

2004-01-01

We present a practical and general methodology that simplifies the task of acquiring and formulating qualitative knowledge for constructing probabilistic graphical models (PGMs). The methodology efficiently captures and communicates expert knowledge, and has significantly eased the model...

Main attributes influencing spent nuclear fuel management

International Nuclear Information System (INIS)

Andreescu, N.; Ohai, D.

1997-01-01

All activities regarding nuclear fuel, following its discharge from the NPP, constitute the spent fuel management and are grouped in two possible back end variants, namely reprocessing (including HLW vitrification and geological disposal) and direct disposal of spent fuel. In order to select the appropriate variant it is necessary to analyse the aggregate fulfillment of the imposed requirements, particularly of the derived attributes, defined as distinguishing characteristics of the factors used in the decision making process. The main identified attributes are the following: - environmental impact, - availability of suitable sites, - non-proliferation degree, -strategy of energy, - technological complexity and technical maturity, -possible further technical improvements, - size of nuclear programme, - total costs, - public acceptance, - peculiarity of CANDU fuel. The significance of the attributes in the Romanian case, taking into consideration the present situation, as a low scenario and a high scenario corresponding to an important development of the nuclear power, after the year 2010, is presented. According to their importance the ranking of attributes is proposed . Subsequently, the ranking could be used for adequate weighing of attributes in order to realize a multi-criteria analysis and a relevant comparison of back end variants. (authors)

Global qualitative analysis of a quartic ecological model

NARCIS (Netherlands)

Broer, Hendrik; Gaiko, Valery A.

2010-01-01

in this paper we complete the global qualitative analysis of a quartic ecological model. In particular, studying global bifurcations of singular points and limit cycles, we prove that the corresponding dynamical system has at most two limit cycles. (C) 2009 Elsevier Ltd. All rights reserved.

The Multi-perspective Process Explorer

NARCIS (Netherlands)

Mannhardt, Felix; De Leoni, Massimiliano; Reijers, Hajo A.

2015-01-01

Organizations use process mining techniques to analyze event data recorded by their information systems. Multi-perspective process mining techniques make use of data attributes attached to events to analyze processes from multiple perspectives. Applying those multi-perspective process mining

Multi-scale climate modelling over Southern Africa using a variable-resolution global model

CSIR Research Space (South Africa)

Engelbrecht, FA

2011-12-01

Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

Improving Geologic and Engineering Models of Midcontinent Fracture and Karst-Modified Reservoirs Using New 3-D Seismic Attributes

Energy Technology Data Exchange (ETDEWEB)

Susan Nissen; Saibal Bhattacharya; W. Lynn Watney; John Doveton

2009-03-31

Our project goal was to develop innovative seismic-based workflows for the incremental recovery of oil from karst-modified reservoirs within the onshore continental United States. Specific project objectives were: (1) to calibrate new multi-trace seismic attributes (volumetric curvature, in particular) for improved imaging of karst-modified reservoirs, (2) to develop attribute-based, cost-effective workflows to better characterize karst-modified carbonate reservoirs and fracture systems, and (3) to improve accuracy and predictiveness of resulting geomodels and reservoir simulations. In order to develop our workflows and validate our techniques, we conducted integrated studies of five karst-modified reservoirs in west Texas, Colorado, and Kansas. Our studies show that 3-D seismic volumetric curvature attributes have the ability to re-veal previously unknown features or provide enhanced visibility of karst and fracture features compared with other seismic analysis methods. Using these attributes, we recognize collapse features, solution-enlarged fractures, and geomorphologies that appear to be related to mature, cockpit landscapes. In four of our reservoir studies, volumetric curvature attributes appear to delineate reservoir compartment boundaries that impact production. The presence of these compartment boundaries was corroborated by reservoir simulations in two of the study areas. Based on our study results, we conclude that volumetric curvature attributes are valuable tools for mapping compartment boundaries in fracture- and karst-modified reservoirs, and we propose a best practices workflow for incorporating these attributes into reservoir characterization. When properly calibrated with geological and production data, these attributes can be used to predict the locations and sizes of undrained reservoir compartments. Technology transfer of our project work has been accomplished through presentations at professional society meetings, peer-reviewed publications

A multi-band, multi-level, multi-electron model for efficient FDTD simulations of electromagnetic interactions with semiconductor quantum wells

Science.gov (United States)

Ravi, Koustuban; Wang, Qian; Ho, Seng-Tiong

2015-08-01

We report a new computational model for simulations of electromagnetic interactions with semiconductor quantum well(s) (SQW) in complex electromagnetic geometries using the finite-difference time-domain method. The presented model is based on an approach of spanning a large number of electron transverse momentum states in each SQW sub-band (multi-band) with a small number of discrete multi-electron states (multi-level, multi-electron). This enables accurate and efficient two-dimensional (2-D) and three-dimensional (3-D) simulations of nanophotonic devices with SQW active media. The model includes the following features: (1) Optically induced interband transitions between various SQW conduction and heavy-hole or light-hole sub-bands are considered. (2) Novel intra sub-band and inter sub-band transition terms are derived to thermalize the electron and hole occupational distributions to the correct Fermi-Dirac distributions. (3) The terms in (2) result in an explicit update scheme which circumvents numerically cumbersome iterative procedures. This significantly augments computational efficiency. (4) Explicit update terms to account for carrier leakage to unconfined states are derived, which thermalize the bulk and SQW populations to a common quasi-equilibrium Fermi-Dirac distribution. (5) Auger recombination and intervalence band absorption are included. The model is validated by comparisons to analytic band-filling calculations, simulations of SQW optical gain spectra, and photonic crystal lasers.

Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

Science.gov (United States)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

Modeling bidding competitiveness and position performance in multi-attribute construction auctions

Directory of Open Access Journals (Sweden)

Pablo Ballesteros-Pérez

2015-12-01

This paper details a practical methodology based on simple statistical calculations for modeling the performance of a single bidder or a group of bidders, constituting a useful resource for analyzing one’s own success while benchmarking potential bidding competitors.

Multi-attribute bilateral bargaining in a one-to-many setting

NARCIS (Netherlands)

E.H. Gerding (Enrico); D.J.A. Somefun (Koye); J.A. La Poutré (Han)

2005-01-01

htmlabstractNegotiations are an important way of reaching agreements between selfish autonomous agents. In this paper we focus on one-to-many bargaining within the context of agent-mediated electronic commerce. We consider an approach where a seller negotiates over multiple interdependent attributes

Multi-Level Marketing as a business model

Directory of Open Access Journals (Sweden)

Bogdan Gregor

2013-03-01

Full Text Available Multi Level Marketing is a very popular business model in the Western countries. It is a kind of hybrid of the method of distribution of goods and the method of building a sales network. It is one of the safest (carries a very low risk ways of conducting a business activity. The knowledge about functioning of this business model, both among theoreticians (scanty literature on the subject and practitioners, is still insufficient in Poland. Thus, the presented paper has been prepared as — in the Authors' opinion — it, at least infinitesimally, bridges the gap in the recognition of Multi Level Marketing issues. The aim of the study was, first of all, to describe Multi Level Marketing, to indicate practical benefits of this business model as well as to present basic systems of calculating a commission, which are used in marketing plans of companies. The discussion was based on the study of literature and the knowledge gained in the course of free-form interviews with the leaders of the sector.

Efficient Multi-Valued Bounded Model Checking for LTL over Quasi-Boolean Algebras

Science.gov (United States)

Andrade, Jefferson O.; Kameyama, Yukiyoshi

Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In this paper, we propose a novel, efficient algorithm for multi-valued bounded model checking. A notable feature of our algorithm is that it is not based on reduction of multi-values into two-values; instead, it generates a single formula which represents multi-valuedness by a suitable encoding, and asks a standard SAT solver to check its satisfiability. Our experimental results show a significant improvement in the number of variables and clauses and also in execution time compared with the reduction-based one.

Algorithm for Financial Derivatives Evaluation in a Generalized Multi-Heston Model

Directory of Open Access Journals (Sweden)

Dan Negura

2013-02-01

Full Text Available In this paper we show how could a financial derivative be estimated based on an assumed Multi-Heston model support.Keywords: Euler Maruyama discretization method, Monte Carlo simulation, Heston model, Double-Heston model, Multi-Heston model

Importance assessment of decision attributes: A qualitative study comparing experts and laypersons

NARCIS (Netherlands)

Heerkens, Johannes M.G.; Norde, Christiaan; van der Heijden, Beatrice

2011-01-01

Purpose – This paper aims to investigate differences between experts and laypersons concerning the way they assess the importance of each of the various decision attributes (cost, risk, feasibility) taken into consideration during decision processes in an organizational setting.

Entropy-optimal weight constraint elicitation with additive multi-attribute utility models

NARCIS (Netherlands)

Valkenhoef , van Gert; Tervonen, Tommi

2016-01-01

We consider the elicitation of incomplete preference information for the additive utility model in terms of linear constraints on the weights. Eliciting incomplete preferences using holistic pair-wise judgments is convenient for the decision maker, but selecting the best pair-wise comparison is

A comparative study of 3D FZI and electrofacies modeling using seismic attribute analysis and neural network technique: A case study of Cheshmeh-Khosh Oil field in Iran

Directory of Open Access Journals (Sweden)

Mahdi Rastegarnia

2016-09-01

Full Text Available Electrofacies are used to determine reservoir rock properties, especially permeability, to simulate fluid flow in porous media. These are determined based on classification of similar logs among different groups of logging data. Data classification is accomplished by different statistical analysis such as principal component analysis, cluster analysis and differential analysis. The aim of this study is to predict 3D FZI (flow zone index and Electrofacies (EFACT volumes from a large volume of 3D seismic data. This study is divided into two parts. In the first part of the study, in order to make the EFACT model, nuclear magnetic resonance (NMR log parameters were employed for developing an Electrofacies diagram based on pore size distribution and porosity variations. Then, a graph-based clustering method, known as multi resolution graph-based clustering (MRGC, was employed to classify and obtain the optimum number of Electrofacies. Seismic attribute analysis was then applied to model each relaxation group in order to build the initial 3D model which was used to reach the final model by applying Probabilistic Neural Network (PNN. In the second part of the study, the FZI 3D model was created by multi attributes technique. Then, this model was improved by three different artificial intelligence systems including PNN, multilayer feed-forward network (MLFN and radial basis function network (RBFN. Finally, models of FZI and EFACT were compared. Results obtained from this study revealed that the two models are in good agreement and PNN method is successful in modeling FZI and EFACT from 3D seismic data for which no Stoneley data or NMR log data are available. Moreover, they may be used to detect hydrocarbon-bearing zones and locate the exact place for producing wells for the future development plans. In addition, the result provides a geologically realistic spatial FZI and reservoir facies distribution which helps to understand the subsurface reservoirs

Assessment of multi class kinematic wave models

NARCIS (Netherlands)

Van Wageningen-Kessels, F.L.M.; Van Lint, J.W.C.; Vuik, C.; Hoogendoorn, S.P.

2012-01-01

In the last decade many multi class kinematic wave (MCKW) traffic ow models have been proposed. MCKW models introduce heterogeneity among vehicles and drivers. For example, they take into account differences in (maximum) velocities and driving style. Nevertheless, the models are macroscopic and the

MULTI: a shared memory approach to cooperative molecular modeling.

Science.gov (United States)

Darden, T; Johnson, P; Smith, H

1991-03-01

A general purpose molecular modeling system, MULTI, based on the UNIX shared memory and semaphore facilities for interprocess communication is described. In addition to the normal querying or monitoring of geometric data, MULTI also provides processes for manipulating conformations, and for displaying peptide or nucleic acid ribbons, Connolly surfaces, close nonbonded contacts, crystal-symmetry related images, least-squares superpositions, and so forth. This paper outlines the basic techniques used in MULTI to ensure cooperation among these specialized processes, and then describes how they can work together to provide a flexible modeling environment.

Efficient Multi-Valued Bounded Model Checking for LTL over Quasi-Boolean Algebras

OpenAIRE

Andrade, Jefferson O.; Kameyama, Yukiyoshi

2012-01-01

Multi-valued Model Checking extends classical, two-valued model checking to multi-valued logic such as Quasi-Boolean logic. The added expressivity is useful in dealing with such concepts as incompleteness and uncertainty in target systems, while it comes with the cost of time and space. Chechik and others proposed an efficient reduction from multi-valued model checking problems to two-valued ones, but to the authors' knowledge, no study was done for multi-valued bounded model checking. In thi...

Analytic Hierarchy Process & Multi Attribute Utility Theory Based Approach for the Selection of Lighting Systems in Residential Buildings: A Case Study

Directory of Open Access Journals (Sweden)

Othman Alshamrani

2018-05-01

Full Text Available This paper presents an approach developed for selecting lighting systems in residential buildings using an Analytic Hierarchy Process (AHP and the Multi Criteria Decision Making Technique (MCDMT. The developed approach considers four selection criteria of lighting systems: life-cycle cost, illumination, environmental performance, and life-span. The criteria of selection, along with the most widely used lighting systems in residential buildings, were determined through questionnaire surveys with suppliers, maintenance managers, and lighting experts. The Analytic Hierarchy Process and Multi Attribute Utility Theory were utilized to assess the significant influence of the identified main and sub-criteria on the selection process, from the design point of view. The developed approach was tested on a real case project in selecting the lighting system for aresidential building in Saudi Arabia. The obtained results show that the life-cycle cost and illumination proprieties, followed by the service life were found to be the most influential measures in the selection process. The results also show that Light-Emitting Diode(LED lighting systems prove to bear the highest initial cost while sustaining the best overall performance.

Multi-Attribute Modelling of Economic and Ecological Impacts of Cropping Systems

NARCIS (Netherlands)

Bohanec, M.; Dzeroski, S.; Znidarsic, M.; Messéan, A.; Scatasta, S.; Wesseler, J.H.H.

2004-01-01

Modelling of economic and ecological impacts of genetically modified crops is a demanding task. We present some preliminary attempts made for the purpose of the ECOGEN project "Soil ecological and economic evaluation of genetically modified crops". One of the goals of the project is to develop a

Quantifying credit portfolio losses under multi-factor models

NARCIS (Netherlands)

G. Colldeforns-Papiol (Gemma); L. Ortiz Gracia (Luis); C.W. Oosterlee (Kees)

2018-01-01

textabstractIn this work, we investigate the challenging problem of estimating credit risk measures of portfolios with exposure concentration under the multi-factor Gaussian and multi-factor t-copula models. It is well-known that Monte Carlo (MC) methods are highly demanding from the computational

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

Directory of Open Access Journals (Sweden)

Lin Zhang

2017-03-01

Full Text Available With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR. This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service.

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

Science.gov (United States)

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

Perceptual grouping does not affect multi-attribute decision making if no processing costs are involved.

Science.gov (United States)

Ettlin, Florence; Bröder, Arndt

2015-05-01

Adaptive strategy selection implies that a decision strategy is chosen based on its fit to the task and situation. However, other aspects, such as the way information is presented, can determine information search behavior; especially when the application of certain strategies over others is facilitated. But are such display effects on multi-attribute decisions also at work when the manipulation does not entail differential costs for different decision strategies? Three Mouselab experiments with hidden information and one eye tracking experiment with an open information board revealed that decision behavior is unaffected by purely perceptual manipulations of the display based on Gestalt principles; that is, based on manipulations that induce no noteworthy processing costs for different information search patterns. We discuss our results in the context of previous findings on display effects; specifically, how the combination of these findings and our results reveal the crucial role of differential processing costs for different strategies for the emergence of display effects. This finding describes a boundary condition of the commonly acknowledged influence of information displays and is in line with the ideas of adaptive strategy selection and cost-benefit tradeoffs. Copyright © 2015. Published by Elsevier B.V.

Multi-model approach to characterize human handwriting motion.

Science.gov (United States)

Chihi, I; Abdelkrim, A; Benrejeb, M

2016-02-01

This paper deals with characterization and modelling of human handwriting motion from two forearm muscle activity signals, called electromyography signals (EMG). In this work, an experimental approach was used to record the coordinates of a pen tip moving on the (x, y) plane and EMG signals during the handwriting act. The main purpose is to design a new mathematical model which characterizes this biological process. Based on a multi-model approach, this system was originally developed to generate letters and geometric forms written by different writers. A Recursive Least Squares algorithm is used to estimate the parameters of each sub-model of the multi-model basis. Simulations show good agreement between predicted results and the recorded data.

Investigating the multi-causal and complex nature of the accident causal influence of construction project features.

Science.gov (United States)

Manu, Patrick A; Ankrah, Nii A; Proverbs, David G; Suresh, Subashini

2012-09-01

Construction project features (CPFs) are organisational, physical and operational attributes that characterise construction projects. Although previous studies have examined the accident causal influence of CPFs, the multi-causal attribute of this causal phenomenon still remain elusive and thus requires further investigation. Aiming to shed light on this facet of the accident causal phenomenon of CPFs, this study examines relevant literature and crystallises the attained insight of the multi-causal attribute by a graphical model which is subsequently operationalised by a derived mathematical risk expression that offers a systematic approach for evaluating the potential of CPFs to cause harm and consequently their health and safety (H&S) risk implications. The graphical model and the risk expression put forth by the study thus advance current understanding of the accident causal phenomenon of CPFs and they present an opportunity for project participants to manage the H&S risk associated with CPFs from the early stages of project procurement. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Attribute for Hydrocarbon Prediction Based on Attenuation

International Nuclear Information System (INIS)

Hermana, Maman; Harith, Z Z T; Sum, C W; Ghosh, D P

2014-01-01

Hydrocarbon prediction is a crucial issue in the oil and gas industry. Currently, the prediction of pore fluid and lithology are based on amplitude interpretation which has the potential to produce pitfalls in certain conditions of reservoir. Motivated by this fact, this work is directed to find out other attributes that can be used to reduce the pitfalls in the amplitude interpretation. Some seismic attributes were examined and studies showed that the attenuation attribute is a better attribute for hydrocarbon prediction. Theoretically, the attenuation mechanism of wave propagation is associated with the movement of fluid in the pore; hence the existence of hydrocarbon in the pore will be represented by attenuation attribute directly. In this paper we evaluated the feasibility of the quality factor ratio of P-wave and S-wave (Qp/Qs) as hydrocarbon indicator using well data and also we developed a new attribute based on attenuation for hydrocarbon prediction -- Normalized Energy Reduction Stack (NERS). To achieve these goals, this work was divided into 3 main parts; estimating the Qp/Qs on well log data, testing the new attribute in the synthetic data and applying the new attribute on real data in Malay Basin data. The result show that the Qp/Qs is better than Poisson's ratio and Lamda over Mu as hydrocarbon indicator. The curve, trend analysis and contrast of Qp/Qs is more powerful at distinguishing pore fluid than Poisson ratio and Lamda over Mu. The NERS attribute was successful in distinguishing the hydrocarbon from brine on synthetic data. Applying this attribute on real data on Malay basin, the NERS attribute is qualitatively conformable with the structure and location where the gas is predicted. The quantitative interpretation of this attribute for hydrocarbon prediction needs to be investigated further

Hybrid attribute-based recommender system for learning material using genetic algorithm and a multidimensional information model

Directory of Open Access Journals (Sweden)

Mojtaba Salehi

2013-03-01

Full Text Available In recent years, the explosion of learning materials in the web-based educational systems has caused difficulty of locating appropriate learning materials to learners. A personalized recommendation is an enabling mechanism to overcome information overload occurred in the new learning environments and deliver suitable materials to learners. Since users express their opinions based on some specific attributes of items, this paper proposes a hybrid recommender system for learning materials based on their attributes to improve the accuracy and quality of recommendation. The presented system has two main modules: explicit attribute-based recommender and implicit attribute-based recommender. In the first module, weights of implicit or latent attributes of materials for learner are considered as chromosomes in genetic algorithm then this algorithm optimizes the weights according to historical rating. Then, recommendation is generated by Nearest Neighborhood Algorithm (NNA using the optimized weight vectors implicit attributes that represent the opinions of learners. In the second, preference matrix (PM is introduced that can model the interests of learner based on explicit attributes of learning materials in a multidimensional information model. Then, a new similarity measure between PMs is introduced and recommendations are generated by NNA. The experimental results show that our proposed method outperforms current algorithms on accuracy measures and can alleviate some problems such as cold-start and sparsity.

Privacy Protection on Multiple Sensitive Attributes

Science.gov (United States)

Li, Zhen; Ye, Xiaojun

In recent years, a privacy model called k-anonymity has gained popularity in the microdata releasing. As the microdata may contain multiple sensitive attributes about an individual, the protection of multiple sensitive attributes has become an important problem. Different from the existing models of single sensitive attribute, extra associations among multiple sensitive attributes should be invested. Two kinds of disclosure scenarios may happen because of logical associations. The Q&S Diversity is checked to prevent the foregoing disclosure risks, with an α Requirement definition used to ensure the diversity requirement. At last, a two-step greedy generalization algorithm is used to carry out the multiple sensitive attributes processing which deal with quasi-identifiers and sensitive attributes respectively. We reduce the overall distortion by the measure of Masking SA.

Primary health care attributes and responses to intimate partner violence in Spain.

Science.gov (United States)

Goicolea, Isabel; Mosquera, Paola; Briones-Vozmediano, Erica; Otero-García, Laura; García-Quinto, Marta; Vives-Cases, Carmen

This study provides an overview of the perceptions of primary care professionals on how the current primary health care (PHC) attributes in Spain could influence health-related responses to intimate partner violence (IPV). A qualitative study was conducted using semi-structured interviews with 160 health professionals working in 16 PHC centres in Spain. Data were analysed using a qualitative content analysis. Four categories emerged from the interview analysis: those committed to the PHC approach, but with difficulties implementing it; community work relying on voluntarism; multidisciplinary team work or professionals who work together?; and continuity of care hindered by heavy work load. Participants felt that person-centred care as well as other attributes of the PHC approach facilitated detecting IPV and a better response to the problem. However, they also pointed out that the current management of the health system (workload, weak supervision and little feedback, misdistribution of human and material resources, etc.) does not facilitate the sustainability of such an approach. There is a gap between the theoretical attributes of PHC and the "reality" of how these attributes are managed in everyday work, and how this influences IPV care. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

Science.gov (United States)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Semantic attributes based texture generation

Science.gov (United States)

Chi, Huifang; Gan, Yanhai; Qi, Lin; Dong, Junyu; Madessa, Amanuel Hirpa

2018-04-01

Semantic attributes are commonly used for texture description. They can be used to describe the information of a texture, such as patterns, textons, distributions, brightness, and so on. Generally speaking, semantic attributes are more concrete descriptors than perceptual features. Therefore, it is practical to generate texture images from semantic attributes. In this paper, we propose to generate high-quality texture images from semantic attributes. Over the last two decades, several works have been done on texture synthesis and generation. Most of them focusing on example-based texture synthesis and procedural texture generation. Semantic attributes based texture generation still deserves more devotion. Gan et al. proposed a useful joint model for perception driven texture generation. However, perceptual features are nonobjective spatial statistics used by humans to distinguish different textures in pre-attentive situations. To give more describing information about texture appearance, semantic attributes which are more in line with human description habits are desired. In this paper, we use sigmoid cross entropy loss in an auxiliary model to provide enough information for a generator. Consequently, the discriminator is released from the relatively intractable mission of figuring out the joint distribution of condition vectors and samples. To demonstrate the validity of our method, we compare our method to Gan et al.'s method on generating textures by designing experiments on PTD and DTD. All experimental results show that our model can generate textures from semantic attributes.

Supervised Multi-Authority Scheme with Blind Signature for IoT with Attribute Based Encryption

Science.gov (United States)

Nissenbaum, O. V.; Ponomarov, K. Y.; Zaharov, A. A.

2018-04-01

This article proposes a three-side cryptographic scheme for verifying device attributes with a Supervisor and a Certification Authority (CA) for attribute-based encryption. Two options are suggested: using a message authentication code and using a digital signature. The first version is suitable for networks with one CA, and the second one for networks with several CAs, including dynamic systems. Also, the addition of this scheme with a blind signature is proposed to preserve the confidentiality of the device attributes from the CA. The introduction gives a definition and a brief historical overview of attribute-based encryption (ABE), addresses the use of ABE in the Internet of Things.

Testing an Attribution Model of Caregiving in a Latino Sample: The Roles of Familismo and the Caregiver-Care Recipient Relationship.

Science.gov (United States)

Villalobos, Bianca T; Bridges, Ana J

2016-07-01

This study tests the parameters of Weiner's attribution model of caregiving, which describes how attributions of controllability relate to emotional reactions, which in turn influence willingness to provide support to stigmatized individuals. To date, the model has not been explored in the context of cultural variables, the caregiver-recipient relationship, or types of support. The present study examined the attribution model using a Latino community sample (N = 96) that was presented with vignettes describing an individual with depression. Support was found for the basic attribution model. Familismo was predictive of attributions of controllability and the basic model was predictive of emotional support, but not instrumental support. Participants were more willing to provide instrumental support to a partner, but had more positive affective reactions toward a sibling. The findings provide important information about contextual factors that may motivate Latino caregivers to provide support. © The Author(s) 2015.

Multi-scale modelling of non-uniform consolidation of uncured toughened unidirectional prepregs

Science.gov (United States)

Sorba, G.; Binetruy, C.; Syerko, E.; Leygue, A.; Comas-Cardona, S.; Belnoue, J. P.-H.; Nixon-Pearson, O. J.; Ivanov, D. S.; Hallett, S. R.; Advani, S. G.

2018-05-01

the sample edge with the multi-scale compaction model after one time step [3]. The ply distortion and resin flow observed in Fig.1 is qualitatively retrieved by the computational model.

Uncertain and multi-objective programming models for crop planting structure optimization

Directory of Open Access Journals (Sweden)

Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG

2016-03-01

Full Text Available Crop planting structure optimization is a significant way to increase agricultural economic benefits and improve agricultural water management. The complexities of fluctuating stream conditions, varying economic profits, and uncertainties and errors in estimated modeling parameters, as well as the complexities among economic, social, natural resources and environmental aspects, have led to the necessity of developing optimization models for crop planting structure which consider uncertainty and multi-objectives elements. In this study, three single-objective programming models under uncertainty for crop planting structure optimization were developed, including an interval linear programming model, an inexact fuzzy chance-constrained programming (IFCCP model and an inexact fuzzy linear programming (IFLP model. Each of the three models takes grayness into account. Moreover, the IFCCP model considers fuzzy uncertainty of parameters/variables and stochastic characteristics of constraints, while the IFLP model takes into account the fuzzy uncertainty of both constraints and objective functions. To satisfy the sustainable development of crop planting structure planning, a fuzzy-optimization-theory-based fuzzy linear multi-objective programming model was developed, which is capable of reflecting both uncertainties and multi-objective. In addition, a multi-objective fractional programming model for crop structure optimization was also developed to quantitatively express the multi-objective in one optimization model with the numerator representing maximum economic benefits and the denominator representing minimum crop planting area allocation. These models better reflect actual situations, considering the uncertainties and multi-objectives of crop planting structure optimization systems. The five models developed were then applied to a real case study in Minqin County, north-west China. The advantages, the applicable conditions and the solution methods

The Aircraft Electric Taxi System: A Qualitative Multi Case Study

Science.gov (United States)

Johnson, Thomas Frank

The problem this research addresses is the airline industry, and the seemingly unwillingness attitude towards adopting ways to taxi aircraft without utilizing thrust from the main engines. The purpose of the study was to get a better understanding of the decision-making process of airline executives, in respect to investing in cost saving technology. A qualitative research method is used from personal interviews with 24 airline executives from two major U.S. airlines, related industry journal articles, and aircraft performance data. The following three research questions are addressed. RQ1. Does the cost of jet fuel influence airline executives' decision of adopting the aircraft electric taxi system technology? RQ2 Does the measurable payback period for a return on investment influence airline executives' decision of adopting ETS technology? RQ3. Does the amount of government assistance influence airline executives' decision of adopting ETS technology? A multi case research study design is used with a triangulation technique. The participant perceptions indicate the need to reduce operating costs, they have concerns about investment risk, and they are in favor of future government sponsored performance improvement projects. Based on the framework, findings and implications of this study, a future research paper could focus on the positive environmental effects of the ETS application. A study could be conducted on current airport area air quality and the effects that aircraft main engine thrust taxiing has on the surrounding air quality.

Labeled experimental choice design for estimating attribute and availability cross effects with N attributes and specific brand attribute levels

DEFF Research Database (Denmark)

Nguyen, Thong Tien

2011-01-01

Experimental designs are required in widely used techniques in marketing research, especially for preference-based conjoint analysis and discrete-choice studies. Ideally, marketing researchers prefer orthogonal designs because this technique could give uncorrelated parameter estimates. However, o...... for implementing designs that is efficient enough to estimate model with N brands, each brand have K attributes, and brand attribute has specific levels. The paper also illustrates an example in food consumption study.......Experimental designs are required in widely used techniques in marketing research, especially for preference-based conjoint analysis and discrete-choice studies. Ideally, marketing researchers prefer orthogonal designs because this technique could give uncorrelated parameter estimates. However......, orthogonal design is not available for every situation. Instead, efficient design based on computerized design algorithm is always available. This paper presents the method of efficient design for estimating brand models having attribute and availability cross effects. The paper gives a framework...

(1)H NMR Metabolic Fingerprinting to Probe Temporal Postharvest Changes on Qualitative Attributes and Phytochemical Profile of Sweet Cherry Fruit.

Science.gov (United States)

Goulas, Vlasios; Minas, Ioannis S; Kourdoulas, Panayiotis M; Lazaridou, Athina; Molassiotis, Athanassios N; Gerothanassis, Ioannis P; Manganaris, George A

2015-01-01

Sweet cherry fruits (Prunus avium cvs. 'Canada Giant', 'Ferrovia') were harvested at commercial maturity stage and analyzed at harvest and after maintenance at room temperature (storage at ∼20°C, shelf life) for 1, 2, 4, 6, and 8 days, respectively. Fruit were initially analyzed for respiration rate, qualitative attributes and textural properties: 'Canada Giant' fruit were characterized by higher weight losses and stem browning index, being more intense over the late stages of shelf life period; meanwhile 'Ferrovia' possessed appreciably better performance even after extended shelf life period. A gradual decrease of respiration rate was monitored in both cultivars, culminated after 8 days at 20°C. The sweet cherry fruit nutraceutical profile was monitored using an array of instrumental techniques (spectrophotometric assays, HPLC, (1)H-NMR). Fruit antioxidant capacity was enhanced with the progress of shelf life period, concomitant with the increased levels of total anthocyanin and of phenolic compounds. 'Ferrovia' fruit presented higher contents of neochlorogenic acid and p-coumaroylquinic acid throughout the shelf life period. We further developed an (1)H-NMR method that allows the study of primary and secondary metabolites in a single running, without previous separation and isolation procedures. Diagnostic peaks were located in the aliphatic region for sugars and organic acids, in the aromatic region for phenolic compounds and at 8.2-8.6 ppm for anthocyanins. This NMR-based methodology provides a unifying tool for quantitative and qualitative characterization of metabolite changes of sweet cherry fruits; it is also expected to be further exploited for monitoring temporal changes in other fleshy fruits.

Accelerating transition dynamics in city regions: A qualitative modeling perspective

NARCIS (Netherlands)

P.J. Valkering (Pieter); Yücel, G. (Gönenç); Gebetsroither-Geringer, E. (Ernst); Markvica, K. (Karin); Meynaerts, E. (Erika); N. Frantzeskaki (Niki)

2017-01-01

textabstractIn this article, we take stock of the findings from conceptual and empirical work on the role of transition initiatives for accelerating transitions as input for modeling acceleration dynamics. We applied the qualitative modeling approach of causal loop diagrams to capture the dynamics

A Bayesian alternative for multi-objective ecohydrological model specification

Science.gov (United States)

Tang, Yating; Marshall, Lucy; Sharma, Ashish; Ajami, Hoori

2018-01-01

Recent studies have identified the importance of vegetation processes in terrestrial hydrologic systems. Process-based ecohydrological models combine hydrological, physical, biochemical and ecological processes of the catchments, and as such are generally more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov chain Monte Carlo (MCMC) techniques. The Bayesian approach offers an appealing alternative to traditional multi-objective hydrologic model calibrations by defining proper prior distributions that can be considered analogous to the ad-hoc weighting often prescribed in multi-objective calibration. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological modeling framework based on a traditional Pareto-based model calibration technique. In our study, a Pareto-based multi-objective optimization and a formal Bayesian framework are implemented in a conceptual ecohydrological model that combines a hydrological model (HYMOD) and a modified Bucket Grassland Model (BGM). Simulations focused on one objective (streamflow/LAI) and multiple objectives (streamflow and LAI) with different emphasis defined via the prior distribution of the model error parameters. Results show more reliable outputs for both predicted streamflow and LAI using Bayesian multi-objective calibration with specified prior distributions for error parameters based on results from the Pareto front in the ecohydrological modeling. The methodology implemented here provides insight into the usefulness of multiobjective Bayesian calibration for ecohydrologic systems and the importance of appropriate prior

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

Science.gov (United States)

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

Science.gov (United States)

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Model-Checking of Linear-Time Properties in Multi-Valued Systems

OpenAIRE

Li, Yongming; Droste, Manfred; Lei, Lihui

2012-01-01

In this paper, we study model-checking of linear-time properties in multi-valued systems. Safety property, invariant property, liveness property, persistence and dual-persistence properties in multi-valued logic systems are introduced. Some algorithms related to the above multi-valued linear-time properties are discussed. The verification of multi-valued regular safety properties and multi-valued $\\omega$-regular properties using lattice-valued automata are thoroughly studied. Since the law o...

Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations

Science.gov (United States)

Ward, Logan; Liu, Ruoqian; Krishna, Amar; Hegde, Vinay I.; Agrawal, Ankit; Choudhary, Alok; Wolverton, Chris

2017-07-01

While high-throughput density functional theory (DFT) has become a prevalent tool for materials discovery, it is limited by the relatively large computational cost. In this paper, we explore using DFT data from high-throughput calculations to create faster, surrogate models with machine learning (ML) that can be used to guide new searches. Our method works by using decision tree models to map DFT-calculated formation enthalpies to a set of attributes consisting of two distinct types: (i) composition-dependent attributes of elemental properties (as have been used in previous ML models of DFT formation energies), combined with (ii) attributes derived from the Voronoi tessellation of the compound's crystal structure. The ML models created using this method have half the cross-validation error and similar training and evaluation speeds to models created with the Coulomb matrix and partial radial distribution function methods. For a dataset of 435 000 formation energies taken from the Open Quantum Materials Database (OQMD), our model achieves a mean absolute error of 80 meV/atom in cross validation, which is lower than the approximate error between DFT-computed and experimentally measured formation enthalpies and below 15% of the mean absolute deviation of the training set. We also demonstrate that our method can accurately estimate the formation energy of materials outside of the training set and be used to identify materials with especially large formation enthalpies. We propose that our models can be used to accelerate the discovery of new materials by identifying the most promising materials to study with DFT at little additional computational cost.

Soil-landscape modelling using fuzzy c-means clustering of attribute data derived from a Digital Elevation Model (DEM).

NARCIS (Netherlands)

Bruin, de S.; Stein, A.

1998-01-01

This study explores the use of fuzzy c-means clustering of attribute data derived from a digital elevation model to represent transition zones in the soil-landscape. The conventional geographic model used for soil-landscape description is not able to properly deal with these. Fuzzy c-means

Thompson revisited. Ein empirisch fundiertes Modell zur Qualität von „Quality-TV“ aus Nutzersicht

Directory of Open Access Journals (Sweden)

Michael Harnischmacher

2015-07-01

Full Text Available Was bedeutet das Attribut „Quality-TV“ eigentlich für das Publikum? Nach welchen Kriterien beurteilen Zuschauerinnen und Zuschauer, ob eine Serie Qualitätsfernsehen ist oder nicht? Im Bereich der rezipientenorientierten Qualitätsforschung bezüglich Fernsehserien sind bislang fast ausschließlich qualitativ erhobene Modelle bedeutsam, am bekanntesten sicherlich die bereits 1996 von Robert J. Thompson vorgeschlagenen 12 Kriterien. Die vorliegende Untersuchung widmet sich nun der Frage, ob diese Qualitätskriterien tatsächlich die „richtigen“ sind. Sind sie für die Zuschauer/innen von Serien bedeutsam für die Einschätzung, ob ein Programm „Quality-TV“ ist oder nicht? Bislang fehlt eine empirische Fundierung der einzelnen Merkmale. Ebenso ungeklärt ist bislang, ob es eine Rangfolge dieser Merkmale gibt. Welche sind bedeutsamer, welche weniger wichtig für die Wahrnehmung einer Serie als Qualitätsprodukt? Die Studie hat Thompsons Vorschlag (unter Bezugnahme auf weitere Studien zum Thema (z.B. Cardwell 2007; Feuer 2007; Dreher 2010; Blanchett 2011; Kumpf 2011 operationalisiert und in einer standardisierten Befragung der Nutzer von 13 Onlineforen zu Qualitätsserien (n=1382 getestet. Auf Basis dieser Befragung kann statistisch nachgewiesen werden, welche Merkmale von den Zuschauer/innen als besonders wichtig angesehen werden und wie diese zu Qualitätsfaktoren zusammengefasst werden können, die das Phänomen „Quality-TV“ aus Zuschauersicht tatsächlich beschreiben können.

Characteristics of Patient-Centered Medical Home Initiatives that Generated Savings for Medicare: a Qualitative Multi-Case Analysis.

Science.gov (United States)

Burton, Rachel A; Lallemand, Nicole M; Peters, Rebecca A; Zuckerman, Stephen

2018-02-05

Through the Multi-Payer Advanced Primary Care Practice (MAPCP) Demonstration, Medicare, Medicaid, and private payers offered supplemental payments to 849 primary care practices that became patient-centered medical homes (PCMHs) in eight states; practices also received technical assistance and data reports. Average Medicare payments were capped at $10 per beneficiary per month in each state. Since there was variation in the eight participating states' demonstration designs, experiences, and outcomes, we conducted a qualitative multi-case analysis to identify the key factors that differentiated states that were estimated to have generated net savings for Medicare from states that did not. States' MAPCP Demonstration initiatives were comprehensively profiled in case studies based on secondary document review, three rounds of annual interviews with state staff, payers, practices, and other stakeholders, and other data sources. Case study findings were summarized in a case-ordered predictor-outcome matrix, which identified the presence or absence of key demonstration design features and experiences and arrayed states based on the amount of net savings or losses they generated for Medicare. We then used this matrix to identify initiative features that were present in at least three of the four states that generated net savings and absent from at least three of the four states that did not generate savings. A majority of the states that generated net savings: required practices to be recognized PCMHs to enter the demonstration, did not allow late entrants into the demonstration, used a consistent demonstration payment model across participating payers, and offered practices opportunities to earn performance bonuses. Practices in states that generated net savings also tended to report receiving the demonstration payments and bonuses they expected to receive, without any issues. Designers of future PCMH initiatives may increase their likelihood of generating net savings by

A qualitative reasoning model of algal bloom in the Danube Delta Biosphere Reserve (DDBR)

NARCIS (Netherlands)

Cioaca, E.; Linnebank, F.E.; Bredeweg, B.; Salles, P.

2009-01-01

This paper presents a Qualitative Reasoning model of the algal bloom phenomenon and its effects in the Danube Delta Biosphere Reserve (DDBR) in Romania. Qualitative Reasoning models represent processes and their cause-effect relationships in a flexible and conceptually rich manner and as such can be

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

Science.gov (United States)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Multi-Hypothesis Modelling Capabilities for Robust Data-Model Integration

Science.gov (United States)

Walker, A. P.; De Kauwe, M. G.; Lu, D.; Medlyn, B.; Norby, R. J.; Ricciuto, D. M.; Rogers, A.; Serbin, S.; Weston, D. J.; Ye, M.; Zaehle, S.

2017-12-01

Large uncertainty is often inherent in model predictions due to imperfect knowledge of how to describe the mechanistic processes (hypotheses) that a model is intended to represent. Yet this model hypothesis uncertainty (MHU) is often overlooked or informally evaluated, as methods to quantify and evaluate MHU are limited. MHU is increased as models become more complex because each additional processes added to a model comes with inherent MHU as well as parametric unceratinty. With the current trend of adding more processes to Earth System Models (ESMs), we are adding uncertainty, which can be quantified for parameters but not MHU. Model inter-comparison projects do allow for some consideration of hypothesis uncertainty but in an ad hoc and non-independent fashion. This has stymied efforts to evaluate ecosystem models against data and intepret the results mechanistically because it is not simple to interpret exactly why a model is producing the results it does and identify which model assumptions are key as they combine models of many sub-systems and processes, each of which may be conceptualised and represented mathematically in various ways. We present a novel modelling framework—the multi-assumption architecture and testbed (MAAT)—that automates the combination, generation, and execution of a model ensemble built with different representations of process. We will present the argument that multi-hypothesis modelling needs to be considered in conjunction with other capabilities (e.g. the Predictive Ecosystem Analyser; PecAn) and statistical methods (e.g. sensitivity anaylsis, data assimilation) to aid efforts in robust data model integration to enhance our predictive understanding of biological systems.

Multi area and multistage expansion-planning of electricity supply with sustainable energy development criteria: a multi objective model

Energy Technology Data Exchange (ETDEWEB)

Unsihuay-Vila, Clodomiro; Marangon-Lima, J.W.; Souza, A.C Zambroni de [Universidade Federal de Itajuba (UNIFEI), MG (Brazil)], emails: clodomirounsihuayvila @gmail.com, marangon@unifei.edu.br, zambroni@unifei.edu.br; Perez-Arriaga, I.J. [Universidad Pontificia Comillas, Madrid (Spain)], email: ipa@mit.edu

2010-07-01

A novel multi objective, multi area and multistage model to long-term expansion-planning of integrated generation and transmission corridors incorporating sustainable energy developing is presented in this paper. The proposed MESEDES model is a multi-regional multi-objective and 'bottom-up' energy model which considers the electricity generation/transmission value-chain, i.e., power generation alternatives including renewable, nuclear and traditional thermal generation along with transmission corridors. The model decides the optimal location and timing of the electricity generation/transmission abroad the multistage planning horizon. The MESEDES model considers three objectives belonging to sustainable energy development criteria such as: a) the minimization of investments and operation costs of : power generation, transmission corridors, energy efficiency (demand side management (DSM) programs) considering CO2 capture technologies; b) minimization of Life Cycle Greenhouse Gas Emissions (LC GHG); c) maximization of the diversification of electricity generation mix. The proposed model consider aspects of the carbon abatement policy under the CDM - Clean Development Mechanism or European Union Greenhouse Gas Emission Trading Scheme. A case study is used to illustrate the proposed framework. (author)

Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

Science.gov (United States)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The

A Model for Generating Multi-hazard Scenarios

Science.gov (United States)

Lo Jacomo, A.; Han, D.; Champneys, A.

2017-12-01

Communities in mountain areas are often subject to risk from multiple hazards, such as earthquakes, landslides, and floods. Each hazard has its own different rate of onset, duration, and return period. Multiple hazards tend to complicate the combined risk due to their interactions. Prioritising interventions for minimising risk in this context is challenging. We developed a probabilistic multi-hazard model to help inform decision making in multi-hazard areas. The model is applied to a case study region in the Sichuan province in China, using information from satellite imagery and in-situ data. The model is not intended as a predictive model, but rather as a tool which takes stakeholder input and can be used to explore plausible hazard scenarios over time. By using a Monte Carlo framework and varrying uncertain parameters for each of the hazards, the model can be used to explore the effect of different mitigation interventions aimed at reducing the disaster risk within an uncertain hazard context.

The Role of Perceptual Similarity, Context, and Situation When Selecting Attributes: Considerations Made by 5-6-Year-Olds in Data Modeling Environments

Science.gov (United States)

Leavy, Aisling; Hourigan, Mairead

2018-01-01

Classroom data modeling involves posing questions, identifying attributes of phenomena, measuring and structuring these attributes, and then composing, revising, and communicating the outcomes. Selecting attributes is a fundamental component of data modeling, and the considerations made when selecting attributes is the focus of this paper. A…

Recruiting Transcultural Qualitative Research Participants: A Conceptual Model

Directory of Open Access Journals (Sweden)

Phyllis Eide

2005-06-01

Full Text Available Working with diverse populations poses many challenges to the qualitative researcher who is a member of the dominant culture. Traditional methods of recruitment and selection (such as flyers and advertisements are often unproductive, leading to missed contributions from potential participants who were not recruited and researcher frustration. In this article, the authors explore recruitment issues related to the concept of personal knowing based on experiences with Aboriginal Hawai'ian and Micronesian populations, wherein knowing and being known are crucial to successful recruitment of participants. They present a conceptual model that incorporates key concepts of knowing the other, cultural context, and trust to guide other qualitative transcultural researchers. They also describe challenges, implications, and concrete suggestions for recruitment of participants.

A GIS-based multi-source and multi-box modeling approach (GMSMB) for air pollution assessment--a North American case study.

Science.gov (United States)

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.

Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic.

Science.gov (United States)

Neumayr, Bernd; Schuetz, Christoph G; Jeusfeld, Manfred A; Schrefl, Michael

2018-01-01

An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.

Employing a Qualitative Description Approach in Health Care Research.

Science.gov (United States)

Bradshaw, Carmel; Atkinson, Sandra; Doody, Owen

2017-01-01

A qualitative description design is particularly relevant where information is required directly from those experiencing the phenomenon under investigation and where time and resources are limited. Nurses and midwives often have clinical questions suitable to a qualitative approach but little time to develop an exhaustive comprehension of qualitative methodological approaches. Qualitative description research is sometimes considered a less sophisticated approach for epistemological reasons. Another challenge when considering qualitative description design is differentiating qualitative description from other qualitative approaches. This article provides a systematic and robust journey through the philosophical, ontological, and epistemological perspectives, which evidences the purpose of qualitative description research. Methods and rigor issues underpinning qualitative description research are also appraised to provide the researcher with a systematic approach to conduct research utilizing this approach. The key attributes and value of qualitative description research in the health care professions will be highlighted with the aim of extending its usage.

The Use of Modelling for Theory Building in Qualitative Analysis

Science.gov (United States)

Briggs, Ann R. J.

2007-01-01

The purpose of this article is to exemplify and enhance the place of modelling as a qualitative process in educational research. Modelling is widely used in quantitative research as a tool for analysis, theory building and prediction. Statistical data lend themselves to graphical representation of values, interrelationships and operational…

Modeling multi-lateral wells

Energy Technology Data Exchange (ETDEWEB)

Su, H. J.; Fong, W. S. [Chevron Petroleum Technology Company (United States)

1998-12-31

A method for modeling multi-lateral wells by using a computational scheme embedded in a general-purpose, finite difference simulator was described. The calculation of wellbore pressure profile for each lateral included the frictional pressure drop along the wellbore and proper fluid mixing at lateral connection points. To obtain a good production profile the Beggs and Brill correlation, a homogenous flow model, and the model proposed by Ouyang et al, which includes an acceleration term and accounts for the lubrication effect due to radial influx, were implemented. Well performance prediction results were compared using the three models. The impact of different tubing sizes on the well performance and the prediction contribution from each lateral were also studied. Results of the study in the hypothetical example and under normal field operating conditions were reviewed. 7 refs., 10 tabs., 3 figs.

Integration of Advanced Probabilistic Analysis Techniques with Multi-Physics Models

Energy Technology Data Exchange (ETDEWEB)

Cetiner, Mustafa Sacit; none,; Flanagan, George F. [ORNL; Poore III, Willis P. [ORNL; Muhlheim, Michael David [ORNL

2014-07-30

An integrated simulation platform that couples probabilistic analysis-based tools with model-based simulation tools can provide valuable insights for reactive and proactive responses to plant operating conditions. The objective of this work is to demonstrate the benefits of a partial implementation of the Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Framework Specification through the coupling of advanced PRA capabilities and accurate multi-physics plant models. Coupling a probabilistic model with a multi-physics model will aid in design, operations, and safety by providing a more accurate understanding of plant behavior. This represents the first attempt at actually integrating these two types of analyses for a control system used for operations, on a faster than real-time basis. This report documents the development of the basic communication capability to exchange data with the probabilistic model using Reliability Workbench (RWB) and the multi-physics model using Dymola. The communication pathways from injecting a fault (i.e., failing a component) to the probabilistic and multi-physics models were successfully completed. This first version was tested with prototypic models represented in both RWB and Modelica. First, a simple event tree/fault tree (ET/FT) model was created to develop the software code to implement the communication capabilities between the dynamic-link library (dll) and RWB. A program, written in C#, successfully communicates faults to the probabilistic model through the dll. A systems model of the Advanced Liquid-Metal Reactor–Power Reactor Inherently Safe Module (ALMR-PRISM) design developed under another DOE project was upgraded using Dymola to include proper interfaces to allow data exchange with the control application (ConApp). A program, written in C+, successfully communicates faults to the multi-physics model. The results of the example simulation were successfully plotted.

Multi-Model Estimation Based Moving Object Detection for Aerial Video

Directory of Open Access Journals (Sweden)

Yanning Zhang

2015-04-01

Full Text Available With the wide development of UAV (Unmanned Aerial Vehicle technology, moving target detection for aerial video has become a popular research topic in the computer field. Most of the existing methods are under the registration-detection framework and can only deal with simple background scenes. They tend to go wrong in the complex multi background scenarios, such as viaducts, buildings and trees. In this paper, we break through the single background constraint and perceive the complex scene accurately by automatic estimation of multiple background models. First, we segment the scene into several color blocks and estimate the dense optical flow. Then, we calculate an affine transformation model for each block with large area and merge the consistent models. Finally, we calculate subordinate degree to multi-background models pixel to pixel for all small area blocks. Moving objects are segmented by means of energy optimization method solved via Graph Cuts. The extensive experimental results on public aerial videos show that, due to multi background models estimation, analyzing each pixel’s subordinate relationship to multi models by energy minimization, our method can effectively remove buildings, trees and other false alarms and detect moving objects correctly.

Sustainable Urban Forestry Potential Based Quantitative And Qualitative Measurement Using Geospatial Technique

International Nuclear Information System (INIS)

Rosli, A Z; Reba, M N M; Roslan, N; Room, M H M

2014-01-01

In order to maintain the stability of natural ecosystems around urban areas, urban forestry will be the best initiative to maintain and control green space in our country. Integration between remote sensing (RS) and geospatial information system (GIS) serves as an effective tool for monitoring environmental changes and planning, managing and developing a sustainable urbanization. This paper aims to assess capability of the integration of RS and GIS to provide information for urban forest potential sites based on qualitative and quantitative by using priority parameter ranking in the new township of Nusajaya. SPOT image was used to provide high spatial accuracy while map of topography, landuse, soils group, hydrology, Digital Elevation Model (DEM) and soil series data were applied to enhance the satellite image in detecting and locating present attributes and features on the ground. Multi-Criteria Decision Making (MCDM) technique provides structural and pair wise quantification and comparison elements and criteria for priority ranking for urban forestry purpose. Slope, soil texture, drainage, spatial area, availability of natural resource, and vicinity of urban area are criteria considered in this study. This study highlighted the priority ranking MCDM is cost effective tool for decision-making in urban forestry planning and landscaping

Sustainable Urban Forestry Potential Based Quantitative And Qualitative Measurement Using Geospatial Technique

Science.gov (United States)

Rosli, A. Z.; Reba, M. N. M.; Roslan, N.; Room, M. H. M.

2014-02-01

In order to maintain the stability of natural ecosystems around urban areas, urban forestry will be the best initiative to maintain and control green space in our country. Integration between remote sensing (RS) and geospatial information system (GIS) serves as an effective tool for monitoring environmental changes and planning, managing and developing a sustainable urbanization. This paper aims to assess capability of the integration of RS and GIS to provide information for urban forest potential sites based on qualitative and quantitative by using priority parameter ranking in the new township of Nusajaya. SPOT image was used to provide high spatial accuracy while map of topography, landuse, soils group, hydrology, Digital Elevation Model (DEM) and soil series data were applied to enhance the satellite image in detecting and locating present attributes and features on the ground. Multi-Criteria Decision Making (MCDM) technique provides structural and pair wise quantification and comparison elements and criteria for priority ranking for urban forestry purpose. Slope, soil texture, drainage, spatial area, availability of natural resource, and vicinity of urban area are criteria considered in this study. This study highlighted the priority ranking MCDM is cost effective tool for decision-making in urban forestry planning and landscaping.

Algorithm development and verification of UASCM for multi-dimension and multi-group neutron kinetics model

International Nuclear Information System (INIS)

Si, S.

2012-01-01

The Universal Algorithm of Stiffness Confinement Method (UASCM) for neutron kinetics model of multi-dimensional and multi-group transport equations or diffusion equations has been developed. The numerical experiments based on transport theory code MGSNM and diffusion theory code MGNEM have demonstrated that the algorithm has sufficient accuracy and stability. (authors)

Attribution Theory and Crisis Intervention Therapy.

Science.gov (United States)

Skilbeck, William M.

It was proposed that existing therapeutic procedures may influence attributions about emotional states. Therefore an attributional analysis of crisis intervention, a model of community-based, short-term consultation, was presented. This analysis suggested that crisis intervention provides attributionally-relevant information about both the source…

Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

Science.gov (United States)

Yang, Qiu

Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.

The learner’s perspective in GP teaching practices with multi-level learners: a qualitative study

Science.gov (United States)

2014-01-01

Background Medical students, junior hospital doctors on rotation and general practice (GP) registrars are undertaking their training in clinical general practices in increasing numbers in Australia. Some practices have four levels of learner. This study aimed to explore how multi-level teaching (also called vertical integration of GP education and training) is occurring in clinical general practice and the impact of such teaching on the learner. Methods A qualitative research methodology was used with face-to-face, semi-structured interviews of medical students, junior hospital doctors, GP registrars and GP teachers in eight training practices in the region that taught all levels of learners. Interviews were audio-recorded and transcribed. Qualitative analysis was conducted using thematic analysis techniques aided by the use of the software package N-Vivo 9. Primary themes were identified and categorised by the co-investigators. Results 52 interviews were completed and analysed. Themes were identified relating to both the practice learning environment and teaching methods used. A practice environment where there is a strong teaching culture, enjoyment of learning, and flexible learning methods, as well as learning spaces and organised teaching arrangements, all contribute to positive learning from a learners’ perspective. Learners identified a number of innovative teaching methods and viewed them as positive. These included multi-level learner group tutorials in the practice, being taught by a team of teachers, including GP registrars and other health professionals, and access to a supernumerary GP supervisor (also termed “GP consultant teacher”). Other teaching methods that were viewed positively were parallel consulting, informal learning and rural hospital context integrated learning. Conclusions Vertical integration of GP education and training generally impacted positively on all levels of learner. This research has provided further evidence about the

Visualization of Spatio-Temporal Relations in Movement Event Using Multi-View

Science.gov (United States)

Zheng, K.; Gu, D.; Fang, F.; Wang, Y.; Liu, H.; Zhao, W.; Zhang, M.; Li, Q.

2017-09-01

Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

VISUALIZATION OF SPATIO-TEMPORAL RELATIONS IN MOVEMENT EVENT USING MULTI-VIEW

Directory of Open Access Journals (Sweden)

K. Zheng

2017-09-01

Full Text Available Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

Multi-Valued Modal Fixed Point Logics for Model Checking

Science.gov (United States)

Nishizawa, Koki

In this paper, I will show how multi-valued logics are used for model checking. Model checking is an automatic technique to analyze correctness of hardware and software systems. A model checker is based on a temporal logic or a modal fixed point logic. That is to say, a system to be checked is formalized as a Kripke model, a property to be satisfied by the system is formalized as a temporal formula or a modal formula, and the model checker checks that the Kripke model satisfies the formula. Although most existing model checkers are based on 2-valued logics, recently new attempts have been made to extend the underlying logics of model checkers to multi-valued logics. I will summarize these new results.

Application of the Multi-Attribute Value Theory for engaging stakeholders in groundwater protection in the Vosvozis catchment in Greece.

Science.gov (United States)

Stefanopoulos, Kyriakos; Yang, Hong; Gemitzi, Alexandra; Tsagarakis, Konstantinos P

2014-02-01

Multi-Attribute Value Theory (MAVT) was used to investigate stakeholders' preferences and beliefs in ameliorating a deteriorating ecosystem, i.e. Vosvozis River and Ismarida Lake in Northeastern Greece. Various monetary and environmental criteria were evaluated with scores and weights by different stakeholder groups and key individuals such as farmers, fishermen, entrepreneurs, residents and ecologists to elicit their preferences concerning alternative protection scenarios. The ultimate objective was to propose policy recommendations for a sustainable water resources management for the case study area. The analysis revealed an overwhelming agreement among stakeholders regarding the dire need for immediate actions in order to preserve and enhance Vosvozis ecosystem. With a two stage evaluation process, the MAVT analysis led to a high consensus among the stakeholders on the alternative that favors water recycling from the wastewater treatment plant combined with small dams for rainwater harvesting. © 2013.

Perceptual attributes for the comparison of head-related transfer functions.

Science.gov (United States)

Simon, Laurent S R; Zacharov, Nick; Katz, Brian F G

2016-11-01

The benefit of using individual head-related transfer functions (HRTFs) in binaural audio is well documented with regards to improving localization precision. However, with the increased use of binaural audio in more complex scene renderings, cognitive studies, and virtual and augmented reality simulations, the perceptual impact of HRTF selection may go beyond simple localization. In this study, the authors develop a list of attributes which qualify the perceived differences between HRTFs, providing a qualitative understanding of the perceptual variance of non-individual binaural renderings. The list of attributes was designed using a Consensus Vocabulary Protocol elicitation method. Participants followed an Individual Vocabulary Protocol elicitation procedure, describing the perceived differences between binaural stimuli based on binauralized extracts of multichannel productions. This was followed by an automated lexical reduction and a series of consensus group meetings during which participants agreed on a list of relevant attributes. Finally, the proposed list of attributes was then evaluated through a listening test, leading to eight valid perceptual attributes for describing the perceptual dimensions affected by HRTF set variations.

Multi-Model Assessment of Trends and Variability in Terrestrial Carbon Uptake in India

Science.gov (United States)

Rao, A. S.; Bala, G.; Ravindranath, N. H.

2015-12-01

Indian terrestrial ecosystem exhibits large temporal and spatial variability in carbon sources and sinks due to its monsoon based climate system, diverse land use and land cover distribution and cultural practices. In this study, a multi-model based assessment is made to study the trends and variability in the land carbon uptake for India over the 20th century. Data from nine models which are a part of a recent land surface model intercomparison project called TRENDY is used for the study. These models are driven with common forcing data over the period of 1901-2010. Model output variables assessed include: gross primary production (GPP), heterotrophic respiration (Rh), autotrophic respiration (Ra) and net primary production (NPP). The net ecosystem productivity (NEP) for the Indian region was calculated as a difference of NPP and Rh and it was found that NEP for the region indicates an estimated increase in uptake over the century by -0.6 TgC/year per year. NPP for India also shows an increasing trend of 2.03% per decade from 1901-2010. Seasonal variation in the multimodel mean NPP is maximum during the southwest monsoon period (JJA) followed by the post monsoon period (SON) and is attributed to the maximum in rainfall for the region during the months of JJA. To attribute the changes seen in the land carbon variables, influence of climatic drivers such as precipitation, temperature and remote influences of large scale phenomenon such as ENSO on the land carbon of the region are also estimated in the study. It is found that although changes in precipitation shows a good correlation to the changes seen in NEP, remote drivers like ENSO do not have much effect on them. The Net Ecosystem Exchange is calculated with the inclusion of the land use change flux and fire flux from the models. NEE suggests that the region behaves as a small sink for carbon with an net uptake of 5 GtC over the past hundred years.

AI/OR computational model for integrating qualitative and quantitative design methods

Science.gov (United States)

Agogino, Alice M.; Bradley, Stephen R.; Cagan, Jonathan; Jain, Pramod; Michelena, Nestor

1990-01-01

A theoretical framework for integrating qualitative and numerical computational methods for optimally-directed design is described. The theory is presented as a computational model and features of implementations are summarized where appropriate. To demonstrate the versatility of the methodology we focus on four seemingly disparate aspects of the design process and their interaction: (1) conceptual design, (2) qualitative optimal design, (3) design innovation, and (4) numerical global optimization.

Importance-truncated shell model for multi-shell valence spaces

Energy Technology Data Exchange (ETDEWEB)

Stumpf, Christina; Vobig, Klaus; Roth, Robert [Institut fuer Kernphysik, TU Darmstadt (Germany)

2016-07-01

The valence-space shell model is one of the work horses in nuclear structure theory. In traditional applications, shell-model calculations are carried out using effective interactions constructed in a phenomenological framework for rather small valence spaces, typically spanned by one major shell. We improve on this traditional approach addressing two main aspects. First, we use new effective interactions derived in an ab initio approach and, thus, establish a connection to the underlying nuclear interaction providing access to single- and multi-shell valence spaces. Second, we extend the shell model to larger valence spaces by applying an importance-truncation scheme based on a perturbative importance measure. In this way, we reduce the model space to the relevant basis states for the description of a few target eigenstates and solve the eigenvalue problem in this physics-driven truncated model space. In particular multi-shell valence spaces are not tractable otherwise. We combine the importance-truncated shell model with refined extrapolation schemes to approximately recover the exact result. We present first results obtained in the importance-truncated shell model with the newly derived ab initio effective interactions for multi-shell valence spaces, e.g., the sdpf shell.

A rough multi-factor model of electricity spot prices

International Nuclear Information System (INIS)

Bennedsen, Mikkel

2017-01-01

We introduce a new continuous-time mathematical model of electricity spot prices which accounts for the most important stylized facts of these time series: seasonality, spikes, stochastic volatility, and mean reversion. Empirical studies have found a possible fifth stylized fact, roughness, and our approach explicitly incorporates this into the model of the prices. Our setup generalizes the popular Ornstein–Uhlenbeck-based multi-factor framework of and allows us to perform statistical tests to distinguish between an Ornstein–Uhlenbeck-based model and a rough model. Further, through the multi-factor approach we account for seasonality and spikes before estimating – and making inference on – the degree of roughness. This is novel in the literature and we present simulation evidence showing that these precautions are crucial for accurate estimation. Lastly, we estimate our model on recent data from six European energy exchanges and find statistical evidence of roughness in five out of six markets. As an application of our model, we show how, in these five markets, a rough component improves short term forecasting of the prices. - Highlights: • Statistical modeling of electricity spot prices • Multi-factor decomposition • Roughness • Electricity price forecasting

Ein dynamisches Multi-Akteurs-Modell zur integrierten Bewertung des Klimawandels

OpenAIRE

Weber, M.

2004-01-01

The interactions between climate and the socio-economic system are investigated with a Multi-Actor Dynamic Integrated Assessment Model (MADIAM) obtained by coupling a nonlinear impulse response model of the climate sub-system (NICCS) to a multi-actor dynamic economic model (MADEM). The main goal is to initiate a model development that is able to treat the dynamics of the coupled climate socio-economic system, including endogenous technological change, in a non-equilibrium situation, thereby o...

Attributes of Lifestyle Consumer Related to the Use of Organic Products Retail Specialist

Directory of Open Access Journals (Sweden)

Sergio Silva Braga Junior

2014-11-01

Full Text Available To evaluate the relationship between attributes of lifestyle and consumption of organic products in specialty retail, this research sought to understand who the consumer of organic products in specialty retail. To serve this purpose, a field survey of qualitative and quantitative nature was conducted with a sample of 60 subjects covered at the time of purchase at a grocery store specializing in organic products in the city of São Paulo/SP. To justify the sample size G*Power 3.1.7 software with the specifications recommended in the literature. The collected sample was sufficient to detect the desired effects of Structural Equation Modeling with Partial Least Squares Method (Partial Least Square - PLS. As a result it was observed that consumers of organic produce state to adopt a healthy lifestyle and attributed the following determinants for buying organic produce factors: the quality and the benefits that accrue to the same health. 

Evaluation of infectious diseases and clinical microbiology specialists' preferences for hand hygiene: analysis using the multi-attribute utility theory and the analytic hierarchy process methods.

Science.gov (United States)

Suner, Aslı; Oruc, Ozlem Ege; Buke, Cagri; Ozkaya, Hacer Deniz; Kitapcioglu, Gul

2017-08-31

Hand hygiene is one of the most effective attempts to control nosocomial infections, and it is an important measure to avoid the transmission of pathogens. However, the compliance of healthcare workers (HCWs) with hand washing is still poor worldwide. Herein, we aimed to determine the best hand hygiene preference of the infectious diseases and clinical microbiology (IDCM) specialists to prevent transmission of microorganisms from one patient to another. Expert opinions regarding the criteria that influence the best hand hygiene preference were collected through a questionnaire via face-to-face interviews. Afterwards, these opinions were examined with two widely used multi-criteria decision analysis (MCDA) methods, the Multi-Attribute Utility Theory (MAUT) and the Analytic Hierarchy Process (AHP). A total of 15 IDCM specialist opinions were collected from diverse private and public hospitals located in İzmir, Turkey. The mean age of the participants was 49.73 ± 8.46, and the mean experience year of the participants in their fields was 17.67 ± 11.98. The findings that we obtained through two distinct decision making methods, the MAUT and the AHP, suggest that alcohol-based antiseptic solution (ABAS) has the highest utility (0.86) and priority (0.69) among the experts' choices. In conclusion, the MAUT and the AHP, decision models developed here indicate that rubbing the hands with ABAS is the most favorable choice for IDCM specialists to prevent nosocomial infection.

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

Science.gov (United States)

Kou, Jisheng; Sun, Shuyu

2016-08-01

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

KAUST Repository

Kou, Jisheng

2016-05-10

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

Determinants attributes in purchase decision: a study in establishments commercialize street food

Directory of Open Access Journals (Sweden)

Hannah Nicchio Loriato

2017-01-01

Full Text Available The attributes of a product can vary greatly in the importance they have for different consumers, and from the idea that there are different degrees of importance in relation to the attributes and importance that influence the buying decision. The purpose of this study is to identify which attributes are crucial for consumers in making buying decisions in establishments that sell street food. It is a study of both qualitative and quantitative nature. In the qualitative phase was conducted semi-structured interviews with 16 customers and analyzed using content analysis.It was carried out one survey, applying 200 questionnaires, to survey data for quantitative phase . The analysis of this quantitative phase was carried out using Excel and SPSS, with the use of multivariate statistical techniques. The results indicated that the service offered is the construct considered crucial to the customers' buying decision. In addition, this study enables the spread of this research scope in the country and contributes to the entrepreneurs in the street food sector seeking strategies to keep themselves firmly in the market.

Multi-infill strategy for kriging models used in variable fidelity optimization

Directory of Open Access Journals (Sweden)

Chao SONG

2018-03-01

Full Text Available In this paper, a computationally efficient optimization method for aerodynamic design has been developed. The low-fidelity model and the multi-infill strategy are utilized in this approach. Low-fidelity data is employed to provide a good global trend for model prediction, and multiple sample points chosen by different infill criteria in each updating cycle are used to enhance the exploitation and exploration ability of the optimization approach. Take the advantages of low-fidelity model and the multi-infill strategy, and no initial sample for the high-fidelity model is needed. This approach is applied to an airfoil design case and a high-dimensional wing design case. It saves a large number of high-fidelity function evaluations for initial model construction. What’s more, faster reduction of an aerodynamic function is achieved, when compared to ordinary kriging using the multi-infill strategy and variable-fidelity model using single infill criterion. The results indicate that the developed approach has a promising application to efficient aerodynamic design when high-fidelity analyses are involved. Keywords: Aerodynamics, Infill criteria, Kriging models, Multi-infill, Optimization

Employing a Qualitative Description Approach in Health Care Research

Science.gov (United States)

Bradshaw, Carmel; Atkinson, Sandra; Doody, Owen

2017-01-01

A qualitative description design is particularly relevant where information is required directly from those experiencing the phenomenon under investigation and where time and resources are limited. Nurses and midwives often have clinical questions suitable to a qualitative approach but little time to develop an exhaustive comprehension of qualitative methodological approaches. Qualitative description research is sometimes considered a less sophisticated approach for epistemological reasons. Another challenge when considering qualitative description design is differentiating qualitative description from other qualitative approaches. This article provides a systematic and robust journey through the philosophical, ontological, and epistemological perspectives, which evidences the purpose of qualitative description research. Methods and rigor issues underpinning qualitative description research are also appraised to provide the researcher with a systematic approach to conduct research utilizing this approach. The key attributes and value of qualitative description research in the health care professions will be highlighted with the aim of extending its usage. PMID:29204457

A fuzzy model for achieving lean attributes for competitive advantages development using AHP-QFD-PROMETHEE

Science.gov (United States)

Roghanian, E.; Alipour, Mohammad

2014-06-01

Lean production has become an integral part of the manufacturing landscape as its link with superior performance and its ability to provide competitive advantage is well accepted among academics and practitioners. Lean production helps producers in overcoming the challenges organizations face through using powerful tools and enablers. However, most companies are faced with restricted resources such as financial and human resources, time, etc., in using these enablers, and are not capable of implementing all these techniques. Therefore, identifying and selecting the most appropriate and efficient tool can be a significant challenge for many companies. Hence, this literature seeks to combine competitive advantages, lean attributes, and lean enablers to determine the most appropriate enablers for improvement of lean attributes. Quality function deployment in fuzzy environment and house of quality matrix are implemented. Throughout the methodology, fuzzy logic is the basis for translating linguistic judgments required for the relationships and correlation matrix to numerical values. Moreover, for final ranking of lean enablers, a multi-criteria decision-making method (PROMETHEE) is adopted. Finally, a case study in automotive industry is presented to illustrate the implementation of the proposed methodology.

Barriers and Facilitators for Health Behavior Change among Adults from Multi-Problem Households: A Qualitative Study

Directory of Open Access Journals (Sweden)

Gera E. Nagelhout

2017-10-01

Full Text Available Multi-problem households are households with problems on more than one of the following core problem areas: socio-economic problems, psycho-social problems, and problems related to child care. The aim of this study was to examine barriers and facilitators for health behavior change among adults from multi-problem households, as well as to identify ideas for a health promotion program. A qualitative study involving 25 semi-structured interviews was conducted among Dutch adults who received intensive family home care for multi-problem households. Results were discussed with eight social workers in a focus group interview. Data were analyzed using the Framework Method. The results revealed that the main reason for not engaging in sports were the costs. Physical activity was facilitated by physically active (transport to work and by dog ownership. Respondents who received a food bank package reported this as a barrier for healthy eating. Those with medical conditions such as diabetes indicated that this motivated them to eat healthily. Smokers and former smokers reported that stress was a major barrier for quitting smoking but that medical conditions could motivate them to quit smoking. A reported reason for not using alcohol was having difficult past experiences such as violence and abuse by alcoholics. Mentioned intervention ideas were: something social, an outdoor sports event, cooking classes, a walking group, and children’s activities in nature. Free or cheap activities that include social interaction and reduce stress are in line with the identified barriers and facilitators. Besides these activities, it may be important to influence the target group’s environment by educating social workers and ensuring healthier food bank packages.

1H NMR metabolic fingerprinting to probe temporal postharvest changes on qualitative attributes and phytochemical profile of sweet cherry fruit

Directory of Open Access Journals (Sweden)

Vlasios eGoulas

2015-11-01

Full Text Available Sweet cherry fruits (Prunus avium cvs. ‘Canada Giant’, ‘Ferrovia’ were harvested at commercial maturity stage and analyzed at harvest and after maintenance at room temperature (storage at ~ 20°C, shelf life for 1, 2, 4, 6 and 8 days, respectively. Fruit were initially analyzed for respiration rate, qualitative attributes and textural properties: ‘Canada Giant’ fruit were characterized by higher weight losses and stem browning index, being more intense over the late stages of shelf life period; meanwhile ‘Ferrovia’ possessed appreciably better performance even after extended shelf life period. A gradual decrease of respiration rate was monitored in both cultivars, culminated after 8 days at 20°C. The sweet cherry fruit nutraceutical profile was monitored using an array of instrumental techniques (spectrophotometric assays, HPLC, 1H-NMR. Fruit antioxidant capacity was enhanced with the progress of shelf life period, concomitant with the increased levels of total anthocyanin and of phenolic compounds. ‘Ferrovia’ fruit presented higher contents of neochlorogenic acid and p-coumarolquinic acid throughout the shelf life period. We further developed an 1H-NMR method that allows the study of primary and secondary metabolites in a single running, without previous separation and isolation procedures. Diagnostic peaks were located in the aliphatic region for sugars and organic acids, in the aromatic region for phenolic compounds and at 8.2 to 8.6 ppm for anthocyanins. This NMR-based methodology provides a unifying tool for quantitative and qualitative characterization of metabolite changes of sweet cherry fruits; it is also expected to be further exploited for monitoring temporal changes in other fleshy fruits.

1H NMR Metabolic Fingerprinting to Probe Temporal Postharvest Changes on Qualitative Attributes and Phytochemical Profile of Sweet Cherry Fruit

Science.gov (United States)

Goulas, Vlasios; Minas, Ioannis S.; Kourdoulas, Panayiotis M.; Lazaridou, Athina; Molassiotis, Athanassios N.; Gerothanassis, Ioannis P.; Manganaris, George A.

2015-01-01

Sweet cherry fruits (Prunus avium cvs. ‘Canada Giant’, ‘Ferrovia’) were harvested at commercial maturity stage and analyzed at harvest and after maintenance at room temperature (storage at ∼20°C, shelf life) for 1, 2, 4, 6, and 8 days, respectively. Fruit were initially analyzed for respiration rate, qualitative attributes and textural properties: ‘Canada Giant’ fruit were characterized by higher weight losses and stem browning index, being more intense over the late stages of shelf life period; meanwhile ‘Ferrovia’ possessed appreciably better performance even after extended shelf life period. A gradual decrease of respiration rate was monitored in both cultivars, culminated after 8 days at 20°C. The sweet cherry fruit nutraceutical profile was monitored using an array of instrumental techniques (spectrophotometric assays, HPLC, 1H-NMR). Fruit antioxidant capacity was enhanced with the progress of shelf life period, concomitant with the increased levels of total anthocyanin and of phenolic compounds. ‘Ferrovia’ fruit presented higher contents of neochlorogenic acid and p-coumaroylquinic acid throughout the shelf life period. We further developed an 1H-NMR method that allows the study of primary and secondary metabolites in a single running, without previous separation and isolation procedures. Diagnostic peaks were located in the aliphatic region for sugars and organic acids, in the aromatic region for phenolic compounds and at 8.2–8.6 ppm for anthocyanins. This NMR-based methodology provides a unifying tool for quantitative and qualitative characterization of metabolite changes of sweet cherry fruits; it is also expected to be further exploited for monitoring temporal changes in other fleshy fruits. PMID:26617616

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

International Nuclear Information System (INIS)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A.

2009-01-01

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

Energy Technology Data Exchange (ETDEWEB)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A. [Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta (Canada)

2009-01-15

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle. (author)

Multi-dimensional database design and implementation of dam safety monitoring system

Directory of Open Access Journals (Sweden)

Zhao Erfeng

2008-09-01

Full Text Available To improve the effectiveness of dam safety monitoring database systems, the development process of a multi-dimensional conceptual data model was analyzed and a logic design was achieved in multi-dimensional database mode. The optimal data model was confirmed by identifying data objects, defining relations and reviewing entities. The conversion of relations among entities to external keys and entities and physical attributes to tables and fields was interpreted completely. On this basis, a multi-dimensional database that reflects the management and analysis of a dam safety monitoring system on monitoring data information has been established, for which factual tables and dimensional tables have been designed. Finally, based on service design and user interface design, the dam safety monitoring system has been developed with Delphi as the development tool. This development project shows that the multi-dimensional database can simplify the development process and minimize hidden dangers in the database structure design. It is superior to other dam safety monitoring system development models and can provide a new research direction for system developers.

State-of-the-Art Report on Multi-scale Modelling of Nuclear Fuels

International Nuclear Information System (INIS)

Bartel, T.J.; Dingreville, R.; Littlewood, D.; Tikare, V.; Bertolus, M.; Blanc, V.; Bouineau, V.; Carlot, G.; Desgranges, C.; Dorado, B.; Dumas, J.C.; Freyss, M.; Garcia, P.; Gatt, J.M.; Gueneau, C.; Julien, J.; Maillard, S.; Martin, G.; Masson, R.; Michel, B.; Piron, J.P.; Sabathier, C.; Skorek, R.; Toffolon, C.; Valot, C.; Van Brutzel, L.; Besmann, Theodore M.; Chernatynskiy, A.; Clarno, K.; Gorti, S.B.; Radhakrishnan, B.; Devanathan, R.; Dumont, M.; Maugis, P.; El-Azab, A.; Iglesias, F.C.; Lewis, B.J.; Krack, M.; Yun, Y.; Kurata, M.; Kurosaki, K.; Largenton, R.; Lebensohn, R.A.; Malerba, L.; Oh, J.Y.; Phillpot, S.R.; Tulenko, J. S.; Rachid, J.; Stan, M.; Sundman, B.; Tonks, M.R.; Williamson, R.; Van Uffelen, P.; Welland, M.J.; Valot, Carole; Stan, Marius; Massara, Simone; Tarsi, Reka

2015-10-01

The Nuclear Science Committee (NSC) of the Nuclear Energy Agency (NEA) has undertaken an ambitious programme to document state-of-the-art of modelling for nuclear fuels and structural materials. The project is being performed under the Working Party on Multi-Scale Modelling of Fuels and Structural Material for Nuclear Systems (WPMM), which has been established to assess the scientific and engineering aspects of fuels and structural materials, describing multi-scale models and simulations as validated predictive tools for the design of nuclear systems, fuel fabrication and performance. The WPMM's objective is to promote the exchange of information on models and simulations of nuclear materials, theoretical and computational methods, experimental validation and related topics. It also provides member countries with up-to-date information, shared data, models, and expertise. The goal is also to assess needs for improvement and address them by initiating joint efforts. The WPMM reviews and evaluates multi-scale modelling and simulation techniques currently employed in the selection of materials used in nuclear systems. It serves to provide advice to the nuclear community on the developments needed to meet the requirements of modelling for the design of different nuclear systems. The original WPMM mandate had three components (Figure 1), with the first component currently completed, delivering a report on the state-of-the-art of modelling of structural materials. The work on modelling was performed by three expert groups, one each on Multi-Scale Modelling Methods (M3), Multi-Scale Modelling of Fuels (M2F) and Structural Materials Modelling (SMM). WPMM is now composed of three expert groups and two task forces providing contributions on multi-scale methods, modelling of fuels and modelling of structural materials. This structure will be retained, with the addition of task forces as new topics are developed. The mandate of the Expert Group on Multi-Scale Modelling of

Qualitative and Quantitative Evaluation of Multi-source Piroxicam ...

African Journals Online (AJOL)

The qualitative and quantitative evaluation of eleven brands of piroxicam capsules marketed in Nigeria is presented. The disintegration time, dissolution rate and absolute drug content were determined in simulated intestinal fluid (SIF) and simulated gastric fluid (SGF) without enzymes. Weight uniformity test was also ...

Disaster Reintegration Model: A Qualitative Analysis on Developing Korean Disaster Mental Health Support Model

Directory of Open Access Journals (Sweden)

Yun-Jung Choi

2018-02-01

Full Text Available This study sought to describe the mental health problems experienced by Korean disaster survivors, using a qualitative research method to provide empirical resources for effective disaster mental health support in Korea. Participants were 16 adults or elderly adults who experienced one or more disasters at least 12 months ago recruited via theoretical sampling. Participants underwent in-depth individual interviews on their disaster experiences, which were recorded and transcribed for qualitative analysis, which followed Strauss and Corbin’s (1998 Grounded theory. After open coding, participants’ experiences were categorized into 130 codes, 43 sub-categories and 17 categories. The categories were further analyzed in a paradigm model, conditional model and the Disaster Reintegration Model, which proposed potentially effective mental health recovery strategies for disaster survivors, health providers and administrators. To provide effective assistance for mental health recovery of disaster survivors, both personal and public resilience should be promoted while considering both cultural and spiritual elements.

Structural interpretations of deformation and fracture behavior of polypropylene/multi-walled carbon nanotube composites

International Nuclear Information System (INIS)

Ganss, Martin; Satapathy, Bhabani K.; Thunga, Mahendra; Weidisch, Roland; Poetschke, Petra; Jehnichen, Dieter

2008-01-01

The deformation and crack resistance behavior of polypropylene (PP) multi-walled carbon nanotube (MWNT) composites have been studied and their interrelation to the structural attributes studied by transmission electron microscopy (TEM), atomic force microscopy (AFM), scanning electron microscopy (SEM), wide-angle X-ray diffraction (WAXD), differential scanning calorimetry (DSC) and polarization light microscopy has been discussed. The composites were produced from industrial available MWNT by extrusion melt-mixing and injection-molding. In stress-strain measurements a strong increase in the yield stress and the Young's modulus at low MWNT contents has been observed, which was attributed to an efficient load transfer between the carbon nanotubes and polypropylene matrix through a good polymer-nanotube adhesion as indicated by SEM. The extent of enhancement in mechanical properties above 1.5 wt.% of MWNT decreased due to an apparently increased tendency of clustering of carbon nanotubes. Several theoretical models have been taken into account to explain the mechanical properties and to demonstrate the applicability of such models to the system under investigation. The crack resistance behavior has been studied with the essential work of fracture (EWF) approach based on post-yield fracture mechanics (PYFM) concept. A maximum in the non-essential work of fracture was observed at 0.5 wt.% MWNT demonstrating enhanced toughness compared to pure PP, followed by a sharp decline as the MWNT content was increased to 1.5 wt.% reveals a ductile-to-semi-ductile transition. Studies on the kinetics of crack propagation aspects have revealed a qualitative picture of the nature of such a transition in the fracture modes

Error detection in GPS observations by means of Multi-process models

DEFF Research Database (Denmark)

Thomsen, Henrik F.

2001-01-01

The main purpose of this article is to present the idea of using Multi-process models as a method of detecting errors in GPS observations. The theory behind Multi-process models, and double differenced phase observations in GPS is presented shortly. It is shown how to model cycle slips in the Mul...

Modeling activity recognition of multi resident using label combination of multi label classification in smart home

Science.gov (United States)

Mohamed, Raihani; Perumal, Thinagaran; Sulaiman, Md Nasir; Mustapha, Norwati; Zainudin, M. N. Shah

2017-10-01

Pertaining to the human centric concern and non-obtrusive way, the ambient sensor type technology has been selected, accepted and embedded in the environment in resilient style. Human activities, everyday are gradually becoming complex and thus complicate the inferences of activities when it involving the multi resident in the same smart environment. Current works solutions focus on separate model between the resident, activities and interactions. Some study use data association and extra auxiliary of graphical nodes to model human tracking information in an environment and some produce separate framework to incorporate the auxiliary for interaction feature model. Thus, recognizing the activities and which resident perform the activity at the same time in the smart home are vital for the smart home development and future applications. This paper will cater the above issue by considering the simplification and efficient method using the multi label classification framework. This effort eliminates time consuming and simplifies a lot of pre-processing tasks comparing with previous approach. Applications to the multi resident multi label learning in smart home problems shows the LC (Label Combination) using Decision Tree (DT) as base classifier can tackle the above problems.

A procurement decision support mechanism on multi-attribute fuzzy-interval auctions

DEFF Research Database (Denmark)

Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt

2016-01-01

Procurement systems are the basis for assuring efficiency and fairness in organizations. Consequently, the development of procurement systems faces an ongoing challenge in designing trading systems that facilitate transparent competition on both price and multiple attributes, as well as ensuring...

COGNITIVE MODELING AS A METHOD OF QUALITATIVE ANALYSIS OF IT PROJECTS

Directory of Open Access Journals (Sweden)

Інна Ігорівна ОНИЩЕНКО

2016-03-01

Full Text Available The example project implementing automated CRM-system demonstrated the possibility and features of cognitive modeling in the qualitative analysis of project risks to determine their additional features. Proposed construction of cognitive models of project risks in information technology within the qualitative risk analysis, additional assessments as a method of ranking risk to characterize the relationship between them. The proposed cognitive model reflecting the relationship between the risk of IT project to assess the negative and the positive impact of certain risks for the remaining risks of project implementation of the automated CRM-system. The ability to influence the risk of a fact of other project risks can increase the priority of risk with low impact on results due to its relationship with other project risks.