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Sample records for hybrid decision approach

  1. A decision support system based on hybrid knowledge approach for nuclear power plant operation

    International Nuclear Information System (INIS)

    Yang, J.O.; Chang, S.H.

    1991-01-01

    This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. Frames and rules are adopted to represent the various knowledge types. Rule-based deduction and abduction are used for shallow and deep knowledge based reasoning respectively. The event-based operational guidelines are provided to the operator according to the diagnosed results

  2. A hybrid life cycle and multi-criteria decision analysis approach for identifying sustainable development strategies of Beijing's taxi fleet

    International Nuclear Information System (INIS)

    Cai, Yanpeng; Applegate, Scott; Yue, Wencong; Cai, Jianying; Wang, Xuan; Liu, Gengyuan; Li, Chunhui

    2017-01-01

    To identify and evaluate sustainable strategies of taxi fleet in Beijing in terms of economic, policy, and environmental implications, a hybrid approach was developed through incorporating multi-criteria decision analysis (MCDA) methods within a general life-cycle analysis (LCA) framework. The approach can (a) help comprehensive evaluate environmental impacts of multiple types of vehicles, (b) facilitate analysis of environmental, economic and policy features of such vehicles, and (c) identify desirable taxi fleet development strategies for the city. The developed approach represented an improvement of the decision-making capability for taxi implementation based on multiple available technologies and their performance that can be specifically tailored to Beijing. The results demonstrated that the proposed approach could comprehensively reflect multiple implications of strategies for the taxi fleet in Beijing to reduce air pollution in the city. The results also indicated that the electric vehicle powered with the year 2020 electricity projections would be the ideal solution, outranking the other alternatives. The conventional vehicle ranked the lowest among the alternatives. The plug-in hybrid vehicle powered by 2020 electricity projects ranked the third, followed by the plug-in hybrid vehicle ranking the fourth, and the hybrid vehicle ranking the fifth. - Highlights: • An hybrid approach was proposed for evaluating sustainable strategies of Beijing's taxi fleet. • This approach was based on the combination of multi-criteria decision analysis methods and life-cycle assessment. • Environmental, economic and policy performances of multiple strategies were compared. • Detailed responses of taxi drivers and local residents were interviewed. • The electric vehicle would be the ideal solution for Beijing Taxi fleet.

  3. A hybrid approach to decision making and information fusion: Combining humans and artificial agents

    NARCIS (Netherlands)

    Groen, Frans C.A.; Pavlin, Gregor; Winterboer, Andi; Evers, Vanessa

    This paper argues that hybrid human–agent systems can support powerful solutions to relevant problems such as Environmental Crisis management. However, it shows that such solutions require comprehensive approaches covering different aspects of data processing, model construction and the usage. In

  4. Hybrid approach for the assessment of PSA models by means of binary decision diagrams

    International Nuclear Information System (INIS)

    Ibanez-Llano, Cristina; Rauzy, Antoine; Melendez, Enrique; Nieto, Francisco

    2010-01-01

    Binary decision diagrams are a well-known alternative to the minimal cutsets approach to assess the reliability Boolean models. They have been applied successfully to improve the fault trees models assessment. However, its application to solve large models, and in particular the event trees coming from the PSA studies of the nuclear industry, remains to date out of reach of an exact evaluation. For many real PSA models it may be not possible to compute the BDD within reasonable amount of time and memory without considering the truncation or simplification of the model. This paper presents a new approach to estimate the exact probabilistic quantification results (probability/frequency) based on combining the calculation of the MCS and the truncation limits, with the BDD approach, in order to have a better control on the reduction of the model and to properly account for the success branches. The added value of this methodology is that it is possible to ensure a real confidence interval of the exact value and therefore an explicit knowledge of the error bound. Moreover, it can be used to measure the acceptability of the results obtained with traditional techniques. The new method was applied to a real life PSA study and the results obtained confirm the applicability of the methodology and open a new viewpoint for further developments.

  5. Hybrid approach for the assessment of PSA models by means of binary decision diagrams

    Energy Technology Data Exchange (ETDEWEB)

    Ibanez-Llano, Cristina, E-mail: cristina.ibanez@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain); Rauzy, Antoine, E-mail: Antoine.RAUZY@3ds.co [Dassault Systemes, 10 rue Marcel Dassault CS 40501, 78946 Velizy Villacoublay Cedex (France); Melendez, Enrique, E-mail: ema@csn.e [Consejo de Seguridad Nuclear (CSN), C/Justo Dorado 11, 28040 Madrid (Spain); Nieto, Francisco, E-mail: nieto@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain)

    2010-10-15

    Binary decision diagrams are a well-known alternative to the minimal cutsets approach to assess the reliability Boolean models. They have been applied successfully to improve the fault trees models assessment. However, its application to solve large models, and in particular the event trees coming from the PSA studies of the nuclear industry, remains to date out of reach of an exact evaluation. For many real PSA models it may be not possible to compute the BDD within reasonable amount of time and memory without considering the truncation or simplification of the model. This paper presents a new approach to estimate the exact probabilistic quantification results (probability/frequency) based on combining the calculation of the MCS and the truncation limits, with the BDD approach, in order to have a better control on the reduction of the model and to properly account for the success branches. The added value of this methodology is that it is possible to ensure a real confidence interval of the exact value and therefore an explicit knowledge of the error bound. Moreover, it can be used to measure the acceptability of the results obtained with traditional techniques. The new method was applied to a real life PSA study and the results obtained confirm the applicability of the methodology and open a new viewpoint for further developments.

  6. Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

    Science.gov (United States)

    Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

    2018-06-01

    Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. A Hybrid Multiple-Criteria Decision-Making Approach for Photovoltaic Solar Plant Location Selection

    Directory of Open Access Journals (Sweden)

    Amy H. I. Lee

    2017-01-01

    Full Text Available Due to decaying fossil resource and increasing environmental consciousness, the demand of renewable energy resources is escalating these days. Photovoltaic solar energy is one of the most popular renewable energy resources in places where sunlight is abundant. The selection of a desirable location for constructing a photovoltaic solar plant is the first and one of the most important stages in the plant construction to provide a long-term energy production. In this paper, a comprehensive multiple-criteria decision-making model, which incorporates the interpretive structural modeling (ISM, fuzzy analytic network process (FANP and VIKOR (VlseKriterijumska OptimizacijaI Kompromisno Resenje in Serbian,meaning multi-criteria optimization and compromise solution, is proposed to select the most suitable photovoltaic solar plant location. The ISM is applied first to determine the interrelationships among the criteria and among the sub-criteria,andtheresults are used to construct a decision-making network. The FANP is applied next to solve the network and to calculate the importance weights of the sub-criteria. Finally, the VIKOR is adopted to determine the ranking of the photovoltaic solar plant locations. The proposed model is applied in a case study in evaluating photovoltaic solar plant locations in Taiwan. By applying the proposed model, decision makers can have a better thinking process and make more appropriate decisions justifiably.

  8. A Hybrid Multiple Criteria Group Decision-Making Approach for Green Supplier Selection in the TFT-LCD Industry

    Directory of Open Access Journals (Sweden)

    Che-Wei Tsui

    2014-01-01

    Full Text Available The awareness of the need for environmental protection is increasing throughout the world. The focuses of green supplier selection are on considering environmental criteria and strengthening the competitiveness of the entire supply chain. The purpose of this study is to develop a green supplier selection procedure for the thin film transistor liquid crystal display (TFT-LCD industry using polarizer suppliers as an example. First, a decision framework for green supplier selection is developed based on literatures and the supplier audit forms provided by an anonymous flat panel display manufacturer in Taiwan. Then, a hybrid multiple criteria group decision-making (MCGDM method is proposed based on analytic hierarchy process (AHP, entropy, elimination and choice expressing the reality III (ELECTRE III, and the linear assignment method to assist the manufacturer in choosing among four polarizer suppliers. The final ranking results for green supplier selection and different opinions from each department are provided. An improvement report is suggested to enhance suppliers’ performance. For the evaluation procedure, most managers emphasize the importance of current capability and the capability of research and development. Furthermore, we found that the subsidiary supplier should improve quality control competence immediately to be considered as the potential candidate of primary supplier.

  9. A hybrid multi-criteria decision modeling approach for the best biodiesel blend selection based on ANP-TOPSIS analysis

    Directory of Open Access Journals (Sweden)

    G. Sakthivel

    2015-03-01

    Full Text Available The ever increasing demand and depletion of fossil fuels had an adverse impact on environmental pollution. The selection of appropriate source of biodiesel and proper blending of biodiesel plays a major role in alternate energy production. This paper describes an application of hybrid Multi Criteria Decision Making (MCDM technique for the selection of optimum fuel blend in fish oil biodiesel for the IC engine. The proposed model, Analytical Network Process (ANP is integrated with Technique for Order Performance by Similarity to Ideal Solution (TOPSIS and VlseKriterijumska Optimizacija I Kompromisno Resenje (in Serbian (VIKOR to evaluate the optimum blend. Evaluation of suitable blend is based on the exploratory analysis of the performance, emission and combustion parameters of the single cylinder, constant speed direct injection diesel engine at different load conditions. Here the ANP is used to determine the relative weights of the criteria, whereas TOPSIS and VIKOR are used for obtaining the final ranking of alternative blends. An efficient pair-wise comparison process and ranking of alternatives can be achieved for optimum blend selection through the integration of ANP with TOPSIS and VIKOR. The obtained preference order of the blends for ANP-VIKOR and ANP-TOPSIS are B20 > Diesel > B40 > B60 > B80 > B100 and B20 > B40 > Diesel > B60 > B80 > B100 respectively. Hence by comparing both these methods, B20 is selected as the best blend to operate the internal combustion engines. This paper highlights a new insight into MCDM techniques to evaluate the best fuel blend for the decision makers such as engine manufactures and R& D engineers to meet the fuel economy and emission norms to empower the green revolution.

  10. Assessment of regions priority for implementation of solar projects in Iran: New application of a hybrid multi-criteria decision making approach

    International Nuclear Information System (INIS)

    Vafaeipour, Majid; Hashemkhani Zolfani, Sarfaraz; Morshed Varzandeh, Mohammad Hossein; Derakhti, Arman; Keshavarz Eshkalag, Mahsa

    2014-01-01

    Highlights: • The economic, environmental, technical, social and risk criteria are considered. • Prioritization of regions for construction of solar power plants in Iran is assessed. • A hybrid MCDM approach ranked 25 scattered cities all around the country. • SWARA ranked the identified criteria, and WASPAS prioritized the alternatives. • Considering the ranked cities, a comprehensive GIS map of the country is provided. - Abstract: One of the promising ways to shift towards sustainable development has been the utilization of solar energy worldwide. Based on its geographical specifications, Iran enjoys high solar potential to implement feasible solar energy projects. However, to obtain the best productivity and payback, identification and prioritization of suitable regions for construction of expensive solar power plants is a delicate issue. In contrast with common assumptions, identifying appropriate geographical regions for implementation of such projects is not only associated with the amount of received solar radiation, but also there are many economic, environmental, technical, social and risk criteria (and their relevant sub-criteria) which must be taken into account. To address the complicated nature of the prioritization challenge caused by existence of various indicators, this paper applies a hybrid Multi-Criteria Decision Making (MCDM) approach and prioritizes 25 scattered cities all around the country for implementation of future solar power plants. For this, both quantitative and qualitative effective indicators are identified to be considered as the inputs to the utilized hybrid model. The Step-wise Weight Assessment Ratio Analysis (SWARA, proposed in 2010) method is employed to rank the identified criteria, and the Weighted Aggregates Sum Product Assessment (WASPAS, proposed in 2012) is applied to evaluate and prioritize the alternatives (cities) where Yazd city ranked first. Eventually via considering the ranked cities, a comprehensive GIS

  11. An Object-Based Classification of Mangroves Using a Hybrid Decision Tree—Support Vector Machine Approach

    Directory of Open Access Journals (Sweden)

    Benjamin W. Heumann

    2011-11-01

    Full Text Available Mangroves provide valuable ecosystem goods and services such as carbon sequestration, habitat for terrestrial and marine fauna, and coastal hazard mitigation. The use of satellite remote sensing to map mangroves has become widespread as it can provide accurate, efficient, and repeatable assessments. Traditional remote sensing approaches have failed to accurately map fringe mangroves and true mangrove species due to relatively coarse spatial resolution and/or spectral confusion with landward vegetation. This study demonstrates the use of the new Worldview-2 sensor, Object-based image analysis (OBIA, and support vector machine (SVM classification to overcome both of these limitations. An exploratory spectral separability showed that individual mangrove species could not be spectrally separated, but a distinction between true and associate mangrove species could be made. An OBIA classification was used that combined a decision-tree classification with the machine-learning SVM classification. Results showed an overall accuracy greater than 94% (kappa = 0.863 for classifying true mangroves species and other dense coastal vegetation at the object level. There remain serious challenges to accurately mapping fringe mangroves using remote sensing data due to spectral similarity of mangrove and associate species, lack of clear zonation between species, and mixed pixel effects, especially when vegetation is sparse or degraded.

  12. A Hybrid Approach of Stepwise Regression, Logistic Regression, Support Vector Machine, and Decision Tree for Forecasting Fraudulent Financial Statements

    Directory of Open Access Journals (Sweden)

    Suduan Chen

    2014-01-01

    Full Text Available As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.

  13. A hybrid approach of stepwise regression, logistic regression, support vector machine, and decision tree for forecasting fraudulent financial statements.

    Science.gov (United States)

    Chen, Suduan; Goo, Yeong-Jia James; Shen, Zone-De

    2014-01-01

    As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.

  14. A hybrid approach for biobjective optimization

    DEFF Research Database (Denmark)

    Stidsen, Thomas Jacob Riis; Andersen, Kim Allan

    2018-01-01

    to singleobjective problems is that no standard multiobjective solvers exist and specialized algorithms need to be programmed from scratch.In this article we will present a hybrid approach, which operates both in decision space and in objective space. The approach enables massive efficient parallelization and can...... be used to a wide variety of biobjective Mixed Integer Programming models. We test the approach on the biobjective extension of the classic traveling salesman problem, on the standard datasets, and determine the full set of nondominated points. This has only been done once before (Florios and Mavrotas...

  15. A Hybrid Approach on Tourism Demand Forecasting

    Science.gov (United States)

    Nor, M. E.; Nurul, A. I. M.; Rusiman, M. S.

    2018-04-01

    Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is challenging to produce an accurate forecast since economic data such as the tourism data is affected by social, economic and environmental factors. In this study, an equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was assessed by taking the each individual method as a benchmark. The results showed that this hybrid approach outperformed the other two models

  16. Decision making by hybrid probabilistic: Possibilistic utility theory

    Directory of Open Access Journals (Sweden)

    Pap Endre

    2009-01-01

    Full Text Available It is presented an approach to decision theory based upon nonprobabilistic uncertainty. There is an axiomatization of the hybrid probabilistic possibilistic mixtures based on a pair of triangular conorm and triangular norm satisfying restricted distributivity law, and the corresponding non-additive Smeasure. This is characterized by the families of operations involved in generalized mixtures, based upon a previous result on the characterization of the pair of continuous t-norm and t-conorm such that the former is restrictedly distributive over the latter. The obtained family of mixtures combines probabilistic and idempotent (possibilistic mixtures via a threshold.

  17. Development of hybrid artificial intelligent based handover decision algorithm

    Directory of Open Access Journals (Sweden)

    A.M. Aibinu

    2017-04-01

    Full Text Available The possibility of seamless handover remains a mirage despite the plethora of existing handover algorithms. The underlying factor responsible for this has been traced to the Handover decision module in the Handover process. Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. The developed model is made up of hybrid of Artificial Neural Network (ANN based prediction model and Fuzzy Logic. On accessing the network, the Received Signal Strength (RSS was acquired over a period of time to form a time series data. The data was then fed to the newly proposed k-step ahead ANN-based RSS prediction system for estimation of prediction model coefficients. The synaptic weights and adaptive coefficients of the trained ANN was then used to compute the k-step ahead ANN based RSS prediction model coefficients. The predicted RSS value was later codified as Fuzzy sets and in conjunction with other measured network parameters were fed into the Fuzzy logic controller in order to finalize handover decision process. The performance of the newly developed k-step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. Results obtained in both cases shows that the proposed algorithm is capable of predicting ahead the RSS value to about ±0.0002 dB. Also, the cascaded effect of the complete handover decision module was also evaluated. Results obtained show that the newly proposed hybrid approach was able to reduce ping-pong effect associated with other handover techniques.

  18. Evaporator modeling - A hybrid approach

    International Nuclear Information System (INIS)

    Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun

    2009-01-01

    In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis

  19. A life-cycle approach to technology, infrastructure, and climate policy decision making: Transitioning to plug-in hybrid electric vehicles and low-carbon electricity

    Science.gov (United States)

    Samaras, Constantine

    In order to mitigate the most severe effects of climate change, large global reductions in the current levels of anthropogenic greenhouse gas (GHG) emissions are required in this century to stabilize atmospheric carbon dioxide (CO2) concentrations at less than double pre-industrial levels. The Intergovernmental Panel on Climate Change (IPCC) fourth assessment report states that GHG emissions should be reduced to 50-80% of 2000 levels by 2050 to increase the likelihood of stabilizing atmospheric CO2 concentrations. In order to achieve the large GHG reductions by 2050 recommended by the IPCC, a fundamental shift and evolution will be required in the energy system. Because the electric power and transportation sectors represent the largest GHG emissions sources in the United States, a unique opportunity for coupling these systems via electrified transportation could achieve synergistic environmental (GHG emissions reductions) and energy security (petroleum displacement) benefits. Plug-in hybrid electric vehicles (PHEVs), which use electricity from the grid to power a portion of travel, could play a major role in reducing greenhouse gas emissions from the transport sector. However, this thesis finds that life cycle GHG emissions from PHEVs depend on the electricity source that is used to charge the battery, so meaningful GHG emissions reductions with PHEVs are conditional on low-carbon electricity sources. Power plants and their associated GHGs are long-lived, and this work argues that decisions made regarding new electricity supplies within the next ten years will affect the potential of PHEVs to play a role in a low-carbon future in the coming decades. This thesis investigates the life cycle engineering, economic, and policy decisions involved in transitioning to PHEVs and low-carbon electricity. The government has a vast array of policy options to promote low-carbon technologies, some of which have proven to be more successful than others. This thesis uses life

  20. A Hybrid Approach to Teaching Managerial Economics

    Science.gov (United States)

    Metzgar, Matthew

    2014-01-01

    Many institutions in higher education are experimenting with hybrid teaching approaches to undergraduate courses. Online resources may provide a number of advantages to students as compared to in-class approaches. Research regarding the effectiveness of hybrid approaches is mixed and still accumulating. This paper discusses the use of a hybrid…

  1. Stock selection using a hybrid MCDM approach

    Directory of Open Access Journals (Sweden)

    Tea Poklepović

    2014-12-01

    Full Text Available The problem of selecting the right stocks to invest in is of immense interest for investors on both emerging and developed capital markets. Moreover, an investor should take into account all available data regarding stocks on the particular market. This includes fundamental and stock market indicators. The decision making process includes several stocks to invest in and more than one criterion. Therefore, the task of selecting the stocks to invest in can be viewed as a multiple criteria decision making (MCDM problem. Using several MCDM methods often leads to divergent rankings. The goal of this paper is to resolve these possible divergent results obtained from different MCDM methods using a hybrid MCDM approach based on Spearman’s rank correlation coefficient. Five MCDM methods are selected: COPRAS, linear assignment, PROMETHEE, SAW and TOPSIS. The weights for all criteria are obtained by using the AHP method. Data for this study includes information on stock returns and traded volumes from March 2012 to March 2014 for 19 stocks on the Croatian capital market. It also includes the most important fundamental and stock market indicators for selected stocks. Rankings using five selected MCDM methods in the stock selection problem yield divergent results. However, after applying the proposed approach the final hybrid rankings are obtained. The results show that the worse stocks to invest in happen to be the same when the industry is taken into consideration or when not. However, when the industry is taken into account, the best stocks to invest in are slightly different, because some industries are more profitable than the others.

  2. Hybrid soft computing approaches research and applications

    CERN Document Server

    Dutta, Paramartha; Chakraborty, Susanta

    2016-01-01

    The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

  3. Hybrid multiple criteria decision-making methods

    DEFF Research Database (Denmark)

    Zavadskas, Edmundas Kazimieras; Govindan, K.; Antucheviciene, Jurgita

    2016-01-01

    Formal decision-making methods can be used to help improve the overall sustainability of industries and organisations. Recently, there has been a great proliferation of works aggregating sustainability criteria by using diverse multiple criteria decision-making (MCDM) techniques. A number of revi...

  4. A Hybrid Approach to the Optimization of Multiechelon Systems

    Directory of Open Access Journals (Sweden)

    Paweł Sitek

    2015-01-01

    Full Text Available In freight transportation there are two main distribution strategies: direct shipping and multiechelon distribution. In the direct shipping, vehicles, starting from a depot, bring their freight directly to the destination, while in the multiechelon systems, freight is delivered from the depot to the customers through an intermediate points. Multiechelon systems are particularly useful for logistic issues in a competitive environment. The paper presents a concept and application of a hybrid approach to modeling and optimization of the Multi-Echelon Capacitated Vehicle Routing Problem. Two ways of mathematical programming (MP and constraint logic programming (CLP are integrated in one environment. The strengths of MP and CLP in which constraints are treated in a different way and different methods are implemented and combined to use the strengths of both. The proposed approach is particularly important for the discrete decision models with an objective function and many discrete decision variables added up in multiple constraints. An implementation of hybrid approach in the ECLiPSe system using Eplex library is presented. The Two-Echelon Capacitated Vehicle Routing Problem (2E-CVRP and its variants are shown as an illustrative example of the hybrid approach. The presented hybrid approach will be compared with classical mathematical programming on the same benchmark data sets.

  5. A Hybrid Approach to Protect Palmprint Templates

    Directory of Open Access Journals (Sweden)

    Hailun Liu

    2014-01-01

    Full Text Available Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach.

  6. The effects of activity-travel context and individual attitudes on car-sharing decisions under travel time uncertainty : a hybrid choice modeling approach

    NARCIS (Netherlands)

    Kim, J.; Rasouli, S.; Timmermans, H.J.P.

    2017-01-01

    People's daily decision to use car-sharing rather than other transport modes for conducting a specific activity has been investigated recently in assessing the market potential of car-sharing systems. Most studies have estimated transport mode choice models with an extended choice set using

  7. Optimal Siting of Charging Stations for Electric Vehicles Based on Fuzzy Delphi and Hybrid Multi-Criteria Decision Making Approaches from an Extended Sustainability Perspective

    Directory of Open Access Journals (Sweden)

    Huiru Zhao

    2016-04-01

    Full Text Available Optimal siting of electric vehicle charging stations (EVCSs is crucial to the sustainable development of electric vehicle systems. Considering the defects of previous heuristic optimization models in tackling subjective factors, this paper employs a multi-criteria decision-making (MCDM framework to address the issue of EVCS siting. The initial criteria for optimal EVCS siting are selected from extended sustainability theory, and the vital sub-criteria are further determined by using a fuzzy Delphi method (FDM, which consists of four pillars: economy, society, environment and technology perspectives. To tolerate vagueness and ambiguity of subjective factors and human judgment, a fuzzy Grey relation analysis (GRA-VIKOR method is employed to determine the optimal EVCS site, which also improves the conventional aggregating function of fuzzy Vlsekriterijumska Optimizacijia I Kompromisno Resenje (VIKOR. Moreover, to integrate the subjective opinions as well as objective information, experts’ ratings and Shannon entropy method are employed to determine combination weights. Then, the applicability of proposed framework is demonstrated by an empirical study of five EVCS site alternatives in Tianjin. The results show that A3 is selected as the optimal site for EVCS, and sub-criteria affiliated with environment obtain much more attentions than that of other sub-criteria. Moreover, sensitivity analysis indicates the selection results remains stable no matter how sub-criteria weights are changed, which verifies the robustness and effectiveness of proposed model and evaluation results. This study provides a comprehensive and effective method for optimal siting of EVCS and also innovates the weights determination and distance calculation for conventional fuzzy VIKOR.

  8. Detection of cardiovascular anomalies: Hybrid systems approach

    KAUST Repository

    Ledezma, Fernando

    2012-06-06

    In this paper, we propose a hybrid interpretation of the cardiovascular system. Based on a model proposed by Simaan et al. (2009), we study the problem of detecting cardiovascular anomalies that can be caused by variations in some physiological parameters, using an observerbased approach. We present the first numerical results obtained. © 2012 IFAC.

  9. An approach for assessing human decision reliability

    International Nuclear Information System (INIS)

    Pyy, P.

    2000-01-01

    This paper presents a method to study human reliability in decision situations related to nuclear power plant disturbances. Decisions often play a significant role in handling of emergency situations. The method may be applied to probabilistic safety assessments (PSAs) in cases where decision making is an important dimension of an accident sequence. Such situations are frequent e.g. in accident management. In this paper, a modelling approach for decision reliability studies is first proposed. Then, a case study with two decision situations with relatively different characteristics is presented. Qualitative and quantitative findings of the study are discussed. In very simple decision cases with time pressure, time reliability correlation proved out to be a feasible reliability modelling method. In all other decision situations, more advanced probabilistic decision models have to be used. Finally, decision probability assessment by using simulator run results and expert judgement is presented

  10. A HYBRID APPROACH FOR RURAL FEEDER DESIGN

    Directory of Open Access Journals (Sweden)

    DAMANJEET KAUR

    2012-08-01

    Full Text Available In this paper, a population based approach for conductor size selection in rural radial distribution system is presented. The proposed hybrid approach implies a particle swarm optimization (PSO approach in combination with mutant property of differential evolution (DE for conductor size selection in radial distribution system. The conductor size for each feeder segment is selected such that the total cost of capital investment and capitalized cost of energy losses is minimized while constraints of voltage at each node and current carrying capacity of conductor is within the limits. The applicability and effectiveness of the proposed method is demonstrated with the help of 32-node test system.

  11. A hybrid approach for minimizing makespan in permutation flowshop scheduling

    DEFF Research Database (Denmark)

    Govindan, Kannan; Balasundaram, R.; Baskar, N.

    2017-01-01

    This work proposes a hybrid approach for solving traditional flowshop scheduling problems to reduce the makespan (total completion time). To solve scheduling problems, a combination of Decision Tree (DT) and Scatter Search (SS) algorithms are used. Initially, the DT is used to generate a seed...... solution which is then given input to the SS to obtain optimal / near optimal solutions of makespan. The DT used the entropy function to convert the given problem into a tree structured format / set of rules. The SS provides an extensive investigation of the search space through diversification...

  12. Hybrid biasing approaches for global variance reduction

    International Nuclear Information System (INIS)

    Wu, Zeyun; Abdel-Khalik, Hany S.

    2013-01-01

    A new variant of Monte Carlo—deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses. - Highlights: ► Hybrid Monte Carlo Deterministic Method based on Gaussian Process Model is introduced. ► Method employs deterministic model to calculate responses correlations. ► Method employs correlations to bias Monte Carlo transport. ► Method compared to FW-CADIS methodology in SCALE code. ► An order of magnitude speed up is achieved for a PWR core model.

  13. Hybrid Multicriteria Group Decision Making Method for Information System Project Selection Based on Intuitionistic Fuzzy Theory

    Directory of Open Access Journals (Sweden)

    Jian Guo

    2013-01-01

    Full Text Available Information system (IS project selection is of critical importance to every organization in dynamic competing environment. The aim of this paper is to develop a hybrid multicriteria group decision making approach based on intuitionistic fuzzy theory for IS project selection. The decision makers’ assessment information can be expressed in the form of real numbers, interval-valued numbers, linguistic variables, and intuitionistic fuzzy numbers (IFNs. All these evaluation pieces of information can be transformed to the form of IFNs. Intuitionistic fuzzy weighted averaging (IFWA operator is utilized to aggregate individual opinions of decision makers into a group opinion. Intuitionistic fuzzy entropy is used to obtain the entropy weights of the criteria. TOPSIS method combined with intuitionistic fuzzy set is proposed to select appropriate IS project in group decision making environment. Finally, a numerical example for information system projects selection is given to illustrate application of hybrid multi-criteria group decision making (MCGDM method based on intuitionistic fuzzy theory and TOPSIS method.

  14. The decision tree approach to classification

    Science.gov (United States)

    Wu, C.; Landgrebe, D. A.; Swain, P. H.

    1975-01-01

    A class of multistage decision tree classifiers is proposed and studied relative to the classification of multispectral remotely sensed data. The decision tree classifiers are shown to have the potential for improving both the classification accuracy and the computation efficiency. Dimensionality in pattern recognition is discussed and two theorems on the lower bound of logic computation for multiclass classification are derived. The automatic or optimization approach is emphasized. Experimental results on real data are reported, which clearly demonstrate the usefulness of decision tree classifiers.

  15. A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran

    Directory of Open Access Journals (Sweden)

    Shakiba Khademolqorani

    2015-01-01

    Full Text Available Bankruptcy prediction is an important problem facing financial decision support for stakeholders of firms, including auditors, managers, shareholders, debt-holders, and potential investors, as well as academic researchers. Popular discourse on financial distress forecasting focuses on developing the discrete models to improve the prediction. The aim of this paper is to develop a novel hybrid financial distress model based on combining various statistical and machine learning methods. Then multiple attribute decision making method is exploited to choose the optimized model from the implemented ones. Proposed approaches have also been applied in Iranian companies that performed previous models and it can be consolidated with the help of the hybrid approach.

  16. A hybrid approach for global sensitivity analysis

    International Nuclear Information System (INIS)

    Chakraborty, Souvik; Chowdhury, Rajib

    2017-01-01

    Distribution based sensitivity analysis (DSA) computes sensitivity of the input random variables with respect to the change in distribution of output response. Although DSA is widely appreciated as the best tool for sensitivity analysis, the computational issue associated with this method prohibits its use for complex structures involving costly finite element analysis. For addressing this issue, this paper presents a method that couples polynomial correlated function expansion (PCFE) with DSA. PCFE is a fully equivalent operational model which integrates the concepts of analysis of variance decomposition, extended bases and homotopy algorithm. By integrating PCFE into DSA, it is possible to considerably alleviate the computational burden. Three examples are presented to demonstrate the performance of the proposed approach for sensitivity analysis. For all the problems, proposed approach yields excellent results with significantly reduced computational effort. The results obtained, to some extent, indicate that proposed approach can be utilized for sensitivity analysis of large scale structures. - Highlights: • A hybrid approach for global sensitivity analysis is proposed. • Proposed approach integrates PCFE within distribution based sensitivity analysis. • Proposed approach is highly efficient.

  17. A hybrid multiple attribute decision making method for solving problems of industrial environment

    Directory of Open Access Journals (Sweden)

    Dinesh Singh

    2011-01-01

    Full Text Available The selection of appropriate alternative in the industrial environment is an important but, at the same time, a complex and difficult problem because of the availability of a wide range of alternatives and similarity among them. Therefore, there is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations. In this paper, a hybrid decision making method of graph theory and matrix approach (GTMA and analytical hierarchy process (AHP is proposed. Three examples are presented to illustrate the potential of the proposed GTMA-AHP method and the results are compared with the results obtained using other decision making methods.

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

    Directory of Open Access Journals (Sweden)

    Chung-Min Wu

    2013-01-01

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

  19. Hybrid Fusion for Biometrics: Combining Score-level and Decision-level Fusion

    NARCIS (Netherlands)

    Tao, Q.; Veldhuis, Raymond N.J.

    2008-01-01

    A general framework of fusion at decision level, which works on ROCs instead of matching scores, is investigated. Under this framework, we further propose a hybrid fusion method, which combines the score-level and decision-level fusions, taking advantage of both fusion modes. The hybrid fusion

  20. Multilayer Approach for Advanced Hybrid Lithium Battery

    KAUST Repository

    Ming, Jun

    2016-06-06

    Conventional intercalated rechargeable batteries have shown their capacity limit, and the development of an alternative battery system with higher capacity is strongly needed for sustainable electrical vehicles and hand-held devices. Herein, we introduce a feasible and scalable multilayer approach to fabricate a promising hybrid lithium battery with superior capacity and multivoltage plateaus. A sulfur-rich electrode (90 wt % S) is covered by a dual layer of graphite/Li4Ti5O12, where the active materials S and Li4Ti5O12 can both take part in redox reactions and thus deliver a high capacity of 572 mAh gcathode -1 (vs the total mass of electrode) or 1866 mAh gs -1 (vs the mass of sulfur) at 0.1C (with the definition of 1C = 1675 mA gs -1). The battery shows unique voltage platforms at 2.35 and 2.1 V, contributed from S, and 1.55 V from Li4Ti5O12. A high rate capability of 566 mAh gcathode -1 at 0.25C and 376 mAh gcathode -1 at 1C with durable cycle ability over 100 cycles can be achieved. Operando Raman and electron microscope analysis confirm that the graphite/Li4Ti5O12 layer slows the dissolution/migration of polysulfides, thereby giving rise to a higher sulfur utilization and a slower capacity decay. This advanced hybrid battery with a multilayer concept for marrying different voltage plateaus from various electrode materials opens a way of providing tunable capacity and multiple voltage platforms for energy device applications. © 2016 American Chemical Society.

  1. A hybrid decision support system for sustainable office building renovation and energy performance improvement

    Energy Technology Data Exchange (ETDEWEB)

    Juan, Yi-Kai [Department of Architecture, National Taiwan University of Science and Technology (NTUST) (China); Center for Sustainable Development and Global Competitiveness, Stanford University (United States); Gao, Peng [Department of Traffic and Transportation Engineering, Tongji University (China); Wang, Jie [Center for Sustainable Development and Global Competitiveness, Stanford University (United States)

    2010-03-15

    Energy consumption of buildings accounts for around 20-40% of all energy consumed in advanced countries. Over the last decade, more and more global organizations are investing significant resources to create sustainably built environments, emphasizing sustainable building renovation processes to reduce energy consumption and carbon dioxide emissions. This study develops an integrated decision support system to assess existing office building conditions and to recommend an optimal set of sustainable renovation actions, considering trade-offs between renovation cost, improved building quality, and environmental impacts. A hybrid approach that combines A* graph search algorithm with genetic algorithms (GA) is used to analyze all possible renovation actions and their trade-offs to develop the optimal solution. A two-stage system validation is performed to demonstrate the practical application of the hybrid approach: zero-one goal programming (ZOGP) and genetic algorithms are adopted to validate the effectiveness of the algorithm. A real-world renovation project is introduced to validate differences in energy performance projected for the renovation solution suggested by the system. The results reveal that the proposed hybrid system is more computationally effective than either ZOGP or GA alone. The system's suggested renovation actions would provide substantial energy performance improvements to the real project if implemented. (author)

  2. A hybrid modeling approach for option pricing

    Science.gov (United States)

    Hajizadeh, Ehsan; Seifi, Abbas

    2011-11-01

    The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.

  3. Decision making under uncertainty: a quasimetric approach.

    Directory of Open Access Journals (Sweden)

    Steve N'Guyen

    Full Text Available We propose a new approach for solving a class of discrete decision making problems under uncertainty with positive cost. This issue concerns multiple and diverse fields such as engineering, economics, artificial intelligence, cognitive science and many others. Basically, an agent has to choose a single or series of actions from a set of options, without knowing for sure their consequences. Schematically, two main approaches have been followed: either the agent learns which option is the correct one to choose in a given situation by trial and error, or the agent already has some knowledge on the possible consequences of his decisions; this knowledge being generally expressed as a conditional probability distribution. In the latter case, several optimal or suboptimal methods have been proposed to exploit this uncertain knowledge in various contexts. In this work, we propose following a different approach, based on the geometric intuition of distance. More precisely, we define a goal independent quasimetric structure on the state space, taking into account both cost function and transition probability. We then compare precision and computation time with classical approaches.

  4. Solving University Scheduling Problem Using Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Aftab Ahmed Shaikh

    2011-10-01

    Full Text Available In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.

  5. Detection of cardiovascular anomalies: Hybrid systems approach

    KAUST Repository

    Ledezma, Fernando; Laleg-Kirati, Taous-Meriem

    2012-01-01

    In this paper, we propose a hybrid interpretation of the cardiovascular system. Based on a model proposed by Simaan et al. (2009), we study the problem of detecting cardiovascular anomalies that can be caused by variations in some physiological

  6. Improving behavioral realism in hybrid energy-economy models using discrete choice studies of personal transportation decisions

    International Nuclear Information System (INIS)

    Horne, M.; Jaccard, M.; Tiedemann, K.

    2005-01-01

    Hybrid energy-economy models combine top-down and bottom-up approaches to explore behaviorally realistic responses to technology-focused policies. This research uses empirically derived discrete choice models to inform key behavioral parameters in CIMS, a hybrid model. The discrete choice models are estimated for vehicle and commuting decisions from a survey of 1150 Canadians. With the choice models integrated into CIMS, we simulate carbon taxes, gasoline vehicle disincentives, and single occupancy vehicle disincentives to show how different policy levers can motivate technological change. We also use the empirical basis for the choice models to portray uncertainty in technological change, costs, and emissions. (author)

  7. A hybrid fuzzy multi-criteria decision making model for green ...

    African Journals Online (AJOL)

    A hybrid fuzzy multi-criteria decision making model for green supplier selection. ... Hence,supplier selection is significant factor in supply chain success. ... reduce purchasing cost, lead time and improve quality and environmental issue.

  8. Hybrid Decision-making Method for Emergency Response System of Unattended Train Operation Metro

    Directory of Open Access Journals (Sweden)

    Bobo Zhao

    2016-04-01

    Full Text Available Suitable selection of the emergency alternatives is a critical issue in emergency response system of Unattended Train Operation (UTO metro system of China. However, there is no available method for dispatcher group in Operating Control Center (OCC to evaluate the decision under emergency situation. It was found that the emergency decision making in UTO metro system is relative with the preferences and the importance of multi-dispatcher in emergency. Regarding these factors, this paper presents a hybrid method to determinate the priority weights of emergency alternatives, which aggregates the preference matrix by constructing the emergency response task model based on the Weighted Ordered Weighted Averaging (WOWA operator. This calculation approach derives the importance weights depending on the dispatcher emergency tasks and integrates it into the Ordered Weighted Averaging (OWA operator weights based on a fuzzy membership relation. A case from train fire is given to demonstrate the feasibility and practicability of the proposed methods for Group Multi-Criteria Decision Making (GMCDM in emergency management of UTO metro system. The innovation of this research is paving the way for a systematic emergency decision-making solution which connects the automatic metro emergency response system with the GMCDM theory.

  9. Three approaches to deal with inconsistent decision tables - Comparison of decision tree complexity

    KAUST Repository

    Azad, Mohammad; Chikalov, Igor; Moshkov, Mikhail

    2013-01-01

    In inconsistent decision tables, there are groups of rows with equal values of conditional attributes and different decisions (values of the decision attribute). We study three approaches to deal with such tables. Instead of a group of equal rows, we consider one row given by values of conditional attributes and we attach to this row: (i) the set of all decisions for rows from the group (many-valued decision approach); (ii) the most common decision for rows from the group (most common decision approach); and (iii) the unique code of the set of all decisions for rows from the group (generalized decision approach). We present experimental results and compare the depth, average depth and number of nodes of decision trees constructed by a greedy algorithm in the framework of each of the three approaches. © 2013 Springer-Verlag.

  10. Multi objective decision making in hybrid energy system design

    Science.gov (United States)

    Merino, Gabriel Guillermo

    The design of grid-connected photovoltaic wind generator system supplying a farmstead in Nebraska has been undertaken in this dissertation. The design process took into account competing criteria that motivate the use of different sources of energy for electric generation. The criteria considered were 'Financial', 'Environmental', and 'User/System compatibility'. A distance based multi-objective decision making methodology was developed to rank design alternatives. The method is based upon a precedence order imposed upon the design objectives and a distance metric describing the performance of each alternative. This methodology advances previous work by combining ambiguous information about the alternatives with a decision-maker imposed precedence order in the objectives. Design alternatives, defined by the photovoltaic array and wind generator installed capacities, were analyzed using the multi-objective decision making approach. The performance of the design alternatives was determined by simulating the system using hourly data for an electric load for a farmstead and hourly averages of solar irradiation, temperature and wind speed from eight wind-solar energy monitoring sites in Nebraska. The spatial variability of the solar energy resource within the region was assessed by determining semivariogram models to krige hourly and daily solar radiation data. No significant difference was found in the predicted performance of the system when using kriged solar radiation data, with the models generated vs. using actual data. The spatial variability of the combined wind and solar energy resources was included in the design analysis by using fuzzy numbers and arithmetic. The best alternative was dependent upon the precedence order assumed for the main criteria. Alternatives with no PV array or wind generator dominated when the 'Financial' criteria preceded the others. In contrast, alternatives with a nil component of PV array but a high wind generator component

  11. A "Hybrid" Approach for Synthesizing Optimal Controllers of Hybrid Systems

    DEFF Research Database (Denmark)

    Zhao, Hengjun; Zhan, Naijun; Kapur, Deepak

    2012-01-01

    to discretization manageable and within bounds. A major advantage of our approach is not only that it avoids errors due to numerical computation, but it also gives a better optimal controller. In order to illustrate our approach, we use the real industrial example of an oil pump provided by the German company HYDAC...

  12. Hybrid perovskites: Approaches towards light-emitting devices

    KAUST Repository

    Alias, Mohd Sharizal

    2016-10-06

    The high optical gain and absorption of organic-inorganic hybrid perovskites have attracted extensive research for photonic device applications. Using the bromide halide as an example, we present key approaches of our work towards realizing efficient perovskites based light-emitters. The approaches involved determination of optical constants for the hybrid perovskites thin films, fabrication of photonic nanostructures in the form of subwavelength grating reflector patterned directly on the hybrid perovskites as light manipulation layer, and enhancing the emission property of the hybrid perovskites by using microcavity structure. Our results provide a platform for realization of hybrid perovskites based light-emitting devices for solid-state lighting and display applications. © 2016 IEEE.

  13. Hybrid perovskites: Approaches towards light-emitting devices

    KAUST Repository

    Alias, Mohd Sharizal; Dursun, Ibrahim; Priante, Davide; Saidaminov, Makhsud I.; Ng, Tien Khee; Bakr, Osman; Ooi, Boon S.

    2016-01-01

    The high optical gain and absorption of organic-inorganic hybrid perovskites have attracted extensive research for photonic device applications. Using the bromide halide as an example, we present key approaches of our work towards realizing efficient perovskites based light-emitters. The approaches involved determination of optical constants for the hybrid perovskites thin films, fabrication of photonic nanostructures in the form of subwavelength grating reflector patterned directly on the hybrid perovskites as light manipulation layer, and enhancing the emission property of the hybrid perovskites by using microcavity structure. Our results provide a platform for realization of hybrid perovskites based light-emitting devices for solid-state lighting and display applications. © 2016 IEEE.

  14. Scalar field dark matter in hybrid approach

    NARCIS (Netherlands)

    Friedrich, Pavel; Prokopec, Tomislav

    2017-01-01

    We develop a hybrid formalism suitable for modeling scalar field dark matter, in which the phase-space distribution associated to the real scalar field is modeled by statistical equal-time two-point functions and gravity is treated by two stochastic gravitational fields in the longitudinal gauge (in

  15. Network approaches for expert decisions in sports.

    Science.gov (United States)

    Glöckner, Andreas; Heinen, Thomas; Johnson, Joseph G; Raab, Markus

    2012-04-01

    This paper focuses on a model comparison to explain choices based on gaze behavior via simulation procedures. We tested two classes of models, a parallel constraint satisfaction (PCS) artificial neuronal network model and an accumulator model in a handball decision-making task from a lab experiment. Both models predict action in an option-generation task in which options can be chosen from the perspective of a playmaker in handball (i.e., passing to another player or shooting at the goal). Model simulations are based on a dataset of generated options together with gaze behavior measurements from 74 expert handball players for 22 pieces of video footage. We implemented both classes of models as deterministic vs. probabilistic models including and excluding fitted parameters. Results indicated that both classes of models can fit and predict participants' initially generated options based on gaze behavior data, and that overall, the classes of models performed about equally well. Early fixations were thereby particularly predictive for choices. We conclude that the analyses of complex environments via network approaches can be successfully applied to the field of experts' decision making in sports and provide perspectives for further theoretical developments. Copyright © 2011 Elsevier B.V. All rights reserved.

  16. APPROACHED DECISION OF THE DIFFERENTIAL EQUATIONS

    Directory of Open Access Journals (Sweden)

    Oleksii B. Krasnozhon

    2011-02-01

    Full Text Available The urgency of the material stated in the article is caused by necessity of development, updating and improvements of methodical operating time on subject matters of issue "Calculus mathematics" which teaching is carried out in conditions of use of information-communication technologies. In the article the program realizations in Mathcad environment of Adams and Runge-Kutt methods of the approached decision of the differential equations are offered; examples on application of the specified methods are brought; the expediency of application of Mathcad environment during mathematical preparation of experts is proved. Perspective directions of the further scientific researches are methodical, mathematical and algorithmic aspects of creation of effective program realizations of numerical methods in Mathcad environment.

  17. A hybrid method for decision making with dependence & feedback under incomplete information

    Directory of Open Access Journals (Sweden)

    Chen Weijie

    2016-01-01

    Full Text Available This paper presents a hybrid method to tackle multiple criteria decision making problems with incomplete weight information in the context of fuzzy soft sets. In order to determine the weights of criteria, we develop a comprehensive two-stage framework. Stage One: We first define the distance between two fuzzy soft numbers. Next, we establish an optimization model based on ideal point of attribute values, by which the attrib-ute weights can be determined. Stage Two: To get the global weights, we use fuzzy cognitive maps to depict the dependent and feedback effect among criteria. Next, we require constructing fuzzy soft set to decide the desirable alternative. Finally, a case study is given to clarify the proposed approach of this paper.

  18. Fuzzy hybrid MCDM approach for selection of wind turbine service technicians

    Directory of Open Access Journals (Sweden)

    Goutam Kumar Bose

    2016-01-01

    Full Text Available This research paper is aimed to present a fuzzy Hybrid Multi-criteria decision making (MCDM methodology for selecting employees. The present study aspires to present the hybrid approach of Fuzzy multiple MCDM techniques with tactical viewpoint to support the recruitment process of wind turbine service technicians. The methodology is based on the application of Fuzzy ARAS (Additive Ratio Assessment and Fuzzy MOORA (Multi-Objective Optimization on basis of Ratio Analysis which are integrated through group decision making (GDM method in the model for selection of wind turbine service technicians’ ranking. Here a group of experts from different fields of expertise are engaged to finalize the decision. Series of tests are conducted regarding physical fitness, technical written test, practical test along with general interview and medical examination to facilitate the final selection using the above techniques. In contrast to single decision making approaches, the proposed group decision making model efficiently supports the wind turbine service technicians ranking process. The effectiveness of the proposed approach manifest from the case study of service technicians required for the maintenance department of wind power plant using Fuzzy ARAS and Fuzzy MOORA. This set of potential technicians is evaluated based on five main criteria.

  19. A hybrid MCDM approach for ranking suppliers by considering ethical factors

    OpenAIRE

    Azadfallah, Mohammad

    2016-01-01

    One of the negative effects of cooperating with un-ethically behaving suppliers is that it may devastate the companies' credibility among employees, customers and the public. In this paper, a hybrid Multiple Criteria Decision Making (MCDM) approach (Disjunctive-WPM method) is proposed to resolve this limitation. The proposed methods consist of the following steps: 1. drop unethical solutions and 2. rank the remaining solutions. Therefore, the aim of t...

  20. Agricultural Tractor Selection: A Hybrid and Multi-Attribute Approach

    Directory of Open Access Journals (Sweden)

    Jorge L. García-Alcaraz

    2016-02-01

    Full Text Available Usually, agricultural tractor investments are assessed using traditional economic techniques that only involve financial attributes, resulting in reductionist evaluations. However, tractors have qualitative and quantitative attributes that must be simultaneously integrated into the evaluation process. This article reports a hybrid and multi-attribute approach to assessing a set of agricultural tractors based on AHP-TOPSIS. To identify the attributes in the model, a survey including eighteen attributes was given to agricultural machinery salesmen and farmers for determining their importance. The list of attributes was presented to a decision group for a case of study, and their importance was estimated using AHP and integrated into the TOPSIS technique. In this case, one tractor was selected from a set of six alternatives, integrating six attributes in the model: initial cost, annual maintenance cost, liters of diesel per hour, safety of the operator, maintainability and after-sale customer service offered by the supplier. Based on the results obtained, the model can be considered easy to apply and to have good acceptance among farmers and salesmen, as there are no special software requirements for the application.

  1. Dynamic Programming Approach for Exact Decision Rule Optimization

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2013-01-01

    This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from

  2. Aiding Lay Decision Making Using a Cognitive Competencies Approach

    OpenAIRE

    Maule, A. J.; Maule, Simon

    2016-01-01

    Two prescriptive approaches have evolved to aid human decision making: just in time interventions that provide support as a decision is being made; and just in case interventions that educate people about future events that they may encounter so that they are better prepared to make an informed decision when these events occur. We review research on these two approaches developed in the context of supporting everyday decisions such as choosing an apartment, a financial product or a medical pr...

  3. Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

    Science.gov (United States)

    Chiadamrong, N.; Piyathanavong, V.

    2017-12-01

    Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

  4. A new hybrid decision framework for prioritizing funding allocation to Iran's energy sector

    International Nuclear Information System (INIS)

    Alipour, M.; Alighaleh, S.; Hafezi, R.; Omranievardi, M.

    2017-01-01

    With the historic nuclear agreement now in effect, Iran's energy sector expects a new transformation to spark back into life. The government seeks to recover the years of backwardness by capital injections and attract foreign cash into the sector long starved of investment. In this respect, an appropriate and convenient resource allocation scheme in a long-term perspective is vital to keep Iran's position as a major energy supplier. This study develops a new hybrid multi-criteria decision-making model through integrating fuzzy Analytical hierarchy process with the Cumulative belief degree model to effectively evaluate energy alternatives for investment in Iran. Fuzzy analytical hierarchy process adds more benefits to the integrated model by providing the fuzzy pairwise comparison to identify weights of criteria while the Cumulative belief degree approach offers higher quality results of overall experts' opinions since it can deal with the missing values. STEEP analysis is also used to ensure capturing influential factors in five categories: social, technological, economic, environmental, and political. As a real application, the proposed methodology is applied to prioritize major energy resources for investment in Iran. Results indicate that natural gas is the ideal option for receiving the highest funding priority followed by solar and oil. - Highlights: • A new hybrid multi-criteria decision making method is proposed. • Cumulative belief degree model is combined with fuzzy analytical hierarchy process. • Utilization of STEEP analysis to capture all influential parameters. • Evaluation of Iran's energy sector to prioritize alternatives for investment. • Natural gas is Iran's best energy investment option followed by solar and oil.

  5. Infectious disease modeling a hybrid system approach

    CERN Document Server

    Liu, Xinzhi

    2017-01-01

    This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.

  6. Uncertain Quality Function Deployment Using a Hybrid Group Decision Making Model

    Directory of Open Access Journals (Sweden)

    Ze-Ling Wang

    2016-11-01

    Full Text Available Quality function deployment (QFD is a widely used quality system tool for translating customer requirements (CRs into the engineering design requirements (DRs of products or services. The conventional QFD analysis, however, has been criticized as having some limitations such as in the assessment of relationships between CRs and DRs, the determination of CR weights and the prioritization of DRs. This paper aims to develop a new hybrid group decision-making model based on hesitant 2-tuple linguistic term sets and an extended QUALIFLEX (qualitative flexible multiple criteria method approach for handling QFD problems with incomplete weight information. First, hesitant linguistic term sets are combined with interval 2-tuple linguistic variables to express various uncertainties in the assessment information of QFD team members. Borrowing the idea of grey relational analysis (GRA, a multiple objective optimization model is constructed to determine the relative weights of CRs. Then, an extended QUALIFLEX approach with an inclusion comparison method is suggested to determine the ranking of the DRs identified in QFD. Finally, an analysis of a market segment selection problem is conducted to demonstrate and validate the proposed QFD approach.

  7. Making Career Decisions--A Sequential Elimination Approach.

    Science.gov (United States)

    Gati, Itamar

    1986-01-01

    Presents a model for career decision making based on the sequential elimination of occupational alternatives, an adaptation for career decisions of Tversky's (1972) elimination-by-aspects theory of choice. The expected utility approach is reviewed as a representative compensatory model for career decisions. Advantages, disadvantages, and…

  8. From Career Decision-Making Styles to Career Decision-Making Profiles: A Multidimensional Approach

    Science.gov (United States)

    Gati, Itamar; Landman, Shiri; Davidovitch, Shlomit; Asulin-Peretz, Lisa; Gadassi, Reuma

    2010-01-01

    Previous research on individual differences in career decision-making processes has often focused on classifying individuals into a few types of decision-making "styles" based on the most dominant trait or characteristic of their approach to the decision process (e.g., rational, intuitive, dependent; Harren, 1979). In this research, an…

  9. Using hybrid expert system approaches for engineering applications

    Science.gov (United States)

    Allen, R. H.; Boarnet, M. G.; Culbert, C. J.; Savely, R. T.

    1987-01-01

    In this paper, the use of hybrid expert system shells and hybrid (i.e., algorithmic and heuristic) approaches for solving engineering problems is reported. Aspects of various engineering problem domains are reviewed for a number of examples with specific applications made to recently developed prototype expert systems. Based on this prototyping experience, critical evaluations of and comparisons between commercially available tools, and some research tools, in the United States and Australia, and their underlying problem-solving paradigms are made. Characteristics of the implementation tool and the engineering domain are compared and practical software engineering issues are discussed with respect to hybrid tools and approaches. Finally, guidelines are offered with the hope that expert system development will be less time consuming, more effective, and more cost-effective than it has been in the past.

  10. Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

    DEFF Research Database (Denmark)

    Shuai, Hang; Ai, Xiaomeng; Wen, Jinyu

    2017-01-01

    This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future...

  11. A novel Monte Carlo approach to hybrid local volatility models

    NARCIS (Netherlands)

    A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

  12. A hybrid approach to designing inbound-resupply strategies

    NARCIS (Netherlands)

    Dullaert, Wout; Vernimmen, Bert; Raa, Birger; Witlox, Frank

    A new hybrid approach was developed to determine the optimal inbound-resupply strategy when suppliers ship goods to receivers. The optimal reorder level was calculated on the basis of a simulation of the distribution of demand and the lead time of the various sourcing alternatives. An evolutionary

  13. A hybrid generative-discriminative approach to speaker diarization

    NARCIS (Netherlands)

    Noulas, A.K.; van Kasteren, T.; Kröse, B.J.A.

    2008-01-01

    In this paper we present a sound probabilistic approach to speaker diarization. We use a hybrid framework where a distribution over the number of speakers at each point of a multimodal stream is estimated with a discriminative model. The output of this process is used as input in a generative model

  14. A hybrid agent-based approach for modeling microbiological systems.

    Science.gov (United States)

    Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

    2008-11-21

    Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

  15. A diagnostic expert system for NPP based on hybrid knowledge approach

    International Nuclear Information System (INIS)

    Yang, Joon On; Chang, Soon Heung

    1989-01-01

    This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem solving behavior modeled in HYPOSS. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies showed a good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

  16. Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2014-01-01

    Full Text Available Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone’s health. Although there are several ways to measure the body fat percentage (BFP, the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR, artificial neural network (ANN, multivariate adaptive regression splines (MARS, and support vector regression (SVR techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models.

  17. Optimization of decision rules based on dynamic programming approach

    KAUST Repository

    Zielosko, Beata

    2014-01-14

    This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.

  18. Hybrid methodological approach to context-dependent speech recognition

    Directory of Open Access Journals (Sweden)

    Dragiša Mišković

    2017-01-01

    Full Text Available Although the importance of contextual information in speech recognition has been acknowledged for a long time now, it has remained clearly underutilized even in state-of-the-art speech recognition systems. This article introduces a novel, methodologically hybrid approach to the research question of context-dependent speech recognition in human–machine interaction. To the extent that it is hybrid, the approach integrates aspects of both statistical and representational paradigms. We extend the standard statistical pattern-matching approach with a cognitively inspired and analytically tractable model with explanatory power. This methodological extension allows for accounting for contextual information which is otherwise unavailable in speech recognition systems, and using it to improve post-processing of recognition hypotheses. The article introduces an algorithm for evaluation of recognition hypotheses, illustrates it for concrete interaction domains, and discusses its implementation within two prototype conversational agents.

  19. A rough set approach for determining weights of decision makers in group decision making.

    Science.gov (United States)

    Yang, Qiang; Du, Ping-An; Wang, Yong; Liang, Bin

    2017-01-01

    This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs' decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member' decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs' evaluations and selections.

  20. A hybrid simulation approach for integrating safety behavior into construction planning: An earthmoving case study.

    Science.gov (United States)

    Goh, Yang Miang; Askar Ali, Mohamed Jawad

    2016-08-01

    One of the key challenges in improving construction safety and health is the management of safety behavior. From a system point of view, workers work unsafely due to system level issues such as poor safety culture, excessive production pressure, inadequate allocation of resources and time and lack of training. These systemic issues should be eradicated or minimized during planning. However, there is a lack of detailed planning tools to help managers assess the impact of their upstream decisions on worker safety behavior. Even though simulation had been used in construction planning, the review conducted in this study showed that construction safety management research had not been exploiting the potential of simulation techniques. Thus, a hybrid simulation framework is proposed to facilitate integration of safety management considerations into construction activity simulation. The hybrid framework consists of discrete event simulation (DES) as the core, but heterogeneous, interactive and intelligent (able to make decisions) agents replace traditional entities and resources. In addition, some of the cognitive processes and physiological aspects of agents are captured using system dynamics (SD) approach. The combination of DES, agent-based simulation (ABS) and SD allows a more "natural" representation of the complex dynamics in construction activities. The proposed hybrid framework was demonstrated using a hypothetical case study. In addition, due to the lack of application of factorial experiment approach in safety management simulation, the case study demonstrated sensitivity analysis and factorial experiment to guide future research. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Decision Dissonance: Evaluating an Approach to Measuring the Quality of Surgical Decision Making

    Science.gov (United States)

    Fowler, Floyd J.; Gallagher, Patricia M.; Drake, Keith M.; Sepucha, Karen R.

    2013-01-01

    Background Good decision making has been increasingly cited as a core component of good medical care, and shared decision making is one means of achieving high decision quality. If it is to be a standard, good measures and protocols are needed for assessing the quality of decisions. Consistency with patient goals and concerns is one defining characteristic of a good decision. A new method for evaluating decision quality for major surgical decisions was examined, and a methodology for collecting the needed data was developed. Methods For a national probability sample of fee-for-service Medicare beneficiaries who had a coronary artery bypass graft (CABG), a lumpectomy or a mastectomy for breast cancer, or surgery for prostate cancer during the last half of 2008, a mail survey of selected patients was carried out about one year after the procedures. Patients’ goals and concerns, knowledge, key aspects of interactions with clinicians, and feelings about the decisions were assessed. A Decision Dissonance Score was created that measured the extent to which patient ratings of goals ran counter to the treatment received. The construct and predictive validity of the Decision Dissonance Score was then assessed. Results When data were averaged across all four procedures, patients with more knowledge and those who reported more involvement reported significantly lower Decision Dissonance Scores. Patients with lower Decision Dissonance Scores also reported more confidence in their decisions and feeling more positively about how the treatment turned out, and they were more likely to say that they would make the same decision again. Conclusions Surveying discharged surgery patients is a feasible way to evaluate decision making, and Decision Dissonance appears to be a promising approach to validly measuring decision quality. PMID:23516764

  2. Neural substrates of approach-avoidance conflict decision-making

    Science.gov (United States)

    Aupperle, Robin L.; Melrose, Andrew J.; Francisco, Alex; Paulus, Martin P.; Stein, Murray B.

    2014-01-01

    Animal approach-avoidance conflict paradigms have been used extensively to operationalize anxiety, quantify the effects of anxiolytic agents, and probe the neural basis of fear and anxiety. Results from human neuroimaging studies support that a frontal-striatal-amygdala neural circuitry is important for approach-avoidance learning. However, the neural basis of decision-making is much less clear in this context. Thus, we combined a recently developed human approach-avoidance paradigm with functional magnetic resonance imaging (fMRI) to identify neural substrates underlying approach-avoidance conflict decision-making. Fifteen healthy adults completed the approach-avoidance conflict (AAC) paradigm during fMRI. Analyses of variance were used to compare conflict to non-conflict (avoid-threat and approach-reward) conditions and to compare level of reward points offered during the decision phase. Trial-by-trial amplitude modulation analyses were used to delineate brain areas underlying decision-making in the context of approach/avoidance behavior. Conflict trials as compared to the non-conflict trials elicited greater activation within bilateral anterior cingulate cortex (ACC), anterior insula, and caudate, as well as right dorsolateral prefrontal cortex. Right caudate and lateral PFC activation was modulated by level of reward offered. Individuals who showed greater caudate activation exhibited less approach behavior. On a trial-by-trial basis, greater right lateral PFC activation related to less approach behavior. Taken together, results suggest that the degree of activation within prefrontal-striatal-insula circuitry determines the degree of approach versus avoidance decision-making. Moreover, the degree of caudate and lateral PFC activation is related to individual differences in approach-avoidance decision-making. Therefore, the AAC paradigm is ideally suited to probe anxiety-related processing differences during approach-avoidance decision-making. PMID:25224633

  3. A Hybrid Multiattribute Decision Making Model for Evaluating Students’ Satisfaction towards Hostels

    Directory of Open Access Journals (Sweden)

    Anath Rau Krishnan

    2015-01-01

    Full Text Available This paper proposes a new hybrid multiattribute decision making (MADM model which deals with the interactions that usually exist between hostel attributes in the process of measuring the students’ satisfaction towards a set of hostels and identifying the optimal strategies for enhancing their satisfaction. The model uses systematic random stratified sampling approach for data collection purpose as students dwelling in hostels are “naturally” clustered by block and gender, factor analysis for extracting large set of hostel attributes into fewer independent factors, λ-measure for characterizing the interactions shared by the attributes within each factor, Choquet integral for aggregating the interactive performance scores within each factor, Mikhailov’s fuzzy analytical hierarchy process (MFAHP for determining the weights of independent factors, and simple weighted average (SWA operator to measure the overall satisfaction score of each hostel. A real evaluation involving fourteen Universiti Utara Malaysia (UUM hostels was carried out in order to demonstrate the model’s feasibility. The same evaluation was performed using an additive aggregation model in order to illustrate the effects of ignoring the interactions shared by attributes in hostel satisfaction analysis.

  4. Multi-criteria decision making approaches for green supply chains

    NARCIS (Netherlands)

    Banasik, Aleksander; Bloemhof-Ruwaard, Jacqueline M.; Kanellopoulos, Argyris; Claassen, G.D.H.; Vorst, van der Jack G.A.J.

    2016-01-01

    Designing Green Supply Chains (GSCs) requires complex decision-support models that can deal with multiple dimensions of sustainability while taking into account specific characteristics of products and their supply chain. Multi-Criteria Decision Making (MCDM) approaches can be used to quantify

  5. Dynamic Programming Approach for Exact Decision Rule Optimization

    KAUST Repository

    Amin, Talha

    2013-01-01

    This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from UCI Machine Learning Repository. © Springer-Verlag Berlin Heidelberg 2013.

  6. Dynamic programming approach to optimization of approximate decision rules

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2013-01-01

    This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number

  7. Social Context Effects on Decision-Making: A Neurobiological Approach

    NARCIS (Netherlands)

    M. Stallen (Mirre)

    2013-01-01

    textabstractThis thesis explores how social context influences the neurobiological processes underlying decision-making. To this end, this research takes an interdisciplinary approach, combining methods and insights from Psychology, Marketing, Economics, and Neuroscience. In particular, behavioural

  8. Reducing Post-Decision Dissonance in International Decisions: The Analytic Hierarchy Process Approach.

    Science.gov (United States)

    DuBois, Frank L.

    1999-01-01

    Describes use of the analytic hierarchy process (AHP) as a teaching tool to illustrate the complexities of decision making in an international environment. The AHP approach uses managerial input to develop pairwise comparisons of relevant decision criteria to efficiently generate an appropriate solution. (DB)

  9. Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

    Directory of Open Access Journals (Sweden)

    Jui-Yu Wu

    2013-01-01

    Full Text Available Stochastic global optimization (SGO algorithms such as the particle swarm optimization (PSO approach have become popular for solving unconstrained global optimization (UGO problems. The PSO approach, which belongs to the swarm intelligence domain, does not require gradient information, enabling it to overcome this limitation of traditional nonlinear programming methods. Unfortunately, PSO algorithm implementation and performance depend on several parameters, such as cognitive parameter, social parameter, and constriction coefficient. These parameters are tuned by using trial and error. To reduce the parametrization of a PSO method, this work presents two efficient hybrid SGO approaches, namely, a real-coded genetic algorithm-based PSO (RGA-PSO method and an artificial immune algorithm-based PSO (AIA-PSO method. The specific parameters of the internal PSO algorithm are optimized using the external RGA and AIA approaches, and then the internal PSO algorithm is applied to solve UGO problems. The performances of the proposed RGA-PSO and AIA-PSO algorithms are then evaluated using a set of benchmark UGO problems. Numerical results indicate that, besides their ability to converge to a global minimum for each test UGO problem, the proposed RGA-PSO and AIA-PSO algorithms outperform many hybrid SGO algorithms. Thus, the RGA-PSO and AIA-PSO approaches can be considered alternative SGO approaches for solving standard-dimensional UGO problems.

  10. Decision theory and choices a complexity approach

    CERN Document Server

    Kirman, Alan; Vinci, Concetto Paolo

    2010-01-01

    In economics agents are assumed to choose on the basis of rational calculations aimed at the maximization of their pleasure or profit. Formally, agents are said to manifest transitive and consistent preferences in attempting to maximize their utility in the presence of several constraints. They operate according to the choice imperative: given a set of alternatives, choose the best. This imperative works well in a static and simplistic framework, but it may fail or vary when 'the best' is changing continuously. This approach has been questioned by a descriptive approach that springing from the

  11. A novel hybridization approach for detection of citrus viroids.

    Science.gov (United States)

    Murcia, N; Serra, P; Olmos, A; Duran-Vila, N

    2009-04-01

    Citrus plants are natural hosts of several viroid species all belonging to the family Pospiviroidae. Previous attempts to detect viroids from field-grown species and cultivars yielded erratic results unless analyses were performed using Etrog citron a secondary bio-amplification host. To overcome the use of Etrog citron a number of RT-PCR approaches have been proposed with different degrees of success. Here we report the suitability of an easy to handle northern hybridization protocol for viroid detection of samples collected from field-grown citrus species and cultivars. The protocol involves: (i) Nucleic acid preparations from bark tissue samples collected from field-grown trees regardless of the growing season and storage conditions; (ii) Separation in 5% PAGE or 1% agarose, blotting to membrane and fixing; (iii) Hybridization with viroid-specific DIG-labelled probes and detection with anti-DIG-alkaline phosphatase conjugate and autoradiography with the CSPD substrate. The method has been tested with viroid-infected trees of sweet orange, lemon, mandarin, grapefruit, sour orange, Swingle citrumello, Tahiti lime and Mexican lime. This novel hybridization approach is extremely sensitive, easy to handle and shortens the time needed for reliable viroid indexing tests. The suitability of PCR generated DIG-labelled probes and the sensitivity achieved when the samples are separated and blotted from non-denaturing gels are discussed.

  12. Aiding Lay Decision Making Using a Cognitive Competencies Approach.

    Science.gov (United States)

    Maule, A J; Maule, Simon

    2015-01-01

    Two prescriptive approaches have evolved to aid human decision making: just in time interventions that provide support as a decision is being made; and just in case interventions that educate people about future events that they may encounter so that they are better prepared to make an informed decision when these events occur. We review research on these two approaches developed in the context of supporting everyday decisions such as choosing an apartment, a financial product or a medical procedure. We argue that the lack of an underlying prescriptive theory has limited the development and evaluation of these interventions. We draw on recent descriptive research on the cognitive competencies that underpin human decision making to suggest new ways of interpreting how and why existing decision aids may be effective and suggest a different way of evaluating their effectiveness. We also briefly outline how our approach has the potential to develop new interventions to support everyday decision making and highlight the benefits of drawing on descriptive research when developing and evaluating interventions.

  13. Forecasting conditional climate-change using a hybrid approach

    Science.gov (United States)

    Esfahani, Akbar Akbari; Friedel, Michael J.

    2014-01-01

    A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.

  14. Benefit-Risk Analysis for Decision-Making: An Approach.

    Science.gov (United States)

    Raju, G K; Gurumurthi, K; Domike, R

    2016-12-01

    The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB). © 2016 American Society for Clinical Pharmacology and Therapeutics.

  15. Compromise between Short- and Long-Term Financial Sustainability: A Hybrid Model for Supporting R&D Decisions

    Directory of Open Access Journals (Sweden)

    Kao-Yi Shen

    2017-03-01

    Full Text Available The debate of “short-termism” has gained increasing interests from various fields, ranging from management to economics; it mainly concerns the decisions or actions taken by businesses that might yield short-term returns at the cost of long-term value or sustainability. Previous studies have highlighted this dilemma faced by managers, mainly from the pressure of capital markets or short-sighted shareholders who crave for immediate financial outcomes; intelligent decision aids that can compromise between the short- and long-term financial sustainability, based on a company’s policy, are highly needed. Therefore, the aim of this study is to develop a multiple-rule-based hybrid decision model to support management teams on prioritizing new R&D projects, considering the financial prospects in dual timeframes (i.e., short- and long-term for sustainability. Furthermore, in the presence of business uncertainty and the limited knowledge of managers on new projects, the intuitionistic fuzzy technique is incorporated. A case of selecting new R&D projects for an IC design company is illustrated using the proposed approach, and the financial data from a group of public-listed IC stocks from Taiwan are inducted to form the decision model. The findings not only support the IC design company to select new projects but also provide business insights to facilitate the understandings of this controversial issue in managerial practice.

  16. A hybrid approach for probabilistic forecasting of electricity price

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Wang, Yelei

    2014-01-01

    to the nonstationarities involved in market clearing prices (MCPs), it is rather difficult to accurately predict MCPs in advance. The challenge is getting intensified as more and more renewable energy and other new technologies emerged in smart grids. Therefore transformation from traditional point forecasts...... electricity price forecasting is proposed in this paper. The effectiveness of the proposed hybrid method has been validated through comprehensive tests using real price data from Australian electricity market.......The electricity market plays a key role in realizing the economic prophecy of smart grids. Accurate and reliable electricity market price forecasting is essential to facilitate various decision making activities of market participants in the future smart grid environment. However, due...

  17. A hybrid approach for efficient anomaly detection using metaheuristic methods

    Directory of Open Access Journals (Sweden)

    Tamer F. Ghanem

    2015-07-01

    Full Text Available Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

  18. Approaches to Low Fuel Regression Rate in Hybrid Rocket Engines

    Directory of Open Access Journals (Sweden)

    Dario Pastrone

    2012-01-01

    Full Text Available Hybrid rocket engines are promising propulsion systems which present appealing features such as safety, low cost, and environmental friendliness. On the other hand, certain issues hamper the development hoped for. The present paper discusses approaches addressing improvements to one of the most important among these issues: low fuel regression rate. To highlight the consequence of such an issue and to better understand the concepts proposed, fundamentals are summarized. Two approaches are presented (multiport grain and high mixture ratio which aim at reducing negative effects without enhancing regression rate. Furthermore, fuel material changes and nonconventional geometries of grain and/or injector are presented as methods to increase fuel regression rate. Although most of these approaches are still at the laboratory or concept scale, many of them are promising.

  19. A hybrid personalized data recommendation approach for geoscience data sharing

    Science.gov (United States)

    WANG, M.; Wang, J.

    2016-12-01

    Recommender systems are effective tools helping Internet users overcome information overloading. The two most widely used recommendation algorithms are collaborating filtering (CF) and content-based filtering (CBF). A number of recommender systems based on those two algorithms were developed for multimedia, online sells, and other domains. Each of the two algorithms has its advantages and shortcomings. Hybrid approaches that combine these two algorithms are better choices in many cases. In geoscience data sharing domain, where the items (datasets) are more informative (in space and time) and domain-specific, no recommender system is specialized for data users. This paper reports a dynamic weighted hybrid recommendation algorithm that combines CF and CBF for geoscience data sharing portal. We first derive users' ratings on items with their historical visiting time by Jenks Natural Break. In the CBF part, we incorporate the space, time, and subject information of geoscience datasets to compute item similarity. Predicted ratings were computed with k-NN method separately using CBF and CF, and then combined with weights. With training dataset we attempted to find the best model describing ideal weights and users' co-rating numbers. A logarithmic function was confirmed to be the best model. The model was then used to tune the weights of CF and CBF on user-item basis with test dataset. Evaluation results show that the dynamic weighted approach outperforms either solo CF or CBF approach in terms of Precision and Recall.

  20. Can quantum approaches benefit biology of decision making?

    Science.gov (United States)

    Takahashi, Taiki

    2017-11-01

    Human decision making has recently been focused in the emerging fields of quantum decision theory and neuroeconomics. The former discipline utilizes mathematical formulations developed in quantum theory, while the latter combines behavioral economics and neurobiology. In this paper, the author speculates on possible future directions unifying the two approaches, by contrasting the roles of quantum theory in the birth of molecular biology of the gene. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Hybrid closure of atrial septal defect: A modified approach

    Directory of Open Access Journals (Sweden)

    Kshitij Sheth

    2015-01-01

    Full Text Available A 3.5-year-old girl underwent transcatheter closure of patent ductus arteriosus in early infancy during which time her secundum atrial septal defect (ASD was left alone. When she came for elective closure of ASD, she was found to have bilaterally blocked femoral veins. The defect was successfully closed with an Amplatzer septal occluder (ASO; St. Jude Medical, Plymouth, MN, USA using a hybrid approach via a sub-mammary mini-thoracotomy incision without using cardiopulmonary bypass. At the end of 1-year follow-up, the child is asymptomatic with device in a stable position without any residual shunt.

  2. Dynamic programming approach to optimization of approximate decision rules

    KAUST Repository

    Amin, Talha

    2013-02-01

    This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number of unordered pairs of rows with different decisions in the decision table T. For a nonnegative real number β, we consider β-decision rules that localize rows in subtables of T with uncertainty at most β. Our algorithm constructs a directed acyclic graph Δβ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most β. The graph Δβ(T) allows us to describe the whole set of so-called irredundant β-decision rules. We can describe all irredundant β-decision rules with minimum length, and after that among these rules describe all rules with maximum coverage. We can also change the order of optimization. The consideration of irredundant rules only does not change the results of optimization. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2012 Elsevier Inc. All rights reserved.

  3. Dynamic programming approach for partial decision rule optimization

    KAUST Repository

    Amin, Talha

    2012-10-04

    This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

  4. Dynamic programming approach for partial decision rule optimization

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2012-01-01

    This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

  5. The balance space approach to multicriteria decision making—involving the decision maker

    OpenAIRE

    Ehrgott, M.

    2002-01-01

    The balance space approach (introduced by Galperin in 1990) provides a new view on multicriteria optimization. Looking at deviations from global optimality of the different objectives, balance points and balance numbers are defined when either different or equal deviations for each objective are allowed. Apportioned balance numbers allow the specification of proportions among the deviations. Through this concept the decision maker can be involved in the decision process. In this paper we prov...

  6. Assessment of New Approaches in Geothermal Exploration Decision Making: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Akar, S.; Young, K. R.

    2015-02-01

    Geothermal exploration projects have significant amount of risk associated with uncertainties encountered in the discovery of the geothermal resource. Understanding when and how to proceed in an exploration program, and when to walk away from a site, are two of the largest challenges for increased geothermal deployment. Current methodologies for exploration decision making is left to subjective by subjective expert opinion which can be incorrectly biased by expertise (e.g. geochemistry, geophysics), geographic location of focus, and the assumed conceptual model. The aim of this project is to develop a methodology for more objective geothermal exploration decision making at a given location, including go-no-go decision points to help developers and investors decide when to give up on a location. In this scope, two different approaches are investigated: 1) value of information analysis (VOIA) which is used for evaluating and quantifying the value of a data before they are purchased, and 2) enthalpy-based exploration targeting based on reservoir size, temperature gradient estimates, and internal rate of return (IRR). The first approach, VOIA, aims to identify the value of a particular data when making decisions with an uncertain outcome. This approach targets the pre-drilling phase of exploration. These estimated VOIs are highly affected by the size of the project and still have a high degree of subjectivity in assignment of probabilities. The second approach, exploration targeting, is focused on decision making during the drilling phase. It starts with a basic geothermal project definition that includes target and minimum required production capacity and initial budgeting for exploration phases. Then, it uses average temperature gradient, reservoir temperature estimates, and production capacity to define targets and go/no-go limits. The decision analysis in this approach is based on achieving a minimum IRR at each phase of the project. This second approach was

  7. An Adaptive and Hybrid Approach for Revisiting the Visibility Pipeline

    Directory of Open Access Journals (Sweden)

    Ícaro Lins Leitão da Cunha

    2016-04-01

    Full Text Available We revisit the visibility problem, which is traditionally known in Computer Graphics and Vision fields as the process of computing a (potentially visible set of primitives in the computational model of a scene. We propose a hybrid solution that uses a dry structure (in the sense of data reduction, a triangulation of the type J1a, to accelerate the task of searching for visible primitives. We came up with a solution that is useful for real-time, on-line, interactive applications as 3D visualization. In such applications the main goal is to load the minimum amount of primitives from the scene during the rendering stage, as possible. For this purpose, our algorithm executes the culling by using a hybrid paradigm based on viewing-frustum, back-face culling and occlusion models. Results have shown substantial improvement over these traditional approaches if applied separately. This novel approach can be used in devices with no dedicated processors or with low processing power, as cell phones or embedded displays, or to visualize data through the Internet, as in virtual museums applications.

  8. A Hybrid Genetic Algorithm Approach for Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Sydulu Maheswarapu

    2011-08-01

    Full Text Available This paper puts forward a reformed hybrid genetic algorithm (GA based approach to the optimal power flow. In the approach followed here, continuous variables are designed using real-coded GA and discrete variables are processed as binary strings. The outcomes are compared with many other methods like simple genetic algorithm (GA, adaptive genetic algorithm (AGA, differential evolution (DE, particle swarm optimization (PSO and music based harmony search (MBHS on a IEEE30 bus test bed, with a total load of 283.4 MW. Its found that the proposed algorithm is found to offer lowest fuel cost. The proposed method is found to be computationally faster, robust, superior and promising form its convergence characteristics.

  9. An object-oriented approach to site characterization decision support

    International Nuclear Information System (INIS)

    Johnson, R.

    1995-01-01

    Effective decision support for site characterization is key to determining the nature and extent of contamination and the associated human and environmental risks. Site characterization data, however, present particular problems to technical analysts and decision-makers. Such data are four dimensional, incorporating temporal and spatial components. Their sheer volume can be daunting -- sites with hundreds of monitoring wells and thousands of samples sent for laboratory analyses are not uncommon. Data are derived from a variety of sources including laboratory analyses, non-intrusive geophysical surveys, historical information, bore logs, in-field estimates of key physical parameters such as aquifer transmissivity, soil moisture content, depth-to-water table, etc. Ultimately, decisions have to be made based on data that are always incomplete, often confusing, inaccurate, or inappropriate, and occasionally wrong. In response to this challenge, two approaches to environmental decision support have arisen, Data Quality Objectives (DQOS) and the Observational Approach (OA). DQOs establish criteria for data collection by clearly defining the decisions that need to be made, the uncertainty that can be tolerated, and the type and amount of data that needs to be collected to satisfy the uncertainty requirements. In practice, DQOs are typically based on statistical measures. The OA accepts the fact that the process of characterizing and remediating contaminated sites is always uncertain. Decision-making with the OA is based on what is known about a site, with contingencies developed for potential future deviations from the original assumptions about contamination nature, extent, and risks posed

  10. Evaluation of wind power generation potential using a three hybrid approach for households in Ardebil Province, Iran

    International Nuclear Information System (INIS)

    Qolipour, Mojtaba; Mostafaeipour, Ali; Shamshirband, Shahaboddin; Alavi, Omid; Goudarzi, Hossein; Petković, Dalibor

    2016-01-01

    Highlights: • Technical–economic feasibility of small wind turbines for six areas in Ardabil province of Iran was investigated. • Hybrid approach of Data Envelopment Analysis, Balanced Scorecard, and Game Theory was analyzed. • HOMER software was used for economic evaluation. • Technical–economic feasibility was studied using wind speed data during 2008–2014. • The areas of Airport, Nir, Namin, BilaSavar, Firozabad and Ardabil were ranked from first to last, respectively. - Abstract: The objective of the present paper is to conduct a thorough technical–economic evaluation for the construction of small wind turbines in six areas within Ardabil province of Iran using the Hybrid Optimization of Multiple Energy Resources software, and also to rank these areas by a hybrid approach composed of Data Envelopment Analysis, Balanced Scorecard, and Game Theory methodologies. Higher accuracy of the proposed hybrid approach and its ability to properly detect the relationships between the decision-making components make it preferable over the simple Data Envelopment Analysis method. Technical–economic feasibility study is conducted by analyzing wind speed data for period from 2008 to 2014 using Hybrid Optimization of Multiple Energy Resources software. In the next step, the type of equipment used in the design, benefit, costs, total net costs, depreciation and amount of generated electricity are obtained separately for each location. The results show that; Airport, Nir, Namin, Bilasavar, Firozabad and Ardabil were rank first to last respectively.

  11. A regret theory approach to decision curve analysis: a novel method for eliciting decision makers' preferences and decision-making.

    Science.gov (United States)

    Tsalatsanis, Athanasios; Hozo, Iztok; Vickers, Andrew; Djulbegovic, Benjamin

    2010-09-16

    Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat) vs. "commissions" (e.g. treating unnecessary) and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may be intuitively more appealing to a decision-maker, particularly

  12. A regret theory approach to decision curve analysis: A novel method for eliciting decision makers' preferences and decision-making

    Directory of Open Access Journals (Sweden)

    Vickers Andrew

    2010-09-01

    Full Text Available Abstract Background Decision curve analysis (DCA has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1, and analytical, deliberative process (system 2, thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. Methods First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. Results We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat vs. "commissions" (e.g. treating unnecessary and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. Conclusions We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may

  13. Genetic algorithm and neural network hybrid approach for job-shop scheduling

    OpenAIRE

    Zhao, Kai; Yang, Shengxiang; Wang, Dingwei

    1998-01-01

    Copyright @ 1998 ACTA Press This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach for job-shop scheduling with respect to the quality of solutions and ...

  14. A Behavioral Decision Making Modeling Approach Towards Hedging Services

    NARCIS (Netherlands)

    Pennings, J.M.E.; Candel, M.J.J.M.; Egelkraut, T.M.

    2003-01-01

    This paper takes a behavioral approach toward the market for hedging services. A behavioral decision-making model is developed that provides insight into how and why owner-managers decide the way they do regarding hedging services. Insight into those choice processes reveals information needed by

  15. A different approach to quantifying fire risks when decision making

    International Nuclear Information System (INIS)

    Hay, Adrian

    1991-01-01

    This article outlines an alternative approach to fire safety design which involves decision making on the basis of risk considerations. The methodology is being developed in conjunction with the nuclear industry but is considered equally applicable to other industrial facilities. (author)

  16. Multimodal Logistics Network Design over Planning Horizon through a Hybrid Meta-Heuristic Approach

    Science.gov (United States)

    Shimizu, Yoshiaki; Yamazaki, Yoshihiro; Wada, Takeshi

    Logistics has been acknowledged increasingly as a key issue of supply chain management to improve business efficiency under global competition and diversified customer demands. This study aims at improving a quality of strategic decision making associated with dynamic natures in logistics network optimization. Especially, noticing an importance to concern with a multimodal logistics under multiterms, we have extended a previous approach termed hybrid tabu search (HybTS). The attempt intends to deploy a strategic planning more concretely so that the strategic plan can link to an operational decision making. The idea refers to a smart extension of the HybTS to solve a dynamic mixed integer programming problem. It is a two-level iterative method composed of a sophisticated tabu search for the location problem at the upper level and a graph algorithm for the route selection at the lower level. To keep efficiency while coping with the resulting extremely large-scale problem, we invented a systematic procedure to transform the original linear program at the lower-level into a minimum cost flow problem solvable by the graph algorithm. Through numerical experiments, we verified the proposed method outperformed the commercial software. The results indicate the proposed approach can make the conventional strategic decision much more practical and is promising for real world applications.

  17. A Hybrid Satellite-Terrestrial Approach to Aeronautical Communication Networks

    Science.gov (United States)

    Kerczewski, Robert J.; Chomos, Gerald J.; Griner, James H.; Mainger, Steven W.; Martzaklis, Konstantinos S.; Kachmar, Brian A.

    2000-01-01

    Rapid growth in air travel has been projected to continue for the foreseeable future. To maintain a safe and efficient national and global aviation system, significant advances in communications systems supporting aviation are required. Satellites will increasingly play a critical role in the aeronautical communications network. At the same time, current ground-based communications links, primarily very high frequency (VHF), will continue to be employed due to cost advantages and legacy issues. Hence a hybrid satellite-terrestrial network, or group of networks, will emerge. The increased complexity of future aeronautical communications networks dictates that system-level modeling be employed to obtain an optimal system fulfilling a majority of user needs. The NASA Glenn Research Center is investigating the current and potential future state of aeronautical communications, and is developing a simulation and modeling program to research future communications architectures for national and global aeronautical needs. This paper describes the primary requirements, the current infrastructure, and emerging trends of aeronautical communications, including a growing role for satellite communications. The need for a hybrid communications system architecture approach including both satellite and ground-based communications links is explained. Future aeronautical communication network topologies and key issues in simulation and modeling of future aeronautical communications systems are described.

  18. A Hybrid Soft Computing Approach for Subset Problems

    Directory of Open Access Journals (Sweden)

    Broderick Crawford

    2013-01-01

    Full Text Available Subset problems (set partitioning, packing, and covering are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S can be partitioned into smaller subsets. All items in S must be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions and set covering (all items must be contained in at least one partition. Here, we present a hybrid solver based on ant colony optimization (ACO combined with arc consistency for solving this kind of problems. ACO is a swarm intelligence metaheuristic inspired on ants behavior when they search for food. It allows to solve complex combinatorial problems for which traditional mathematical techniques may fail. By other side, in constraint programming, the solving process of Constraint Satisfaction Problems can dramatically reduce the search space by means of arc consistency enforcing constraint consistencies either prior to or during search. Our hybrid approach was tested with set covering and set partitioning dataset benchmarks. It was observed that the performance of ACO had been improved embedding this filtering technique in its constructive phase.

  19. A hybrid data compression approach for online backup service

    Science.gov (United States)

    Wang, Hua; Zhou, Ke; Qin, MingKang

    2009-08-01

    With the popularity of Saas (Software as a service), backup service has becoming a hot topic of storage application. Due to the numerous backup users, how to reduce the massive data load is a key problem for system designer. Data compression provides a good solution. Traditional data compression application used to adopt a single method, which has limitations in some respects. For example data stream compression can only realize intra-file compression, de-duplication is used to eliminate inter-file redundant data, compression efficiency cannot meet the need of backup service software. This paper proposes a novel hybrid compression approach, which includes two levels: global compression and block compression. The former can eliminate redundant inter-file copies across different users, the latter adopts data stream compression technology to realize intra-file de-duplication. Several compressing algorithms were adopted to measure the compression ratio and CPU time. Adaptability using different algorithm in certain situation is also analyzed. The performance analysis shows that great improvement is made through the hybrid compression policy.

  20. Systematic approaches to data analysis from the Critical Decision Method

    Directory of Open Access Journals (Sweden)

    Martin Sedlár

    2015-01-01

    Full Text Available The aim of the present paper is to introduce how to analyse the qualitative data from the Critical Decision Method. At first, characterizing the method provides the meaningful introduction into the issue. This method used in naturalistic decision making research is one of the cognitive task analysis methods, it is based on the retrospective semistructured interview about critical incident from the work and it may be applied in various domains such as emergency services, military, transport, sport or industry. Researchers can make two types of methodological adaptation. Within-method adaptations modify the way of conducting the interviews and cross-method adaptations combine this method with other related methods. There are many decsriptions of conducting the interview, but the descriptions how the data should be analysed are rare. Some researchers use conventional approaches like content analysis, grounded theory or individual procedures with reference to the objectives of research project. Wong (2004 describes two approaches to data analysis proposed for this method of data collection, which are described and reviewed in the details. They enable systematic work with a large amount of data. The structured approach organizes the data according to an a priori analysis framework and it is suitable for clearly defined object of research. Each incident is studied separately. At first, the decision chart showing the main decision points and then the incident summary are made. These decision points are used to identify the relevant statements from the transcript, which are analysed in terms of the Recognition-Primed Decision Model. Finally, the results from all the analysed incidents are integrated. The limitation of the structured approach is it may not reveal some interesting concepts. The emergent themes approach helps to identify these concepts while maintaining a systematic framework for analysis and it is used for exploratory research design. It

  1. Dry Port Location Problem: A Hybrid Multi-Criteria Approach

    Directory of Open Access Journals (Sweden)

    BENTALEB Fatimazahra

    2016-03-01

    Full Text Available Choosing a location for a dry port is a problem which becomes more essential and crucial. This study deals with the problem of locating dry ports. On this matter, a model combining multi-criteria (MACBETH and mono-criteria (BARYCENTER methods to find a solution to dry port location problem has been proposed. In the first phase, a systematic literature review was carried out on dry port location problem and then a methodological classification was presented for this research. In the second phase, a hybrid multi-criteria approach was developed in order to determine the best dry port location taking different criteria into account. A Computational practice and a qualitative analysis from a case study in the Moroccan context have been provided. The results show that the optimal location is very convenient with the geographical region and the government policies.

  2. Decision-theoretic approaches to non-knowledge in economics

    OpenAIRE

    Svetlova, Ekaterina; van Elst, Henk

    2014-01-01

    We review two strands of conceptual approaches to the formal representation of a decision maker's non-knowledge at the initial stage of a static one-person, one-shot decision problem in economic theory. One focuses on representations of non-knowledge in terms of probability measures over sets of mutually exclusive and exhaustive consequence-relevant states of Nature, the other deals with unawareness of potentially important events by means of sets of states that are less complete than the ful...

  3. Multi-criteria Group Decision Making Approach for Teacher Recruitment in Higher Education under Simplified Neutrosophic Environment

    Directory of Open Access Journals (Sweden)

    Kalyan Mondal

    2014-12-01

    Full Text Available Teacher recruitment is a multi-criteria group decisionmaking process involving subjectivity, imprecision, and fuzziness that can be suitably represented by neutrosophic sets. Neutrosophic set, a generalization of fuzzy sets is characterized by a truth-membership function, falsity-membership function and an indeterminacy-membership function. These functions are real standard or non-standard subsets of ] 0-, 1+[ .There is no restriction on the sum of the functions, so the sum lies between ]0-, 3+[. A neutrosophic approach is a more general and suitable way to deal with imprecise information, when compared to a fuzzy set. The purpose of this study is to develop a neutrosophic multi-criteria group decision-making model based on hybrid scoreaccuracy functions for teacher recruitment in higher education. Eight criteria obtained from expert opinions are considered for recruitment process. The criteria are namely academic performance index, teaching aptitude, subject knowledge, research experience, leadership quality, personality, management capacity, and personal values. In this paper we use the score and accuracy functions and the hybrid score-accuracy functions of single valued neutrosophic numbers (SVNNs and ranking method for SVNNs. Then, multi-criteria group decision-making method with unknown weights for attributes and incompletely known weights for decision makers is used based on the hybrid score-accuracy functions under single valued neutrosophic environments. We use weight model for attributes based on the hybrid score-accuracy functions to derive the weights of decision makers and attributes from the decision matrices represented by the form of SVNNs to decrease the effect of some unreasonable evaluations. Moreover, we use the overall evaluation formulae of the weighted hybrid scoreaccuracy functions for each alternative to rank the alternatives and recruit the most desirable teachers. Finally, an educational problem for teacher selection is

  4. Heuristic hybrid game approach for fleet condition-based maintenance planning

    International Nuclear Information System (INIS)

    Feng, Qiang; Bi, Xiong; Zhao, Xiujie; Chen, Yiran; Sun, Bo

    2017-01-01

    The condition-based maintenance (CBM) method is commonly used to select appropriate maintenance opportunities according to equipment status over a period of time. The CBM of aircraft fleets is a fleet maintenance planning problem. In this problem, mission requirements, resource constraints, and aircraft statuses are considered to find an optimal strategy set. Given that the maintenance strategies for each aircraft are finite, fleet CBM can be treated as a combinatorial optimization problem. In this study, the process of making a decision on the CBM of military fleets is analyzed. The fleet CBM problem is treated as a two-stage dynamic decision-making problem. Aircraft are divided into dispatch and standby sets; thus, the problem scale is significantly reduced. A heuristic hybrid game (HHG) approach comprising a competition game and a cooperative game is proposed on the basis of heuristic rule. In the dispatch set, a competition game approach is proposed to search for a local optimal strategy matrix. A cooperative game method for the two sets is also proposed to ensure global optimization. Finally, a case study regarding a fleet comprising 20 aircraft is conducted, with the results proving that the approach efficiently generates outcomes that meet the mission risk-oriented schedule requirement. - Highlights: • A new heuristic hybrid game method for fleet condition-based maintenance is proposed. • The problem is simplified by hierarchical solving based on dispatch and standby set. • The local optimal solution is got by competition game algorithm for dispatch set. • The global optimal solution is got by cooperative game algorithm between two sets.

  5. Attention-level transitory response: a novel hybrid BCI approach

    Science.gov (United States)

    Diez, Pablo F.; Garcés Correa, Agustina; Orosco, Lorena; Laciar, Eric; Mut, Vicente

    2015-10-01

    Objective. People with disabilities may control devices such as a computer or a wheelchair by means of a brain-computer interface (BCI). BCI based on steady-state visual evoked potentials (SSVEP) requires visual stimulation of the user. However, this SSVEP-based BCI suffers from the ‘Midas touch effect’, i.e., the BCI can detect an SSVEP even when the user is not gazing at the stimulus. Then, these incorrect detections deteriorate the performance of the system, especially in asynchronous BCI because ongoing EEG is classified. In this paper, a novel transitory response of the attention-level of the user is reported. It was used to develop a hybrid BCI (hBCI). Approach. Three methods are proposed to detect the attention-level of the user. They are based on the alpha rhythm and theta/beta rate. The proposed hBCI scheme is presented along with these methods. Hence, the hBCI sends a command only when the user is at a high-level of attention, or in other words, when the user is really focused on the task being performed. The hBCI was tested over two different EEG datasets. Main results. The performance of the hybrid approach is superior to the standard one. Improvements of 20% in accuracy and 10 bits min-1 are reported. Moreover, the attention-level is extracted from the same EEG channels used in SSVEP detection and this way, no extra hardware is needed. Significance. A transitory response of EEG signal is used to develop the attention-SSVEP hBCI which is capable of reducing the Midas touch effect.

  6. Hybrid x-space: a new approach for MPI reconstruction.

    Science.gov (United States)

    Tateo, A; Iurino, A; Settanni, G; Andrisani, A; Stifanelli, P F; Larizza, P; Mazzia, F; Mininni, R M; Tangaro, S; Bellotti, R

    2016-06-07

    Magnetic particle imaging (MPI) is a new medical imaging technique capable of recovering the distribution of superparamagnetic particles from their measured induced signals. In literature there are two main MPI reconstruction techniques: measurement-based (MB) and x-space (XS). The MB method is expensive because it requires a long calibration procedure as well as a reconstruction phase that can be numerically costly. On the other side, the XS method is simpler than MB but the exact knowledge of the field free point (FFP) motion is essential for its implementation. Our simulation work focuses on the implementation of a new approach for MPI reconstruction: it is called hybrid x-space (HXS), representing a combination of the previous methods. Specifically, our approach is based on XS reconstruction because it requires the knowledge of the FFP position and velocity at each time instant. The difference with respect to the original XS formulation is how the FFP velocity is computed: we estimate it from the experimental measurements of the calibration scans, typical of the MB approach. Moreover, a compressive sensing technique is applied in order to reduce the calibration time, setting a fewer number of sampling positions. Simulations highlight that HXS and XS methods give similar results. Furthermore, an appropriate use of compressive sensing is crucial for obtaining a good balance between time reduction and reconstructed image quality. Our proposal is suitable for open geometry configurations of human size devices, where incidental factors could make the currents, the fields and the FFP trajectory irregular.

  7. Nuclear emergency response planning based on participatory decision analytic approaches

    International Nuclear Information System (INIS)

    Sinkko, K.

    2004-10-01

    This work was undertaken in order to develop methods and techniques for evaluating systematically and comprehensively protective action strategies in the case of a nuclear or radiation emergency. This was done in a way that the concerns and issues of all key players related to decisions on protective actions could be aggregated into decision- making transparently and in an equal manner. An approach called facilitated workshop, based on the theory of Decision Analysis, was tailored and tested in the planning of actions to be taken. The work builds on case studies in which it was assumed that a hypothetical accident in a nuclear power plant had led to a release of considerable amounts of radionuclides and therefore different types of protective actions should be considered. Altogether six workshops were organised in which all key players were represented, i.e., the authorities, expert organisations, industry and agricultural producers. The participants were those responsible for preparing advice or presenting matters for those responsible for the formal decision-making. Many preparatory meetings were held with various experts to prepare information for the workshops. It was considered essential that the set-up strictly follow the decision- making process to which the key players are accustomed. Key players or stakeholders comprise responsible administrators and organisations, politicians as well as representatives of the citizens affected and other persons who will and are likely to take part in decision-making in nuclear emergencies. The realistic nature and the disciplined process of a facilitated workshop and commitment to decision-making yielded up insight in many radiation protection issues. The objectives and attributes which are considered in a decision on protective actions were discussed in many occasions and were defined for different accident scenario to come. In the workshops intervention levels were derived according justification and optimisation

  8. A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products

    Directory of Open Access Journals (Sweden)

    Animesh Debnath

    2017-07-01

    Full Text Available Due to the increasing size of the population, society faces several challenges for sustainable and adequate agricultural production, quality, distribution, and food safety in the strategic project portfolio selection (SPPS. The initial adaptation of strategic portfolio management of genetically modified (GM Agro by-products (Ab-Ps is a huge challenge in terms of processing the agro food product supply-chain practices in an environmentally nonthreatening way. As a solution to the challenges, the socio-economic characteristics for SPPS of GM food purchasing scenarios are studied. Evaluation and selection of the GM agro portfolio management are the dynamic issues due to physical and immaterial criteria involving a hybrid multiple criteria decision making (MCDM approach, combining modified grey Decision-Making Trial and Evaluation Laboratory (DEMATEL, Multi-Attributive Border Approximation area Comparison (MABAC and sensitivity analysis. Evaluation criteria are grouped into social, differential and beneficial clusters, and the modified DEMATEL procedure is used to derive the criteria weights. The MABAC method is applied to rank the strategic project portfolios according to the aggregated preferences of decision makers (DMs. The usefulness of the proposed research framework is validated with a case study. The GM by-products are found to be the best portfolio. Moreover, this framework can unify the policies of agro technological improvement, corporate social responsibility (CSR and agro export promotion.

  9. Decision From Indecision: Conservation of Thangka Significance, Perspectives and Approaches

    Directory of Open Access Journals (Sweden)

    Jacinta Boon Nee Loh

    2002-11-01

    Full Text Available Art may be entwined with religion, encompassing a spiritual message beyond artistic form and design. The thangka is one such sacred art in this world. Each thangka is created for a specific purpose and will always be different from other ones. It is for this reason and other values that they are conserved for the present and the future. The thangka poses complex challenges for conservators because of its composite nature and the wealth of values it embodies. It demands a balanced approach that looks into its material and conceptual integrity. Each of us has different aesthetic standards in interpretation of the thangka. This research explores the approaches and perspectives of thangka conservation, in particular embroidered/ appliqué thangkas and the influence of their significance in the decision-making process of their conservation. Through this investigation, the author establishes a framework of decision-making and her perspectives to thangka conservation.

  10. HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.

    Science.gov (United States)

    Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

    2017-12-01

    For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm. HAMDA took not only network structure and information propagation but also node attribution into consideration, resulting in a satisfactory prediction performance. Specifically, HAMDA obtained AUCs of 0.9035 and 0.8395 in the frameworks of global and local leave-one-out cross validation, respectively. Meanwhile, HAMDA also achieved good performance with AUC of 0.8965 ± 0.0012 in 5-fold cross validation. Additionally, we conducted case studies about three important human cancers for performance evaluation of HAMDA. As a result, 90% (Lymphoma), 86% (Prostate Cancer) and 92% (Kidney Cancer) of top 50 predicted miRNAs were confirmed by recent experiment literature, which showed the reliable prediction ability of HAMDA. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

    Science.gov (United States)

    Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

    2016-01-01

    Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

  12. An energy management approach of hybrid vehicles using traffic preview information for energy saving

    International Nuclear Information System (INIS)

    Zheng, Chunhua; Xu, Guoqing; Xu, Kun; Pan, Zhongming; Liang, Quan

    2015-01-01

    Highlights: • Energy management approach of hybrid vehicles using traffic preview information. • Vehicle velocity profile and fuel consumption are optimized at the same time. • It is proved that a further energy saving is achieved by the proposed approach. • The proposed approach is useful especially for autonomous hybrid vehicles. - Abstract: The traffic preview information is very helpful for hybrid vehicles when distributing the power requirement of the vehicle to power sources and when determining the next driving route of the vehicle. In this research, an energy management approach for hybrid vehicles is proposed, which optimizes the vehicle velocity profile while minimizing the fuel consumption with the help of the traffic preview information, so that a further energy saving for hybrid vehicles can be achieved. The Pontryagin’s Minimum Principle (PMP) is adopted on the proposed approach. A fuel cell hybrid vehicle (FCHV) is selected as an example, and the proposed energy management approach is applied to the FCHV in a computer simulation environment for the offline and online cases respectively. Simulation results show that the fuel economy of the FCHV is improved by the proposed energy management approach compared to a benchmark case where the driving cycle is fixed and only the hybrid power split (allocation) ratio is optimized. The proposed energy management approach is useful especially for the autonomous hybrid vehicles.

  13. The hybrid thermography approach applied to architectural structures

    Science.gov (United States)

    Sfarra, S.; Ambrosini, D.; Paoletti, D.; Nardi, I.; Pasqualoni, G.

    2017-07-01

    This work contains an overview of infrared thermography (IRT) method and its applications relating to the investigation of architectural structures. In this method, the passive approach is usually used in civil engineering, since it provides a panoramic view of the thermal anomalies to be interpreted also thanks to the use of photographs focused on the region of interest (ROI). The active approach, is more suitable for laboratory or indoor inspections, as well as for objects having a small size. The external stress to be applied is thermal, coming from non-natural apparatus such as lamps or hot / cold air jets. In addition, the latter permits to obtain quantitative information related to defects not detectable to the naked eyes. Very recently, the hybrid thermography (HIRT) approach has been introduced to the attention of the scientific panorama. It can be applied when the radiation coming from the sun, directly arrives (i.e., possibly without the shadow cast effect) on a surface exposed to the air. A large number of thermograms must be collected and a post-processing analysis is subsequently applied via advanced algorithms. Therefore, an appraisal of the defect depth can be obtained passing through the calculation of the combined thermal diffusivity of the materials above the defect. The approach is validated herein by working, in a first stage, on a mosaic sample having known defects while, in a second stage, on a Church built in L'Aquila (Italy) and covered with a particular masonry structure called apparecchio aquilano. The results obtained appear promising.

  14. New Hybrid Multiple Attribute Decision-Making Model for Improving Competence Sets: Enhancing a Company’s Core Competitiveness

    Directory of Open Access Journals (Sweden)

    Kuan-Wei Huang

    2016-02-01

    Full Text Available A company’s core competitiveness depends on the strategic allocation of its human resources in alignment with employee capabilities. Competency models can identify the range of capabilities at a company’s disposal, and this information can be used to develop internal or external education training policies for sustainable development. Such models can ensure the importation of a strategic orientation reflecting the growth of its employee competence set and enhancing human resource sustainably. This approach ensures that the most appropriate people are assigned to the most appropriate positions. In this study, we proposed a new hybrid multiple attributed decision-making model by using the Decision-making trial and Evaluation Laboratory Technique (DEMATEL to construct an influential network relation map (INRM and determined the influential weights by using the basic concept of the analytic network process (called DEMATEL-based ANP, DANP; the influential weights were then adopted with a modified Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR method. A simple forecasting technique as an iteration function was also proposed. The proposed model was effective. We expect that the proposed model can facilitate making timely revisions, reflecting the growth of employee competence sets, reducing the performance gap toward the aspiration level, and ensuring the sustainability of a company.

  15. Particle swarm optimization of driving torque demand decision based on fuel economy for plug-in hybrid electric vehicle

    International Nuclear Information System (INIS)

    Shen, Peihong; Zhao, Zhiguo; Zhan, Xiaowen; Li, Jingwei

    2017-01-01

    In this paper, an energy management strategy based on logic threshold is proposed for a plug-in hybrid electric vehicle. The plug-in hybrid electric vehicle powertrain model is established using MATLAB/Simulink based on experimental tests of the power components, which is validated by the comparison with the verified simulation model which is built in the AVL Cruise. The influence of the driving torque demand decision on the fuel economy of plug-in hybrid electric vehicle is studied using a simulation. The optimization method for the driving torque demand decision, which refers to the relationship between the accelerator pedal opening and driving torque demand, from the perspective of fuel economy is formulated. The dynamically changing inertia weight particle swarm optimization is used to optimize the decision parameters. The simulation results show that the optimized driving torque demand decision can improve the PHEV fuel economy by 15.8% and 14.5% in the fuel economy test driving cycle of new European driving cycle and worldwide harmonized light vehicles test respectively, using the same rule-based energy management strategy. The proposed optimization method provides a theoretical guide for calibrating the parameters of driving torque demand decision to improve the fuel economy of the real plug-in hybrid electric vehicle. - Highlights: • The influence of the driving torque demand decision on the fuel economy is studied. • The optimization method for the driving torque demand decision is formulated. • An improved particle swarm optimization is utilized to optimize the parameters. • Fuel economy is improved by using the optimized driving torque demand decision.

  16. Investigation of Multi-Criteria Decision Consistency: A Triplex Approach to Optimal Oilfield Portfolio Investment Decisions

    Science.gov (United States)

    Qaradaghi, Mohammed

    Complexity of the capital intensive oil and gas portfolio investments is continuously growing. It is manifested in the constant increase in the type, number and degree of risks and uncertainties, which consequently lead to more challenging decision making problems. A typical complex decision making problem in petroleum exploration and production (E&P) is the selection and prioritization of oilfields/projects in a portfolio investment. Prioritizing oilfields maybe required for different purposes, including the achievement of a targeted production and allocation of limited available development resources. These resources cannot be distributed evenly nor can they be allocated based on the oilfield size or production capacity alone since various other factors need to be considered simultaneously. These factors may include subsurface complexity, size of reservoir, plateau production and needed infrastructure in addition to other issues of strategic concern, such as socio-economic, environmental and fiscal policies, particularly when the decision making involves governments or national oil companies. Therefore, it would be imperative to employ decision aiding tools that not only address these factors, but also incorporate the decision makers' preferences clearly and accurately. However, the tools commonly used in project portfolio selection and optimization, including intuitive approaches, vary in their focus and strength in addressing the different criteria involved in such decision problems. They are also disadvantaged by a number of drawbacks, which may include lacking the capacity to address multiple and interrelated criteria, uncertainty and risk, project relationship with regard to value contribution and optimum resource utilization, non-monetary attributes, decision maker's knowledge and expertise, in addition to varying levels of ease of use and other practical and theoretical drawbacks. These drawbacks have motivated researchers to investigate other tools and

  17. A hybrid ensemble learning approach to star-galaxy classification

    Science.gov (United States)

    Kim, Edward J.; Brunner, Robert J.; Carrasco Kind, Matias

    2015-10-01

    There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template-fitting method. Using data from the CFHTLenS survey (Canada-France-Hawaii Telescope Lensing Survey), we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2 (Deep Extragalactic Evolutionary Probe Phase 2 ), SDSS (Sloan Digital Sky Survey), VIPERS (VIMOS Public Extragalactic Redshift Survey), and VVDS (VIMOS VLT Deep Survey), and when the demographics of sources in a low-quality training set do not match the demographics of objects in the test data set. We demonstrate that our Bayesian combination technique improves the overall performance over any individual classification method in these scenarios. Thus, strategies that combine the predictions of different classifiers may prove to be optimal in currently ongoing and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

  18. Mobile phone use while driving: a hybrid modeling approach.

    Science.gov (United States)

    Márquez, Luis; Cantillo, Víctor; Arellana, Julián

    2015-05-01

    The analysis of the effects that mobile phone use produces while driving is a topic of great interest for the scientific community. There is consensus that using a mobile phone while driving increases the risk of exposure to traffic accidents. The purpose of this research is to evaluate the drivers' behavior when they decide whether or not to use a mobile phone while driving. For that, a hybrid modeling approach that integrates a choice model with the latent variable "risk perception" was used. It was found that workers and individuals with the highest education level are more prone to use a mobile phone while driving than others. Also, "risk perception" is higher among individuals who have been previously fined and people who have been in an accident or almost been in an accident. It was also found that the tendency to use mobile phones while driving increases when the traffic speed reduces, but it decreases when the fine increases. Even though the urgency of the phone call is the most important explanatory variable in the choice model, the cost of the fine is an important attribute in order to control mobile phone use while driving. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. A Multimetric Approach for Handoff Decision in Heterogeneous Wireless Networks

    Science.gov (United States)

    Kustiawan, I.; Purnama, W.

    2018-02-01

    Seamless mobility and service continuity anywhere at any time are an important issue in the wireless Internet. This research proposes a scheme to make handoff decisions effectively in heterogeneous wireless networks using a fuzzy system. Our design lies in an inference engine which takes RSS (received signal strength), data rate, network latency, and user preference as strategic determinants. The logic of our engine is realized on a UE (user equipment) side in faster reaction to network dynamics while roaming across different radio access technologies. The fuzzy system handles four metrics jointly to deduce a moderate decision about when to initiate handoff. The performance of our design is evaluated by simulating move-out mobility scenarios. Simulation results show that our scheme outperforms other approaches in terms of reducing unnecessary handoff.

  20. Entrepreneurial decision-making using the knightian uncertainty approach

    Directory of Open Access Journals (Sweden)

    Maria Sylvia Macchione Saes

    2013-12-01

    Full Text Available The article discusses the behavioral aspects that affect the entrepreneurs' decision making under the Knightian uncertainty approach. Since the profit arising from entrepreneurial activity represents the reward of an immeasurable and subjective risk, it has been hypothesized that innovative entrepreneurs have excessive optimism and confidence, which leads them to invest in high-risk activities. A behavioral model of decision making under uncertainty is used to test the hypothesis of overconfidence. This model is based on Bayesian inference, which allows us to model the assumption that these entrepreneurs are overconfident. We conclude that, under the hypothesis of overconfidence, these entrepreneurs decide to invest, despite the fact that the expected utility model indicates the contrary. This theoretical finding could explain why there are a large number of business failures in the first years of activity.

  1. Integrating climate change criteria in reforestation projects using a hybrid decision-support system

    Science.gov (United States)

    Curiel-Esparza, Jorge; Gonzalez-Utrillas, Nuria; Canto-Perello, Julian; Martin-Utrillas, Manuel

    2015-09-01

    The selection of appropriate species in a reforestation project has always been a complex decision-making problem in which, due mostly to government policies and other stakeholders, not only economic criteria but also other environmental issues interact. Climate change has not usually been taken into account in traditional reforestation decision-making strategies and management procedures. Moreover, there is a lack of agreement on the percentage of each one of the species in reforestation planning, which is usually calculated in a discretionary way. In this context, an effective multicriteria technique has been developed in order to improve the process of selecting species for reforestation in the Mediterranean region of Spain. A hybrid Delphi-AHP methodology is proposed, which includes a consistency analysis in order to reduce random choices. As a result, this technique provides an optimal percentage distribution of the appropriate species to be used in reforestation planning. The highest values of the weight given for each subcriteria corresponded to FR (fire forest response) and PR (pests and diseases risk), because of the increasing importance of the impact of climate change in the forest. However, CB (conservation of biodiversitiy) was in the third position in line with the aim of reforestation. Therefore, the most suitable species were Quercus faginea (19.75%) and Quercus ilex (19.35%), which offer a good balance between all the factors affecting the success and viability of reforestation.

  2. Organic Micropollutants Removal from Water by Oxidation and Other Processes:QSAR Models, Decision Support System and Hybrids of Processes

    KAUST Repository

    Sudhakaran, Sairam

    2013-08-01

    The presence of organic micropollutants (OMPs) in water is of great environmental concern. OMPs such as endocrine disruptors and certain pharmaceuticals have shown alarming effects on aquatic life. OMPs are included in the priority list of contaminants in several government directorate frameworks. The low levels of OMPs concentration (ng/L to μg/L) force the use of sophisticated analytical instruments. Although, the techniques to detect OMPs are progressing, the focus of current research is only on limited, important OMPs due to the high amount of time, cost and effort involved in analyzing them. Alternatively, quantitative structure activity relationship (QSAR) models help to screen processes and propose appropriate options without considerable experimental effort. QSAR models are well-established in regulatory bodies as a method to screen toxic chemicals. The goal of the present thesis was to develop QSAR models for OMPs removal by oxidation. Apart from the QSAR models, a decision support system (DSS) based on multi-criteria analysis (MCA) involving socio-economic-technical and sustainability aspects was developed. Also, hybrids of different water treatment processes were studied to propose a sustainable water treatment train for OMPs removal. In order to build the QSAR models, the ozone/hydroxyl radical rate constants or percent removals of the OMPs were compiled. Several software packages were used to 5 compute the chemical properties of OMPs and perform statistical analyses. For DSS, MCA was used since it allows the comparison of qualitative (non-monetary, non-metric) and quantitative criteria (e.g., costs). Quadrant plots were developed to study the hybrid of natural and advanced water treatment processes. The QSAR models satisfied both chemical and statistical criteria. The DSS resulted in natural treatment and ozonation as the preferred processes for OMPs removal. The QSAR models can be used as a screening tool for OMPs removal by oxidation. Moreover, the

  3. Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

    Science.gov (United States)

    Bennett, Casey C; Hauser, Kris

    2013-01-01

    In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal

  4. [Rational drug use: an economic approach to decision making].

    Science.gov (United States)

    Mota, Daniel Marques; da Silva, Marcelo Gurgel Carlos; Sudo, Elisa Cazue; Ortún, Vicente

    2008-04-01

    The present article approaches rational drug use (RDU) from the economical point of view. The implementation of RDU implies in costs and involves acquisition of knowledge and behavioral changes of several agents. The difficulties in implementing RDU may be due to shortage problems, information asymmetry, lack of information, uncertain clinical decisions, externalities, time-price, incentives for drug prescribers and dispensers, drug prescriber preferences and marginal utility. Health authorities, among other agencies, must therefore regularize, rationalize and control drug use to minimize inefficiency in pharmaceutical care and to prevent exposing the population to unnecessary health risks.

  5. Relative efficiency of hydrogen technologies for the hydrogen economy : a fuzzy AHP/DEA hybrid model approach

    International Nuclear Information System (INIS)

    Lee, S.

    2009-01-01

    As a provider of national energy security, the Korean Institute of Energy Research is seeking to establish a long term strategic technology roadmap for a hydrogen-based economy. This paper addressed 5 criteria regarding the strategy, notably economic impact, commercial potential, inner capacity, technical spinoff, and development cost. The fuzzy AHP and DEA hybrid model were used in a two-stage multi-criteria decision making approach to evaluate the relative efficiency of hydrogen technologies for the hydrogen economy. The fuzzy analytic hierarchy process reflects the uncertainty of human thoughts with interval values instead of clear-cut numbers. It therefore allocates the relative importance of 4 criteria, notably economic impact, commercial potential, inner capacity and technical spin-off. The relative efficiency of hydrogen technologies for the hydrogen economy can be measured via data envelopment analysis. It was concluded that the scientific decision making approach can be used effectively to allocate research and development resources and activities

  6. Relative efficiency of hydrogen technologies for the hydrogen economy : a fuzzy AHP/DEA hybrid model approach

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S. [Korea Inst. of Energy Research, Daejeon (Korea, Republic of). Energy Policy Research Division; Mogi, G. [Tokyo Univ., (Japan). Dept. of Technology Management for Innovation, Graduate School of Engineering; Kim, J. [Korea Inst. of Energy Research, Daejeon (Korea, Republic of)

    2009-07-01

    As a provider of national energy security, the Korean Institute of Energy Research is seeking to establish a long term strategic technology roadmap for a hydrogen-based economy. This paper addressed 5 criteria regarding the strategy, notably economic impact, commercial potential, inner capacity, technical spinoff, and development cost. The fuzzy AHP and DEA hybrid model were used in a two-stage multi-criteria decision making approach to evaluate the relative efficiency of hydrogen technologies for the hydrogen economy. The fuzzy analytic hierarchy process reflects the uncertainty of human thoughts with interval values instead of clear-cut numbers. It therefore allocates the relative importance of 4 criteria, notably economic impact, commercial potential, inner capacity and technical spin-off. The relative efficiency of hydrogen technologies for the hydrogen economy can be measured via data envelopment analysis. It was concluded that the scientific decision making approach can be used effectively to allocate research and development resources and activities.

  7. Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

    DEFF Research Database (Denmark)

    Soares, João; Valle, Zita; Morais, Hugo

    2013-01-01

    This paper presents a decision support Tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy ressource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application...... of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network...... constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance...

  8. Mass Optimization of Battery/Supercapacitors Hybrid Systems Based on a Linear Programming Approach

    Science.gov (United States)

    Fleury, Benoit; Labbe, Julien

    2014-08-01

    The objective of this paper is to show that, on a specific launcher-type mission profile, a 40% gain of mass is expected using a battery/supercapacitors active hybridization instead of a single battery solution. This result is based on the use of a linear programming optimization approach to perform the mass optimization of the hybrid power supply solution.

  9. A Bayesian sequential processor approach to spectroscopic portal system decisions

    Energy Technology Data Exchange (ETDEWEB)

    Sale, K; Candy, J; Breitfeller, E; Guidry, B; Manatt, D; Gosnell, T; Chambers, D

    2007-07-31

    The development of faster more reliable techniques to detect radioactive contraband in a portal type scenario is an extremely important problem especially in this era of constant terrorist threats. Towards this goal the development of a model-based, Bayesian sequential data processor for the detection problem is discussed. In the sequential processor each datum (detector energy deposit and pulse arrival time) is used to update the posterior probability distribution over the space of model parameters. The nature of the sequential processor approach is that a detection is produced as soon as it is statistically justified by the data rather than waiting for a fixed counting interval before any analysis is performed. In this paper the Bayesian model-based approach, physics and signal processing models and decision functions are discussed along with the first results of our research.

  10. Decision Tree Approach to Discovering Fraud in Leasing Agreements

    Directory of Open Access Journals (Sweden)

    Horvat Ivan

    2014-09-01

    Full Text Available Background: Fraud attempts create large losses for financing subjects in modern economies. At the same time, leasing agreements have become more and more popular as a means of financing objects such as machinery and vehicles, but are more vulnerable to fraud attempts. Objectives: The goal of the paper is to estimate the usability of the data mining approach in discovering fraud in leasing agreements. Methods/Approach: Real-world data from one Croatian leasing firm was used for creating tow models for fraud detection in leasing. The decision tree method was used for creating a classification model, and the CHAID algorithm was deployed. Results: The decision tree model has indicated that the object of the leasing agreement had the strongest impact on the probability of fraud. Conclusions: In order to enhance the probability of the developed model, it would be necessary to develop software that would enable automated, quick and transparent retrieval of data from the system, processing according to the rules and displaying the results in multiple categories.

  11. A hybrid agent-based computational economics and optimization approach for supplier selection problem

    Directory of Open Access Journals (Sweden)

    Zahra Pourabdollahi

    2017-12-01

    Full Text Available Supplier evaluation and selection problem is among the most important of logistics decisions that have been addressed extensively in supply chain management. The same logistics decision is also important in freight transportation since it identifies trade relationships between business establishments and determines commodity flows between production and consumption points. The commodity flows are then used as input to freight transportation models to determine cargo movements and their characteristics including mode choice and shipment size. Various approaches have been proposed to explore this latter problem in previous studies. Traditionally, potential suppliers are evaluated and selected using only price/cost as the influential criteria and the state-of-practice methods. This paper introduces a hybrid agent-based computational economics and optimization approach for supplier selection. The proposed model combines an agent-based multi-criteria supplier evaluation approach with a multi-objective optimization model to capture both behavioral and economical aspects of the supplier selection process. The model uses a system of ordered response models to determine importance weights of the different criteria in supplier evaluation from a buyers’ point of view. The estimated weights are then used to calculate a utility for each potential supplier in the market and rank them. The calculated utilities are then entered into a mathematical programming model in which best suppliers are selected by maximizing the total accrued utility for all buyers and minimizing total shipping costs while balancing the capacity of potential suppliers to ensure market clearing mechanisms. The proposed model, herein, was implemented under an operational agent-based supply chain and freight transportation framework for the Chicago Metropolitan Area.

  12. When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

    KAUST Repository

    Liu, Xiao; Liu, An; Zhang, Xiangliang; Li, Zhixu; Liu, Guanfeng; Zhao, Lei; Zhou, Xiaofang

    2017-01-01

    result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP

  13. A quantitative approach to choose among multiple mutually exclusive decisions: comparative expected utility theory

    OpenAIRE

    Zhu, Pengyu

    2018-01-01

    Mutually exclusive decisions have been studied for decades. Many well-known decision theories have been defined to help people either to make rational decisions or to interpret people's behaviors, such as expected utility theory, regret theory, prospect theory, and so on. The paper argues that none of these decision theories are designed to provide practical, normative and quantitative approaches for multiple mutually exclusive decisions. Different decision-makers should naturally make differ...

  14. Multi-criteria decision making on selection of solar–wind hybrid power station location: A case of China

    International Nuclear Information System (INIS)

    Yunna, Wu; Geng, Shuai

    2014-01-01

    Highlights: • We summarize the evaluation attributes from the perspective of project management. • The duties of roles are defined in the decision process. • The decision framework can provide various rankings of alternatives. • A China’s solar–wind hybrid power station location selection case is study. - Abstract: Site selection plays an important role in the entire life cycle of solar–wind hybrid power station (SWHPS) project and is worthy to further study. There are problems in the present researches: first, the SWHPS site evaluation results are difficult to be understood by the project managers due to the evaluations of SWHPS site are few from the perspective of project management. Second, the independence of experts is difficult to be protected since the undefined duties of roles in the evaluation process Third, the project managers cannot consider the alternatives thoroughly because that the evaluation result is single. Hence the innovativeness of this paper is as follows: first, the evaluation attributes of SWHPS site selection are summarized from the perspective of project management; second, the duties of roles in the decision process are defined; third, according to the principle of practicality, a decision framework of SWHPS site selection is built based on the analytic hierarchy process method, the merits of this decision framework are that it can provide various rankings of alternatives and is easy to be used. Finally, a case study of China demonstrates the effectiveness of decision framework

  15. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    Energy Technology Data Exchange (ETDEWEB)

    Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

    2011-02-15

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  16. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    International Nuclear Information System (INIS)

    Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.

    2011-01-01

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  17. A regret theory approach to decision curve analysis: A novel method for eliciting decision makers' preferences and decision-making

    OpenAIRE

    Vickers Andrew; Hozo Iztok; Tsalatsanis Athanasios; Djulbegovic Benjamin

    2010-01-01

    Abstract Background Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. ...

  18. A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries

    Directory of Open Access Journals (Sweden)

    Wen-An Yang

    2016-01-01

    Full Text Available Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles and its failure can lead to reduced capability, downtime, and even catastrophic breakdowns. Remaining useful life (RUL prediction of lithium-ion batteries before the future failure event is extremely crucial for proactive maintenance/safety actions. This study proposes a hybrid prognostic approach that can predict the RUL of degraded lithium-ion batteries using physical laws and data-driven modeling simultaneously. In this hybrid prognostic approach, the relevant vectors obtained with the selective kernel ensemble-based relevance vector machine (RVM learning algorithm are fitted to the physical degradation model, which is then extrapolated to failure threshold for estimating the RUL of the lithium-ion battery of interest. The experimental results indicated that the proposed hybrid prognostic approach can accurately predict the RUL of degraded lithium-ion batteries. Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs like the conventional backpropagation (BP algorithm and support vector machines (SVMs. In addition, an investigation is also conducted to identify the effects of RVM learning algorithm on the proposed hybrid prognostic approach.

  19. Applying Fuzzy Decision Making Approach to IT Outsourcing Supplier Selection

    OpenAIRE

    Gülcin Büyüközkan; Mehmet Sakir Ersoy

    2009-01-01

    The decision of information technology (IT) outsourcing requires close attention to the evaluation of supplier selection process because the selection decision involves conflicting multiple criteria and is replete with complex decision making problems. Selecting the most appropriate suppliers is considered an important strategic decision that may impact the performance of outsourcing engagements. The objective of this paper is to aid decision makers to evaluate and assess possible IT outsourc...

  20. Assessing testamentary and decision-making capacity: Approaches and models.

    Science.gov (United States)

    Purser, Kelly; Rosenfeld, Tuly

    2015-09-01

    The need for better and more accurate assessments of testamentary and decision-making capacity grows as Australian society ages and incidences of mentally disabling conditions increase. Capacity is a legal determination, but one on which medical opinion is increasingly being sought. The difficulties inherent within capacity assessments are exacerbated by the ad hoc approaches adopted by legal and medical professionals based on individual knowledge and skill, as well as the numerous assessment paradigms that exist. This can negatively affect the quality of assessments, and results in confusion as to the best way to assess capacity. This article begins by assessing the nature of capacity. The most common general assessment models used in Australia are then discussed, as are the practical challenges associated with capacity assessment. The article concludes by suggesting a way forward to satisfactorily assess legal capacity given the significant ramifications of getting it wrong.

  1. Hybridization success is largely limited to homoploid Prunus hybrids: a multidisciplinary approach

    Czech Academy of Sciences Publication Activity Database

    Macková, L.; Vít, Petr; Ďurišová, Ľ.; Eliáš, P. Jr.; Urfus, T.

    2017-01-01

    Roč. 303, č. 4 (2017), s. 481-495 ISSN 0378-2697 Institutional support: RVO:67985939 Keywords : absolute genome size * interspecific hybridization * embryology Subject RIV: EF - Botanics OBOR OECD: Plant sciences, botany Impact factor: 1.239, year: 2016

  2. A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid Wind Turbine Rotors

    DEFF Research Database (Denmark)

    Herbert-Acero, José F.; Martínez-Lauranchet, Jaime; Probst, Oliver

    2014-01-01

    of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize...

  3. Hybrid Engine Powered City Car: Fuzzy Controlled Approach

    Science.gov (United States)

    Rahman, Ataur; Mohiuddin, AKM; Hawlader, MNA; Ihsan, Sany

    2017-03-01

    This study describes a fuzzy controlled hybrid engine powered car. The car is powered by the lithium ion battery capacity of 1000 Wh is charged by the 50 cc hybrid engine and power regenerative mode. The engine is operated with lean mixture at 3000 rpm to charge the battery. The regenerative mode that connects with the engine generates electrical power of 500-600 W for the deceleration of car from 90 km/h to 20 km/h. The regenerated electrical power has been used to power the air-conditioning system and to meet the other electrical power. The battery power only used to propel the car. The regenerative power also found charging the battery for longer operation about 40 minutes and more. The design flexibility of this vehicle starts with whole-vehicle integration based on radical light weighting, drag reduction, and accessory efficiency. The energy efficient hybrid engine cut carbon dioxide (CO2) and nitrogen oxides (N2O) emission about 70-80% as the loads on the crankshaft such as cam-follower and its associated rotating components are replaced by electromagnetic systems, and the flywheel, alternator and starter motor are replaced by a motor generator. The vehicle was tested and found that it was able to travel 70 km/litre with the power of hybrid engine.

  4. A promising hybrid approach to SPECT attenuation correction

    International Nuclear Information System (INIS)

    Lewis, N.H.; Faber, T.L.; Corbett, J.R.; Stokely, E.M.

    1984-01-01

    Most methods for attenuation compensation in SPECT either rely on the assumption of uniform attenuation, or use slow iteration to achieve accuracy. However, hybrid methods that combine iteration with simple multiplicative correction can accommodate nonuniform attenuation, and such methods converge faster than other iterative techniques. The authors evaluated two such methods, which differ in use of a damping factor to control convergence. Both uniform and nonuniform attenuation were modeled, using simulated and phantom data for a rotating gamma camera. For simulations done with 360 0 data and the correct attenuation map, activity levels were reconstructed to within 5% of the correct values after one iteration. Using 180 0 data, reconstructed levels in regions representing lesion and background were within 5% of the correct values in three iterations; however, further iterations were needed to eliminate the characteristic streak artifacts. The damping factor had little effect on 360 0 reconstruction, but was needed for convergence with 180 0 data. For both cold- and hot-lesion models, image contrast was better from the hybrid methods than from the simpler geometric-mean corrector. Results from the hybrid methods were comparable to those obtained using the conjugate-gradient iterative method, but required 50-100% less reconstruction time. The relative speed of the hybrid methods, and their accuracy in reconstructing photon activity in the presence of nonuniform attenuation, make them promising tools for quantitative SPECT reconstruction

  5. Using a Hybrid Approach for a Leadership Cohort Program

    Science.gov (United States)

    Norman, Maxine A.

    2013-01-01

    Because information technology continues to change rapidly, Extension is challenged with learning and using technology appropriately. We assert Extension cannot shy away from the challenges but must embrace technology because audiences and external forces demand it. A hybrid, or blended, format of a leadership cohort program was offered to public…

  6. Facile approach to prepare Pt decorated SWNT/graphene hybrid catalytic ink

    Energy Technology Data Exchange (ETDEWEB)

    Mayavan, Sundar, E-mail: sundarmayavan@cecri.res.in [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Mandalam, Aditya; Balasubramanian, M. [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Sim, Jun-Bo [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Choi, Sung-Min, E-mail: sungmin@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of)

    2015-07-15

    Highlights: • Pt NPs were in situ synthesized onto CNT–graphene support in aqueous solution. • The as-prepared material was used directly as a catalyst ink without further treatment. • Catalyst ink is active toward methanol oxidation. • This approach realizes both scalable and greener production of hybrid catalysts. - Abstract: Platinum nanoparticles were in situ synthesized onto hybrid support involving graphene and single walled carbon nanotube in aqueous solution. We investigate the reduction of graphene oxide, and platinum nanoparticle functionalization on hybrid support by X-ray photoelectron spectroscopy, Raman spectroscopy, X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The as-prepared platinum on hybrid support was used directly as a catalyst ink without further treatment and is active toward methanol oxidation. This work realizes both scalable and greener production of highly efficient hybrid catalysts, and would be valuable for practical applications of graphene based fuel cell catalysts.

  7. Six Sigma Project Selection Using Fuzzy TOPSIS Decision Making Approach

    Directory of Open Access Journals (Sweden)

    Rajeev Rathi

    2015-05-01

    Full Text Available Six Sigma is considered as a logical business strategy that attempts to identify and eliminate the defects or failures for improving the quality of product and processes. A decision on project selection in Six Sigma is always very critical; it plays a key role in successful implementation of Six Sigma. Selection of a right Six Sigma project is essentially important for an automotive company because it greatly influences the manufacturing costs. This paper discusses an approach for right Six Sigma project selection at an automotive industry using fuzzy logic based TOPSIS method. The fuzzy TOPSIS is a well recognized tool to undertake the fuzziness of the data involved in choosing the right preferences. In this context, evaluation criteria have been designed for selection of best alternative. The weights of evaluation criteria are calculated by using the MDL (modified digital logic method and final ranking is calculated through priority index obtained by using fuzzy TOPSIS method. In the selected case study, this approach has rightly helped to identify the right project for implementing Six Sigma for achieving improvement in productivity.

  8. Decision-making in multinational enterprises: concepts and research approaches.

    OpenAIRE

    Ghertman M

    1984-01-01

    ILO pub. Working paper on decision making processes in multinational enterprises - gives definition, type and classification of decision making in large enterprises; outlines the centralization decentralization theory and the iterative process; notes research needs. Bibliography.

  9. A Hybrid Approach for Thread Recommendation in MOOC Forums

    OpenAIRE

    Ahmad. A. Kardan; Amir Narimani; Foozhan Ataiefard

    2017-01-01

    Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC ...

  10. Interactive Digital Storytelling: Towards a Hybrid Conceptual Approach

    OpenAIRE

    Spierling, Ulrike

    2005-01-01

    1 Introduction In this contribution, Interactive Digital Storytelling is viewed as a hybrid form of game design and cinematic storytelling for the understanding and making of future learning and entertainment applications. The paper shall present formal design models that provide a conceptual bridge between both traditional linear narrative techniques as well as agent-based emergent conversations with virtual characters. In summary, a theoretical classification of thinking models for authors ...

  11. A hybrid clustering and classification approach for predicting crash injury severity on rural roads.

    Science.gov (United States)

    Hasheminejad, Seyed Hessam-Allah; Zahedi, Mohsen; Hasheminejad, Seyed Mohammad Hossein

    2018-03-01

    As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011-2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.

  12. A novel approach for fire recognition using hybrid features and manifold learning-based classifier

    Science.gov (United States)

    Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

    2018-03-01

    Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

  13. Control and fault diagnosis based sliding mode observer of a multicellular converter: Hybrid approach

    KAUST Repository

    Benzineb, Omar

    2013-01-01

    In this article, the diagnosis of a three cell converter is developed. The hybrid nature of the system represented by the presence of continuous and discrete dynamics is taken into account in the control design. The idea is based on using a hybrid control and an observer-type sliding mode to generate residuals from the observation errors of the system. The simulation results are presented at the end to illustrate the performance of the proposed approach. © 2013 FEI STU.

  14. An hybrid and non-modern approach to urban studies

    Directory of Open Access Journals (Sweden)

    Marc Grau i Solés

    2012-03-01

    Full Text Available This article draws upon the so-called Forat de la Vergonya urban controversy and the urban transformation process of a neighborhood in Barcelona: el Casc Antic. Drawing on inputs from Actor-Network Theory (ANT, the city is explored as a multiple urban assemblage. Besides, we analyze the dichotomous nature of the modern notion of politics. Especially, the role of object-subject dichotomy is explored. Through the analysis of citizen participation opportunities we propose a new hybrid notion of citizen participation and urban policy.

  15. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and fault...... can be used as a test signal for sanity check at the commissioning or for detection of faults hidden by regulatory actions of the controller. The method is tested on the two tank benchmark example. ©2009 IEEE....

  16. A Bayesian decision approach to rainfall thresholds based flood warning

    Directory of Open Access Journals (Sweden)

    M. L. V. Martina

    2006-01-01

    Full Text Available Operational real time flood forecasting systems generally require a hydrological model to run in real time as well as a series of hydro-informatics tools to transform the flood forecast into relatively simple and clear messages to the decision makers involved in flood defense. The scope of this paper is to set forth the possibility of providing flood warnings at given river sections based on the direct comparison of the quantitative precipitation forecast with critical rainfall threshold values, without the need of an on-line real time forecasting system. This approach leads to an extremely simplified alert system to be used by non technical stakeholders and could also be used to supplement the traditional flood forecasting systems in case of system failures. The critical rainfall threshold values, incorporating the soil moisture initial conditions, result from statistical analyses using long hydrological time series combined with a Bayesian utility function minimization. In the paper, results of an application of the proposed methodology to the Sieve river, a tributary of the Arno river in Italy, are given to exemplify its practical applicability.

  17. A Decision Analytic Approach to Exposure-Based Chemical ...

    Science.gov (United States)

    The manufacture of novel synthetic chemicals has increased in volume and variety, but often the environmental and health risks are not fully understood in terms of toxicity and, in particular, exposure. While efforts to assess risks have generally been effective when sufficient data are available, the hazard and exposure data necessary to assess risks adequately are unavailable for the vast majority of chemicals in commerce. The US Environmental Protection Agency has initiated the ExpoCast Program to develop tools for rapid chemical evaluation based on potential for exposure. In this context, a model is presented in which chemicals are evaluated based on inherent chemical properties and behaviorally-based usage characteristics over the chemical’s life cycle. These criteria are assessed and integrated within a decision analytic framework, facilitating rapid assessment and prioritization for future targeted testing and systems modeling. A case study outlines the prioritization process using 51 chemicals. The results show a preliminary relative ranking of chemicals based on exposure potential. The strength of this approach is the ability to integrate relevant statistical and mechanistic data with expert judgment, allowing for an initial tier assessment that can further inform targeted testing and risk management strategies. The National Exposure Research Laboratory′s (NERL′s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in suppor

  18. A generic approach for the design of organizational decision support systems (ODSS)

    OpenAIRE

    Chalal, Rachid; National Institute of Computer Science; Nader, Fahima; National Institute of Computer Science

    2007-01-01

    The paper proposes a generic approach to design and develop an Organizational Decision Support System (ODSS). This approach is based at the follows definition: the ODSS is considered as the experts' memory and their decision-taking. Therefore, the ODSS is constituted by two elements, a strategic DSS and a specific referential of the decision situation. Our generic approach for ODSS design is based on the MUSIC (Management and Use of Co-operative Information Systems) model. An illustration of ...

  19. An automated approach to the design of decision tree classifiers

    Science.gov (United States)

    Argentiero, P.; Chin, R.; Beaudet, P.

    1982-01-01

    An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.

  20. IT Portfolio Management: A Holistic Approach to Outsourcing Decisions

    OpenAIRE

    Ho, Luke; ATKINS, Anthony

    2009-01-01

    This chapter provides an introduction to the advent of Information Technology Outsourcing (ITO) and its impact on portfolio management in modern day decision-making. Specifically, it outlines the use of the Application Portfolio Matrix (APM) by companies in formulating their strategic IT direction and why such techniques may be unsuitable for outsourcing decisions, which are inherently complex and multi-faceted in nature. Consequently, there is a need for alternative decision support tools to...

  1. Mathematical modelling approach to collective decision-making

    OpenAIRE

    Zabzina, Natalia

    2017-01-01

    In everyday situations individuals make decisions. For example, a tourist usually chooses a crowded or recommended restaurant to have dinner. Perhaps it is an individual decision, but the observed pattern of decision-making is a collective phenomenon. Collective behaviour emerges from the local interactions that give rise to a complex pattern at the group level. In our example, the recommendations or simple copying the choices of others make a crowded restaurant even more crowded. The rules o...

  2. A Game-Chain-Based Approach for Decision Making

    OpenAIRE

    An, Tingyu; Watanabe, tsunami

    2009-01-01

    Nowadays, with the rapid development of information society, decision-making problems become more and more complicated especially in large scale systems such as infrastructure, environmental and industrial fields, which are usually accompanied by psychological competition between involved parties in a complicated, uncertain and dynamic situation. From a holistic perspective of system, a specific decision-making method which is described as game-chain-based decision making has been proposed in...

  3. THE INFLUENCE OF TOP MANAGEMENT DEMOGRAPHIC CHARACTERISTICS ON DECISION MAKING APPROACHES

    Directory of Open Access Journals (Sweden)

    Ivana Bulog

    2016-12-01

    Full Text Available Today’s organizational environment requires managers to be an excellent decision maker with the ability to make effective decisions which will shape business performance. Because of the role that managers have in today’s business settings, research interest in the relationship between individual characteristics and managerial decision making in all its aspects has increased over the last decade. This paper aims to provide an overview and discussion of how individuals make choices and decisions by examining the influence of top management demographic characteristics on decision making approaches. Findings suggest that demographic characteristics appear to be valuable for predicting which decision making approach managers prefer. The results of the study show that the average age and education level of decision makers is positively related to the rational decision making approach and negatively to the intuitive decision making approach. Tenure is positively related to the intuitive decision making approach, but the influence is not statistically significant. Also, a difference in the decision making approach was found with respect to gender. In light of the research findings, implications and limitations were discussed and some possibilities for future research are suggested.

  4. Decision science: a scientific approach to enhance public health budgeting.

    Science.gov (United States)

    Honoré, Peggy A; Fos, Peter J; Smith, Torney; Riley, Michael; Kramarz, Kim

    2010-01-01

    The allocation of resources for public health programming is a complicated and daunting responsibility. Financial decision-making processes within public health agencies are especially difficult when not supported with techniques for prioritizing and ranking alternatives. This article presents a case study of a decision analysis software model that was applied to the process of identifying funding priorities for public health services in the Spokane Regional Health District. Results on the use of this decision support system provide insights into how decision science models, which have been used for decades in business and industry, can be successfully applied to public health budgeting as a means of strengthening agency financial management processes.

  5. Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

    Science.gov (United States)

    Li, Yan

    2017-05-25

    The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

  6. A Decision Theory Approach to College Resource Allocation.

    Science.gov (United States)

    Baldwin, Charles W.

    Current budgeting techniques are reviewed in relation to their application to higher education, including (1) incremental budgeting, where decisions are based primarily upon former levels of expenditures, (2) zero-based budgeting, involving the establishment and ranking of "decision packages", (3) Planning and Programming Budgeting…

  7. Effects of approach and withdrawal motivation on interactive economic decisions

    NARCIS (Netherlands)

    Harle, Katia; Sanfey, A.G.

    2010-01-01

    Although recent economic models of human decision making have recognised the role of emotion as an important biasing factor, the impact of incidental emotion on decisions has remained poorly explored. To address this question, we jointly explored the role of emotional valence (i.e., positive vs.

  8. Towards an integrated approach in supporting microbiological food safety decisions

    NARCIS (Netherlands)

    Havelaar, A.H.; Bräunig, J.; Christiansen, K.; Cornu, M.; Hald, T.; Mangen, M.J.J.; Molbak, K.; Pielaat, A.; Snary, E.; Pelt, van W.; Velthuis, A.G.J.; Wahlström, H.

    2007-01-01

    Decisions on food safety involve consideration of a wide range of concerns including the public health impact of foodborne illness, the economic importance of the agricultural sector and the food industry, and the effectiveness and efficiency of interventions. To support such decisions, we propose

  9. Boldness affects foraging decisions in barnacle geese: an experimental approach

    NARCIS (Netherlands)

    Kurvers, R.H.J.M.; Nolet, B.A.; Prins, H.H.T.; Ydenberg, R.C.; Oers, van K.

    2012-01-01

    Individuals foraging in groups constantly need to make decisions, such as when to leave a group, when to join a group, and when to move collectively to another feeding site. In recent years, it has become evident that personality may affect these foraging decisions, but studies where individuals are

  10. A fuzzy hybrid approach for project manager selection

    Directory of Open Access Journals (Sweden)

    Ahmad Jafarnejad Chaghooshi

    2016-09-01

    Full Text Available Suitable project manager has a significant impact on successful accomplishment of the project. Managers should possess such skills in order to effectively cope with the competition. In this respect, selecting managers based on their skills can lead to a competitive advantage towards the achievement of organizational goals. selection of the suitable project manager can be viewed as a multi-criteria decision making (MCDM problem and an extensive evaluation of criteria, such as Technical skills, experience skills, Personal qualities and the related criteria must be considered in the selection process of project manager. The fuzzy set theory and MCDM methods appears as an essential tools to provide a decision framework that incorporates imprecise judgments and multi criteria nature of project manager selection process inherent in this process. This paper proposes the joint use of the Fuzzy DEMATEL (FDEMATEL and Fuzzy VIKOR methods for the decision-making process of selecting the most suitable managers for projects. First, with the opinions of the senior managers based on project management competency model (ICB-IPMA, all the criteria required for the selection are gathered. Then the FDEMATEL method is used to prioritize the importance of various criteria and FVIKOR used to rank the alternatives in a preferred order to select the best project managers from a number of alternatives. Next, a real case study used to illustrate the process of the proposed method. Finally, some conclusions are discussed at the end of this study.

  11. Improving "At-Action" Decision-Making in Team Sports through a Holistic Coaching Approach

    Science.gov (United States)

    Light, Richard L.; Harvey, Stephen; Mouchet, Alain

    2014-01-01

    This article draws on Game Sense pedagogy and complex learning theory (CLT) to make suggestions for improving decision-making ability in team sports by adopting a holistic approach to coaching with a focus on decision-making "at-action". It emphasizes the complexity of decision-making and the need to focus on the game as a whole entity,…

  12. A Hybrid ACO Approach to the Matrix Bandwidth Minimization Problem

    Science.gov (United States)

    Pintea, Camelia-M.; Crişan, Gloria-Cerasela; Chira, Camelia

    The evolution of the human society raises more and more difficult endeavors. For some of the real-life problems, the computing time-restriction enhances their complexity. The Matrix Bandwidth Minimization Problem (MBMP) seeks for a simultaneous permutation of the rows and the columns of a square matrix in order to keep its nonzero entries close to the main diagonal. The MBMP is a highly investigated {NP}-complete problem, as it has broad applications in industry, logistics, artificial intelligence or information recovery. This paper describes a new attempt to use the Ant Colony Optimization framework in tackling MBMP. The introduced model is based on the hybridization of the Ant Colony System technique with new local search mechanisms. Computational experiments confirm a good performance of the proposed algorithm for the considered set of MBMP instances.

  13. Hybrid Quantum-Classical Approach to Quantum Optimal Control.

    Science.gov (United States)

    Li, Jun; Yang, Xiaodong; Peng, Xinhua; Sun, Chang-Pu

    2017-04-14

    A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely, computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving answers from the quantum simulator, classical computing devices update the control parameters until an optimal control solution is found. To demonstrate the quantum-classical scheme in experiment, we use a seven-qubit nuclear magnetic resonance system, on which we have succeeded in optimizing state preparation without involving classical computation of the large Hilbert space evolution.

  14. Heuristics: foundations for a novel approach to medical decision making.

    Science.gov (United States)

    Bodemer, Nicolai; Hanoch, Yaniv; Katsikopoulos, Konstantinos V

    2015-03-01

    Medical decision-making is a complex process that often takes place during uncertainty, that is, when knowledge, time, and resources are limited. How can we ensure good decisions? We present research on heuristics-simple rules of thumb-and discuss how medical decision-making can benefit from these tools. We challenge the common view that heuristics are only second-best solutions by showing that they can be more accurate, faster, and easier to apply in comparison to more complex strategies. Using the example of fast-and-frugal decision trees, we illustrate how heuristics can be studied and implemented in the medical context. Finally, we suggest how a heuristic-friendly culture supports the study and application of heuristics as complementary strategies to existing decision rules.

  15. Hybrid simulation of reactor kinetics in CANDU reactors using a modal approach

    International Nuclear Information System (INIS)

    Monaghan, B.M.; McDonnell, F.N.; Hinds, H.W.T.; m.

    1980-01-01

    A hybrid computer model for simulating the behaviour of large CANDU (Canada Deuterium Uranium) reactor cores is presented. The main dynamic variables are expressed in terms of weighted sums of a base set of spatial natural-mode functions with time-varying co-efficients. This technique, known as the modal or synthesis approach, permits good three-dimensional representation of reactor dynamics and is well suited to hybrid simulation. The hybrid model provides improved man-machine interaction and real-time capability. The model was used in two applications. The first studies the transient that follows a loss of primary coolant and reactor shutdown; the second is a simulation of the dynamics of xenon, a fission product which has a high absorption cross-section for neutrons and thus has an important effect on reactor behaviour. Comparison of the results of the hybrid computer simulation with those of an all-digital one is good, within 1% to 2%

  16. A decision analysis approach to climate adaptation: comparing multiple pathways for multi-decadal decision making

    Science.gov (United States)

    Lin, B. B.; Little, L.

    2013-12-01

    Policy planners around the world are required to consider the implications of adapting to climatic change across spatial contexts and decadal timeframes. However, local level information for planning is often poorly defined, even though climate adaptation decision-making is made at this scale. This is especially true when considering sea level rise and coastal impacts of climate change. We present a simple approach using sea level rise simulations paired with adaptation scenarios to assess a range of adaptation options available to local councils dealing with issues of beach recession under present and future sea level rise and storm surge. Erosion and beach recession pose a large socioeconomic risk to coastal communities because of the loss of key coastal infrastructure. We examine the well-known adaptation technique of beach nourishment and assess various timings and amounts of beach nourishment at decadal time spans in relation to beach recession impacts. The objective was to identify an adaptation strategy that would allow for a low frequency of management interventions, the maintenance of beach width, and the ability to minimize variation in beach width over the 2010 to 2100 simulation period. 1000 replications of each adaptation option were produced against the 90 year simulation in order to model the ability each adaptation option to achieve the three key objectives. Three sets of adaptation scenarios were identified. Within each scenario, a number of adaptation options were tested. The three scenarios were: 1) Fixed periodic beach replenishment of specific amounts at 20 and 50 year intervals, 2) Beach replenishment to the initial beach width based on trigger levels of recession (5m, 10m, 20m), and 3) Fixed period beach replenishment of a variable amount at decadal intervals (every 10, 20, 30, 40, 50 years). For each adaptation option, we show the effectiveness of each beach replenishment scenario to maintain beach width and consider the implications of more

  17. HYBRID EDUCATION: THE ESTIMATION IN THE CATEGORIES OF INFORMATION-AXIOLOGICAL APPROACH

    Directory of Open Access Journals (Sweden)

    A. S. Kizilova

    2018-01-01

    Full Text Available Introduction: a hybrid assessment of reality is a new information-axiological level of communication between people. The term "hybrid (hybrid training" has been used as a result of the integration of digital and communication technologies in the form of online courses.Materials and methods: the main Russian forms of education are analyzed. The evaluation of the forms of education in the categories of the information-axiological approach is made on the basis of the following idea: everything is interchangeable, since everything has value. The mixing principles and models used in the process of hybrid formation are considered. Due to the fact that any mixed training requires planning, the analysis of the project and the target group, content analysis and financial analysis in this process is carried out.Results: specific educational methods are studied at the Bauman MSTU, subject to a hybrid assessment in the categories of the information-axiological approach. The analysis showed that the above explanation of the term "hybrid formation" is extremely narrow and one-sided. In particular, the search for information on volunteer education and the search for a socially-based education was conducted not only in the Bauman MSTU, but in Russia as a whole. However, the result was the portals of international student organizations with their own projects. Another example of a different interpretation of the "hybrid education" may be the assumption of quite axiologically new duties.Discussion and Conclusions: hybrid education is not limited to any temporal and territorial framework. It can manifest itself not only in the Internet-sphere, but also in the most diverse spheres of everyday life, with the interaction of various people and entire societies.

  18. Bayesian networks for clinical decision support: A rational approach to dynamic decision-making under uncertainty

    NARCIS (Netherlands)

    Gerven, M.A.J. van

    2007-01-01

    This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed

  19. Hybrid energy system evaluation in water supply system energy production: neural network approach

    Energy Technology Data Exchange (ETDEWEB)

    Goncalves, Fabio V.; Ramos, Helena M. [Civil Engineering Department, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal); Reis, Luisa Fernanda R. [Universidade de Sao Paulo, EESC/USP, Departamento de Hidraulica e Saneamento., Avenida do Trabalhador Saocarlense, 400, Sao Carlos-SP (Brazil)

    2010-07-01

    Water supply systems are large consumers of energy and the use of hybrid systems for green energy production is this new proposal. This work presents a computational model based on neural networks to determine the best configuration of a hybrid system to generate energy in water supply systems. In this study the energy sources to make this hybrid system can be the national power grid, micro-hydro and wind turbines. The artificial neural network is composed of six layers, trained to use data generated by a model of hybrid configuration and an economic simulator - CES. The reason for the development of an advanced model of forecasting based on neural networks is to allow rapid simulation and proper interaction with hydraulic and power model simulator - HPS. The results show that this computational model is useful as advanced decision support system in the design of configurations of hybrid power systems applied to water supply systems, improving the solutions in the development of its global energy efficiency.

  20. Multi-criteria decision making--an approach to setting priorities in health care.

    Science.gov (United States)

    Nobre, F F; Trotta, L T; Gomes, L F

    1999-12-15

    The objective of this paper is to present a multi-criteria decision making (MCDM) approach to support public health decision making that takes into consideration the fuzziness of the decision goals and the behavioural aspect of the decision maker. The approach is used to analyse the process of health technology procurement in a University Hospital in Rio de Janeiro, Brazil. The method, known as TODIM, relies on evaluating alternatives with a set of decision criteria assessed using an ordinal scale. Fuzziness in generating criteria scores and weights or conflicts caused by dealing with different viewpoints of a group of decision makers (DMs) are solved using fuzzy set aggregation rules. The results suggested that MCDM models, incorporating fuzzy set approaches, should form a set of tools for public health decision making analysis, particularly when there are polarized opinions and conflicting objectives from the DM group. Copyright 1999 John Wiley & Sons, Ltd.

  1. Granular computing and decision-making interactive and iterative approaches

    CERN Document Server

    Chen, Shyi-Ming

    2015-01-01

    This volume is devoted to interactive and iterative processes of decision-making– I2 Fuzzy Decision Making, in brief. Decision-making is inherently interactive. Fuzzy sets help realize human-machine communication in an efficient way by facilitating a two-way interaction in a friendly and transparent manner. Human-centric interaction is of paramount relevance as a leading guiding design principle of decision support systems.   The volume provides the reader with an updated and in-depth material on the conceptually appealing and practically sound methodology and practice of I2 Fuzzy Decision Making. The book engages a wealth of methods of fuzzy sets and Granular Computing, brings new concepts, architectures and practice of fuzzy decision-making providing the reader with various application studies.   The book is aimed at a broad audience of researchers and practitioners in numerous disciplines in which decision-making processes play a pivotal role and serve as a vehicle to produce solutions to existing prob...

  2. Intuition and emotion: examining two non-rational approaches in complex decision making

    OpenAIRE

    Huang, Tori Yu-wen

    2012-01-01

    This thesis was designed to examine two non-rational decision approaches in individual and team decision making. In Chapter 2 (Paper 1), a normative theory about how people should use intuition in making complex decisions is proposed. I draw from extant literature to derive why allowing intuition to interrupt analysis is beneficial to complex decision processes. In Chapter 3 (Paper 2), the theory of intuitive interruptions is applied to the entrepreneurial context. I argue that allowing intui...

  3. A hybrid approach to simulate multiple photon scattering in X-ray imaging

    International Nuclear Information System (INIS)

    Freud, N.; Letang, J.-M.; Babot, D.

    2005-01-01

    A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or γ-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results

  4. A hybrid approach to simulate multiple photon scattering in X-ray imaging

    Energy Technology Data Exchange (ETDEWEB)

    Freud, N. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)]. E-mail: nicolas.freud@insa-lyon.fr; Letang, J.-M. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France); Babot, D. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)

    2005-01-01

    A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or {gamma}-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results.

  5. Decision tree approach for classification of remotely sensed satellite ...

    Indian Academy of Sciences (India)

    sensed satellite data using open source support. Richa Sharma .... Decision tree classification techniques have been .... the USGS Earth Resource Observation Systems. (EROS) ... for shallow water, 11% were for sparse and dense built-up ...

  6. Decision tree approach for classification of remotely sensed satellite

    Indian Academy of Sciences (India)

    DTC) algorithm for classification of remotely sensed satellite data (Landsat TM) using open source support. The decision tree is constructed by recursively partitioning the spectral distribution of the training dataset using WEKA, open source ...

  7. Spatial and Temporal Flood Risk Assessment for Decision Making Approach

    Science.gov (United States)

    Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

    2018-03-01

    Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

  8. Comparing performance of organization on implementation of customer relationship management systems using ANP and TOPSIS hybrid approach

    Directory of Open Access Journals (Sweden)

    A. Abedi

    2017-01-01

    Full Text Available As the customers are the main reason of the formation and survival of the organization, not only understanding their obvious needs, but also forecasting, determining and guiding their hidden needs, design and implementing plans of offering services for meeting these needs for attracting customers are among cornerstone of any activity in the organization. In this research, one compares the performance of e-commerce organizations, including three firms, namely Dijikala, Bamilo and Iranian regarding the implementation of Customer Relationship Management system using multiple criteria decision making approach. Along with this, hybrid fuzzy multiple criteria decision-making approach, including fuzzy network analysis has been used for examining the priority of each one of the dimensions and indexes of the proposed model and fuzzy TOPSIS technic for examining discussed options priority. The statistical population of this paper includes 12 experts, including directors and managements and assistances of three e-commerce firms. The results obtained from the study show that customer output group has the highest weight among other variables. Similarly, among evaluated indexes, the customer loyalty dimension has the highest weight in the implementation of Customer Relationship Management. The results of TOPSIS approach also show that among the studied firms, Dijikala has the best performance in implementing Customer Relationship Management.

  9. Accrual based accounting implementation: An approach for modelling major decisions

    OpenAIRE

    Ratno Agriyanto; Abdul Rohman; Dwi Ratmono; Imam Ghozali

    2016-01-01

    Over the last three decades the main issues of implementation of accrual based accounting government institutions in Indonesia. Implementation of accrual based accounting in government institutions amid debate about the usefulness of accounting information for decision-making. Empirical study shows that the accrual based of accounting information on a government institution is not used for decision making. The research objective was to determine the impact of the implementation of the accrual...

  10. The Constructive Role of Decisions: Implications from a quantum Approach

    Science.gov (United States)

    2016-12-01

    probabilities to events from quantum mechanics, without any of the physics . Classical Theory (CT) has been the dominant probabilistic framework in decision...forces the ‘system’ to identify with the result of the measurement. In physics , measuring the position of an elementary particle makes the particle have...digital context in moral decision making In this digital age, we spend a lot of time interacting with computer screens, smartphones and other digital

  11. Business intelligence and financial decision-making: a theoretical approach

    OpenAIRE

    Mary Julieth Murillo Junco; Gustavo Cáceres Castellanos

    2013-01-01

    This paper deals with a literature review about the origin, development and implementation of Business Intelligence focused directly to solving problems in the financial area of the different organizations. Wanted contextualize how it tools have been incorporated into the decision making processes of modern business. A feature of the way it makes decisions has to do with the rational use made of the information available, and it is in this field where information technology and communication ...

  12. Effective Approach to Elevate the Intelligence of Management Decision System

    Institute of Scientific and Technical Information of China (English)

    杨保安; 朱明; 唐志杰; 陈思

    2003-01-01

    Based on the sticking point of the low intelligence of the existing management decision system,this paper puts forward the idea of enriching and refining the knowledge of the system and endowing it with the ability to learn by means of adopting three types of heterogeneous knowledge representation and knowledge management measures.At length,this paper outlines the basic framework of an intelligence system for the sake of management decision problem.

  13. Business intelligence and financial decision-making: a theoretical approach

    Directory of Open Access Journals (Sweden)

    Mary Julieth Murillo Junco

    2013-01-01

    Full Text Available This paper deals with a literature review about the origin, development and implementation of Business Intelligence focused directly to solving problems in the financial area of the different organizations. Wanted contextualize how it tools have been incorporated into the decision making processes of modern business. A feature of the way it makes decisions has to do with the rational use made of the information available, and it is in this field where information technology and communication play a role today

  14. A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid Wind Turbine Rotors

    Directory of Open Access Journals (Sweden)

    José F. Herbert-Acero

    2014-01-01

    Full Text Available This work presents a novel framework for the aerodynamic design and optimization of blades for small horizontal axis wind turbines (WT. The framework is based on a state-of-the-art blade element momentum model, which is complemented with the XFOIL 6.96 software in order to provide an estimate of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize the aerodynamic efficiency of small WT (SWT rotors for a wide range of operational conditions. The design variables are (1 the airfoil shape at the different blade span positions and the radial variation of the geometrical variables of (2 chord length, (3 twist angle, and (4 thickness along the blade span. A wind tunnel validation study of optimized rotors based on the NACA 4-digit airfoil series is presented. Based on the experimental data, improvements in terms of the aerodynamic efficiency, the cut-in wind speed, and the amount of material used during the manufacturing process were achieved. Recommendations for the aerodynamic design of SWT rotors are provided based on field experience.

  15. Strategic Decision Making for Organizational Sustainability: The Implications of Servant Leadership and Sustainable Leadership Approaches

    OpenAIRE

    Judita Peterlin; Noel J. Pearse; Vlado Dimovski

    2015-01-01

    This conceptual paper explores the implications of servant leadership and sustainable leadership for strategic decision making by the top management of an organization. It is argued that a different type of leadership is required if effective strategic decisions are to be made in organizations striving to become more sustainable and that servant leadership and sustainable leadership approaches provide a sound basis to inform these decisions. The contributions of these two leadership approache...

  16. A Low Cost, Hybrid Approach to Data Mining, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed effort will combine a low cost physical modeling approach with inductive, data-centered modeling in an aerosopace relevant context to demonstrate...

  17. Hybrid Metaheuristic Approach for Nonlocal Optimization of Molecular Systems.

    Science.gov (United States)

    Dresselhaus, Thomas; Yang, Jack; Kumbhar, Sadhana; Waller, Mark P

    2013-04-09

    Accurate modeling of molecular systems requires a good knowledge of the structure; therefore, conformation searching/optimization is a routine necessity in computational chemistry. Here we present a hybrid metaheuristic optimization (HMO) algorithm, which combines ant colony optimization (ACO) and particle swarm optimization (PSO) for the optimization of molecular systems. The HMO implementation meta-optimizes the parameters of the ACO algorithm on-the-fly by the coupled PSO algorithm. The ACO parameters were optimized on a set of small difluorinated polyenes where the parameters exhibited small variance as the size of the molecule increased. The HMO algorithm was validated by searching for the closed form of around 100 molecular balances. Compared to the gradient-based optimized molecular balance structures, the HMO algorithm was able to find low-energy conformations with a 87% success rate. Finally, the computational effort for generating low-energy conformation(s) for the phenylalanyl-glycyl-glycine tripeptide was approximately 60 CPU hours with the ACO algorithm, in comparison to 4 CPU years required for an exhaustive brute-force calculation.

  18. A Hybrid Approach to Spatial Multiplexing in Multiuser MIMO Downlinks

    Directory of Open Access Journals (Sweden)

    Spencer Quentin H

    2004-01-01

    Full Text Available In the downlink of a multiuser multiple-input multiple-output (MIMO communication system, simultaneous transmission to several users requires joint optimization of the transmitted signals. Allowing all users to have multiple antennas adds an additional degree of complexity to the problem. In this paper, we examine the case where a single base station transmits to multiple users using linear processing (beamforming at each of the antenna arrays. We propose generalizations of several previous iterative algorithms for multiuser transmit beamforming that allow multiple antennas and multiple data streams for each user, and that take into account imperfect channel estimates at the transmitter. We then present a new hybrid algorithm that is based on coordinated transmit-receive beamforming, and combines the strengths of nonorthogonal iterative solutions with zero-forcing solutions. The problem of distributing power among the subchannels is solved by using standard bit-loading algorithms combined with the subchannel gains resulting from the zero-forcing solution. The result is a significant performance improvement over equal power distribution. At the same time, the number of iterations required to compute the final solution is reduced.

  19. Multi-level and hybrid modelling approaches for systems biology.

    Science.gov (United States)

    Bardini, R; Politano, G; Benso, A; Di Carlo, S

    2017-01-01

    During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

  20. A new approach to flow simulation using hybrid models

    Science.gov (United States)

    Solgi, Abazar; Zarei, Heidar; Nourani, Vahid; Bahmani, Ramin

    2017-11-01

    The necessity of flow prediction in rivers, for proper management of water resource, and the need for determining the inflow to the dam reservoir, designing efficient flood warning systems and so forth, have always led water researchers to think about models with high-speed response and low error. In the recent years, the development of Artificial Neural Networks and Wavelet theory and using the combination of models help researchers to estimate the river flow better and better. In this study, daily and monthly scales were used for simulating the flow of Gamasiyab River, Nahavand, Iran. The first simulation was done using two types of ANN and ANFIS models. Then, using wavelet theory and decomposing input signals of the used parameters, sub-signals were obtained and were fed into the ANN and ANFIS to obtain hybrid models of WANN and WANFIS. In this study, in addition to the parameters of precipitation and flow, parameters of temperature and evaporation were used to analyze their effects on the simulation. The results showed that using wavelet transform improved the performance of the models in both monthly and daily scale. However, it had a better effect on the monthly scale and the WANFIS was the best model.

  1. Hybrid Enhanced Epidermal SpaceSuit Design Approaches

    Science.gov (United States)

    Jessup, Joseph M.

    A Space suit that does not rely on gas pressurization is a multi-faceted problem that requires major stability controls to be incorporated during design and construction. The concept of Hybrid Epidermal Enhancement space suit integrates evolved human anthropomorphic and physiological adaptations into its functionality, using commercially available bio-medical technologies to address shortcomings of conventional gas pressure suits, and the impracticalities of MCP suits. The prototype HEE Space Suit explored integumentary homeostasis, thermal control and mobility using advanced bio-medical materials technology and construction concepts. The goal was a space suit that functions as an enhanced, multi-functional bio-mimic of the human epidermal layer that works in attunement with the wearer rather than as a separate system. In addressing human physiological requirements for design and construction of the HEE suit, testing regimes were devised and integrated into the prototype which was then subject to a series of detailed tests using both anatomical reproduction methods and human subject.

  2. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Science.gov (United States)

    Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin; Choo, Kim-Kwang Raymond

    2016-01-01

    To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO).

  3. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Directory of Open Access Journals (Sweden)

    Firdaus Afifi

    Full Text Available To deal with the large number of malicious mobile applications (e.g. mobile malware, a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS and particle swarm optimization (PSO. Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE and ant colony optimization (ANFIS-ACO.

  4. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware

    Science.gov (United States)

    Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin

    2016-01-01

    To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO). PMID:27611312

  5. A hybrid clustering approach to recognition of protein families in 114 microbial genomes

    Directory of Open Access Journals (Sweden)

    Gogarten J Peter

    2004-04-01

    Full Text Available Abstract Background Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function. Standard clustering methods such as single-linkage clustering capture a history of cluster topologies as a function of threshold, but in practice their usefulness is limited because unrelated sequences join clusters before biologically meaningful families are fully constituted, e.g. as the result of matches to so-called promiscuous domains. Use of the Markov Cluster algorithm avoids this non-specificity, but does not preserve topological or threshold information about protein families. Results We describe a hybrid approach to sequence-based clustering of proteins that combines the advantages of standard and Markov clustering. We have implemented this hybrid approach over a relational database environment, and describe its application to clustering a large subset of PDB, and to 328577 proteins from 114 fully sequenced microbial genomes. To demonstrate utility with difficult problems, we show that hybrid clustering allows us to constitute the paralogous family of ATP synthase F1 rotary motor subunits into a single, biologically interpretable hierarchical grouping that was not accessible using either single-linkage or Markov clustering alone. We describe validation of this method by hybrid clustering of PDB and mapping SCOP families and domains onto the resulting clusters. Conclusion Hybrid (Markov followed by single-linkage clustering combines the advantages of the Markov Cluster algorithm (avoidance of non-specific clusters resulting from matches to promiscuous domains and single-linkage clustering (preservation of topological information as a function of threshold. Within the individual Markov clusters, single-linkage clustering is a more-precise instrument, discerning sub-clusters of biological relevance. Our hybrid approach thus provides a computationally efficient

  6. Molecular and morphological approaches for species delimitation and hybridization investigations of two Cichla species

    Directory of Open Access Journals (Sweden)

    Andrea A. F. Mourão

    Full Text Available ABSTRACT The hybridization is a widely-discussed issue in several studies with fish species. For some authors, hybridization may be related with diversification and speciation of several groups, or also with the extinction of populations or species. Difficulties to differentiate species and hybrids may be a problem to correctly apply a management of wild species, because hybrid lineages, especially the advanced ones, may resemble the parental species. The genus Cichla Bloch & Schneider, 1801 constitutes an interesting experimental model, considering that hybridization and taxonomic uncertainties hinder a correct identification. Considering these problems, in this study, we developed genetic methodologies and applied meristic and morphometric approaches in wild samples in order to identify species and for test a possible hybridization between Cichla kelberi Kullander & Ferreira, 2006 and Cichla piquiti Kullander & Ferreira, 2006. For this, C. kelberi, C. piquiti and potential hybrid ( carijó individuals were collected in Paraná and Tietê rivers (SP, Brazil. For meristic and morphometric methods, the individuals were analyzed using the statistical software Pcord 5:31, while for molecular methods, primers for PCR-multiplex were designed and enzyme for PCR-RFLP were selected, under the species-specific nucleotide. All results indicated that the carijó is not an interspecific hybrid, because it presented identical genetic pattern and morphology closed to C. piquiti. Thus, we propose that carijó is a C. piquiti morphotype. In addition, this study promotes a new molecular tool that could be used in future research, monitoring and management programs of the genus Cichla.

  7. A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

    Science.gov (United States)

    Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

    2017-12-01

    Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

  8. Bioenergy II. Biomass Valorisation by a Hybrid Thermochemical Fractionation Approach

    Energy Technology Data Exchange (ETDEWEB)

    De Wild, P.J.; Den Uil, H.; Reith, J.H. [ECN Biomass, Coal and Environmental Research, Petten (Netherlands); Lunshof, A.; Hendriks, C.; Van Eck, E. [Radboud University, Nijmegen (Netherlands); Heeres, E. [University of Groningen, Groningen (Netherlands)

    2009-11-15

    The need for green renewable sources is adamant because of the adverse effects of the increasing use of fossil fuels on our society. Biomass has been considered as a very attractive candidate for green energy carriers, chemicals and materials. The development of cheap and efficient fractionation technology to separate biomass into its main constituents is highly desirable. It enables treatment of each constituent separately, using dedicated conversion technologies to get specific target chemicals. The synergistic combination of aquathermolysis (hot pressurised water treatment) and pyrolysis (thermal degradation in the absence of oxygen) is a promising thermolysis option, integrating fractionation of biomass with production of valuable chemicals. Batch aquathermolysis in an autoclave and subsequent pyrolysis using bubbling fluidised bed reactor technology with beech, poplar, spruce and straw indicate the potential of this hybrid concept to valorise lignocellulosic biomass. Hemicellulose-derived furfural was obtained in yields that ranged from 2 wt% for spruce to 8 wt% for straw. Hydroxymethylfurfural from hemicellulose was obtained in yields from 0.3 wt% for poplar to 3 wt% for spruce. Pyrolysis of the aquathermolised biomass types resulted in 8 wt% (straw) to 11 wt% (spruce) of cellulose-derived levoglucosan. Next to the furfurals and levoglucosan, appreciable amounts of acetic acid were obtained as well from the aquathermolysis step, ranging from 1 wt% for spruce to 5 wt% for straw. To elucidate relations between the chemical changes occurring in the biomass during the integrated process and type and amount of the chemical products formed, a 13C-solid state NMR study has been conducted. Main conclusions are that aquathermolysis results in hemicellulose degradation to lower molecular weight components. Lignin ether bonds are broken, but apart from that, lignin is hardly affected by the aquathermolysis. Cellulose is also retained, although it seems to become more

  9. Statistical comparison of a hybrid approach with approximate and exact inference models for Fusion 2+

    Science.gov (United States)

    Lee, K. David; Wiesenfeld, Eric; Gelfand, Andrew

    2007-04-01

    One of the greatest challenges in modern combat is maintaining a high level of timely Situational Awareness (SA). In many situations, computational complexity and accuracy considerations make the development and deployment of real-time, high-level inference tools very difficult. An innovative hybrid framework that combines Bayesian inference, in the form of Bayesian Networks, and Possibility Theory, in the form of Fuzzy Logic systems, has recently been introduced to provide a rigorous framework for high-level inference. In previous research, the theoretical basis and benefits of the hybrid approach have been developed. However, lacking is a concrete experimental comparison of the hybrid framework with traditional fusion methods, to demonstrate and quantify this benefit. The goal of this research, therefore, is to provide a statistical analysis on the comparison of the accuracy and performance of hybrid network theory, with pure Bayesian and Fuzzy systems and an inexact Bayesian system approximated using Particle Filtering. To accomplish this task, domain specific models will be developed under these different theoretical approaches and then evaluated, via Monte Carlo Simulation, in comparison to situational ground truth to measure accuracy and fidelity. Following this, a rigorous statistical analysis of the performance results will be performed, to quantify the benefit of hybrid inference to other fusion tools.

  10. The business case for condition-based maintenance: a hybrid (non-) financial approach

    NARCIS (Netherlands)

    Tiddens, W.W.; Tinga, T.; Braaksma, A.J.J.; Brouwer, O.; Cepin, Marko; Bris, Radim

    2017-01-01

    Although developing business cases is key for evaluating project success, the costs and benefits of condition-based maintenance (CBM) implementations are often not explicitly defined and evaluated. Using the design science methodology, we developed a hybrid business case approach to help managers

  11. A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

  12. Students' Game Performance Improvements during a Hybrid Sport Education-Step-Game-Approach Volleyball Unit

    Science.gov (United States)

    Araújo, Rui; Mesquita, Isabel; Hastie, Peter; Pereira, Cristiana

    2016-01-01

    The purpose of this study was to examine a hybrid combination of sport education and the step-game-approach (SGA) on students' gameplay performance in volleyball, taking into account their sex and skill-level. Seventeen seventh-grade students (seven girls, 10 boys, average age 11.8) participated in a 25-lesson volleyball season, in which the…

  13. TwitterNEED: a hybrid approach for named entity extraction and disambiguation for tweets

    NARCIS (Netherlands)

    Habib, Mena Badieh; van Keulen, Maurice

    Twitter is a rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing tasks. In this paper, we present TwitterNEED, a hybrid approach for Named Entity Extraction and Named Entity Disambiguation for tweets. We

  14. A hybrid system approach to airspeed, angle of attack and sideslip estimation in Unmanned Aerial Vehicles

    KAUST Repository

    Shaqura, Mohammad; Claudel, Christian

    2015-01-01

    , low power autopilots in real-time. The computational method is based on a hybrid decomposition of the modes of operation of the UAV. A Bayesian approach is considered for estimation, in which the estimated airspeed, angle of attack and sideslip

  15. A Hybrid Approach to Processing Big Data Graphs on Memory-Restricted Systems

    KAUST Repository

    Harshvardhan,; West, Brandon; Fidel, Adam; Amato, Nancy M.; Rauchwerger, Lawrence

    2015-01-01

    that sacrifice performance. In this work, we propose a novel RAM-Disk hybrid approach to graph processing that can scale well from a single shared-memory node to large distributed-memory systems. It works by partitioning the graph into sub graphs that fit in RAM

  16. Accrual based accounting implementation: An approach for modelling major decisions

    Directory of Open Access Journals (Sweden)

    Ratno Agriyanto

    2016-12-01

    Full Text Available Over the last three decades the main issues of implementation of accrual based accounting government institutions in Indonesia. Implementation of accrual based accounting in government institutions amid debate about the usefulness of accounting information for decision-making. Empirical study shows that the accrual based of accounting information on a government institution is not used for decision making. The research objective was to determine the impact of the implementation of the accrual based accounting to the accrual basis of accounting information use for decision-making basis. We used the survey questionnaires. The data were processed by SEM using statistical software WarpPLS. The results showed that the implementation of the accrual based accounting in City Government Semarang has significantly positively associated with decision-making. Another important finding is the City Government officials of Semarang have personality, low tolerance of ambiguity is a negative effect on the relationship between the implementation of the accrual based accounting for decision making

  17. A Hybrid Change Detection Approach for Damage Detection and Recovery Monitoring

    Science.gov (United States)

    de Alwis Pitts, Dilkushi; Wieland, Marc; Wang, Shifeng; So, Emily; Pittore, Massimiliano

    2014-05-01

    Following a disaster, change detection via pre- and post-event very high resolution remote sensing images is an essential technique for damage assessment and recovery monitoring over large areas in complex urban environments. Most assessments to date focus on detection, destruction and recovery of man-made objects that facilitate shelter and accessibility, such as buildings, roads, bridges, etc., as indicators for assessment and better decision making. Moreover, many current change-detection mechanisms do not use all the data and knowledge which are often available for the pre-disaster state. Recognizing the continuous rather than dichotomous character of the data-rich/data-poor distinction permits the incorporation of ancillary data and existing knowledge into the processing flow. Such incorporation could improve the reliability of the results and thereby enhance the usability of robust methods for disaster management. This study proposes an application-specific and robust change detection method from multi-temporal very high resolution multi-spectral satellite images. This hybrid indicator-specific method uses readily available pre-disaster GIS data and integrates existing knowledge into the processing flow to optimize the change detection while offering the possibility to target specific types of changes to man-made objects. The indicator-specific information of the GIS objects is used as a series of masks to treat the GIS objects with similar characteristics similarly for better accuracy. The proposed approach is based on a fusion of a multi-index change detection method based on gradient, texture and edge similarity filters. The change detection index is flexible for disaster cases in which the pre-disaster and post-disaster images are not of the same resolution. The proposed automated method is evaluated with QuickBird and Ikonos datasets for abrupt changes soon after disaster. The method could also be extended in a semi-automated way for monitoring

  18. A hybrid linked data approach to support asset management

    NARCIS (Netherlands)

    Luiten, G.T.; Bohms, H.M.; O'Keeffe, A.; Nederveen, S. van; Bakker, J.; Wikstrom, L.

    2016-01-01

    This paper evaluates experiences with applying a linked data approach for coping with the many challenges for information management in asset management from the perspective of National Road Authorities (NRAs). As influential players, NRAs are often the initiators of innovation in the civil

  19. Regulatory approach to risk informed decision making in India

    International Nuclear Information System (INIS)

    Chande, S.K.; Koley, J.

    2001-01-01

    Atomic Energy Regulatory Board (AERB), the authority for licensing and monitoring safety in Indian Nuclear Power Plants (NPPs), makes use of insights gained from PSA together with the results of the other deterministic analyses in taking decisions regarding the acceptability of the safety of the NPPs. PSA provides an estimation of risks; it also gives information on a balanced design by revealing interaction between engineered features and weak areas in a design. For regulatory use, PSA needs to be carried out using standardized methodology and state of the art technology. PSA helps regulators in taking faster and consistent decisions. Keeping in mind the limitations associated with PSA study, AERB has decided to adopt risk-informed decision making in regulatory licensing process. This paper describes the AERB policy regarding PSA and gives an overview of the experience in this area. (author)

  20. Concurrent approach for evolving compact decision rule sets

    Science.gov (United States)

    Marmelstein, Robert E.; Hammack, Lonnie P.; Lamont, Gary B.

    1999-02-01

    The induction of decision rules from data is important to many disciplines, including artificial intelligence and pattern recognition. To improve the state of the art in this area, we introduced the genetic rule and classifier construction environment (GRaCCE). It was previously shown that GRaCCE consistently evolved decision rule sets from data, which were significantly more compact than those produced by other methods (such as decision tree algorithms). The primary disadvantage of GRaCCe, however, is its relatively poor run-time execution performance. In this paper, a concurrent version of the GRaCCE architecture is introduced, which improves the efficiency of the original algorithm. A prototype of the algorithm is tested on an in- house parallel processor configuration and the results are discussed.

  1. Restraining approach for the spurious kinematic modes in hybrid equilibrium element

    Science.gov (United States)

    Parrinello, F.

    2013-10-01

    The present paper proposes a rigorous approach for the elimination of spurious kinematic modes in hybrid equilibrium elements, for three well known mesh patches. The approach is based on the identification of the dependent equations in the set of inter-element and boundary equilibrium equations of the sides involved in the spurious kinematic mode. Then the kinematic variables related to the dependent equations are reciprocally constrained and, by application of master slave elimination method, the set of inter-element equilibrium equations is reduced to full rank. The elastic solutions produced by means of the proposed approach verify the homogeneous, the inter-element and the boundary equilibrium equations. Hybrid stress formulation is developed in a rigorous mathematical setting. The results of linear elastic analysis obtained by the proposed approach and by classical displacement based method are compared for some structural examples.

  2. Narrative Interest Standard: A Novel Approach to Surrogate Decision-Making for People With Dementia.

    Science.gov (United States)

    Wilkins, James M

    2017-06-17

    Dementia is a common neurodegenerative process that can significantly impair decision-making capacity as the disease progresses. When a person is found to lack capacity to make a decision, a surrogate decision-maker is generally sought to aid in decision-making. Typical bases for surrogate decision-making include the substituted judgment standard and the best interest standard. Given the heterogeneous and progressive course of dementia, however, these standards for surrogate decision-making are often insufficient in providing guidance for the decision-making for a person with dementia, escalating the likelihood of conflict in these decisions. In this article, the narrative interest standard is presented as a novel and more appropriate approach to surrogate decision-making for people with dementia. Through case presentation and ethical analysis, the standard mechanisms for surrogate decision-making for people with dementia are reviewed and critiqued. The narrative interest standard is then introduced and discussed as a dementia-specific model for surrogate decision-making. Through incorporation of elements of a best interest standard in focusing on the current benefit-burden ratio and elements of narrative to provide context, history, and flexibility for values and preferences that may change over time, the narrative interest standard allows for elaboration of an enriched context for surrogate decision-making for people with dementia. More importantly, however, a narrative approach encourages the direct contribution from people with dementia in authoring the story of what matters to them in their lives.

  3. Decisive Interactions between the Heterocyclic Moiety and the Cluster Observed in Polyoxometalate-Surfactant Hybrid Crystals

    Directory of Open Access Journals (Sweden)

    Saki Otobe

    2015-04-01

    Full Text Available Inorganic-organic hybrid crystals were successfully obtained as single crystals by using polyoxotungstate anion and cationic dodecylpyridazinium (C12pda and dodecylpyridinium (C12py surfactants. The decatungstate (W10 anion was used as the inorganic component, and the crystal structures were compared. In the crystal comprising C12pda (C12pda-W10, the heterocyclic moiety directly interacted with W10, which contributed to a build-up of the crystal structure. On the other hand, the crystal consisting of C12py (C12py-W10 had similar crystal packing and molecular arrangement to those in the W10 crystal hybridized with other pyridinium surfactants. These results indicate the significance of the heterocyclic moiety of the surfactant to construct hybrid crystals with polyoxometalate anions.

  4. A Hybrid approach for aeroacoustic analysis of the engine exhaust system

    OpenAIRE

    Sathyanarayana, Y; Munjal, ML

    2000-01-01

    This paper presents a new hybrid approach for prediction of noise radiation from engine exhaust systems. It couples the time domain analysis of the engine and the frequency domain analysis of the muffler, and has the advantages of both. In this approach, cylinder/cavity is analyzed in the time domain to calculate the exhaust mass flux history at the exhaust valve by means of the method of characteristics, avoiding the tedious procedure of interpolation at every mesh point and solving a number...

  5. Unilateral robotic hybrid mini-maze: a novel experimental approach.

    Science.gov (United States)

    Moslemi, Mohammad; Rawashdeh, Badi; Meyer, Mark; Nguyen, Duy; Poston, Robert; Gharagozloo, Farid

    2016-03-01

    A complete Cox maze IV procedure is difficult to accomplish using current endoscopic and minimally invasive techniques. These techniques are hampered by inability to adequately dissect the posterior structures of the heart and place all necessary lesions. We present a novel approach, using robotic technology, that achieves placement of all the lesions of the complete maze procedure. In three cadaveric human models, the technical feasibility of using robotic instruments through the right chest to dissect the posterior structures of the heart and place all Cox maze lesions was performed. The entire posterior aspect of the heart was dissected in the cadaveric model facilitating successful placement of all Cox maze IV lesions with robotic assistance through minimally invasive incisions. The robotic Cox maze IV procedure through the novel right thoracic approach is feasible. This obviates the need for sternotomy and avoids the associated morbidity of the conventional Cox-maze procedure. Copyright © 2015 John Wiley & Sons, Ltd.

  6. The evolution of green jobs in Scotland: A hybrid approach

    International Nuclear Information System (INIS)

    Connolly, Kevin; Allan, Grant J; McIntyre, Stuart G

    2016-01-01

    In support of its ambitious target to reduce CO_2 emissions the Scottish Government is aiming to have the equivalent of 100% of Scottish electricity consumption generated from renewable sources by 2020. This is, at least in part, motivated by an expectation of subsequent employment growth in low carbon and renewable energy technologies; however there is no official data source to track employment in these areas. This has led to a variety of definitions, methodologies and alternative estimates being produced. Building on a recent study (Bishop and Brand, 2013) we develop a “hybrid” approach which combines the detail of “bottom-up” surveys with “top-down” trend data to produce estimates on employment in Low Carbon Environmental Goods and Services (LCEGS). We demonstrate this methodology to produce estimates for such employment in Scotland between 2004 and 2012. Our approach shows how survey and official sources can combine to produce a more timely measure of employment in LCEGS activities, assisting policymakers in tracking, consistently, developments. Applying our approach, we find that over this period employment in LCEGS in Scotland grew, but that this was more volatile than aggregate employment, and in particular that employment in this sector was particularly badly hit during the great recession. - Highlights: • A “hybrid” approach estimates green jobs from bottom-up detail and top-down data. • Illustrative results show the evolution of such jobs in Scotland from 2004 to 2012. • Method provides policymakers a timely measure of the jobs success of energy policy.

  7. Hybrid approaches to nanometer-scale patterning: Exploiting tailored intermolecular interactions

    International Nuclear Information System (INIS)

    Mullen, Thomas J.; Srinivasan, Charan; Shuster, Mitchell J.; Horn, Mark W.; Andrews, Anne M.; Weiss, Paul S.

    2008-01-01

    In this perspective, we explore hybrid approaches to nanometer-scale patterning, where the precision of molecular self-assembly is combined with the sophistication and fidelity of lithography. Two areas - improving existing lithographic techniques through self-assembly and fabricating chemically patterned surfaces - will be discussed in terms of their advantages, limitations, applications, and future outlook. The creation of such chemical patterns enables new capabilities, including the assembly of biospecific surfaces to be recognized by, and to capture analytes from, complex mixtures. Finally, we speculate on the potential impact and upcoming challenges of these hybrid strategies.

  8. Approach to decision modeling for an ignition test reactor

    International Nuclear Information System (INIS)

    Howland, H.R.; Varljen, T.C.

    1977-01-01

    A comparison matrix decision model is applied to candidates for a D-T ignition tokamak (TNS), including assessment of semi-quantifiable or judgemental factors as well as quantitative ones. The results show that TNS is mission-sensitive with a choice implied between near-term achievability and reactor technology

  9. Measuring local autonomy: A decision-making approach

    NARCIS (Netherlands)

    Fleurke, F.; Willemse, R.

    2006-01-01

    In studies on central-local relations it is common to assess local autonomy in a deductive way. The extent of local autonomy is determined by measuring the central legal and financial competence, after which the remaining room for local decision-making is determined. The outcome of this indirect

  10. Life-oriented approach for urban policy decision-making: Surveys and applications

    OpenAIRE

    Junyi Zhang; Yubing Xiong; Minh Tu Tran

    2014-01-01

    In this study, we propose an additional approach, called life-oriented approach, for supporting urban policy decisions. The life-oriented approach argues that people's decisions on various life choices are not independent of each other and that an understanding of life choices should not be constrained by the boundary of any single discipline. People's life choices are closely linked with the quality of life (QOL), which can be roughly captured from the perspective of life domains such as res...

  11. A hybrid, coupled approach for modeling charged fluids from the nano to the mesoscale

    Science.gov (United States)

    Cheung, James; Frischknecht, Amalie L.; Perego, Mauro; Bochev, Pavel

    2017-11-01

    We develop and demonstrate a new, hybrid simulation approach for charged fluids, which combines the accuracy of the nonlocal, classical density functional theory (cDFT) with the efficiency of the Poisson-Nernst-Planck (PNP) equations. The approach is motivated by the fact that the more accurate description of the physics in the cDFT model is required only near the charged surfaces, while away from these regions the PNP equations provide an acceptable representation of the ionic system. We formulate the hybrid approach in two stages. The first stage defines a coupled hybrid model in which the PNP and cDFT equations act independently on two overlapping domains, subject to suitable interface coupling conditions. At the second stage we apply the principles of the alternating Schwarz method to the hybrid model by using the interface conditions to define the appropriate boundary conditions and volume constraints exchanged between the PNP and the cDFT subdomains. Numerical examples with two representative examples of ionic systems demonstrate the numerical properties of the method and its potential to reduce the computational cost of a full cDFT calculation, while retaining the accuracy of the latter near the charged surfaces.

  12. Numerical schemes for the hybrid modeling approach of gas-particle turbulent flows

    International Nuclear Information System (INIS)

    Dorogan, K.

    2012-01-01

    Hybrid Moments/PDF methods have shown to be well suitable for the description of poly-dispersed turbulent two-phase flows in non-equilibrium which are encountered in some industrial situations involving chemical reactions, combustion or sprays. They allow to obtain a fine enough physical description of the poly-dispersity, non-linear source terms and convection phenomena. However, their approximations are noised with the statistical error, which in several situations may be a source of a bias. An alternative hybrid Moments-Moments/PDF approach examined in this work consists in coupling the Moments and the PDF descriptions, within the description of the dispersed phase itself. This hybrid method could reduce the statistical error and remove the bias. However, such a coupling is not straightforward in practice and requires the development of accurate and stable numerical schemes. The approaches introduced in this work rely on the combined use of the up-winding and relaxation-type techniques. They allow to obtain stable unsteady approximations for a system of partial differential equations containing non-smooth external data which are provided by the PDF part of the model. A comparison of the results obtained using the present method with those of the 'classical' hybrid approach is presented in terms of the numerical errors for a case of a co-current gas-particle wall jet. (author)

  13. A Hybrid Decision-Making Model for Selecting Container Seaport in the Persian Gulf

    Directory of Open Access Journals (Sweden)

    Jafar Sayareh

    2014-04-01

    Full Text Available Ports have always played a vital role in international transportation. Port selection decision is a process that requires consideration of many important and relevant criteria. The selection of the influential decision-making criteria is also a significant and vital issue which demands cautious thoughts. The main objective of this paper is to weigh the most dominant decision-making criteria by Technique for Order Preference to Similarity by Ideal Solution (TOPSIS and select an optimised container seaport in the Persian Gulf by Analytical Hierarchy Process (AHP according to decisive port selection factors. This paper presents an extensive review of port selection decision-making attributes in different past studies. Finally, by using TOPSIS and AHP, the findings of this research suggest that the working time, stevedoring rate, safety, port entrance, sufficient draft, capacity of port facilities, operating cost, number of berths, ship chandelling, and international policies are critical factors for selecting container seaport in the Persian Gulf.

  14. Shaping decisions in volleyball An ecological approach to decision-making in volleyball passing

    NARCIS (Netherlands)

    Barsingerhorn, Annemiek D.; Zaal, Frank T. J. M.; De Poel, Harjo J.; Pepping, Gert-Jan

    2013-01-01

    To extend research on decision-making in sport we addressed the choices volleyball-players are faced with in a simple volleyball pass-return task. We manipulated the distance that eight experienced volleyball players had to cover for successful ball passing, and mapped their passing technique (i.e.,

  15. Entity recognition in the biomedical domain using a hybrid approach.

    Science.gov (United States)

    Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

    2017-11-09

    This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

  16. The approaches for the decision support in case natural hazards

    Science.gov (United States)

    Vyazilov, Evgeny; Chunyaev, Nikita

    2013-04-01

    In spite of using highly automated systems of measurement, collecting, storing, handling, prediction and delivery of information on the marine environment, including natural hazards, the amount of damage from natural phenomena increases. Because information on the marine environment delivered to the industrial facilities not effectively used. To such information pays little attention by individual decision-makers and not always perform preventive measures necessary for reduce and prevent damage. Automation of information support will improve the efficiency management of the marine activities. In Russia develops "The Unified system of the information about World ocean" (ESIMO, http://esimo.ru/), that integrates observation, analysis, prognostic and climate data. Necessary to create tools to automatic selection natural disasters through all integrated data; notification decision-makers about arising natural hazards - software agent; provision of information in a compact form for the decision-makers; assessment of possible damage and costs to the preventive measures; providing information on the impacts of environment on economic facilities and recommendations for decision-making; the use of maps, diagrams, tables for reporting. Tools for automatic selection designed for identification of natural phenomena based on the resources ESIMO and corresponding critical values of the indicators environment. The result of this module will be constantly updated database of critical situations of environment for each object or technological process. To operational notify and provide current information about natural hazards proposes using a software agent that is installed on the computer decision-makers, which is activated in case critical situations and provides a minimum of information. In the event of natural disaster software agent should be able to inform decision-makers about this, providing information on the current situation, and the possibility for more and detailed

  17. A bottom-up approach for the synthesis of highly ordered fullerene-intercalated graphene hybrids

    Directory of Open Access Journals (Sweden)

    Dimitrios eGournis

    2015-02-01

    Full Text Available Much of the research effort on graphene focuses on its use as a building block for the development of new hybrid nanostructures with well-defined dimensions and properties suitable for applications such as gas storage, heterogeneous catalysis, gas/liquid separations, nanosensing and biomedicine. Towards this aim, here we describe a new bottom-up approach, which combines self-assembly with the Langmuir Schaefer deposition technique to synthesize graphene-based layered hybrid materials hosting fullerene molecules within the interlayer space. Our film preparation consists in a bottom-up layer-by-layer process that proceeds via the formation of a hybrid organo-graphene oxide Langmuir film. The structure and composition of these hybrid fullerene-containing thin multilayers deposited on hydrophobic substrates were characterized by a combination of X-ray diffraction, Raman and X-ray photoelectron spectroscopies, atomic force microscopy and conductivity measurements. The latter revealed that the presence of C60 within the interlayer spacing leads to an increase in electrical conductivity of the hybrid material as compared to the organo-graphene matrix alone.

  18. A hybrid approach to device integration on a genetic analysis platform

    International Nuclear Information System (INIS)

    Brennan, Des; Justice, John; Aherne, Margaret; Galvin, Paul; Jary, Dorothee; Kurg, Ants; Berik, Evgeny; Macek, Milan

    2012-01-01

    Point-of-care (POC) systems require significant component integration to implement biochemical protocols associated with molecular diagnostic assays. Hybrid platforms where discrete components are combined in a single platform are a suitable approach to integration, where combining multiple device fabrication steps on a single substrate is not possible due to incompatible or costly fabrication steps. We integrate three devices each with a specific system functionality: (i) a silicon electro-wetting-on-dielectric (EWOD) device to move and mix sample and reagent droplets in an oil phase, (ii) a polymer microfluidic chip containing channels and reservoirs and (iii) an aqueous phase glass microarray for fluorescence microarray hybridization detection. The EWOD device offers the possibility of fully integrating on-chip sample preparation using nanolitre sample and reagent volumes. A key challenge is sample transfer from the oil phase EWOD device to the aqueous phase microarray for hybridization detection. The EWOD device, waveguide performance and functionality are maintained during the integration process. An on-chip biochemical protocol for arrayed primer extension (APEX) was implemented for single nucleotide polymorphism (SNiP) analysis. The prepared sample is aspirated from the EWOD oil phase to the aqueous phase microarray for hybridization. A bench-top instrumentation system was also developed around the integrated platform to drive the EWOD electrodes, implement APEX sample heating and image the microarray after hybridization. (paper)

  19. New MPPT algorithm for PV applications based on hybrid dynamical approach

    KAUST Repository

    Elmetennani, Shahrazed

    2016-10-24

    This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

  20. Mixed H∞ and passive control for linear switched systems via hybrid control approach

    Science.gov (United States)

    Zheng, Qunxian; Ling, Youzhu; Wei, Lisheng; Zhang, Hongbin

    2018-03-01

    This paper investigates the mixed H∞ and passive control problem for linear switched systems based on a hybrid control strategy. To solve this problem, first, a new performance index is proposed. This performance index can be viewed as the mixed weighted H∞ and passivity performance. Then, the hybrid controllers are used to stabilise the switched systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. The design of state updating controllers not only depends on the pre-switching subsystem and the post-switching subsystem, but also depends on the measurable output signal. The hybrid controllers proposed in this paper can include some existing ones as special cases. Combine the multiple Lyapunov functions approach with the average dwell time technique, new sufficient conditions are obtained. Under the new conditions, the closed-loop linear switched systems are globally uniformly asymptotically stable with a mixed H∞ and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example and a practical example are given.

  1. Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach

    Directory of Open Access Journals (Sweden)

    Oliveira Rui

    2010-09-01

    Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.

  2. New MPPT algorithm for PV applications based on hybrid dynamical approach

    KAUST Repository

    Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem; Djemai, M.; Tadjine, M.

    2016-01-01

    This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

  3. A rational approach to decision making in toxicology.

    Science.gov (United States)

    Jackson, B A; Sass, N L

    1984-06-01

    The application of the Kepner-Tregoe (C. H. Kepner and B. B. Tregoe, 1981, The New Rational Manager, Princeton Res. Press, Princeton, N. J.) problem solving technique to the evaluation and interpretation of toxicological information is described. Data from a chronic study provide an illustrative example. In this study an excess in the number of urinary bladder neoplasms was observed in male rats exposed to diets containing the test chemical. No similar effect was seen in treated female rats. Both male and female mice exposed to treatment also exhibited no effect. Whether treatment was the cause of the observed increase should be based on all the scientific and technical information that is relevant to this decision. The Kepner-Tregoe method of problem analysis captures this information in a framework that makes it easily understood. This is especially desirable if the judgments that are a vital part of regulatory decision making are to be adequately communicated.

  4. Engaging the public in decision-making. A Swiss approach

    International Nuclear Information System (INIS)

    Herrmann, A.

    1998-01-01

    The Swiss public is still involved in main decisions which may be concern them. The nuclear industry knows a lot about the difficulties of advancing with projects such as repository or new plants. The temptation is very high to change the existing law to simplify the procedure of authorization. But this would be a very bad way to circumvent the distrust of public against nuclear projects. Everywhere today politicians are promoting the empowerment of responsible citizens: in health care, consumers decision and so on. In the domain of nuclear concerns this empowerment is extremely important: especially in this field the public has rights and needs which must be taken into account. (R.P.)

  5. A Hybrid Harmony Search Algorithm Approach for Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Mimoun YOUNES

    2012-08-01

    Full Text Available Optimal Power Flow (OPF is one of the main functions of Power system operation. It determines the optimal settings of generating units, bus voltage, transformer tap and shunt elements in Power System with the objective of minimizing total production costs or losses while the system is operating within its security limits. The aim of this paper is to propose a novel methodology (BCGAs-HSA that solves OPF including both active and reactive power dispatch It is based on combining the binary-coded genetic algorithm (BCGAs and the harmony search algorithm (HSA to determine the optimal global solution. This method was tested on the modified IEEE 30 bus test system. The results obtained by this method are compared with those obtained with BCGAs or HSA separately. The results show that the BCGAs-HSA approach can converge to the optimum solution with accuracy compared to those reported recently in the literature.

  6. Fairness Concerns and Corrupt Decisions :an Experimental Approach

    OpenAIRE

    Epp, Lena; Leszczynska, Nastassia

    2017-01-01

    This study investigates the impact of a public officials' fairness considerations towards citizens in a petty corruption situation. Other-regarding preferences, and, more particularly, fairness concerns are widely acknowledged as crucial elements of individual economic decision-making. In petty corruption contexts, public officials are to a large extent aware of differences between citizens. Here, we experimentally investigate how fairness considerations may impact on corrupt behaviour. Our n...

  7. Decision Usefulness Approach Of Accounting Information: Bagaimana Informasi Akuntansi Menjadi Useful ?

    Directory of Open Access Journals (Sweden)

    Zarah Puspitaningtyas

    2010-10-01

    Full Text Available Application of decision usefulness approach to produce accounting information that is relevant and reliable. Relevant information, that has the capacity to affect the confidence of investors about future returns, and should be released in a timely manner.The concept of decision usefulness of accounting information plays an important role in identifying problems for users of financial reports and selection of accounting information that users of financial statements to make the best decision. To apply the concept of decision usefulness is necessary linkages with the various theories in economics and finance. Decision usefulness approach assumes that individual decision makers are rational, that is individuals who will choose the action that will yield the highest expected utility.

  8. A Decision Logic Approach to Mill’s Eliminative Induction

    Directory of Open Access Journals (Sweden)

    Piętka Dariusz

    2015-09-01

    Full Text Available The subject of the paper is a contemporary interpretation of J.S. Mill’s elimination method using selected concepts of Zdzisław Pawlak’s decision logic. The aim of the interpretation is to reformulate the original rules (canons of Mill’s induction so that they correspond more precisely to his concept of cause as a complex sufficient condition. In the first part of the paper, we turn to Mill’s writings and justify the thesis that in his understanding the cause is an aggregation of circumstances, and not a single circumstance; next, we point out that Mill’s original canons (for example the canon of agreement and the canon of difference do not allow causes-aggregations to be singled out from empirical data. In the second part of this paper, we present such aspects of Z. Pawlak’s decision logic that serve as the basis for the formalisation of the method of eliminative induction. We describe exhaustively the schema of induction that involves a gradual - divided into three stages - simplification of a set of implications corresponding to the observed dependencies [system of potential causes, effect]. The simplification is deductive because it maintains consistency within the set of implications. We show that such schema is ideal for isolating complex causes (aggregations of circumstances, ultimately described using complex conditional formulas of decision logic.

  9. NBI - plasma vaporization hybrid approach in bladder cancer endoscopic management.

    Science.gov (United States)

    Stănescu, F; Geavlete, B; Georgescu, D; Jecu, M; Moldoveanu, C; Adou, L; Bulai, C; Ene, C; Geavlete, P

    2014-06-15

    A prospective study was performed aiming to evaluate the surgical efficacy, perioperative safety profile, diagnostic accuracy and medium term results of a multi-modal approach consisting in narrow band imaging (NBI) cystoscopy and bipolar plasma vaporization (BPV) when compared to the standard protocol represented by white light cystoscopy (WLC) and transurethral resection of bladder tumors (TURBT). A total of 260 patients with apparently at least one bladder tumor over 3 cm were included in the trial. In the first group, 130 patients underwent conventional and NBI cystoscopy followed by BPV, while in a similar number of cases of the second arm, classical WLC and TURBT were applied. In all non-muscle invasive bladder tumors' (NMIBT) pathologically confirmed cases, standard monopolar Re-TUR was performed at 4-6 weeks after the initial intervention, followed by one year' BCG immunotherapy. The follow-up protocol included abdominal ultrasound, urinary cytology and WLC, performed every 3 months for a period of 2 years. The obturator nerve stimulation, bladder wall perforation, mean hemoglobin level drop, postoperative bleeding, catheterization period and hospital stay were significantly reduced for the plasma vaporization technique by comparison to conventional resection. Concerning tumoral detection, the present data confirmed the NBI superiority when compared to standard WLC regardless of tumor stage (95.3% vs. 65.1% for CIS, 93.3% vs. 82.2% for pTa, 97.4% vs. 94% for pT1, 95% vs. 84.2% overall). During standard Re-TUR the overall (6.3% versus 17.4%) and primary site (3.6% versus 12.8%) residual tumors' rates were significantly lower for the NBI-BPV group. The 1 (7.2% versus 18.3%) and 2 (11.5% versus 25.8%) years' recurrence rates were substantially lower for the combined approach. NBI cystoscopy significantly improved diagnostic accuracy, while bipolar technology showed a higher surgical efficiency, lower morbidity and faster postoperative recovery. The combined

  10. 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 ...

  11. MULTIPLE CRITERIA DECISION MAKING APPROACH FOR INDUSTRIAL ENGINEER SELECTION USING FUZZY AHP-FUZZY TOPSIS

    OpenAIRE

    Deliktaş, Derya; ÜSTÜN, Özden

    2018-01-01

    In this study, a fuzzy multiple criteria decision-making approach is proposed to select an industrial engineer among ten candidates in a manufacturing environment. The industrial engineer selection problem is a special case of the personal selection problem. This problem, which has hierarchical structure of criteria and many decision makers, contains many criteria. The evaluation process of decision makers also includes ambiguous parameters. The fuzzy AHP is used to determin...

  12. On categorical approach to derived preference relations in some decision making problems

    OpenAIRE

    Rozen, Victor V.; Zhitomirski, Grigori

    2005-01-01

    A structure called a decision making problem is considered. The set of outcomes (consequences) is partially ordered according to the decision maker's preferences. The problem is how these preferences affect a decision maker to prefer one of his strategies (or acts) to another, i.e. it is to describe so called derived preference relations. This problem is formalized by using category theory approach and reduced to a pure algebraical question. An effective method is suggested to build all reaso...

  13. The Needs of Hybrid Systems Configuration for Real - Time Decision - Making Process in Surgery

    National Research Council Canada - National Science Library

    Tritto, G

    2001-01-01

    ...: sensors, actuators, mechatronic systems and tools in Minimally Invasive Surgery (MIS) and Microsurgery require nonlinear interpretation and control systems to interface with the computer-assisted decision making process of the surgeon at work...

  14. Hybrid empirical--theoretical approach to modeling uranium adsorption

    International Nuclear Information System (INIS)

    Hull, Larry C.; Grossman, Christopher; Fjeld, Robert A.; Coates, John T.; Elzerman, Alan W.

    2004-01-01

    An estimated 330 metric tons of U are buried in the radioactive waste Subsurface Disposal Area (SDA) at the Idaho National Engineering and Environmental Laboratory (INEEL). An assessment of U transport parameters is being performed to decrease the uncertainty in risk and dose predictions derived from computer simulations of U fate and transport to the underlying Snake River Plain Aquifer. Uranium adsorption isotherms were measured for 14 sediment samples collected from sedimentary interbeds underlying the SDA. The adsorption data were fit with a Freundlich isotherm. The Freundlich n parameter is statistically identical for all 14 sediment samples and the Freundlich K f parameter is correlated to sediment surface area (r 2 =0.80). These findings suggest an efficient approach to material characterization and implementation of a spatially variable reactive transport model that requires only the measurement of sediment surface area. To expand the potential applicability of the measured isotherms, a model is derived from the empirical observations by incorporating concepts from surface complexation theory to account for the effects of solution chemistry. The resulting model is then used to predict the range of adsorption conditions to be expected in the vadose zone at the SDA based on the range in measured pore water chemistry. Adsorption in the deep vadose zone is predicted to be stronger than in near-surface sediments because the total dissolved carbonate decreases with depth

  15. Artificial Intelligence Framework for Simulating Clinical Decision-Making: A Markov Decision Process Approach

    OpenAIRE

    Bennett, Casey C.; Hauser, Kris

    2013-01-01

    In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This serves two potential functions: 1) a simulation environment for expl...

  16. A Novel Method for Dynamic Multicriteria Decision Making with Hybrid Evaluation Information

    OpenAIRE

    Shihu Liu; Tauqir Ahmed Moughal

    2014-01-01

    How to select the most desirable pattern(s) is often a crucial step for decision making problem. By taking uncertainty as well as dynamic of database into consideration, in this paper, we construct a dynamic multicriteria decision making procedure, where the evaluation information of criteria is expressed by real number, intuitionistic fuzzy number, and interval-valued intuitionistic fuzzy number. During the process of algorithm construction, the evaluation information at all time episodes is...

  17. Hybrid modeling approach to improve the forecasting capability for the gaseous radionuclide in a nuclear site

    International Nuclear Information System (INIS)

    Jeong, Hyojoon; Hwang, Wontae; Kim, Eunhan; Han, Moonhee

    2012-01-01

    Highlights: ► This study is to improve the reliability of air dispersion modeling. ► Tracer experiments assumed gaseous radionuclides were conducted at a nuclear site. ► The performance of a hybrid modeling combined ISC with ANFIS was investigated.. ► Hybrid modeling approach shows better performance rather than a single ISC model. - Abstract: Predicted air concentrations of radioactive materials are important for an environmental impact assessment for the public health. In this study, the performance of a hybrid modeling combined with the industrial source complex (ISC) model and an adaptive neuro-fuzzy inference system (ANFIS) for predicting tracer concentrations was investigated. Tracer dispersion experiments were performed to produce the field data assuming the accidental release of radioactive material. ANFIS was trained in order that the outputs of the ISC model are similar to the measured data. Judging from the higher correlation coefficients between the measured and the calculated ones, the hybrid modeling approach could be an appropriate technique for an improvement of the modeling capability to predict the air concentrations for radioactive materials.

  18. Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

    Science.gov (United States)

    Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

  19. How Decision Support Systems Can Benefit from a Theory of Change Approach

    Science.gov (United States)

    Allen, Will; Cruz, Jennyffer; Warburton, Bruce

    2017-06-01

    Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

  20. How Decision Support Systems Can Benefit from a Theory of Change Approach.

    Science.gov (United States)

    Allen, Will; Cruz, Jennyffer; Warburton, Bruce

    2017-06-01

    Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

  1. Beyond Bioethics: A Child Rights-Based Approach to Complex Medical Decision-Making.

    Science.gov (United States)

    Wade, Katherine; Melamed, Irene; Goldhagen, Jeffrey

    2016-01-01

    This analysis adopts a child rights approach-based on the principles, standards, and norms of child rights and the U.N. Convention on the Rights of the Child (CRC)-to explore how decisions could be made with regard to treatment of a severely impaired infant (Baby G). While a child rights approach does not provide neat answers to ethically complex issues, it does provide a framework for decision-making in which the infant is viewed as an independent rights-holder. The state has obligations to develop the capacity of those who make decisions for infants in such situations to meet their obligations to respect, protect, and fulfill their rights as delineated in the CRC. Furthermore, a child rights approach requires procedural clarity and transparency in decision-making processes. As all rights in the CRC are interdependent and indivisible, all must be considered in the process of ethical decision-making, and the reasons for decisions must be delineated by reference to how these rights were considered. It is also important that decisions that are made in this context be monitored and reviewed to ensure consistency. A rights-based framework ensures decision-making is child-centered and that there are transparent criteria and legitimate procedures for making decisions regarding the child's most basic human right: the right to life, survival, and development.

  2. Safeguards decision making in the public and regulatory environment, and the potential role of quantitative approaches

    International Nuclear Information System (INIS)

    Sherr, T.S.

    1981-01-01

    This paper briefly examines the nature of the safeguards program's objectives and constraints, and the inherent limitations on comprehensive quantification. It discusses the nature of the public and regulatory processes employed in safeguards decision making, and examines their implications regarding the potential role of quantitative approaches to safeguards policy and operational decision making

  3. Variations in Decision-Making Approach to Tertiary Teaching: A Case Study in Vietnam

    Science.gov (United States)

    Nguyen, Thanh Tien

    2016-01-01

    Although the question of what to teach and how to teach has received much attention from the literature, little was known about the way in which academics in teaching groups make decision on what and how to teach. This paper reports an analysis of variations in the decision-making approach to tertiary teaching through academics' practices of…

  4. Risk aversion and risk seeking in multicriteria forest management: a Markov decision process approach

    Science.gov (United States)

    Joseph Buongiorno; Mo Zhou; Craig Johnston

    2017-01-01

    Markov decision process models were extended to reflect some consequences of the risk attitude of forestry decision makers. One approach consisted of maximizing the expected value of a criterion subject to an upper bound on the variance or, symmetrically, minimizing the variance subject to a lower bound on the expected value.  The other method used the certainty...

  5. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    International Nuclear Information System (INIS)

    Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

    2011-01-01

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

  6. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

    2011-01-15

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

  7. Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

    Science.gov (United States)

    Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel

    2014-01-01

    The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

  8. Forecasting Optimal Solar Energy Supply in Jiangsu Province (China: A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

    Directory of Open Access Journals (Sweden)

    Xiuli Zhao

    2014-01-01

    Full Text Available The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

  9. Advanced control approach for hybrid systems based on solid oxide fuel cells

    International Nuclear Information System (INIS)

    Ferrari, Mario L.

    2015-01-01

    Highlights: • Advanced new control system for SOFC based hybrid plants. • Proportional–Integral approach with feed-forward technology. • Good control of fuel cell temperature. • All critical properties maintained inside safe conditions. - Abstract: This paper shows a new advanced control approach for operations in hybrid systems equipped with solid oxide fuel cell technology. This new tool, which combines feed-forward and standard proportional–integral techniques, controls the system during load changes avoiding failures and stress conditions detrimental to component life. This approach was selected to combine simplicity and good control performance. Moreover, the new approach presented in this paper eliminates the need for mass flow rate meters and other expensive probes, as usually required for a commercial plant. Compared to previous works, better performance is achieved in controlling fuel cell temperature (maximum gradient significantly lower than 3 K/min), reducing the pressure gap between cathode and anode sides (at least a 30% decrease during transient operations), and generating a higher safe margin (at least a 10% increase) for the Steam-to-Carbon Ratio. This new control system was developed and optimized using a hybrid system transient model implemented, validated and tested within previous works. The plant, comprising the coupling of a tubular solid oxide fuel cell stack with a microturbine, is equipped with a bypass valve able to connect the compressor outlet with the turbine inlet duct for rotational speed control. Following model development and tuning activities, several operative conditions were considered to show the new control system increased performance compared to previous tools (the same hybrid system model was used with the new control approach). Special attention was devoted to electrical load steps and ramps considering significant changes in ambient conditions

  10. Hybrid Approach of Aortic Diseases: Zone 1 Delivery and Volumetric Analysis on the Descending Aorta

    Directory of Open Access Journals (Sweden)

    José Augusto Duncan

    Full Text Available Abstract Introduction: Conventional techniques of surgical correction of arch and descending aortic diseases remains as high-risk procedures. Endovascular treatments of abdominal and descending thoracic aorta have lower surgical risk. Evolution of both techniques - open debranching of the arch and endovascular approach of the descending aorta - may extend a less invasive endovascular treatment for a more extensive disease with necessity of proximal landing zone in the arch. Objective: To evaluate descending thoracic aortic remodeling by means of volumetric analysis after hybrid approach of aortic arch debranching and stenting the descending aorta. Methods: Retrospective review of seven consecutive patients treated between September 2014 and August 2016 for diseases of proximal descending aorta (aneurysms and dissections by hybrid approach to deliver the endograft at zone 1. Computed tomography angiography were analyzed using a specific software to calculate descending thoracic aorta volumes pre- and postoperatively. Results: Follow-up was done in 100% of patients with a median time of 321 days (range, 41-625 days. No deaths or permanent neurological complications were observed. There were no endoleaks or stent migrations. Freedom from reintervention was 100% at 300 days and 66% at 600 days. Median volume reduction was of 45.5 cm3, representing a median volume shrinkage by 9.3%. Conclusion: Hybrid approach of arch and descending thoracic aorta diseases is feasible and leads to a favorable aortic remodeling with significant volume reduction.

  11. Does the acceptance of hybrid learning affect learning approaches in France?

    Science.gov (United States)

    Marco, Lionel Di; Venot, Alain; Gillois, Pierre

    2017-01-01

    Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (Paffected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.

  12. Social security and retirement decision: A positive and normative approach

    OpenAIRE

    Cremer, Helmuth; Lozachmeur, Jean-Marie; Pestieau, Pierre

    2006-01-01

    Social insurance for the elderly is judged responsible for the widely observed trend towards early retirement. In a world of laissez-faire or in a first-best setting, there would be no such trend. However, when first-best instruments are not available, because health and productivity are not observable, the optimal social insurance policy may imply a distortion on the retirement decision. The main point we make is that while there is no doubt that retirement systems induce an excessive bias t...

  13. Conflicts about nuclear power safety: a decision theoretic approach

    International Nuclear Information System (INIS)

    Winterfeldt, D.V.; Rios, M.

    1980-01-01

    A series of psychological studies indicate that people's judgements of risks from energy production in general and nuclear power plants in particular deviate from technical and statistical estimates because social and psychological variables influence people's risk perception. After reviewing these studies a decision analytic methodology is outlined which incorporates such social and psychological variables in a formal analysis of the risks and benefits of nuclear energy production. The methodology is intended to identify groups with differing risk-benefit perceptions and to elicit and quantify their values and concerns. Such group and value structures are presented for the problem of choosing between a nuclear plant, a coal plant, and a conservation strategy

  14. Enterprise identity management towards an investment decision support approach

    CERN Document Server

    Royer, Denis

    2013-01-01

    ?The introduction of Enterprise Identity Management Systems (EIdMS) in organizations even beyond the purely technological level is a costly and challenging endeavor. However, for decision makers it seems difficult to fully understand the impacts and opportunities arising from the introduction of EIdMS. This book explores the relevant aspects for an ex-ante evaluation of EIdMS. Therefore it examines this domain by employing a qualitative expert interview study to better understand the nature of EIdMS, as they are situated between security and productive IT systems. To this regard, the focus is

  15. A hybrid approach to select features and classify diseases based on medical data

    Science.gov (United States)

    AbdelLatif, Hisham; Luo, Jiawei

    2018-03-01

    Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms

  16. A Cross-Layer User Centric Vertical Handover Decision Approach Based on MIH Local Triggers

    Science.gov (United States)

    Rehan, Maaz; Yousaf, Muhammad; Qayyum, Amir; Malik, Shahzad

    Vertical handover decision algorithm that is based on user preferences and coupled with Media Independent Handover (MIH) local triggers have not been explored much in the literature. We have developed a comprehensive cross-layer solution, called Vertical Handover Decision (VHOD) approach, which consists of three parts viz. mechanism for collecting and storing user preferences, Vertical Handover Decision (VHOD) algorithm and the MIH Function (MIHF). MIHF triggers the VHOD algorithm which operates on user preferences to issue handover commands to mobility management protocol. VHOD algorithm is an MIH User and therefore needs to subscribe events and configure thresholds for receiving triggers from MIHF. In this regard, we have performed experiments in WLAN to suggest thresholds for Link Going Down trigger. We have also critically evaluated the handover decision process, proposed Just-in-time interface activation technique, compared our proposed approach with prominent user centric approaches and analyzed our approach from different aspects.

  17. Hourly forecasting of global solar radiation based on multiscale decomposition methods: A hybrid approach

    International Nuclear Information System (INIS)

    Monjoly, Stéphanie; André, Maïna; Calif, Rudy; Soubdhan, Ted

    2017-01-01

    This paper introduces a new approach for the forecasting of solar radiation series at 1 h ahead. We investigated on several techniques of multiscale decomposition of clear sky index K_c data such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) and Wavelet Decomposition. From these differents methods, we built 11 decomposition components and 1 residu signal presenting different time scales. We performed classic forecasting models based on linear method (Autoregressive process AR) and a non linear method (Neural Network model). The choice of forecasting method is adaptative on the characteristic of each component. Hence, we proposed a modeling process which is built from a hybrid structure according to the defined flowchart. An analysis of predictive performances for solar forecasting from the different multiscale decompositions and forecast models is presented. From multiscale decomposition, the solar forecast accuracy is significantly improved, particularly using the wavelet decomposition method. Moreover, multistep forecasting with the proposed hybrid method resulted in additional improvement. For example, in terms of RMSE error, the obtained forecasting with the classical NN model is about 25.86%, this error decrease to 16.91% with the EMD-Hybrid Model, 14.06% with the EEMD-Hybid model and to 7.86% with the WD-Hybrid Model. - Highlights: • Hourly forecasting of GHI in tropical climate with many cloud formation processes. • Clear sky Index decomposition using three multiscale decomposition methods. • Combination of multiscale decomposition methods with AR-NN models to predict GHI. • Comparison of the proposed hybrid model with the classical models (AR, NN). • Best results using Wavelet-Hybrid model in comparison with classical models.

  18. Decision Tree Approach to Discovering Fraud in Leasing Agreements

    OpenAIRE

    Horvat Ivan; Pejić Bach Mirjana; Merkač Skok Marjana

    2014-01-01

    Background: Fraud attempts create large losses for financing subjects in modern economies. At the same time, leasing agreements have become more and more popular as a means of financing objects such as machinery and vehicles, but are more vulnerable to fraud attempts. Objectives: The goal of the paper is to estimate the usability of the data mining approach in discovering fraud in leasing agreements. Methods/Approach: Real-world data from one Croatian leasing firm was used for creating tow mo...

  19. Integrated approach for fusion multi-physics coupled analyses based on hybrid CAD and mesh geometries

    Energy Technology Data Exchange (ETDEWEB)

    Qiu, Yuefeng, E-mail: yuefeng.qiu@kit.edu; Lu, Lei; Fischer, Ulrich

    2015-10-15

    Highlights: • Integrated approach for neutronics, thermal and structural analyses was developed. • MCNP5/6, TRIPOLI-4 were coupled with CFX, Fluent and ANSYS Workbench. • A novel meshing approach has been proposed for describing MC geometry. - Abstract: Coupled multi-physics analyses on fusion reactor devices require high-fidelity neutronic models, and flexible, accurate data exchanging between various calculation codes. An integrated coupling approach has been developed to enable the conversion of CAD, mesh, or hybrid geometries for Monte Carlo (MC) codes MCNP5/6, TRIPOLI-4, and translation of nuclear heating data for CFD codes Fluent, CFX and structural mechanical software ANSYS Workbench. The coupling approach has been implemented based on SALOME platform with CAD modeling, mesh generation and data visualization capabilities. A novel meshing approach has been developed for generating suitable meshes for MC geometry descriptions. The coupling approach has been concluded to be reliable and efficient after verification calculations of several application cases.

  20. Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

    Science.gov (United States)

    Wallace, Byron C; Noel-Storr, Anna; Marshall, Iain J; Cohen, Aaron M; Smalheiser, Neil R; Thomas, James

    2017-11-01

    Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML. We trained a classifier to discriminate between citations that describe RCTs and those that do not. We then adopted a simple strategy of automatically excluding citations deemed very unlikely to be RCTs by the classifier and deferring to crowdworkers otherwise. Combining ML and crowdsourcing provides a highly sensitive RCT identification strategy (our estimates suggest 95%-99% recall) with substantially less effort (we observed a reduction of around 60%-80%) than relying on manual screening alone. Hybrid crowd-ML strategies warrant further exploration for biomedical curation/annotation tasks. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  1. A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

    Science.gov (United States)

    Marzban, Hamid Reza

    2018-05-01

    In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.

  2. A Study on a Hybrid Approach for Diagnosing Faults in Nuclear Power Plant

    International Nuclear Information System (INIS)

    Yang, M.; Zhang, Z.J.; Peng, M.J.; Yan, S.Y.; Wang, H.; Ouyang, J.

    2006-01-01

    Proper and rapid identification of malfunctions is of premier importance for the safe operation of Nuclear Power Plants (NPP). Many monitoring or/and diagnosis methodologies based on artificial and computational intelligence have been proposed to aid operator to understand system problems, perform trouble-shooting action and reduce human error under serious pressure. However, because no single method is adequate to handle all requirements for diagnostic system, hybrid approaches where different methods work in conjunction to solve parts of the problem interest researchers greatly. In this study, Multilevel Flow Models (MFM) and Artificial Neural Network (ANN) are proposed and employed to develop a fault diagnosis system with the intention of improving the success rate of recognition on the one hand, and improving the understandability of diagnostic process and results on the other hand. Several simulation cases were conducted for evaluating the performance of the proposed diagnosis system. The simulation results validated the effectiveness of the proposed hybrid approach. (authors)

  3. Neuro-genetic hybrid approach for the solution of non-convex economic dispatch problem

    International Nuclear Information System (INIS)

    Malik, T.N.; Asar, A.U.

    2009-01-01

    ED (Economic Dispatch) is non-convex constrained optimization problem, and is used for both on line and offline studies in power system operation. Conventionally, it is solved as convex problem using optimization techniques by approximating generator input/output characteristic. Curves of monotonically increasing nature thus resulting in an inaccurate dispatch. The GA (Genetic Algorithm) has been used for the solution of this problem owing to its inherent ability to address the convex and non-convex problems equally. This approach brings the solution to the global minimum region of search space in a short time and then takes longer time to converge to near optimal results. GA based hybrid approaches are used to fine tune the near optimal results produced by GA. This paper proposes NGH (Neuro Genetic Hybrid) approach to solve the economic dispatch with valve point effect. The proposed approach combines the GA with the ANN (Artificial Neural Network) using SI (Swarm Intelligence) learning rule. The GA acts as a global optimizer and the neural network fine tunes the GA results to the desired targets. Three machines standard test system has been tested for validation of the approach. Comparing the results with GA and NGH model based on back-propagation learning, the proposed approach gives contrast improvements showing the promise of the approach. (author)

  4. Towards Integrating the Principlist and Casuist Approaches to Ethical Decisions via Multi-Criterial Support

    DEFF Research Database (Denmark)

    Kaltoft, Mette Kjer; Nielsen, Jesper Bo; Salkeld, Glenn

    2016-01-01

    of each option, as a contribution to enhanced deliberation. As proof of concept and method an exemplar aid adds veracity and confidentiality to beneficence, non-maleficence, autonomy and justice, as the criteria, with case-based reasoning supplying the necessary inputs for the decision of whether a nurse......An interactive decision support tool based on Multi-Criteria Decision Analysis (MCDA) can help health professionals integrate the principlist (principle-based) and casuist (case-based) approaches to ethical decision making in both their training and practice. MCDA can incorporate generic ethical...

  5. Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

    OpenAIRE

    Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

    2015-01-01

    Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

  6. A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction

    Science.gov (United States)

    Benvenuto, Federico; Piana, Michele; Campi, Cristina; Massone, Anna Maria

    2018-01-01

    This paper introduces a novel method for flare forecasting, combining prediction accuracy with the ability to identify the most relevant predictive variables. This result is obtained by means of a two-step approach: first, a supervised regularization method for regression, namely, LASSO is applied, where a sparsity-enhancing penalty term allows the identification of the significance with which each data feature contributes to the prediction; then, an unsupervised fuzzy clustering technique for classification, namely, Fuzzy C-Means, is applied, where the regression outcome is partitioned through the minimization of a cost function and without focusing on the optimization of a specific skill score. This approach is therefore hybrid, since it combines supervised and unsupervised learning; realizes classification in an automatic, skill-score-independent way; and provides effective prediction performances even in the case of imbalanced data sets. Its prediction power is verified against NOAA Space Weather Prediction Center data, using as a test set, data in the range between 1996 August and 2010 December and as training set, data in the range between 1988 December and 1996 June. To validate the method, we computed several skill scores typically utilized in flare prediction and compared the values provided by the hybrid approach with the ones provided by several standard (non-hybrid) machine learning methods. The results showed that the hybrid approach performs classification better than all other supervised methods and with an effectiveness comparable to the one of clustering methods; but, in addition, it provides a reliable ranking of the weights with which the data properties contribute to the forecast.

  7. Clinical decision-making and therapeutic approaches in osteopathy - a qualitative grounded theory study.

    Science.gov (United States)

    Thomson, Oliver P; Petty, Nicola J; Moore, Ann P

    2014-02-01

    There is limited understanding of how osteopaths make decisions in relation to clinical practice. The aim of this research was to construct an explanatory theory of the clinical decision-making and therapeutic approaches of experienced osteopaths in the UK. Twelve UK registered osteopaths participated in this constructivist grounded theory qualitative study. Purposive and theoretical sampling was used to select participants. Data was collected using semi-structured interviews which were audio-recorded and transcribed. As the study approached theoretical sufficiency, participants were observed and video-recorded during a patient appointment, which was followed by a video-prompted interview. Constant comparative analysis was used to analyse and code data. Data analysis resulted in the construction of three qualitatively different therapeutic approaches which characterised participants and their clinical practice, termed; Treater, Communicator and Educator. Participants' therapeutic approach influenced their approach to clinical decision-making, the level of patient involvement, their interaction with patients, and therapeutic goals. Participants' overall conception of practice lay on a continuum ranging from technical rationality to professional artistry, and contributed to their therapeutic approach. A range of factors were identified which influenced participants' conception of practice. The findings indicate that there is variation in osteopaths' therapeutic approaches to practice and clinical decision-making, which are influenced by their overall conception of practice. This study provides the first explanatory theory of the clinical decision-making and therapeutic approaches of osteopaths. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Two-stage decision approach to material accounting

    International Nuclear Information System (INIS)

    Opelka, J.H.; Sutton, W.B.

    1982-01-01

    The validity of the alarm threshold 4sigma has been checked for hypothetical large and small facilities using a two-stage decision model in which the diverter's strategic variable is the quantity diverted, and the defender's strategic variables are the alarm threshold and the effectiveness of the physical security and material control systems in the possible presence of a diverter. For large facilities, the material accounting system inherently appears not to be a particularly useful system for the deterrence of diversions, and essentially no improvement can be made by lowering the alarm threshold below 4sigma. For small facilities, reduction of the threshold to 2sigma or 3sigma is a cost effective change for the accounting system, but is probably less cost effective than making improvements in the material control and physical security systems

  9. Decision support models for solid waste management: Review and game-theoretic approaches

    International Nuclear Information System (INIS)

    Karmperis, Athanasios C.; Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios

    2013-01-01

    Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decision support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed

  10. Decision support models for solid waste management: Review and game-theoretic approaches

    Energy Technology Data Exchange (ETDEWEB)

    Karmperis, Athanasios C., E-mail: athkarmp@mail.ntua.gr [Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechniou 9, 15780 Athens (Greece); Army Corps of Engineers, Hellenic Army General Staff, Ministry of Defence (Greece); Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios [Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechniou 9, 15780 Athens (Greece)

    2013-05-15

    Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decision support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.

  11. A Novel Combined Hybrid Approach to Enable Revascularisation of a Trauma-Induced Subclavian Artery Injury

    Directory of Open Access Journals (Sweden)

    C.N. Sabbagh

    Full Text Available : Introduction: This case highlights the complexity of upper limb revascularization after a subclavian artery traumatic injury and strengthens the role of a hybrid/multi-disciplinary approach to such injuries. Report: A 45-year-old male patient presented with an acute right upper limb following a traumatic injury to the right subclavian artery due to a motor vehicle accident (MVA. Associated injuries included an unstable cervical spine injury, a large open right clavicular injury, and a brain injury, which limited the potential revascularisation options available. The arm was revascularised using a hybrid endovascular/open surgical approach, namely embolization of the proximal subclavian artery (just distal to vertebral artery and a right common femoral artery to distal axillary artery bypass using prosthetic material. Discussion: Blunt injuries to the subclavian artery are often high impact, complex and associated with multiple injuries to surrounding structures, which limit the role of standard procedures used in the elective setting. This case highlights the role of multidisciplinary team involvement, using a hybrid approach and a novel distal inflow site to restore upper limb perfusion. Keywords: Upper limb, Ischemia, Trauma, Revascularization

  12. Modeling bidding decision in engineering field with incomplete information: A static game–based approach

    Directory of Open Access Journals (Sweden)

    Zhi-xing Huang

    2016-01-01

    Full Text Available Corporate investment decision about engineering projects is a key issue for project management. This article aims to study the process of bidding decision-making in engineering field under the condition of incomplete information and investigating the influence of bidders’ game behaviors on investment decision. With reasonable assumed scenes, this article uses an approach to describe the decision process for bidding. The approach is based on the static game theory. With the proposed model, the effectiveness of game participants and the objective function are put forward, and the characteristics of price quotation and the best strategies of bidders under the equilibrium condition are discussed. The results can give a better understanding of investment decision in engineering management and are helpful for tenderees to avoid excessive competition among bidders.

  13. Brand deletion: How the decision-making approach affects deletion success

    OpenAIRE

    Víctor Temprano-García; Ana Isabel Rodríguez-Escudero; Javier Rodríguez-Pinto

    2018-01-01

    Literature on brand deletion (BD), a critical and topical decision within a firm's marketing strategy, is extremely scarce. The present research is concerned with the decision-making process and examines the effect on BD success of three different approaches to decision-making – rational, intuitive and political – and of the interaction between the rational and political approaches. The moderating effect of the type of BD – i.e., total brand killing or disposal vs. brand name change – is also...

  14. Strategic Decision Making for Organizational Sustainability: The Implications of Servant Leadership and Sustainable Leadership Approaches

    Directory of Open Access Journals (Sweden)

    Judita Peterlin

    2015-12-01

    Full Text Available This conceptual paper explores the implications of servant leadership and sustainable leadership for strategic decision making by the top management of an organization. It is argued that a different type of leadership is required if effective strategic decisions are to be made in organizations striving to become more sustainable and that servant leadership and sustainable leadership approaches provide a sound basis to inform these decisions. The contributions of these two leadership approaches are explored, before considering the implications for leadership development. Particularly, the inclusion in leadership development programmes of values based leadership, and the development of integrative thinking, is discussed.

  15. Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

    Science.gov (United States)

    Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

    2016-01-01

    Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

  16. Towards an integrated approach in supporting microbiological food safety decisions

    DEFF Research Database (Denmark)

    Havelaar, A.H.; Braunig, J.; Christiansen, K.

    2007-01-01

    an integrated scientific approach combining veterinary and medical epidemiology, risk assessment for the farm-to-fork food chain as well as agricultural and health economy. Scientific advice is relevant in all stages of the policy cycle: to assess the magnitude of the food safety problem, to define...

  17. A symptom based decision tree approach to boiling water reactor emergency operating procedures

    International Nuclear Information System (INIS)

    Knobel, R.C.

    1984-01-01

    This paper describes a Decision Tree approach to development of BWR Emergency Operating Procedures for use by operators during emergencies. This approach utilizes the symptom based Emergency Procedure Guidelines approved for implementation by the USNRC. Included in the paper is a discussion of the relative merits of the event based Emergency Operating Procedures currently in use at USBWR plants. The body of the paper is devoted to a discussion of the Decision Tree Approach to Emergency Operating Procedures soon to be implemented at two United States Boiling Water Reactor plants, why this approach solves many of the problems with procedures indentified in the post accident reviews of Three Mile Island procedures, and why only now is this approach both desirable and feasible. The paper discusses how nuclear plant simulators were involved in the development of the Emergency Operating Procedure decision trees, and in the verification and validation of these procedures. (orig./HP)

  18. Interventionist and participatory approaches to flood risk mitigation decisions: two case studies in the Italian Alps

    Science.gov (United States)

    Bianchizza, C.; Del Bianco, D.; Pellizzoni, L.; Scolobig, A.

    2012-04-01

    Flood risk mitigation decisions pose key challenges not only from a technical but also from a social, economic and political viewpoint. There is an increasing demand for improving the quality of these processes by including different stakeholders - and especially by involving the local residents in the decision making process - and by guaranteeing the actual improvement of local social capacities during and after the decision making. In this paper we analyse two case studies of flood risk mitigation decisions, Malborghetto-Valbruna and Vipiteno-Sterzing, in the Italian Alps. In both of them, mitigation works have been completed or planned, yet following completely different approaches especially in terms of responses of residents and involvement of local authorities. In Malborghetto-Valbruna an 'interventionist' approach (i.e. leaning towards a top down/technocratic decision process) was used to make decisions after the flood event that affected the municipality in the year 2003. In Vipiteno-Sterzing, a 'participatory' approach (i.e. leaning towards a bottom-up/inclusive decision process) was applied: decisions about risk mitigation measures were made by submitting different projects to the local citizens and by involving them in the decision making process. The analysis of the two case studies presented in the paper is grounded on the results of two research projects. Structured and in-depth interviews, as well as questionnaire surveys were used to explore residents' and local authorities' orientations toward flood risk mitigation. Also a SWOT analysis (Strengths, Weaknesses, Opportunities and Threats) involving key stakeholders was used to better understand the characteristics of the communities and their perception of flood risk mitigation issues. The results highlight some key differences between interventionist and participatory approaches, together with some implications of their adoption in the local context. Strengths and weaknesses of the two approaches

  19. Probabilistic seasonal Forecasts to deterministic Farm Leve Decisions: Innovative Approach

    Science.gov (United States)

    Mwangi, M. W.

    2015-12-01

    Climate change and vulnerability are major challenges in ensuring household food security. Climate information services have the potential to cushion rural households from extreme climate risks. However, most the probabilistic nature of climate information products is not easily understood by majority of smallholder farmers. Despite the probabilistic nature, climate information have proved to be a valuable climate risk adaptation strategy at the farm level. This calls for innovative ways to help farmers understand and apply climate information services to inform their farm level decisions. The study endeavored to co-design and test appropriate innovation systems for climate information services uptake and scale up necessary for achieving climate risk development. In addition it also determined the conditions necessary to support the effective performance of the proposed innovation system. Data and information sources included systematic literature review, secondary sources, government statistics, focused group discussions, household surveys and semi-structured interviews. Data wasanalyzed using both quantitative and qualitative data analysis techniques. Quantitative data was analyzed using the Statistical Package for Social Sciences (SPSS) software. Qualitative data was analyzed using qualitative techniques, which involved establishing the categories and themes, relationships/patterns and conclusions in line with the study objectives. Sustainable livelihood, reduced household poverty and climate change resilience were the impact that resulted from the study.

  20. Decision Making under Ecological Regime Shift: An Experimental Economic Approach

    OpenAIRE

    Kawata, Yukichika

    2011-01-01

    Environmental economics postulates the assumption of homo economicus and presumes that externality occurs as a result of the rational economic activities of economic agents. This paper examines this assumption using an experimental economic approach in the context of regime shift, which has been receiving increasing attention. We observe that when externality does not exist, economic agents (subjects of experimemt) act economically rationally, but when externality exists, economic agents avoi...

  1. The Impact of a Hybrid Sport Education-Invasion Games Competence Model Soccer Unit on Students' Decision Making, Skill Execution and Overall Game Performance

    Science.gov (United States)

    Mesquita, Isabel; Farias, Claudio; Hastie, Peter

    2012-01-01

    The purpose of this study was to examine the impact of a hybrid Sport Education-Invasion Games Competence Model (SE-IGCM) unit application on students' improvements in decision making, skill execution and overall game performance, during a soccer season. Twenty-six fifth-grade students from a Portuguese public elementary school participated in a…

  2. A hybrid choice model with nonlinear utility functions and bounded distributions for latent variables : application to purchase intention decisions of electric cars

    NARCIS (Netherlands)

    Kim, J.; Rasouli, S.; Timmermans, H.J.P.

    2014-01-01

    The hybrid choice model (HCM) provides a powerful framework to account for heterogeneity across decision-makers in terms of different underlying latent attitudes. Typically, effects of the latent attitudes have been represented assuming linear utility functions. In contributing to the further

  3. A hybrid choice model with a nonlinear utility function and bounded distribution for latent variables : application to purchase intention decisions of electric cars

    NARCIS (Netherlands)

    Kim, J.; Rasouli, S.; Timmermans, H.J.P.

    2016-01-01

    The hybrid choice model (HCM) provides a powerful framework to account for heterogeneity across decision-makers in terms of different underlying latent attitudes. Typically, effects of the latent attitudes have been represented assuming linear utility functions. In contributing to the further

  4. A Hybrid Approach to Cognitive Engineering: Supporting Development of a Revolutionary Warfighter-Centered Command and Control System

    National Research Council Canada - National Science Library

    Ockerman, Jennifer; McKneely, Jennifer A; Koterba, Nathan

    2005-01-01

    ...) for the requirements analysis and design of revolutionary command and control systems and domains. This hybrid approach uses knowledge elicitation and representation techniques from several current cognitive engineering methodologies...

  5. Hybrid Decision Making: When Interpretable Models Collaborate With Black-Box Models

    OpenAIRE

    Wang, Tong

    2018-01-01

    Interpretable machine learning models have received increasing interest in recent years, especially in domains where humans are involved in the decision-making process. However, the possible loss of the task performance for gaining interpretability is often inevitable. This performance downgrade puts practitioners in a dilemma of choosing between a top-performing black-box model with no explanations and an interpretable model with unsatisfying task performance. In this work, we propose a nove...

  6. A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

    Science.gov (United States)

    Oh, Yoo Rhee; Kim, Hong Kook

    In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

  7. A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

    Science.gov (United States)

    Dickman, Christopher T D; Moehring, Amanda J

    2013-01-01

    When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW) sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56%) of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

  8. A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

    Directory of Open Access Journals (Sweden)

    Christopher T D Dickman

    Full Text Available When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56% of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

  9. A Gaussian process regression based hybrid approach for short-term wind speed prediction

    International Nuclear Information System (INIS)

    Zhang, Chi; Wei, Haikun; Zhao, Xin; Liu, Tianhong; Zhang, Kanjian

    2016-01-01

    Highlights: • A novel hybrid approach is proposed for short-term wind speed prediction. • This method combines the parametric AR model with the non-parametric GPR model. • The relative importance of different inputs is considered. • Different types of covariance functions are considered and combined. • It can provide both accurate point forecasts and satisfactory prediction intervals. - Abstract: This paper proposes a hybrid model based on autoregressive (AR) model and Gaussian process regression (GPR) for probabilistic wind speed forecasting. In the proposed approach, the AR model is employed to capture the overall structure from wind speed series, and the GPR is adopted to extract the local structure. Additionally, automatic relevance determination (ARD) is used to take into account the relative importance of different inputs, and different types of covariance functions are combined to capture the characteristics of the data. The proposed hybrid model is compared with the persistence model, artificial neural network (ANN), and support vector machine (SVM) for one-step ahead forecasting, using wind speed data collected from three wind farms in China. The forecasting results indicate that the proposed method can not only improve point forecasts compared with other methods, but also generate satisfactory prediction intervals.

  10. Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

    Science.gov (United States)

    Koeppen, W. C.; Pilger, E.; Wright, R.

    2011-07-01

    We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

  11. A Hybrid Column Generation approach for an Industrial Waste Collection Routing Problem

    DEFF Research Database (Denmark)

    Hauge, Kristian; Larsen, Jesper; Lusby, Richard Martin

    2014-01-01

    , while empty containers must be returned to the depot to await further assignments. Unlike, the traditional ROROR problem, where vehicles may transport one skip container at a time regardless of whether it is full or not, we consider cases in which a vehicle can transport up to eight containers, at most...... two of which can be full. We propose a Generalized Set Partitioning formulation of the problem and describe a hybrid column generation procedure to solve it. A fast Tabu Search heuristic is used to generate new columns. The proposed methodology is tested on nine data sets, four of which are actual......, real-world problem instances. Results indicate that the hybrid column generation outperforms a purely heuristic approach in terms of both running time and solution quality. High quality solutions to problems containing up to 100 orders can be solved in approximately 15 minutes....

  12. A hybrid least squares support vector machines and GMDH approach for river flow forecasting

    Science.gov (United States)

    Samsudin, R.; Saad, P.; Shabri, A.

    2010-06-01

    This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

  13. A frequency domain approach to analyzing passive battery-ultracapacitor hybrids supplying periodic pulsed current loads

    International Nuclear Information System (INIS)

    Kuperman, Alon; Aharon, Ilan; Kara, Avi; Malki, Shalev

    2011-01-01

    Highlights: → Passive battery-ultracapacitor hybrids are examined. → Frequency domain analysis is employed. → The ultracapacitor branch operates as a low-pass filter for the battery. → The battery supplies the average load demand. → Design requirements are discussed. - Abstract: A Fourier-based analysis of passive battery-ultracapacitor hybrid sources is introduced in the manuscript. The approach is first introduced for a general load, and then is followed by a study for a case of periodic pulsed current load. It is shown that the ultracapacitor branch is perceived by the battery as a low-pass filter, which absorbs the majority of the high frequency harmonic current and letting the battery to supply the average load demand in addition to the small part of dynamic current. Design requirements influence on the ultracapacitor capacitance and internal resistance choice are quantitatively discussed. The theory is enforced by simulation and experimental results, showing an excellent agreement.

  14. A hybrid approach to solving the problem of design of nuclear fuel cells

    International Nuclear Information System (INIS)

    Montes T, J. L.; Perusquia del C, R.; Ortiz S, J. J.; Castillo, A.

    2015-09-01

    An approach to solving the problem of fuel cell design for BWR power reactor is presented. For this purpose the hybridization of a method based in heuristic knowledge rules called S15 and the advantages of a meta-heuristic method is proposed. The synergy of potentialities of both techniques allows finding solutions of more quality. The quality of each solution is obtained through a multi-objective function formed from the main cell parameters that are provided or obtained during the simulation with the CASMO-4 code. To evaluate this alternative of solution nuclear fuel cells of reference of nuclear power plant of Laguna Verde were used. The results show that in a systematic way the results improve when both methods are coupled. As a result of the hybridization process of the mentioned techniques an improvement is achieved in a range of 2% with regard to the achieved results in an independent way by the S15 method. (Author)

  15. Formal verification of dynamic hybrid systems: a NuSMV-based model checking approach

    Directory of Open Access Journals (Sweden)

    Xu Zhi

    2018-01-01

    Full Text Available Software security is an important and challenging research topic in developing dynamic hybrid embedded software systems. Ensuring the correct behavior of these systems is particularly difficult due to the interactions between the continuous subsystem and the discrete subsystem. Currently available security analysis methods for system risks have been limited, as they rely on manual inspections of the individual subsystems under simplifying assumptions. To improve this situation, a new approach is proposed that is based on the symbolic model checking tool NuSMV. A dual PID system is used as an example system, for which the logical part and the computational part of the system are modeled in a unified manner. Constraints are constructed on the controlled object, and a counter-example path is ultimately generated, indicating that the hybrid system can be analyzed by the model checking tool.

  16. Non-adaptive and adaptive hybrid approaches for enhancing water quality management

    Science.gov (United States)

    Kalwij, Ineke M.; Peralta, Richard C.

    2008-09-01

    SummaryUsing optimization to help solve groundwater management problems cost-effectively is becoming increasingly important. Hybrid optimization approaches, that combine two or more optimization algorithms, will become valuable and common tools for addressing complex nonlinear hydrologic problems. Hybrid heuristic optimizers have capabilities far beyond those of a simple genetic algorithm (SGA), and are continuously improving. SGAs having only parent selection, crossover, and mutation are inefficient and rarely used for optimizing contaminant transport management. Even an advanced genetic algorithm (AGA) that includes elitism (to emphasize using the best strategies as parents) and healing (to help assure optimal strategy feasibility) is undesirably inefficient. Much more efficient than an AGA is the presented hybrid (AGCT), which adds comprehensive tabu search (TS) features to an AGA. TS mechanisms (TS probability, tabu list size, search coarseness and solution space size, and a TS threshold value) force the optimizer to search portions of the solution space that yield superior pumping strategies, and to avoid reproducing similar or inferior strategies. An AGCT characteristic is that TS control parameters are unchanging during optimization. However, TS parameter values that are ideal for optimization commencement can be undesirable when nearing assumed global optimality. The second presented hybrid, termed global converger (GC), is significantly better than the AGCT. GC includes AGCT plus feedback-driven auto-adaptive control that dynamically changes TS parameters during run-time. Before comparing AGCT and GC, we empirically derived scaled dimensionless TS control parameter guidelines by evaluating 50 sets of parameter values for a hypothetical optimization problem. For the hypothetical area, AGCT optimized both well locations and pumping rates. The parameters are useful starting values because using trial-and-error to identify an ideal combination of control

  17. A hybrid approach for integrated healthcare cooperative purchasing and supply chain configuration.

    Science.gov (United States)

    Rego, Nazaré; Claro, João; Pinho de Sousa, Jorge

    2014-12-01

    This paper presents an innovative and flexible approach for recommending the number, size and composition of purchasing groups, for a set of hospitals willing to cooperate, while minimising their shared supply chain costs. This approach makes the financial impact of the various cooperation alternatives transparent to the group and the individual participants, opening way to a negotiation process concerning the allocation of the cooperation costs and gains. The approach was developed around a hybrid Variable Neighbourhood Search (VNS)/Tabu Search metaheuristic, resulting in a flexible tool that can be applied to purchasing groups with different characteristics, namely different operative and market circumstances, and to supply chains with different topologies and atypical cost characteristics. Preliminary computational results show the potential of the approach in solving a broad range of problems.

  18. Fuzzy methods in decision making process - A particular approach in manufacturing systems

    Science.gov (United States)

    Coroiu, A. M.

    2015-11-01

    We are living in a competitive environment, so we can see and understand that the most of manufacturing firms do the best in order to accomplish meeting demand, increasing quality, decreasing costs, and delivery rate. In present a stake point of interest is represented by the development of fuzzy technology. A particular approach for this is represented through the development of methodologies to enhance the ability to managed complicated optimization and decision making aspects involving non-probabilistic uncertainty with the reason to understand, development, and practice the fuzzy technologies to be used in fields such as economic, engineering, management, and societal problems. Fuzzy analysis represents a method for solving problems which are related to uncertainty and vagueness; it is used in multiple areas, such as engineering and has applications in decision making problems, planning and production. As a definition for decision making process we can use the next one: result of mental processes based upon cognitive process with a main role in the selection of a course of action among several alternatives. Every process of decision making can be represented as a result of a final choice and the output can be represented as an action or as an opinion of choice. Different types of uncertainty can be discovered in a wide variety of optimization and decision making problems related to planning and operation of power systems and subsystems. The mixture of the uncertainty factor in the construction of different models serves for increasing their adequacy and, as a result, the reliability and factual efficiency of decisions based on their analysis. Another definition of decision making process which came to illustrate and sustain the necessity of using fuzzy method: the decision making is an approach of choosing a strategy among many different projects in order to achieve some purposes and is formulated as three different models: high risk decision, usual risk

  19. A hybrid mathematical modeling approach of the metabolic fate of a fluorescent sphingolipid analogue to predict cancer chemosensitivity.

    Science.gov (United States)

    Molina-Mora, J A; Kop-Montero, M; Quirós-Fernández, I; Quiros, S; Crespo-Mariño, J L; Mora-Rodríguez, R A

    2018-04-13

    Sphingolipid (SL) metabolism is a complex biological system that produces and transforms ceramides and other molecules able to modulate other cellular processes, including survival or death pathways key to cell fate decisions. This signaling pathway integrates several types of stress signals, including chemotherapy, into changes in the activity of its metabolic enzymes, altering thereby the cellular composition of bioactive SLs. Therefore, the SL pathway is a promising sensor of chemosensitivity in cancer and a target hub to overcome resistance. However, there is still a gap in our understanding of how chemotherapeutic drugs can disturb the SL pathway in order to control cellular fate. We propose to bridge this gap by a systems biology approach to integrate i) a dynamic model of SL analogue (BODIPY-FL fluorescent-sphingomyelin analogue, SM-BOD) metabolism, ii) a Gaussian mixture model (GMM) of the fluorescence features to identify how the SL pathway senses the effect of chemotherapy and iii) a fuzzy logic model (FLM) to associate SL composition with cell viability by semi-quantitative rules. Altogether, this hybrid model approach was able to predict the cell viability of double experimental perturbations with chemotherapy, indicating that the SL pathway is a promising sensor to design strategies to overcome drug resistance in cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

  20. A hybrid modelling approach to simulating foot-and-mouth disease outbreaks in Australian livestock

    Directory of Open Access Journals (Sweden)

    Richard A Bradhurst

    2015-03-01

    Full Text Available Foot-and-mouth disease (FMD is a highly contagious and economically important viral disease of cloven-hoofed animals. Australia's freedom from FMD underpins a valuable trade in live animals and animal products. An outbreak of FMD would result in the loss of export markets and cause severe disruption to domestic markets. The prevention of, and contingency planning for, FMD are of key importance to government, industry, producers and the community. The spread and control of FMD is complex and dynamic due to a highly contagious multi-host pathogen operating in a heterogeneous environment across multiple jurisdictions. Epidemiological modelling is increasingly being recognized as a valuable tool for investigating the spread of disease under different conditions and the effectiveness of control strategies. Models of infectious disease can be broadly classified as: population-based models that are formulated from the top-down and employ population-level relationships to describe individual-level behaviour, individual-based models that are formulated from the bottom-up and aggregate individual-level behaviour to reveal population-level relationships, or hybrid models which combine the two approaches into a single model.The Australian Animal Disease Spread (AADIS hybrid model employs a deterministic equation-based model (EBM to model within-herd spread of FMD, and a stochastic, spatially-explicit agent-based model (ABM to model between-herd spread and control. The EBM provides concise and computationally efficient predictions of herd prevalence and clinical signs over time. The ABM captures the complex, stochastic and heterogeneous environment in which an FMD epidemic operates. The AADIS event-driven hybrid EBM/ABM architecture is a flexible, efficient and extensible framework for modelling the spread and control of disease in livestock on a national scale. We present an overview of the AADIS hybrid approach and a description of the model

  1. A proposed approach to backfit decision-making using risk assessment and benefit-cost methodology

    International Nuclear Information System (INIS)

    O'Donnell, E.P.; Raney, T.J.

    1984-01-01

    This paper outlines a proposed approach to backfit decision-making which utilizes quantitative risk assessment techniques, benefit-cost methodology and decision criteria. In general terms, it is structured to provide an objective framework for decision-making aimed at ensuring a positive return on backfit investment while allowing for inclusion of subjective value judgments by the decision-maker. The distributions of the independent variables are combined to arrive at an overall probability distribution for the benefit-cost ratio. In this way, the decision-maker can explicitly establish the probability or level of confidence that a particular backfit will yield benefits in excess of cost. An example is presented demonstrating the application of methodology to a specific plant backfit. (orig.)

  2. An engineering approach to modelling, decision support and control for sustainable systems.

    Science.gov (United States)

    Day, W; Audsley, E; Frost, A R

    2008-02-12

    Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability-all essential to sustainable systems.

  3. A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

    Science.gov (United States)

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-08-03

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

  4. A Semantic Approach with Decision Support for Safety Service in Smart Home Management

    Directory of Open Access Journals (Sweden)

    Xiaoci Huang

    2016-08-01

    Full Text Available Research on smart homes (SHs has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

  5. Towards a single European electricity market. A structured approach to regulatory mode decision-making

    International Nuclear Information System (INIS)

    De Jong, H.M.

    2009-01-01

    This study focuses on the processes through which the rules and regulations that govern European electricity markets - and inherently, their integration process - are established. So far, European policy makers have largely followed a 'trial-and-error' approach to finding an appropriate regulatory mode (process) for dealing effectively with market integration issues. This unstructured approach to regulatory mode selection leads to several problems: - Today's trial-and-error strategy of shifting from one regulatory mode to another is time-consuming. - In the regulatory mode selection process, certain key principles of good governance are insufficiently considered. - European regulatory processes are experienced as vague, intransparent, and illegitimate by 'outside' stakeholders. This study develops a 'structured approach to regulatory mode decision-making' (STARMODE) based on the theory of decision modelling in policy management and a case study exploring three key market integration issues in the field of electricity markets: interconnector investment, congestion management and market transparency. The main objective is to present a systematic and comprehensive framework for analysing and improving regulatory mode decision-making in the context of the European Union, focusing on electricity market integration. The STARMODE approach is generally applicable to (and relevant for) European market integration issues in industries characterized by a natural monopoly and/or an essential service. The approach may also contribute to national regulatory mode decision-making and multi-state decision-making in other continents.

  6. A multidimensional approach to food production decision making

    Science.gov (United States)

    Davis, K. F.; Chhatre, A.; Chiarelli, D. D.; Fargione, J.; Rao, N.; Richter, B. D.; Singh, D.; DeFries, R. S.

    2017-12-01

    Humanity faces the grand challenge of feeding a growing, more affluent population in the coming decades while reducing the environmental burden of agriculture. Approaches that integrate food security and environmental goals offer promise for achieving a more sustainable global food system. Here we use the case of cereal production in India to explore a multidimensional framework intended to inform sustainable pathways in food security. We show that by placing greater emphasis on cereals alternative to rice and wheat (i.e., maize, millets, and sorghum) it is possible for the country to realize substantial water savings and greenhouse gas emission reductions, enhance the climate resilience of farmers, and address important nutrient deficiencies. By replacing rice areas in each district with the most consumed alternative cereals, we show that it is possible to reduce consumptive freshwater demand by 22%, improve the production of iron (+27%), zinc (+11%), and fiber (+31%), and maintain protein supply with only a modest reduction in calories (-9%). Replacing rice areas with the most locally produced alternative cereal or the cereal with the lowest water footprint yielded even greater benefits across all dimensions. These multiple benefits can be realized without cropland expansion and take into account the geographies of dietary preference and local knowledge on cultivation.

  7. Rash Decisions: An Approach to Dangerous Rashes Based on Morphology.

    Science.gov (United States)

    Santistevan, Jamie; Long, Brit; Koyfman, Alex

    2017-04-01

    Rash is a common complaint in the emergency department. Many causes of rash are benign; however, some patients may have a life-threatening diagnosis. This review will present an algorithmic approach to rashes, focusing on life-threatening causes of rash in each category. Rash is common, with a wide range of etiologies. The differential is broad, consisting of many conditions that are self-resolving. However, several conditions associated with rash are life threatening. Several keys can be utilized to rapidly diagnose and manage these deadly rashes. Thorough history and physical examination, followed by consideration of red flags, are essential. This review focuses on four broad categories based on visual and tactile characteristic patterns of rashes: petechial/purpuric, erythematous, maculopapular, and vesiculobullous. Rashes in each morphologic group will be further categorized based on clinical features such as the presence or absence of fever and distribution of skin lesions. Rashes can be divided into petechial/purpuric, erythematous, maculopapular, and vesiculobullous. After this differentiation, the presence of fever and systemic signs of illness should be assessed. Through the breakdown of rashes into these classes, emergency providers can ensure deadly conditions are considered. Published by Elsevier Inc.

  8. A Fuzzy Decision Making Approach for Supplier Selection in Healthcare Industry

    OpenAIRE

    Zeynep Sener; Mehtap Dursun

    2014-01-01

    Supplier evaluation and selection is one of the most important components of an effective supply chain management system. Due to the expanding competition in healthcare, selecting the right medical device suppliers offers great potential for increasing quality while decreasing costs. This paper proposes a fuzzy decision making approach for medical supplier selection. A real-world medical device supplier selection problem is presented to illustrate the application of the proposed decision meth...

  9. A multi-criteria decision approach to sorting actions for promoting energy efficiency

    International Nuclear Information System (INIS)

    Pires Neves, Luis; Gomes Martins, Antonio; Henggeler Antunes, Carlos; Candido Dias, Luis

    2008-01-01

    This paper proposes a multi-criteria decision approach for sorting energy-efficiency initiatives, promoted by electric utilities, with or without public funds authorized by a regulator, or promoted by an independent energy agency, overcoming the limitations and drawbacks of cost-benefit analysis. The proposed approach is based on the ELECTRE-TRI multi-criteria method and allows the consideration of different kinds of impacts, although avoiding difficult measurements and unit conversions. The decision is based on all the significant effects of the initiative, both positive and negative, including ancillary effects often forgotten in cost-benefit analysis. The ELECTRE-TRI, as most multi-criteria methods, provides to the decision maker the ability of controlling the relevance each impact can have on the final decision in a transparent way. The decision support process encompasses a robustness analysis, which, together with a good documentation of the parameters supplied into the model, should support sound decisions. The models were tested with a set of real-world initiatives and compared with possible decisions based on cost-benefit analysis

  10. An Evaluation on Factors Influencing Decision making for Malaysia Disaster Management: The Confirmatory Factor Analysis Approach

    Science.gov (United States)

    Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.

    2017-12-01

    For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.

  11. Decision aiding in public policy generation and implementation: a multicriteria approach to evaluate territorial resilience

    Directory of Open Access Journals (Sweden)

    Maria Franca Norese

    2016-12-01

    Full Text Available A decision aid process should be the result of an interaction between analysts, decision makers and stakeholders. Decision aiding is sometimes required when the problem situation is new and a formal decision system does not exist. Its role becomes that of facilitating the Intelligence phase of a decision process. In other situations, a criticism of certain policy making processes and their use of data, which may be available in institutional databases or are required as indicators for the decision process, motivates an intervention oriented towards structure knowledge and improvements of these processes. A preliminary study, which includes modelling and application of multi-criteria methods, can clarify a complex and new situation, propose a consistent approach for the later phases of a decision process or propose a different and more effective use of the data. A case study is proposed here to describe this methodological approach in relation to the disaster resilience of municipalities near the mbrone River, in Tuscany (Italy.

  12. Fracture heuristics: surgical decision for approaches to distal radius fractures. A surgeon's perspective.

    Science.gov (United States)

    Wichlas, Florian; Tsitsilonis, Serafim; Kopf, Sebastian; Krapohl, Björn Dirk; Manegold, Sebastian

    2017-01-01

    Introduction: The aim of the present study is to develop a heuristic that could replace the surgeon's analysis for the decision on the operative approach of distal radius fractures based on simple fracture characteristics. Patients and methods: Five hundred distal radius fractures operated between 2011 and 2014 were analyzed for the surgeon's decision on the approach used. The 500 distal radius fractures were treated with open reduction and internal fixation through palmar, dorsal, and dorsopalmar approaches with 2.4 mm locking plates or underwent percutaneous fixation. The parameters that should replace the surgeon's analysis were the fractured palmar cortex, and the frontal and the sagittal split of the articular surface of the distal radius. Results: The palmar approach was used for 422 (84.4%) fractures, the dorsal approach for 39 (7.8%), and the combined dorsopalmar approach for 30 (6.0%). Nine (1.8%) fractures were treated percutaneously. The correlation between the fractured palmar cortex and the used palmar approach was moderate (r=0.464; p<0.0001). The correlation between the frontal split and the dorsal approach, including the dorsopalmar approach, was strong (r=0.715; p<0.0001). The sagittal split had only a weak correlation for the dorsal and dorsopalmar approach (r=0.300; p<0.0001). Discussion: The study shows that the surgical decision on the preferred approach is dictated through two simple factors, even in the case of complex fractures. Conclusion: When the palmar cortex is displaced in distal radius fractures, a palmar approach should be used. When there is a displaced frontal split of the articular surface, a dorsal approach should be used. When both are present, a dorsopalmar approach should be used. These two simple parameters could replace the surgeon's analysis for the surgical approach.

  13. A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

    Science.gov (United States)

    Madani, Kaveh; Lund, Jay R.

    2011-05-01

    Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

  14. A new approach to enhance the performance of decision tree for classifying gene expression data.

    Science.gov (United States)

    Hassan, Md; Kotagiri, Ramamohanarao

    2013-12-20

    Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.

  15. A hybrid bio-jetting approach for directly engineering living cells

    International Nuclear Information System (INIS)

    Kwok, Albert; Irvine, Scott; Arumuganathar, Sumathy; Jayasinghe, Suwan N; McEwan, Jean R

    2008-01-01

    This paper reports developments on a hybrid cell-engineering protocol coupling both bio-electrosprays and aerodynamically assisted bio-jets for process-handling living cells. The current work demonstrates the ability to couple these two cell-jetting protocols for handling a wide range of cells for deposition. The post-treated cells are assessed for their viability by way of flow cytometry, which illustrates a significant population of viable cells post-treatment in comparison to those controls. This work is the first example of coupling these two protocols for the process handling of living cells. The hybrid protocol demonstrates the achievement of stable cone jetting of a cellular suspension in the single-needle configuration which was previously unachieved with single-needle bio-electrosprays. Furthermore the living cells explored in these investigations expressed GFP, thus demonstrating the ability to couple gene therapy with this hybrid protocol. Hence, this approach could one day be explored for building biologically viable tissues incorporating a therapeutic payload for combating a range of cellular/tissue-based pathologies

  16. Opposition-Based Memetic Algorithm and Hybrid Approach for Sorting Permutations by Reversals.

    Science.gov (United States)

    Soncco-Álvarez, José Luis; Muñoz, Daniel M; Ayala-Rincón, Mauricio

    2018-02-21

    Sorting unsigned permutations by reversals is a difficult problem; indeed, it was proved to be NP-hard by Caprara (1997). Because of its high complexity, many approximation algorithms to compute the minimal reversal distance were proposed until reaching the nowadays best-known theoretical ratio of 1.375. In this article, two memetic algorithms to compute the reversal distance are proposed. The first one uses the technique of opposition-based learning leading to an opposition-based memetic algorithm; the second one improves the previous algorithm by applying the heuristic of two breakpoint elimination leading to a hybrid approach. Several experiments were performed with one-hundred randomly generated permutations, single benchmark permutations, and biological permutations. Results of the experiments showed that the proposed OBMA and Hybrid-OBMA algorithms achieve the best results for practical cases, that is, for permutations of length up to 120. Also, Hybrid-OBMA showed to improve the results of OBMA for permutations greater than or equal to 60. The applicability of our proposed algorithms was checked processing permutations based on biological data, in which case OBMA gave the best average results for all instances.

  17. Energy level alignment at hybridized organic-metal interfaces from a GW projection approach

    Science.gov (United States)

    Chen, Yifeng; Tamblyn, Isaac; Quek, Su Ying

    Energy level alignments at organic-metal interfaces are of profound importance in numerous (opto)electronic applications. Standard density functional theory (DFT) calculations generally give incorrect energy level alignments and missing long-range polarization effects. Previous efforts to address this problem using the many-electron GW method have focused on physisorbed systems where hybridization effects are insignificant. Here, we use state-of-the-art GW methods to predict the level alignment at the amine-Au interface, where molecular levels do hybridize with metallic states. This non-trivial hybridization implies that DFT result is a poor approximation to the quasiparticle states. However, we find that the self-energy operator is approximately diagonal in the molecular basis, allowing us to use a projection approach to predict the level alignments. Our results indicate that the metallic substrate reduces the HOMO-LUMO gap by 3.5 4.0 eV, depending on the molecular coverage/presence of Au adatoms. Our GW results are further compared with those of a simple image charge model that describes the level alignment in physisorbed systems. Syq and YC acknowledge Grant NRF-NRFF2013-07 and the medium-sized centre program from the National Research Foundation, Singapore.

  18. A hybrid model using decision tree and neural network for credit scoring problem

    Directory of Open Access Journals (Sweden)

    Amir Arzy Soltan

    2012-08-01

    Full Text Available Nowadays credit scoring is an important issue for financial and monetary organizations that has substantial impact on reduction of customer attraction risks. Identification of high risk customer can reduce finished cost. An accurate classification of customer and low type 1 and type 2 errors have been investigated in many studies. The primary objective of this paper is to develop a new method, which chooses the best neural network architecture based on one column hidden layer MLP, multiple columns hidden layers MLP, RBFN and decision trees and ensembling them with voting methods. The proposed method of this paper is run on an Australian credit data and a private bank in Iran called Export Development Bank of Iran and the results are used for making solution in low customer attraction risks.

  19. Nanotubule and Tour Molecule Based Molecular Electronics: Suggestion for a Hybrid Approach

    Science.gov (United States)

    Srivastava, Deepak; Saini, Subhash (Technical Monitor)

    1998-01-01

    Recent experimental and theoretical attempts and results indicate two distinct broad pathways towards future molecular electronic devices and architectures. The first is the approach via Tour type ladder molecules and their junctions which can be fabricated with solution phase chemical approaches. Second are fullerenes or nanotubules and their junctions which may have better conductance, switching and amplifying characteristics but can not be made through well controlled and defined chemical means. A hybrid approach combining the two pathways to take advantage of the characteristics of both is suggested. Dimension and scale of such devices would be somewhere in between isolated molecule and nanotubule based devices but it maybe possible to use self-assembly towards larger functional and logicalunits.

  20. Photo-Ionization of Noble Gases: A Demonstration of Hybrid Coupled Channels Approach

    Directory of Open Access Journals (Sweden)

    Vinay Pramod Majety

    2015-01-01

    Full Text Available We present here an application of the recently developed hybrid coupled channels approach to study photo-ionization of noble gas atoms: Neon and Argon. We first compute multi-photon ionization rates and cross-sections for these inert gas atoms with our approach and compare them with reliable data available from R-matrix Floquet theory. The good agreement between coupled channels and R-matrix Floquet theory show that our method treats multi-electron systems on par with the well established R-matrix theory. We then apply the time dependent surface flux (tSURFF method with our approach to compute total and angle resolved photo-electron spectra from Argon with linearly and circularly polarized 12 nm wavelength laser fields, a typical wavelength available from Free Electron Lasers (FELs.

  1. A Hybrid Approach to Processing Big Data Graphs on Memory-Restricted Systems

    KAUST Repository

    Harshvardhan,

    2015-05-01

    With the advent of big-data, processing large graphs quickly has become increasingly important. Most existing approaches either utilize in-memory processing techniques that can only process graphs that fit completely in RAM, or disk-based techniques that sacrifice performance. In this work, we propose a novel RAM-Disk hybrid approach to graph processing that can scale well from a single shared-memory node to large distributed-memory systems. It works by partitioning the graph into sub graphs that fit in RAM and uses a paging-like technique to load sub graphs. We show that without modifying the algorithms, this approach can scale from small memory-constrained systems (such as tablets) to large-scale distributed machines with 16, 000+ cores.

  2. Optimising risk reduction: An expected utility approach for marginal risk reduction during regulatory decision making

    International Nuclear Information System (INIS)

    Li Jiawei; Pollard, Simon; Kendall, Graham; Soane, Emma; Davies, Gareth

    2009-01-01

    In practice, risk and uncertainty are essentially unavoidable in many regulation processes. Regulators frequently face a risk-benefit trade-off since zero risk is neither practicable nor affordable. Although it is accepted that cost-benefit analysis is important in many scenarios of risk management, what role it should play in a decision process is still controversial. One criticism of cost-benefit analysis is that decision makers should consider marginal benefits and costs, not present ones, in their decision making. In this paper, we investigate the problem of regulatory decision making under risk by applying expected utility theory and present a new approach of cost-benefit analysis. Directly taking into consideration the reduction of the risks, this approach achieves marginal cost-benefit analysis. By applying this approach, the optimal regulatory decision that maximizes the marginal benefit of risk reduction can be considered. This provides a transparent and reasonable criterion for stakeholders involved in the regulatory activity. An example of evaluating seismic retrofitting alternatives is provided to demonstrate the potential of the proposed approach.

  3. When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

    KAUST Repository

    Liu, Xiao

    2017-03-21

    Privacy risks of recommender systems have caused increasing attention. Users’ private data is often collected by probably untrusted recommender system in order to provide high-quality recommendation. Meanwhile, malicious attackers may utilize recommendation results to make inferences about other users’ private data. Existing approaches focus either on keeping users’ private data protected during recommendation computation or on preventing the inference of any single user’s data from the recommendation result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP) with randomized perturbation (RP). We theoretically show the noise added by RP has limited effect on recommendation accuracy and the noise added by DP can be well controlled based on the sensitivity analysis of functions on the perturbed data. Extensive experiments on three large-scale real world datasets show that the hybrid approach generally provides more privacy protection with acceptable recommendation accuracy loss, and surprisingly sometimes achieves better privacy without sacrificing accuracy, thus validating its feasibility in practice.

  4. Identification and Prediction of Large Pedestrian Flow in Urban Areas Based on a Hybrid Detection Approach

    Directory of Open Access Journals (Sweden)

    Kaisheng Zhang

    2016-12-01

    Full Text Available Recently, population density has grown quickly with the increasing acceleration of urbanization. At the same time, overcrowded situations are more likely to occur in populous urban areas, increasing the risk of accidents. This paper proposes a synthetic approach to recognize and identify the large pedestrian flow. In particular, a hybrid pedestrian flow detection model was constructed by analyzing real data from major mobile phone operators in China, including information from smartphones and base stations (BS. With the hybrid model, the Log Distance Path Loss (LDPL model was used to estimate the pedestrian density from raw network data, and retrieve information with the Gaussian Progress (GP through supervised learning. Temporal-spatial prediction of the pedestrian data was carried out with Machine Learning (ML approaches. Finally, a case study of a real Central Business District (CBD scenario in Shanghai, China using records of millions of cell phone users was conducted. The results showed that the new approach significantly increases the utility and capacity of the mobile network. A more reasonable overcrowding detection and alert system can be developed to improve safety in subway lines and other hotspot landmark areas, such as the Bundle, People’s Square or Disneyland, where a large passenger flow generally exists.

  5. Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

    Directory of Open Access Journals (Sweden)

    JingRui Zhang

    2015-03-01

    Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

  6. Hybrid generative-discriminative approach to age-invariant face recognition

    Science.gov (United States)

    Sajid, Muhammad; Shafique, Tamoor

    2018-03-01

    Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

  7. An Approach for Designing Thermal Management Systems for Electric and Hybrid Vehicle Battery Packs

    International Nuclear Information System (INIS)

    Pesaran, Ahmad A.; Keyser, Matthew; Burch, Steve

    1999-01-01

    If battery packs for electric vehicles (EVs) and hybrid electric vehicles (HEVs) are to operate effectively in all climates, thermal management of the packs is essential. In this paper, we will review a systematic approach for designing and evaluating battery pack thermal management systems. A thermal management system using air as the heat transfer medium is less complicated than a system using liquid cooling/heating. Generally, for parallel HEVs, an air thermal management system is adequate, whereas for EVs and series HEVs, liquid-based systems may be required for optimum thermal performance. Further information on battery thermal management can be found on the Web site www.ctts.nrel.gov/BTM

  8. AEROSTATIC AND AERODYNAMIC MODULES OF A HYBRID BUOYANT AIRCRAFT: AN ANALYTICAL APPROACH

    Directory of Open Access Journals (Sweden)

    Anwar Ul Haque

    2015-05-01

    Full Text Available An analytical approach is essential for the estimation of the requirements of aerodynamic and aerostatic lift for a hybrid buoyant aircraft. Such aircrafts have two different modules to balance the weight of aircraft; aerostatic module and aerodynamic module. Both these modules are to be treated separately for estimation of the mass budget of propulsion systems and required power. In the present work, existing relationships of aircraft and airship are reviewed for its further application for these modules. Limitations of such relationships are also disussed and it is precieved that it will provide a strating point for better understanding of design anatomy of such aircraft.

  9. "Elephant trunk" and endovascular stentgrafting : a hybrid approach to the treatment of extensive thoracic aortic aneurysm

    OpenAIRE

    Holubec, Tomás; Raupach, Jan; Dominik, Jan; Vojácek, Jan

    2013-01-01

    hybrid approach to elephant trunk technique for treatment of thoracic aortic aneurysms combines a conventional surgical and endovascular therapy. Compared to surgery alone, there is a presumption that mortality and morbidity is reduced. We present a case report of a 42-year-old man with a giant aneurysm of the entire thoracic aorta, significant aortic and tricuspid regurgitation and ventricular septum defect. The patient underwent multiple consecutive operations and interventions having, am...

  10. Towards a comprehensive theory for He II: I. A zero-temperature hybrid approach

    International Nuclear Information System (INIS)

    Ghassib, H.B.; Khudeir, A.M.

    1982-09-01

    A simple hybrid approach based on a gauge theory as well as a Hartree formalism, is presented for He II at zero temperature. Although this is intended to be merely a first step in an all-embracing theory, it already resolves quite neatly several old inconsistencies and corrects a few errors. As an illustration of its feasibility, a crude but instructive calculation is performed for the static structure factor of the system at low momentum transfers. A number of planned extensions and generalizations are outlined. (author)

  11. An integrated optimization approach for a hybrid energy system in electric vehicles

    International Nuclear Information System (INIS)

    Hung, Yi-Hsuan; Wu, Chien-Hsun

    2012-01-01

    Highlights: ► Second-order control-oriented dynamics for a battery/supercapacitor EV is modeled. ► Multiple for-loop programming and global searchwith constraints are main design principles of integrated optimization algorithm (IOA). ► Optimal hybridization is derived based on maximizing energy storage capacity. ► Optimal energy management in three EV operation modes is searched based on minimizing total consumed power. ► Simulation results prove that 6+% of total energy is saved by the IOA method. -- Abstract: This paper develops a simple but innovative integrated optimization approach (IOA) for deriving the best solutions of component sizing and control strategies of a hybrid energy system (HES) which consists of a lithium battery and a supercapacitor module. To implement IOA, a multiple for-loop structure with a preset cost function is needed to globally calculate the best hybridization and energy management of the HES. For system hybridization, the optimal size ratio is evaluated by maximizing the HES energy stored capacity at various costs. For energy management, the optimal power distribution combined with a three-mode rule-based strategy is searched to minimize the total consumed energy. Combining above two for-loop structures and giving a time-dependent test scenario, the IOA is derived by minimizing the accumulated HES power. Simulation results show that 6% of the total HES energy can be saved in the IOA case compared with the original system in two driving cycles: ECE and UDDS, and two vehicle weights, respectively. It proves that the IOA effectively derives the maximum energy storage capacity and the minimum energy consumption of the HES at the same time. Experimental verification will be carried out in the near future.

  12. Merging building maintainability and sustainability assessment: A multicriteria decision making approach

    Science.gov (United States)

    Asmone, A. S.; Chew, M. Y. L.

    2018-02-01

    Accurately predicting maintainability has been a challenge due to the complex nature of buildings, yet it is an important research area with a rising necessity. This paper explores the use of multicriteria decision making approach for merging maintainability and sustainability elements into building grading systems to attain long-term sustainability in the building industry. The paper conducts a systematic literature review on multicriteria decision analysis approach and builds on the existing knowledge of maintainability to achieve this. A conceptual framework is developed to bridge the gap between building operations and maintenance with green facilities management by forecasting green maintainability at the design stage.

  13. Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

    Science.gov (United States)

    Lee, G.; Jun, K. S.; Chung, E.-S.

    2015-04-01

    This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

  14. Brand deletion: How the decision-making approach affects deletion success

    Directory of Open Access Journals (Sweden)

    Víctor Temprano-García

    2018-04-01

    Full Text Available Literature on brand deletion (BD, a critical and topical decision within a firm's marketing strategy, is extremely scarce. The present research is concerned with the decision-making process and examines the effect on BD success of three different approaches to decision-making – rational, intuitive and political – and of the interaction between the rational and political approaches. The moderating effect of the type of BD – i.e., total brand killing or disposal vs. brand name change – is also analyzed. The model is tested on a sample of 155 cases of BD. Results point to positive effects on BD success of both rationality and intuition, and a negative effect of politics. Findings also indicate that the negative impact of political behavior on BD success is minimized in the absence of evidence and objective information and when the BD is undertaken through a brand name change. JEL classification: L10, M31, Keywords: Brand deletion, Rational decision-making, Intuitive decision-making, Political decision-making, Brand deletion success

  15. Helping patients to reach decisions regarding their treatment: Do 'non-directive' approaches cause systematic bias?

    Science.gov (United States)

    MacInnes, Joy Anne; Salkovskis, Paul M; Wroe, Abigail; Hope, Tony

    2015-11-01

    does this study add? The hypothetical decision about whether or not, in future, to take statins for elevated cholesterol levels was influenced by positive but not by negative focussing. Results were consistent with the theoretical framework. This study extends previous work on influences on the decision to undertake health screening and vaccination to treatment offered as secondary prevention. 'Non-directive' approaches to helping facilitate decisions can modify those decisions, and as such cannot be regarded as non-directive. © 2015 The British Psychological Society.

  16. A simplified computational fluid-dynamic approach to the oxidizer injector design in hybrid rockets

    Science.gov (United States)

    Di Martino, Giuseppe D.; Malgieri, Paolo; Carmicino, Carmine; Savino, Raffaele

    2016-12-01

    Fuel regression rate in hybrid rockets is non-negligibly affected by the oxidizer injection pattern. In this paper a simplified computational approach developed in an attempt to optimize the oxidizer injector design is discussed. Numerical simulations of the thermo-fluid-dynamic field in a hybrid rocket are carried out, with a commercial solver, to investigate into several injection configurations with the aim of increasing the fuel regression rate and minimizing the consumption unevenness, but still favoring the establishment of flow recirculation at the motor head end, which is generated with an axial nozzle injector and has been demonstrated to promote combustion stability, and both larger efficiency and regression rate. All the computations have been performed on the configuration of a lab-scale hybrid rocket motor available at the propulsion laboratory of the University of Naples with typical operating conditions. After a preliminary comparison between the two baseline limiting cases of an axial subsonic nozzle injector and a uniform injection through the prechamber, a parametric analysis has been carried out by varying the oxidizer jet flow divergence angle, as well as the grain port diameter and the oxidizer mass flux to study the effect of the flow divergence on heat transfer distribution over the fuel surface. Some experimental firing test data are presented, and, under the hypothesis that fuel regression rate and surface heat flux are proportional, the measured fuel consumption axial profiles are compared with the predicted surface heat flux showing fairly good agreement, which allowed validating the employed design approach. Finally an optimized injector design is proposed.

  17. A Survey of Game Theoretic Approaches to Modelling Decision-Making in Information Warfare Scenarios

    Directory of Open Access Journals (Sweden)

    Kathryn Merrick

    2016-07-01

    Full Text Available Our increasing dependence on information technologies and autonomous systems has escalated international concern for information- and cyber-security in the face of politically, socially and religiously motivated cyber-attacks. Information warfare tactics that interfere with the flow of information can challenge the survival of individuals and groups. It is increasingly important that both humans and machines can make decisions that ensure the trustworthiness of information, communication and autonomous systems. Subsequently, an important research direction is concerned with modelling decision-making processes. One approach to this involves modelling decision-making scenarios as games using game theory. This paper presents a survey of information warfare literature, with the purpose of identifying games that model different types of information warfare operations. Our contribution is a systematic identification and classification of information warfare games, as a basis for modelling decision-making by humans and machines in such scenarios. We also present a taxonomy of games that map to information warfare and cyber crime problems as a precursor to future research on decision-making in such scenarios. We identify and discuss open research questions including the role of behavioural game theory in modelling human decision making and the role of machine decision-making in information warfare scenarios.

  18. A decision science approach for integrating social science in climate and energy solutions

    Science.gov (United States)

    Wong-Parodi, Gabrielle; Krishnamurti, Tamar; Davis, Alex; Schwartz, Daniel; Fischhoff, Baruch

    2016-06-01

    The social and behavioural sciences are critical for informing climate- and energy-related policies. We describe a decision science approach to applying those sciences. It has three stages: formal analysis of decisions, characterizing how well-informed actors should view them; descriptive research, examining how people actually behave in such circumstances; and interventions, informed by formal analysis and descriptive research, designed to create attractive options and help decision-makers choose among them. Each stage requires collaboration with technical experts (for example, climate scientists, geologists, power systems engineers and regulatory analysts), as well as continuing engagement with decision-makers. We illustrate the approach with examples from our own research in three domains related to mitigating climate change or adapting to its effects: preparing for sea-level rise, adopting smart grid technologies in homes, and investing in energy efficiency for office buildings. The decision science approach can facilitate creating climate- and energy-related policies that are behaviourally informed, realistic and respectful of the people whom they seek to aid.

  19. An expert panel approach to support risk-informed decision making

    International Nuclear Information System (INIS)

    Pulkkinen, U.; Simola, K.

    2000-01-01

    The report describes the expert panel methodology developed for supporting risk-informed decision making. The aim of an expert panel is to achieve a balanced utilisation of information and expertise from several disciplines in decision-making including probabilistic safety assessment as one decision criterion. We also summarise the application of the methodology in the STUK's RI-ISI (Risk-Informed In-Service Inspection) pilot study, where the expert panel approach was used to combine the deterministic information on degradation mechanisms and probabilistic information on pipe break consequences. The expert panel served both as a critical review of the preliminary results and as a decision support for the final definition of risk categories of piping. (orig.)

  20. A Benefit-Risk Analysis Approach to Capture Regulatory Decision-Making: Multiple Myeloma.

    Science.gov (United States)

    Raju, G K; Gurumurthi, Karthik; Domike, Reuben; Kazandjian, Dickran; Landgren, Ola; Blumenthal, Gideon M; Farrell, Ann; Pazdur, Richard; Woodcock, Janet

    2018-01-01

    Drug regulators around the world make decisions about drug approvability based on qualitative benefit-risk analysis. In this work, a quantitative benefit-risk analysis approach captures regulatory decision-making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression-free survival (PFS), and objective response rate (ORR) which are different than benefit-risk analysis based on overall survival (OS). Twenty-three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit-risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit-risk framework. © 2017 American Society for Clinical Pharmacology and Therapeutics.

  1. Prediction of shape diameter undergoing coil embolization of saccular intracranial aneurysm treatment using a hybrid decision support system

    International Nuclear Information System (INIS)

    Owasirikul, Wiwat; Tantivatana, Jaturon; Gansawat, Duangrat; Auethavekiat, Supatana

    2013-01-01

    The purpose of the study was to design a hybrid decision support system (HDSS) that could simulate the embolized coil selection pattern of the radiologists in aneurysms treatment. As the longest available length of the coils should be used in most cases, therefore only the shape diameter (SD) selection was modeled and varied. Ninety-eight aneurysms successfully treated by a radiologist with coil embolization were divided into two groups (86 for training and 12 randomly selected for validating). Eight aneurysms treated by another radiologist were also used to cross validate the proposed HDSS. The HDSS was developed using the classification and the linear regression methods (LRM). The dome and the width of an aneurysm were used as the system inputs. The system outputs were the SDs of the first three coils indexed according to the insertion order. The HDSS that consisted of Bagging classification and LRM achieved the highest accuracy for all cases. The errors were within 1 mm for the SD selection of the first two coils. For the third coil, the SD selection within 1 mm bound had 80 % accuracy. The experimental results indicated the feasibility of using the HDSS as the guidance for selecting the SDs of the first two coils. The selection of the third coil required more training data for the rarely used SD. Moreover, the cross validation with another radiologist showed the feasibility of using the proposed HDSS as the guidance, however further validation with more data is recommended.

  2. The First Flight Decision for New Human Spacecraft Vehicles - A General Approach

    Science.gov (United States)

    Schaible, Dawn M.; Sumrall, John Phillip

    2011-01-01

    Determining when it is safe to fly a crew on a launch vehicle/spacecraft for the first time, especially when the test flight is a part of the overall system certification process, has long been a challenge for program decision makers. The decision on first flight is ultimately the judgment of the program and agency management in conjunction with the design and operations team. To aid in this decision process, a NASA team undertook the task to develop a generic framework for evaluating whether any given program or commercial provider has sufficiently complete and balanced plans in place to allow crewmembers to safely fly on human spaceflight systems for the first time. It was the team s goal to establish a generic framework that could easily be applied to any new system, although the system design and intended mission would require specific assessment. Historical data shows that there are multiple approaches that have been successful in first flight with crew. These approaches have always been tailored to the specific system design, mission objectives, and launch environment. Because specific approaches may vary significantly between different system designs and situations, prescriptive instructions or thorough checklists cannot be provided ahead of time. There are, however, certain general approaches that should be applied in thinking through the decision for first flight. This paper addresses some of the most important factors to consider when developing a new system or evaluating an existing system for whether or not it is safe to fly humans to/from space. In the simplest terms, it is time to fly crew for the first time when it is safe to do so and the benefit of the crewed flight is greater than the residual risk. This is rarely a straight-forward decision. The paper describes the need for experience, sound judgment, close involvement of the technical and management teams, and established decision processes. In addition, the underlying level of confidence the

  3. A hybrid filtering approach for storage optimization in main-memory cloud database

    Directory of Open Access Journals (Sweden)

    Ghada M. Afify

    2015-11-01

    Full Text Available Enterprises and cloud service providers face dramatic increase in the amount of data stored in private and public clouds. Thus, data storage costs are growing hastily because they use only one single high-performance storage tier for storing all cloud data. There’s considerable potential to reduce cloud costs by classifying data into active (hot and inactive (cold. In the main-memory databases research, recent works focus on approaches to identify hot/cold data. Most of these approaches track tuple accesses to identify hot/cold tuples. In contrast, we introduce a novel Hybrid Filtering Approach (HFA that tracks both tuples and columns accesses in main-memory databases. Our objective is to enhance the performance in terms of three dimensions: storage space, query elapsed time and CPU time. In order to validate the effectiveness of our approach, we realized its concrete implementation on Hekaton, a SQL’s server memory-optimized engine using the well-known TPC-H benchmark. Experimental results show that the proposed HFA outperforms Hekaton approach in respect of all performance dimensions. In specific, HFA reduces the storage space by average of 44–96%, reduces the query elapsed time by average of 25–93% and reduces the CPU time by average of 31–97% compared to the traditional database approach.

  4. An Odometry-free Approach for Simultaneous Localization and Online Hybrid Map Building

    Directory of Open Access Journals (Sweden)

    Wei Hong Chin

    2016-11-01

    Full Text Available In this paper, a new approach is proposed for mobile robot localization and hybrid map building simultaneously without using any odometry hardware system. The proposed method termed as Genetic Bayesian ARAM which comprises two main components: 1 Steady state genetic algorithm (SSGA for self-localization and occupancy grid map building; 2 Bayesian Adaptive Resonance Associative Memory (ARAM for online topological map building. The model of the explored environment is formed as a hybrid representation, both topological and grid-based, and it is incrementally constructed during the exploration process. During occupancy map building, robot estimated self-position is updated by SSGA. At the same time, robot estimated self position is transmit to Bayesian ARAM for topological map building and localization. The effectiveness of our proposed approach is validated by a number of standardized benchmark datasets and real experimental results carried on mobile robot. Benchmark datasets are used to verify the proposed method capable of generating topological map in different environment conditions. Real robot experiment is to verify the proposed method can be implemented in real world.

  5. Hybrid discrete PSO and OPF approach for optimization of biomass fueled micro-scale energy system

    International Nuclear Information System (INIS)

    Gómez-González, M.; López, A.; Jurado, F.

    2013-01-01

    Highlights: ► Method to determine the optimal location and size of biomass power plants. ► The proposed approach is a hybrid of PSO algorithm and optimal power flow. ► Comparison among the proposed algorithm and other methods. ► Computational costs are enough lower than that required for exhaustive search. - Abstract: This paper addresses generation of electricity in the specific aspect of finding the best location and sizing of biomass fueled gas micro-turbine power plants, taking into account the variables involved in the problem, such as the local distribution of biomass resources, biomass transportation and extraction costs, operation and maintenance costs, power losses costs, network operation costs, and technical constraints. In this paper a hybrid method is introduced employing discrete particle swarm optimization and optimal power flow. The approach can be applied to search the best sites and capacities to connect biomass fueled gas micro-turbine power systems in a distribution network among a large number of potential combinations and considering the technical constraints of the network. A fair comparison among the proposed algorithm and other methods is performed.

  6. Output Tracking Control of Switched Hybrid Systems: A Fliess Functional Expansion Approach

    Directory of Open Access Journals (Sweden)

    Fenghua He

    2013-01-01

    Full Text Available The output tracking problem is investigated for a nonlinear affine system with multiple modes of continuous control inputs. We convert the family of nonlinear affine systems under consideration into a switched hybrid system by introducing a multiple-valued logic variable. The Fliess functional expansion is adopted to express the input and output relationship of the switched hybrid system. The optimal switching control is determined for a multiple-step output tracking performance index. The proposed approach is applied to a multitarget tracking problem for a flight vehicle aiming for one real target with several decoys flying around it in the terminal guidance course. These decoys appear as apparent targets and have to be distinguished with the approaching of the flight vehicle. The guidance problem of one flight vehicle versus multiple apparent targets should be considered if no large miss distance might be caused due to the limitation of the flight vehicle maneuverability. The target orientation at each time interval is determined. Simulation results show the effectiveness of the proposed method.

  7. Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels

    Directory of Open Access Journals (Sweden)

    Antonino Laudani

    2015-01-01

    Full Text Available A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented. The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model. Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task. The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form. The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters. It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture. Validations are made on about 10000 PV panels belonging to the California Energy Commission database.

  8. A diagnostic expert system for the nuclear power plant b ased on the hybrid knowledge approach

    International Nuclear Information System (INIS)

    Yang, J.O.; Chang, S.H.

    1989-01-01

    A diagnostic expert system, the hybrid knowledge based plant operation supporting system (HYPOSS), which has been developed to support operators' decisionmaking during the transients of the nuclear power plant, is described. HYPOSS adopts the hybrid knowledge approach, which combines both shallow and deep knowledge to take advantage of the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure. They are structural, functional, behavioral, and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions, respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem-solving behavior modeled in HYPOSS. The event-based operational guidelines are provided to the operator according to the diagnosed results. If the exact anomalies cannot be identified while some of the critical safety functions are challenged, the function-based operational guidelines are provided to the operator. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies show good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

  9. A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran

    International Nuclear Information System (INIS)

    Mostafavi, Elham Sadat; Ramiyani, Sara Saeidi; Sarvar, Rahim; Moud, Hashem Izadi; Mousavi, Seyyed Mohammad

    2013-01-01

    This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated annealing (SA), called GP/SA. The solar radiation was formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years in two cities of Iran were used to develop GP/SA-based models. Separate models were established for each city. The generalization of the models was verified using a separate testing database. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the solar radiation. The derived models make accurate predictions of the solar global radiation and notably outperform the existing models. -- Highlights: ► A hybrid approach is presented for the estimation of the solar global radiation. ► The proposed method integrates the capabilities of GP and SA. ► Several climatological and meteorological parameters are included in the analysis. ► The GP/SA models make accurate predictions of the solar global radiation.

  10. Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

    Directory of Open Access Journals (Sweden)

    Yuliang Su

    2015-04-01

    Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

  11. A hybrid simulated annealing approach to handle energy resource management considering an intensive use of electric vehicles

    DEFF Research Database (Denmark)

    Sousa, Tiago; Vale, Zita; Carvalho, Joao Paulo

    2014-01-01

    The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed...... to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated...... annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA...

  12. A Hybrid Heuristic Optimization Approach for Leak Detection in Pipe Networks Using Ordinal Optimization Approach and the Symbiotic Organism Search

    Directory of Open Access Journals (Sweden)

    Chao-Chih Lin

    2017-10-01

    Full Text Available A new transient-based hybrid heuristic approach is developed to optimize a transient generation process and to detect leaks in pipe networks. The approach couples the ordinal optimization approach (OOA and the symbiotic organism search (SOS to solve the optimization problem by means of iterations. A pipe network analysis model (PNSOS is first used to determine steady-state head distribution and pipe flow rates. The best transient generation point and its relevant valve operation parameters are optimized by maximizing the objective function of transient energy. The transient event is created at the chosen point, and the method of characteristics (MOC is used to analyze the transient flow. The OOA is applied to sift through the candidate pipes and the initial organisms with leak information. The SOS is employed to determine the leaks by minimizing the sum of differences between simulated and computed head at the observation points. Two synthetic leaking scenarios, a simple pipe network and a water distribution network (WDN, are chosen to test the performance of leak detection ordinal symbiotic organism search (LDOSOS. Leak information can be accurately identified by the proposed approach for both of the scenarios. The presented technique makes a remarkable contribution to the success of leak detection in the pipe networks.

  13. A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

    Science.gov (United States)

    Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

    2015-11-19

    Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

  14. Executive function, approach sensitivity, and emotional decision making as influences on risk behaviors in young adults.

    Science.gov (United States)

    Patrick, Megan E; Blair, Clancy; Maggs, Jennifer L

    2008-05-01

    Relations among executive function, behavioral approach sensitivity, emotional decision making, and risk behaviors (alcohol use, drug use, and delinquent behavior) were examined in single female college students (N = 72). Hierarchical multiple regressions indicated a significant Approach Sensitivity x Working Memory interaction in which higher levels of alcohol use were associated with the combination of greater approach tendency and better working memory. This Approach Sensitivity x Working Memory interaction was also marginally significant for drug use and delinquency. Poor emotional decision making, as measured by a gambling task, was also associated with higher levels of alcohol use, but only for individuals low in inhibitory control. Findings point to the complexity of relations among aspects of self-regulation and personality and provide much needed data on neuropsychological correlates of risk behaviors in a nonclinical population.

  15. Data mining approach to bipolar cognitive map development and decision analysis

    Science.gov (United States)

    Zhang, Wen-Ran

    2002-03-01

    A data mining approach to cognitive mapping is presented based on bipolar logic, bipolar relations, and bipolar clustering. It is shown that a correlation network derived from a database can be converted to a bipolar cognitive map (or bipolar relation). A transitive, symmetric, and reflexive bipolar relation (equilibrium relation) can be used to identify focal links in decision analysis. It can also be used to cluster a set of events or itemsets into three different clusters: coalition sets, conflict sets, and harmony sets. The coalition sets are positively correlated events or itemsets; each conflict set is a negatively correlated set of two coalition subsets; and a harmony set consists of events that are both negatively and positively correlated. A cognitive map and the clusters can then be used for online decision analysis. This approach combines knowledge discovery with the views of decision makers and provides an effective means for online analytical processing (OLAP) and online analytical mining (OLAM).

  16. A life cycle analysis approach to D and D decision-making

    International Nuclear Information System (INIS)

    Yuracko, K.L.; Gresalfi, M.; Yerace, P.; Krstich, M.; Gerrick, D.

    1998-05-01

    This paper describes a life cycle analysis (LCA) approach that makes decontamination and decommissioning (D and D) of US Department of Energy facilities more efficient and more responsive to the concerns of the society. With the considerable complexity of D and D projects and their attendant environmental and health consequences, projects can no longer be designed based on engineering and economic criteria alone. Using the LCA D and D approach, the evaluation of material disposition alternatives explicitly includes environmental impacts, health and safety impacts, socioeconomic impacts, and stakeholder attitudes -- in addition to engineering and economic criteria. Multi-attribute decision analysis is used to take into consideration the uncertainties and value judgments that are an important part of all material disposition decisions. Use of the LCA D and D approach should lead to more appropriate selections of material disposition pathways and a decision-making process that is both understandable and defensible. The methodology and procedures of the LCA D and D approach are outlined and illustrated by an application of the approach at the Department of Energy's West Valley Demonstration Project. Specifically, LCA was used to aid decisions on disposition of soil and concrete from the Tank Pad D and D Project. A decision tree and the Pollution Prevention/Waste Minimization Users Guide for Environmental Restoration Projects were used to identify possible alternatives for disposition of the soil and concrete. Eight alternatives encompassing source reduction, segregation, treatment, and disposal were defined for disposition of the soil; two alternatives were identified for disposition of the concrete. Preliminary results suggest that segregation and treatment are advantageous in the disposition of both the soil and the concrete. This and other recent applications illustrate the strength and ease of application of the LCA D and D approach

  17. A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN

    Directory of Open Access Journals (Sweden)

    Yimei Kang

    2014-04-01

    Full Text Available Energy efficiency is usually a significant goal in wireless sensor networks (WSNs. In this work, an energy efficient chain (EEC data routing approach is first presented. The coverage and connectivity of WSNs are discussed based on EEC. A hybrid node scheduling approach is then proposed. It includes sleep scheduling for cyclically monitoring regions of interest in time-driven modes and wakeup scheduling for tracking emergency events in event-driven modes. A failure rate is introduced to the sleep scheduling to improve the reliability of the system. A wakeup sensor threshold and a sleep time threshold are introduced in the wakeup scheduling to reduce the consumption of energy to the possible extent. The results of the simulation show that the proposed algorithm can extend the effective lifetime of the network to twice that of PEAS. In addition, the proposed methods are computing efficient because they are very simple to implement.

  18. A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Jian Xiong

    2012-01-01

    Full Text Available This paper addresses multiobjective flexible job-shop scheduling problem (FJSP with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach (H-MOEA is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to maintain the diversity of individuals. In the proposed H-MOEA, well-designed chromosome representation and genetic operators are developed for FJSP. Moreover, a local search procedure based on critical path theory is incorporated in H-MOEA to improve the convergence ability of the algorithm. Experiment results on several well-known benchmark instances demonstrate the efficiency and stability of the proposed algorithm. The comparison with other recently published approaches validates that H-MOEA can obtain Pareto-optimal solutions with better quality and/or diversity.

  19. A Practical Approach to Improve Optical Channel Utilization Period for Hybrid FSO/RF Systems

    Directory of Open Access Journals (Sweden)

    Ahmet Akbulut

    2014-01-01

    Full Text Available In hybrid FSO/RF systems, mostly a hard switching mechanism is preferred in case of the FSO signal level falls below to the predefined threshold. In this work, a computationally simple approach is proposed to increase the utilization of the FSO channels bandwidth advantage. For the channel, clear air conditions have been supposed with the atmospheric turbulence. In this approach, FSO bit rate is adaptively changed to achieve desired BER performance. An IM/DD modulation, OOK (NRZ format has been used to show the benefit of the proposed method. Furthermore, to be more realistic with respect to the atmospheric turbulence variations within a day, some experimental observations have been followed up.

  20. Approach of decision making based on the analytic hierarchy process for urban landscape management.

    Science.gov (United States)

    Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan

    2013-03-01

    This paper proposes a two-stage group decision making approach to urban landscape management and planning supported by the analytic hierarchy process. The proposed approach combines an application of the consensus convergence model and the weighted geometric mean method. The application of the proposed approach is shown on a real urban landscape planning problem with a park-forest in Belgrade, Serbia. Decision makers were policy makers, i.e., representatives of several key national and municipal institutions, and experts coming from different scientific fields. As a result, the most suitable management plan from the set of plans is recognized. It includes both native vegetation renewal in degraded areas of park-forest and continued maintenance of its dominant tourism function. Decision makers included in this research consider the approach to be transparent and useful for addressing landscape management tasks. The central idea of this paper can be understood in a broader sense and easily applied to other decision making problems in various scientific fields.

  1. Approach of Decision Making Based on the Analytic Hierarchy Process for Urban Landscape Management

    Science.gov (United States)

    Srdjevic, Zorica; Lakicevic, Milena; Srdjevic, Bojan

    2013-03-01

    This paper proposes a two-stage group decision making approach to urban landscape management and planning supported by the analytic hierarchy process. The proposed approach combines an application of the consensus convergence model and the weighted geometric mean method. The application of the proposed approach is shown on a real urban landscape planning problem with a park-forest in Belgrade, Serbia. Decision makers were policy makers, i.e., representatives of several key national and municipal institutions, and experts coming from different scientific fields. As a result, the most suitable management plan from the set of plans is recognized. It includes both native vegetation renewal in degraded areas of park-forest and continued maintenance of its dominant tourism function. Decision makers included in this research consider the approach to be transparent and useful for addressing landscape management tasks. The central idea of this paper can be understood in a broader sense and easily applied to other decision making problems in various scientific fields.

  2. Which Types of Leadership Styles Do Followers Prefer? A Decision Tree Approach

    Science.gov (United States)

    Salehzadeh, Reza

    2017-01-01

    Purpose: The purpose of this paper is to propose a new method to find the appropriate leadership styles based on the followers' preferences using the decision tree technique. Design/methodology/approach: Statistical population includes the students of the University of Isfahan. In total, 750 questionnaires were distributed; out of which, 680…

  3. Fuzzy Group Decision Making Approach for Ranking Work Stations Based on Physical Pressure

    Directory of Open Access Journals (Sweden)

    Hamed Salmanzadeh

    2014-06-01

    Full Text Available This paper proposes a Fuzzy Group Decision Making approach for ranking work stations based on physical pressure. Fuzzy group decision making approach allows experts to evaluate different ergonomic factors using linguistic terms such as very high, high, medium, low, very low, rather than precise numerical values. In this way, there is no need to measure parameters and evaluation can be easily made in a group. According to ergonomics much work contents and situations, accompanied with multiple parameters and uncertainties, fuzzy group decision making is the best way to evaluate such a chameleon of concept. A case study was down to utilize the approach and illustrate its application in ergonomic assessment and ranking the work stations based on work pressure and found that this approach provides flexibility, practicality, efficiency in making decision around ergonomics areas. The normalized defuzzification numbers which are resulted from this method are compared with result of quantitative assessment of Automotive Assembly Work Sheet auto, it’s demonstrated that the proposed method result is 10% less than Automotive Assembly Work Sheet, approximately.

  4. A decision tree approach using silvics to guide planning for forest restoration

    Science.gov (United States)

    Sharon M. Hermann; John S. Kush; John C. Gilbert

    2013-01-01

    We created a decision tree based on silvics of longleaf pine (Pinus palustris) and historical descriptions to develop approaches for restoration management at Horseshoe Bend National Military Park located in central Alabama. A National Park Service goal is to promote structure and composition of a forest that likely surrounded the 1814 battlefield....

  5. A Composite Modelling Approach to Decision Support by the Use of the CBA-DK Model

    DEFF Research Database (Denmark)

    Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen

    2007-01-01

    This paper presents a decision support system for assessment of transport infrastructure projects. The composite modelling approach, COSIMA, combines a cost-benefit analysis by use of the CBA-DK model with multi-criteria analysis applying the AHP and SMARTER techniques. The modelling uncertaintie...

  6. Examining Preservice Teachers' Classroom Management Decisions in Three Case-Based Teaching Approaches

    Science.gov (United States)

    Cevik, Yasemin Demiraslan; Andre, Thomas

    2013-01-01

    This study was aimed at comparing the impact of three types of case-based approaches (worked example, faded work example, and case-based reasoning) on preservice teachers' decision making and reasoning skills related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three…

  7. Which Cooperative Ownership Model Performs Better? A Financial-Decision Aid Approach

    NARCIS (Netherlands)

    Kalogeras, N.; Pennings, J.M.E.; Benos, T.; Doumpos, M.

    2013-01-01

    In this article the financial/ownership structures of agribusiness cooperatives are analyzed to examine whether new cooperative models perform better than the more traditional ones. The assessment procedure introduces a new financial decision-aid approach, which is based on data-analysis techniques

  8. An Exploration of How Elementary School Principals Approach the Student Retention Decision Process

    Science.gov (United States)

    Martinez-Hicks, Laura M.

    2012-01-01

    This is a constructivist grounded theory study investigating how elementary principals approach the student retention decision process in their schools. Twenty-two elementary principals participated in the study using a selective or snowball sampling method. Principals worked in one of three districts in a mid-Atlantic state and had experience as…

  9. Approaches to Aggregation and Decision Making-A Health Economics Approach: An ISPOR Special Task Force Report [5].

    Science.gov (United States)

    Phelps, Charles E; Lakdawalla, Darius N; Basu, Anirban; Drummond, Michael F; Towse, Adrian; Danzon, Patricia M

    2018-02-01

    The fifth section of our Special Task Force report identifies and discusses two aggregation issues: 1) aggregation of cost and benefit information across individuals to a population level for benefit plan decision making and 2) combining multiple elements of value into a single value metric for individuals. First, we argue that additional elements could be included in measures of value, but such elements have not generally been included in measures of quality-adjusted life-years. For example, we describe a recently developed extended cost-effectiveness analysis (ECEA) that provides a good example of how to use a broader concept of utility. ECEA adds two features-measures of financial risk protection and income distributional consequences. We then discuss a further option for expanding this approach-augmented CEA, which can introduce many value measures. Neither of these approaches, however, provide a comprehensive measure of value. To resolve this issue, we review a technique called multicriteria decision analysis that can provide a comprehensive measure of value. We then discuss budget-setting and prioritization using multicriteria decision analysis, issues not yet fully resolved. Next, we discuss deliberative processes, which represent another important approach for population- or plan-level decisions used by many health technology assessment bodies. These use quantitative information on CEA and other elements, but the group decisions are reached by a deliberative voting process. Finally, we briefly discuss the use of stated preference methods for developing "hedonic" value frameworks, and conclude with some recommendations in this area. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  10. Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach.

    Directory of Open Access Journals (Sweden)

    Kristen Feher

    Full Text Available Heterosis, the greater vigor of hybrids compared to their parents, has been exploited in maize breeding for more than 100 years to produce ever better performing elite hybrids of increased yield. Despite extensive research, the underlying mechanisms shaping the extent of heterosis are not well understood, rendering the process of selecting an optimal set of parental lines tedious. This study is based on a dataset consisting of 112 metabolite levels in young roots of four parental maize inbred lines and their corresponding twelve hybrids, along with the roots' biomass as a heterotic trait. Because the parental biomass is a poor predictor for hybrid biomass, we established a model framework to deduce the biomass of the hybrid from metabolite profiles of its parental lines. In the proposed framework, the hybrid metabolite levels are expressed relative to the parental levels by incorporating the standard concept of additivity/dominance, which we name the Combined Relative Level (CRL. Our modeling strategy includes a feature selection step on the parental levels which are demonstrated to be predictive of CRL across many hybrid metabolites. We demonstrate that these selected parental metabolites are further predictive of hybrid biomass. Our approach directly employs the diallel structure in a multivariate fashion, whereby we attempt to not only predict macroscopic phenotype (biomass, but also molecular phenotype (metabolite profiles. Therefore, our study provides the first steps for further investigations of the genetic determinants to metabolism and, ultimately, growth. Finally, our success on the small-scale experiments implies a valid strategy for large-scale experiments, where parental metabolite profiles may be used together with profiles of selected hybrids as a training set to predict biomass of all possible hybrids.

  11. Assessing Market Development and Innovation Project Management Factors Using the PICEA-g Hybrid Evolutionary Multi-Criteria Decision Technique. The Calcimine Company Case Study

    Directory of Open Access Journals (Sweden)

    S. Ghaffari

    2017-12-01

    Full Text Available Project management includes the consideration of complex decision modes used in modern decision support techniques. The aim of this paper was to prioritize such factors and evaluate their effects on project management and optimal control. Their effect on management and optimal project control are evaluated in frame of a statistical hypothesis. A new algorithm, "IPICEA-g" is proposed for the assessment. A questionnaire is used for data collection distributed between 56 employees of the CALCIMINE Company. T-test, two-sentence test, ANP method, FUZZY SEAMATEL and the IPICEA-g hybrid algorithm, are employed for data analyzing. Results are further discussed and conclusions are drawn.

  12. A dynamic Bayesian network based approach to safety decision support in tunnel construction

    International Nuclear Information System (INIS)

    Wu, Xianguo; Liu, Huitao; Zhang, Limao; Skibniewski, Miroslaw J.; Deng, Qianli; Teng, Jiaying

    2015-01-01

    This paper presents a systemic decision approach with step-by-step procedures based on dynamic Bayesian network (DBN), aiming to provide guidelines for dynamic safety analysis of the tunnel-induced road surface damage over time. The proposed DBN-based approach can accurately illustrate the dynamic and updated feature of geological, design and mechanical variables as the construction progress evolves, in order to overcome deficiencies of traditional fault analysis methods. Adopting the predictive, sensitivity and diagnostic analysis techniques in the DBN inference, this approach is able to perform feed-forward, concurrent and back-forward control respectively on a quantitative basis, and provide real-time support before and after an accident. A case study in relating to dynamic safety analysis in the construction of Wuhan Yangtze Metro Tunnel in China is used to verify the feasibility of the proposed approach, as well as its application potential. The relationships between the DBN-based and BN-based approaches are further discussed according to analysis results. The proposed approach can be used as a decision tool to provide support for safety analysis in tunnel construction, and thus increase the likelihood of a successful project in a dynamic project environment. - Highlights: • A dynamic Bayesian network (DBN) based approach for safety decision support is developed. • This approach is able to perform feed-forward, concurrent and back-forward analysis and control. • A case concerning dynamic safety analysis in Wuhan Yangtze Metro Tunnel in China is presented. • DBN-based approach can perform a higher accuracy than traditional static BN-based approach

  13. Proposed prediction algorithms based on hybrid approach to deal with anomalies of RFID data in healthcare

    Directory of Open Access Journals (Sweden)

    A. Anny Leema

    2013-07-01

    Full Text Available The RFID technology has penetrated the healthcare sector due to its increased functionality, low cost, high reliability, and easy-to-use capabilities. It is being deployed for various applications and the data captured by RFID readers increase according to timestamp resulting in an enormous volume of data duplication, false positive, and false negative. The dirty data stream generated by the RFID readers is one of the main factors limiting the widespread adoption of RFID technology. In order to provide reliable data to RFID application, it is necessary to clean the collected data and this should be done in an effective manner before they are subjected to warehousing. The existing approaches to deal with anomalies are physical, middleware, and deferred approach. The shortcomings of existing approaches are analyzed and found that robust RFID system can be built by integrating the middleware and deferred approach. Our proposed algorithms based on hybrid approach are tested in the healthcare environment which predicts false positive, false negative, and redundant data. In this paper, healthcare environment is simulated using RFID and the data observed by RFID reader consist of anomalies false positive, false negative, and duplication. Experimental evaluation shows that our cleansing methods remove errors in RFID data more accurately and efficiently. Thus, with the aid of the planned data cleaning technique, we can bring down the healthcare costs, optimize business processes, streamline patient identification processes, and improve patient safety.

  14. An Introduction to the Hybrid Approach of Neural Networks and the Linear Regression Model : An Illustration in the Hedonic Pricing Model of Building Costs

    OpenAIRE

    浅野, 美代子; マーコ, ユー K.W.

    2007-01-01

    This paper introduces the hybrid approach of neural networks and linear regression model proposed by Asano and Tsubaki (2003). Neural networks are often credited with its superiority in data consistency whereas the linear regression model provides simple interpretation of the data enabling researchers to verify their hypotheses. The hybrid approach aims at combing the strengths of these two well-established statistical methods. A step-by-step procedure for performing the hybrid approach is pr...

  15. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew

    2017-12-06

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  16. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew; McCabe, Matthew

    2017-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  17. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    Science.gov (United States)

    Houborg, Rasmus; McCabe, Matthew F.

    2018-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory 'predictor' variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association with

  18. The role of information systems in management decision making-an theoretical approach

    Directory of Open Access Journals (Sweden)

    PhD. Associate Professor Department of Management & Informatics Mihane Berisha-Namani

    2010-12-01

    Full Text Available In modern conditions of globalisation and development of information technology, information processing activities have come to be seen as essential to successful of businesses and organizations. Information has become essential to make decisions and crucial asset in organisations, whereas information systems is technology required for information processing. The application of information systems technology in business and organisations has opened up new possibilities for running and managing organisations, as well as has improved management decision making. The purpose of this paper is to give an understanding of the role that information systems have in management decision making and to discuss the possibilities how managers of organisations can make best use of information systems. The paper starts with identifying the functions of management and managerial roles and continue with information systems usage in three levels of decision making. It specifically addresses the way how information systems can help managers reduce uncertainty in decision making and includes some important implications of information systems usage for managers. Thus, this study provide a framework of effective use of information systems generally and offers an alternative approach to investigate the impact that information systems technology have in management decision making specifically

  19. A multicriteria decision making approach applied to improving maintenance policies in healthcare organizations.

    Science.gov (United States)

    Carnero, María Carmen; Gómez, Andrés

    2016-04-23

    Healthcare organizations have far greater maintenance needs for their medical equipment than other organization, as many are used directly with patients. However, the literature on asset management in healthcare organizations is very limited. The aim of this research is to provide more rational application of maintenance policies, leading to an increase in quality of care. This article describes a multicriteria decision-making approach which integrates Markov chains with the multicriteria Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH), to facilitate the best choice of combination of maintenance policies by using the judgements of a multi-disciplinary decision group. The proposed approach takes into account the level of acceptance that a given alternative would have among professionals. It also takes into account criteria related to cost, quality of care and impact of care cover. This multicriteria approach is applied to four dialysis subsystems: patients infected with hepatitis C, infected with hepatitis B, acute and chronic; in all cases, the maintenance strategy obtained consists of applying corrective and preventive maintenance plus two reserve machines. The added value in decision-making practices from this research comes from: (i) integrating the use of Markov chains to obtain the alternatives to be assessed by a multicriteria methodology; (ii) proposing the use of MACBETH to make rational decisions on asset management in healthcare organizations; (iii) applying the multicriteria approach to select a set or combination of maintenance policies in four dialysis subsystems of a health care organization. In the multicriteria decision making approach proposed, economic criteria have been used, related to the quality of care which is desired for patients (availability), and the acceptance that each alternative would have considering the maintenance and healthcare resources which exist in the organization, with the inclusion of a

  20. The feminist approach in the decision-making process for treatment of women with breast cancer.

    Science.gov (United States)

    Szumacher, Ewa

    2006-09-01

    The principal aim of this review was to investigate a feminist approach to the decision-making process for women with breast cancer. Empirical research into patient preferences for being informed about and participating in healthcare decisions has some limitations because it is mostly quantitative and designed within the dominant medical culture. Indigenous medical knowledge and alternative medical treatments are not widely accepted because of the lack of confirmed efficacy of such treatments in evidence-based literature. While discussing their treatment options with oncologists, women with breast cancer frequently express many concerns regarding treatment side effects, and sometimes decline conventional treatment when the risks are too high. A search of all relevant literary sources, including Pub-Med, ERIC, Medline, and the Ontario Institute for Studies in Education at the University of Toronto was conducted. The key words for selection of the articles were "feminism," "decision-making," "patients preferences for treatment," and "breast cancer." Fifty-one literary sources were selected. The review was divided into the following themes: (1) limitations of the patient decision-making process in conventional medicine; (2) participation of native North American patients in healthcare decisions; (3) towards a feminist approach to breast cancer; and (4) towards a feminist theory of breast cancer. This article discusses the importance of a feminist approach to the decision-making process for treatment of patients with breast cancer. As the literature suggests, the needs of minority patients are not completely fulfilled in Western medical culture. Introducing feminist theory into evidence-based medicine will help patients to be better informed about treatment choices and will assist them to select treatment according to their own beliefs and values.

  1. An approach for identification of unknown viruses using sequencing-by-hybridization.

    Science.gov (United States)

    Katoski, Sarah E; Meyer, Hermann; Ibrahim, Sofi

    2015-09-01

    Accurate identification of biological threat agents, especially RNA viruses, in clinical or environmental samples can be challenging because the concentration of viral genomic material in a given sample is usually low, viral genomic RNA is liable to degradation, and RNA viruses are extremely diverse. A two-tiered approach was used for initial identification, then full genomic characterization of 199 RNA viruses belonging to virus families Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, and Togaviridae. A Sequencing-by-hybridization (SBH) microarray was used to tentatively identify a viral pathogen then, the identity is confirmed by guided next-generation sequencing (NGS). After optimization and evaluation of the SBH and NGS methodologies with various virus species and strains, the approach was used to test the ability to identify viruses in blinded samples. The SBH correctly identified two Ebola viruses in the blinded samples within 24 hr, and by using guided amplicon sequencing with 454 GS FLX, the identities of the viruses in both samples were confirmed. SBH provides at relatively low-cost screening of biological samples against a panel of viral pathogens that can be custom-designed on a microarray. Once the identity of virus is deduced from the highest hybridization signal on the SBH microarray, guided (amplicon) NGS sequencing can be used not only to confirm the identity of the virus but also to provide further information about the strain or isolate, including a potential genetic manipulation. This approach can be useful in situations where natural or deliberate biological threat incidents might occur and a rapid response is required. © 2015 Wiley Periodicals, Inc.

  2. Comparing Approaches for the Integration of Stakeholder Perspectives in Environmental Decision Making

    Directory of Open Access Journals (Sweden)

    Anna Scolobig

    2016-11-01

    Full Text Available Including stakeholder perspectives in environmental decision making is in many countries a legal requirement and is widely seen as beneficial as it can help increase decision legitimacy, likelihood of implementation, and quality of the outcome. Whereas the theoretical literature on stakeholder engagement is large, less attention has been devoted to comparing and discussing different methodological approaches. Here, we compare three approaches—multi-criteria analysis, plural rationality theory, and scenario construction—that include stakeholders’ perspectives in environmental decision making. We find differences between the approaches concerning the assumptions about stakeholder rationality and whether experts and/or stakeholders are in charge of framing the problem. Further differences concern the type of data input from stakeholders and how it is used by the experts, as well as the role of stakeholders and whether they are involved early—already for identifying options—or later in the process, for evaluating or ranking alternatives analyzed by the experts. The choice of approach thus predetermines the type and depth of stakeholder engagement. No approach is “better” than another, but they are suited for different problems and research aims: the choice of the approach, however, has a large impact on the results.

  3. Utility and impact of early t(15;17) identification by Fluorescence In Situ Hybridization (FISH) in clinical decision making for patients in Acute Promyelocytic Leukemia (APL).

    Science.gov (United States)

    Kolhe, R; Mangaonkar, A; Mansour, J; Clemmons, A; Shaw, J; Dupont, B; Walczak, L; Mondal, A; Rojiani, A; Jillella, A; Kota, V

    2015-08-01

    Acute Promyelocytic Leukemia (APL) is a curable malignancy with studies showing above 90% survival. However, population-based studies looking at survival suggest that approximately 30% of patients with APL die during induction. Early demonstration of t(15;17) will lead to accurate decision making regarding treatment. The aim of this project was to validate earlier time frames for the Abbott Molecular Vysis LSI promyelocytic leukemia (PML)/ retinoic acid receptor alpha (RARA) fluorescence in situ hybridization (FISH) probe (ASR 6-16 h). Twenty patients (15 APL cases and five non-APL cases) were selected for validating various hybridization times for the FISH probe. Expected normal signal pattern was two red and two green signals (2R2G), and the most common expected abnormal signal pattern was two fusion (yellow) signals, one red and one green (2F1R1G) and/or one fusion, one red and one green (1F1R1G). The specificity of the probe ranged from 84% at 2 h, 86% at 4 h, 84% at 6 h, and 87% for overnight hybridization. The sensitivity increased from 79% at 2 h, 80% at 4 h, 81% at 6 h to 87% for overnight hybridization. Based on the validation studies, we recommend reading of FISH results at the 4-h incubation mark for a preliminary diagnosis and confirmation with overnight hybridization. © 2015 John Wiley & Sons Ltd.

  4. Decision-Making and Problem-Solving Approaches in Pharmacy Education.

    Science.gov (United States)

    Martin, Lindsay C; Donohoe, Krista L; Holdford, David A

    2016-04-25

    Domain 3 of the Center for the Advancement of Pharmacy Education (CAPE) 2013 Educational Outcomes recommends that pharmacy school curricula prepare students to be better problem solvers, but are silent on the type of problems they should be prepared to solve. We identified five basic approaches to problem solving in the curriculum at a pharmacy school: clinical, ethical, managerial, economic, and legal. These approaches were compared to determine a generic process that could be applied to all pharmacy decisions. Although there were similarities in the approaches, generic problem solving processes may not work for all problems. Successful problem solving requires identification of the problems faced and application of the right approach to the situation. We also advocate that the CAPE Outcomes make explicit the importance of different approaches to problem solving. Future pharmacists will need multiple approaches to problem solving to adapt to the complexity of health care.

  5. The Importance of Being Hybrid for Spatial Epidemic Models:A Multi-Scale Approach

    Directory of Open Access Journals (Sweden)

    Arnaud Banos

    2015-11-01

    Full Text Available This work addresses the spread of a disease within an urban system, definedas a network of interconnected cities. The first step consists of comparing two differentapproaches: a macroscopic one, based on a system of coupled Ordinary DifferentialEquations (ODE Susceptible-Infected-Recovered (SIR systems exploiting populations onnodes and flows on edges (so-called metapopulational model, and a hybrid one, couplingODE SIR systems on nodes and agents traveling on edges. Under homogeneous conditions(mean field approximation, this comparison leads to similar results on the outputs on whichwe focus (the maximum intensity of the epidemic, its duration and the time of the epidemicpeak. However, when it comes to setting up epidemic control strategies, results rapidlydiverge between the two approaches, and it appears that the full macroscopic model is notcompletely adapted to these questions. In this paper, we focus on some control strategies,which are quarantine, avoidance and risk culture, to explore the differences, advantages anddisadvantages of the two models and discuss the importance of being hybrid when modelingand simulating epidemic spread at the level of a whole urban system.

  6. Modular approach for conversion to the ion-hybrid wave and α gyroresonance

    International Nuclear Information System (INIS)

    Kaufman, A.N.; Morehead, J.J.; Brizard, A.J.; Tracy, E.R.

    1997-01-01

    Linear conversion of an incoming magnetosonic wave (a.k.a. fast or compressional wave) to an ion-hybrid wave can be considered as a 3-step process in ray phase space. This is demonstrated by casting the cold-fluid model into the Friedland-Kaufman normal form for linear mode conversion. First, the incoming magnetosonic ray (MSR) converts a fraction of its action to an intermediate ion-hybrid ray (IHR), with the transmitted ray proceeding through the conversion layer. The IHR propagates in k-space to a second conversion point, where it converts in turn a fraction of its action into a reflected MSR, with the remainder of the its action constituting the converted IHR. The modular approach gives exact agreement with the more standard Budden formulation for the transmission, reflection and conversion coefficients, but has the important advantage of exposing the intermediate IHR. The existence of the intermediate IHR has important physical consequences as it can resonate with α particles. We estimate the time-integrated damping coefficient between the two conversions and show that ∫γdt is of order -100, thus the IH wave is completely annihilated between conversions and transfers its energy to the α close-quote s. This suggests that proposals to use the IH mode for current drive or DT heating are likely to fail in the presence of fusion α close-quote s. copyright 1997 American Institute of Physics

  7. A hybrid approach to automatic de-identification of psychiatric notes.

    Science.gov (United States)

    Lee, Hee-Jin; Wu, Yonghui; Zhang, Yaoyun; Xu, Jun; Xu, Hua; Roberts, Kirk

    2017-11-01

    De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing system for automatic de-identification of psychiatric notes, which was designed to participate in the 2016 CEGS N-GRID shared task Track 1. The system has a hybrid structure that combines machine leaning techniques and rule-based approaches. The rule-based components exploit the structure of the psychiatric notes as well as characteristic surface patterns of PHI mentions. The machine learning components utilize supervised learning with rich features. In addition, the system performance was boosted with integration of additional data to the training set through domain adaptation. The hybrid system showed overall micro-averaged F-score 90.74 on the test set, second-best among all the participants of the CEGS N-GRID task. Copyright © 2017. Published by Elsevier Inc.

  8. Aeroacoustic analysis of the human phonation process based on a hybrid acoustic PIV approach

    Science.gov (United States)

    Lodermeyer, Alexander; Tautz, Matthias; Becker, Stefan; Döllinger, Michael; Birk, Veronika; Kniesburges, Stefan

    2018-01-01

    The detailed analysis of sound generation in human phonation is severely limited as the accessibility to the laryngeal flow region is highly restricted. Consequently, the physical basis of the underlying fluid-structure-acoustic interaction that describes the primary mechanism of sound production is not yet fully understood. Therefore, we propose the implementation of a hybrid acoustic PIV procedure to evaluate aeroacoustic sound generation during voice production within a synthetic larynx model. Focusing on the flow field downstream of synthetic, aerodynamically driven vocal folds, we calculated acoustic source terms based on the velocity fields obtained by time-resolved high-speed PIV applied to the mid-coronal plane. The radiation of these sources into the acoustic far field was numerically simulated and the resulting acoustic pressure was finally compared with experimental microphone measurements. We identified the tonal sound to be generated downstream in a small region close to the vocal folds. The simulation of the sound propagation underestimated the tonal components, whereas the broadband sound was well reproduced. Our results demonstrate the feasibility to locate aeroacoustic sound sources inside a synthetic larynx using a hybrid acoustic PIV approach. Although the technique employs a 2D-limited flow field, it accurately reproduces the basic characteristics of the aeroacoustic field in our larynx model. In future studies, not only the aeroacoustic mechanisms of normal phonation will be assessable, but also the sound generation of voice disorders can be investigated more profoundly.

  9. Integrated assessment of the global warming problem: A decision-analytical approach

    International Nuclear Information System (INIS)

    Van Lenthe, J.; Hendrickx, L.; Vlek, C.A.J.

    1994-12-01

    The multi-disciplinary character of the global warming problem asks for an integrated assessment approach for ordering and combining the various physical, ecological, economical, and sociological results. The Netherlands initiated their own National Research Program (NRP) on Global Air Pollution and Climate Change (NRP). The first phase (NRP-1) identified the integration theme as one of five central research themes. The second phase (NRP-2) shows a growing concern for integrated assessment issues. The current two-year research project 'Characterizing the risks: a comparative analysis of the risks of global warming and of relevant policy options, which started in September 1993, comes under the integrated assessment part of the Dutch NRP. The first part of the interim report describes the search for an integrated assessment methodology. It starts with emphasizing the need for integrated assessment at a relatively high level of aggregation and from a policy point of view. The conclusion will be that a decision-analytical approach might fit the purpose of a policy-oriented integrated modeling of the global warming problem. The discussion proceeds with an account on decision analysis and its explicit incorporation and analysis of uncertainty. Then influence diagrams, a relatively recent development in decision analysis, are introduced as a useful decision-analytical approach for integrated assessment. Finally, a software environment for creating and analyzing complex influence diagram models is discussed. The second part of the interim report provides a first, provisional integrated modeling of the global warming problem, emphasizing on the illustration of the decision-analytical approach. Major problem elements are identified and an initial problem structure is developed. The problem structure is described in terms of hierarchical influence diagrams. At some places the qualitative structure is filled with quantitative data

  10. Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

    Directory of Open Access Journals (Sweden)

    Ahmed Hussein

    2018-01-01

    Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

  11. Informed Consent Obtainment, Malpractice Litigation, and the Potential Role of Shared Decision Making Approaches

    DEFF Research Database (Denmark)

    Birkeland, Søren

    2015-01-01

    of the iceberg as lack of patient ‘ownership’ of the DM is not always exposed or may be explicated otherwise (alleged substandard behavior or surgery etc). SDM approaches possibly may sometimes prevent IC duty breaches, assist documenting the DM process, and reduce litigation occurrence.......Internationally, there is increasing recognition of Shared Decision Making (SDM) and Decision Aids (DAs) as measures to increase patient involvement in – and satisfaction with - decision making (DM), improve health care communication, and address bioethical autonomy principles and informed consent...... search term ‘consent’; 15th May 2015). Among 3291 lawsuits, 229 with explicit IC judgments were found. They mostly concerned the hospital sector (179; 78%) and commonly involved surgery (69), gyn/obstetrics (33), and gen. medicine (20; incl, eg, cardiology). 21 affected minor patients and 36 were cancer...

  12. Numerical Prediction of Combustion-induced Noise using a hybrid LES/CAA approach

    Science.gov (United States)

    Ihme, Matthias; Pitsch, Heinz; Kaltenbacher, Manfred

    2006-11-01

    Noise generation in technical devices is an increasingly important problem. Jet engines in particular produce sound levels that not only are a nuisance but may also impair hearing. The noise emitted by such engines is generated by different sources such as jet exhaust, fans or turbines, and combustion. Whereas the former acoustic mechanisms are reasonably well understood, combustion-generated noise is not. A methodology for the prediction of combustion-generated noise is developed. In this hybrid approach unsteady acoustic source terms are obtained from an LES and the propagation of pressure perturbations are obtained using acoustic analogies. Lighthill's acoustic analogy and a non-linear wave equation, accounting for variable speed of sound, have been employed. Both models are applied to an open diffusion flame. The effects on the far field pressure and directivity due to the variation of speed of sound are analyzed. Results for the sound pressure level will be compared with experimental data.

  13. Optimum design of brake friction material using hybrid entropy-GRA approach

    Directory of Open Access Journals (Sweden)

    Kumar Naresh

    2016-01-01

    Full Text Available The effect of Kevlar and natural fibres on the performance of brake friction materials was evaluated. Four friction material specimens were developed by varying the proportion of Kevlar and natural fibres. Two developed composite contained 5-10 wt.% of Kevlar fibre while in the other two the Kevlar fibre was replaced with same amount of natural fibre. SAE J661 protocol was used for the assessment of the tribological properties on a Chase testing machine. Result shows that the specimens containing Kevlar fibres shows higher friction and wear performance, whereas Kevlar replacement with natural fibre resulted in improved fade, recovery and friction fluctuations. Further hybrid entropy-GRA (grey relation analysis approach was applied to select the optimal friction materials using various performance defining attributes (PDA including friction, wear, fade, recovery, friction fluctuations and cost. The friction materials with 10 wt% of natural fibre exhibited the best overall quality.

  14. A Model Predictive Control Approach for Fuel Economy Improvement of a Series Hydraulic Hybrid Vehicle

    Directory of Open Access Journals (Sweden)

    Tri-Vien Vu

    2014-10-01

    Full Text Available This study applied a model predictive control (MPC framework to solve the cruising control problem of a series hydraulic hybrid vehicle (SHHV. The controller not only regulates vehicle velocity, but also engine torque, engine speed, and accumulator pressure to their corresponding reference values. At each time step, a quadratic programming problem is solved within a predictive horizon to obtain the optimal control inputs. The objective is to minimize the output error. This approach ensures that the components operate at high efficiency thereby improving the total efficiency of the system. The proposed SHHV control system was evaluated under urban and highway driving conditions. By handling constraints and input-output interactions, the MPC-based control system ensures that the system operates safely and efficiently. The fuel economy of the proposed control scheme shows a noticeable improvement in comparison with the PID-based system, in which three Proportional-Integral-Derivative (PID controllers are used for cruising control.

  15. A Hybrid dasymetric and machine learning approach to high-resolution residential electricity consumption modeling

    Energy Technology Data Exchange (ETDEWEB)

    Morton, April M [ORNL; Nagle, Nicholas N [ORNL; Piburn, Jesse O [ORNL; Stewart, Robert N [ORNL; McManamay, Ryan A [ORNL

    2017-01-01

    As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for detailed information regarding residential energy consumption patterns has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy consumption, the majority of techniques are highly dependent on region-specific data sources and often require building- or dwelling-level details that are not publicly available for many regions in the United States. Furthermore, many existing methods do not account for errors in input data sources and may not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more general hybrid approach to high-resolution residential electricity consumption modeling by merging a dasymetric model with a complementary machine learning algorithm. The method s flexible data requirement and statistical framework ensure that the model both is applicable to a wide range of regions and considers errors in input data sources.

  16. HYBRID APPROACHES TO THE FORMALISATION OF EXPERT KNOWLEDGE CONCERNING TEMPORAL REGULARITIES IN THE TIME SERIES GROUP OF A SYSTEM MONITORING DATABASE

    Directory of Open Access Journals (Sweden)

    E. S. Staricov

    2016-01-01

    Full Text Available Objectives. The presented research problem concerns data regularities for an unspecified time series based on an approach to the expert formalisation of knowledge integrated into a decision-making mechanism. Method. A context-free grammar, consisting of a modification of universal temporal grammar, is used to describe regularities. Using the rules of the developed grammar, an expert can describe patterns in the group of time series. A multi-dimensional matrix pattern of the behaviour of a group of time series is used in a real-time decision-making regime in the expert system to implements a universal approach to the description of the dynamics of these changes in the expert system. The multidimensional matrix pattern is specifically intended for decision-making in an expert system; the modified temporal grammar is used to identify patterns in the data. Results. It is proposed to use the temporal relations of the series and fix observation values in the time interval as ―From-To‖, ―Before‖, ―After‖, ―Simultaneously‖ and ―Duration‖. A syntactically oriented converter of descriptions is developed. A schema for the creation and application of matrix patterns in expert systems is drawn up. Conclusion. The advantage of the implementation of the proposed hybrid approaches consists in a reduction of the time taken for identifying temporal patterns and an automation of the matrix pattern of the decision-making system based on expert descriptions verified using live data derived from relationships in the monitoring data. 

  17. A Dynamic Intelligent Decision Approach to Dependency Modeling of Project Tasks in Complex Engineering System Optimization

    Directory of Open Access Journals (Sweden)

    Tinggui Chen

    2013-01-01

    Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.

  18. Dual-acting of Hybrid Compounds - A New Dawn in the Discovery of Multi-target Drugs: Lead Generation Approaches.

    Science.gov (United States)

    Abdolmaleki, Azizeh; Ghasemi, Jahan B

    2017-01-01

    Finding high quality beginning compounds is a critical job at the start of the lead generation stage for multi-target drug discovery (MTDD). Designing hybrid compounds as selective multitarget chemical entity is a challenge, opportunity, and new idea to better act against specific multiple targets. One hybrid molecule is formed by two (or more) pharmacophore group's participation. So, these new compounds often exhibit two or more activities going about as multi-target drugs (mtdrugs) and may have superior safety or efficacy. Application of integrating a range of information and sophisticated new in silico, bioinformatics, structural biology, pharmacogenomics methods may be useful to discover/design, and synthesis of the new hybrid molecules. In this regard, many rational and screening approaches have followed by medicinal chemists for the lead generation in MTDD. Here, we review some popular lead generation approaches that have been used for designing multiple ligands (DMLs). This paper focuses on dual- acting chemical entities that incorporate a part of two drugs or bioactive compounds to compose hybrid molecules. Also, it presents some of key concepts and limitations/strengths of lead generation methods by comparing combination framework method with screening approaches. Besides, a number of examples to represent applications of hybrid molecules in the drug discovery are included. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  19. Improved Wetland Classification Using Eight-Band High Resolution Satellite Imagery and a Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Charles R. Lane

    2014-12-01

    Full Text Available Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of wetland maps derived with moderate resolution imagery and traditional techniques have been limited and often unsatisfactory. We explored and evaluated the utility of a newly launched high-resolution, eight-band satellite system (Worldview-2; WV2 for identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta of Lake Baikal, Russia, using a hybrid approach and a novel application of Indicator Species Analysis (ISA. We achieved an overall classification accuracy of 86.5% (Kappa coefficient: 0.85 for 22 classes of aquatic and wetland habitats and found that additional metrics, such as the Normalized Difference Vegetation Index and image texture, were valuable for improving the overall classification accuracy and particularly for discriminating among certain habitat classes. Our analysis demonstrated that including WV2’s four spectral bands from parts of the spectrum less commonly used in remote sensing analyses, along with the more traditional bandwidths, contributed to the increase in the overall classification accuracy by ~4% overall, but with considerable increases in our ability to discriminate certain communities. The coastal band improved differentiating open water and aquatic (i.e., vegetated habitats, and the yellow, red-edge, and near-infrared 2 bands improved discrimination among different vegetated aquatic and terrestrial habitats. The use of ISA provided statistical rigor in developing associations between spectral classes and field-based data. Our analyses demonstrated the utility of a hybrid approach and the benefit of additional bands and metrics in providing the first spatially explicit mapping of a large and heterogeneous wetland system.

  20. Theoretical Approaches in the Context of Spatial Planning Decisions and the Relation with Urban Sustainability

    Science.gov (United States)

    Kumlu, Kadriye Burcu Yavuz; Tüdeş, Şule

    2017-10-01

    The sustainability agenda has maintained its importance since the days, when the production system took its capitalist form, as well as the population in the urban areas started to rise. Increasing number of both goods and the people have caused the degradation of the certain systems, which generate the urban areas. These systems could mainly be classified as social, environmental, physical and economical systems. Today, urban areas still have difficulty to protect those systems, due to the significant demand of the population. Therefore, studies related with the sustainable issues are significant in the sense of continuity of the urban systems. Therefore, in this paper, those studies in the context of the effects of physical decisions taken in the spatial planning process on urban sustainability, will be examined. The components of the physical decisions are limited to land use, density and design. Land use decisions will be examined in the context of mixed land use. On the other hand, decisions related with density will be analyzed in the sense of population density and floor area ratio (FAR). Besides, design decisions will be examined, by linking them with neighborhood design criteria. Additionally, the term of urban sustainability will only be limited to its social and environmental contexts in this study. Briefly stated, studies in the sustainable literature concerned with the effects of land use, density and design decisions taken in the spatial planning process on the social and environmental sustainability will be examined in this paper. After the compilation and the analyze of those studies, a theoretical approach will be proposed to determine social and environmental sustainability in the context of land use, density and design decisions, taken in the spatial planning process.

  1. A risk-based approach to flood management decisions in a nonstationary world

    Science.gov (United States)

    Rosner, Ana; Vogel, Richard M.; Kirshen, Paul H.

    2014-03-01

    Traditional approaches to flood management in a nonstationary world begin with a null hypothesis test of "no trend" and its likelihood, with little or no attention given to the likelihood that we might ignore a trend if it really existed. Concluding a trend exists when it does not, or rejecting a trend when it exists are known as type I and type II errors, respectively. Decision-makers are poorly served by statistical and/or decision methods that do not carefully consider both over- and under-preparation errors, respectively. Similarly, little attention is given to how to integrate uncertainty in our ability to detect trends into a flood management decision context. We show how trend hypothesis test results can be combined with an adaptation's infrastructure costs and damages avoided to provide a rational decision approach in a nonstationary world. The criterion of expected regret is shown to be a useful metric that integrates the statistical, economic, and hydrological aspects of the flood management problem in a nonstationary world.

  2. Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

    Science.gov (United States)

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

  3. A hybrid wavelet transform based short-term wind speed forecasting approach.

    Science.gov (United States)

    Wang, Jujie

    2014-01-01

    It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China's wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

  4. A HYBRID GENETIC ALGORITHM-NEURAL NETWORK APPROACH FOR PRICING CORES AND REMANUFACTURED CORES

    Directory of Open Access Journals (Sweden)

    M. Seidi

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT:Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. Remanufacturing is an industrial process that makes used products reusable. One of the important aspects in both reverse logistics and remanufacturing is the pricing of returned and remanufactured products (called cores. In this paper, we focus on pricing the cores and remanufactured cores. First we present a mathematical model for this purpose. Since this model does not satisfy our requirements, we propose a simulation optimisation approach. This approach consists of a hybrid genetic algorithm based on a neural network employed as the fitness function. We use automata learning theory to obtain the learning rate required for training the neural network. Numerical results demonstrate that the optimal value of the acquisition price of cores and price of remanufactured cores is obtained by this approach.

    AFRIKAANSE OPSOMMING: Volhoubaarheid het ‘n belangrike saak geword in die meeste ekonomieë, wat verskeie maatskappye genoop het om produkherwinning en omgekeerde logistiek te onder oë te neem. Hervervaardiging is ‘n industriële proses wat gebruikte produkte weer bruikbaar maak. Een van die belangrike aspekte in beide omgekeerde logistiek en hervervaardiging is die prysbepaling van herwinne en hervervaardigde produkte. Hierdie artikel fokus op die prysbepalingsaspekte by wyse van ‘n wiskundige model.

  5. A Hybrid Multi-Criteria Decision Model for Technological Innovation Capability Assessment: Research on Thai Automotive Parts Firms

    Directory of Open Access Journals (Sweden)

    Sumrit Detcharat

    2013-01-01

    Full Text Available The efficient appraisal of technological innovation capabilities (TICs of enterprises is an important factor to enhance competitiveness. This study aims to evaluate and rank TICs evaluation criteria in order to provide a practical insight of systematic analysis by gathering the qualified experts’ opinions combined with three methods of multi-criteria decision making approach. Firstly, Fuzzy Delphi method is used to screen TICs evaluation criteria from the recent published researches. Secondly, the Analytic Hierarchy Process is utilized to compute the relative important weights. Lastly, the VIKOR method is used to rank the enterprises based on TICs evaluation criteria. An empirical study is applied for Thai automotive parts firms to illustrate the proposed methods. This study found that the interaction between criteria is essential and influences TICs; furthermore, this ranking development of TICs assessment is also one of key management tools to simply facilitate and offer a new mindset for managements of other related industries.

  6. A Multicriteria Decision Making Approach for Estimating the Number of Clusters in a Data Set

    Science.gov (United States)

    Peng, Yi; Zhang, Yong; Kou, Gang; Shi, Yong

    2012-01-01

    Determining the number of clusters in a data set is an essential yet difficult step in cluster analysis. Since this task involves more than one criterion, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper proposes a multiple criteria decision making (MCDM)-based approach to estimate the number of clusters for a given data set. In this approach, MCDM methods consider different numbers of clusters as alternatives and the outputs of any clustering algorithm on validity measures as criteria. The proposed method is examined by an experimental study using three MCDM methods, the well-known clustering algorithm–k-means, ten relative measures, and fifteen public-domain UCI machine learning data sets. The results show that MCDM methods work fairly well in estimating the number of clusters in the data and outperform the ten relative measures considered in the study. PMID:22870181

  7. Multi criteria decision making approaches for green supplier evaluation and selection

    DEFF Research Database (Denmark)

    Govindan, Kannan; Rajendran, S.; Sarkis, J.

    2015-01-01

    A large and growing body of literature to supplier evaluation and selection exists. Literature on green supplier evaluation that considers environmental factors are relatively limited. Recently, in supply chain management decision making, approaches for evaluating green supplier performance have ...... us to identify improvements for green supplier selection process and possible future directions.......A large and growing body of literature to supplier evaluation and selection exists. Literature on green supplier evaluation that considers environmental factors are relatively limited. Recently, in supply chain management decision making, approaches for evaluating green supplier performance have...... used both qualitative and quantitative environmental data. Given this evolving research field, the goal and purpose of this paper is to analyze research in international scientific journals and international conference proceedings that focus on green supplier selection. We propose the following...

  8. Infrared exploration of the architectural heritage: from passive infrared thermography to hybrid infrared thermography (HIRT approach

    Directory of Open Access Journals (Sweden)

    Sfarra, S.

    2016-09-01

    Full Text Available Up to now, infrared thermographic approaches have been considered either passive or active. In the latter case, the heat flux is historically attributed to a non-natural heat source. The use of the sun has recently been incorporated into the active approach thanks to multi-temporal inspections. In this paper, an innovative hybrid thermographic (HIRT approach is illustrated. It combines both the time component and the solar source to obtain quantitative information such as the defect depth. Thermograms were obtained by inspecting the facade of the Santa Maria Collemaggio church (L’Aquila, Italy, whereas quantitative results related to the sub-superficial discontinuities were obtained thanks to the use of advanced techniques. Experimental results linked to passive approach (i.e., the mosaicking procedure of the thermograms performed by selecting a set of historic churches are also included in order to explain, when and where, the hybrid procedure should be used.Hasta la fecha, los enfoques sobre la termografía infrarroja han sido considerados, o pasivos, o activos. En este último caso, el flujo de calor se obtiene a través de una fuente de calor no natural. El uso de energía solar ha sido recientemente incorporado al enfoque activo gracias a los estudios multitemporales. En este trabajo, se ilustra un enfoque innovador de la termografía híbrida (HIRT. Se combina tanto el componente de tiempo y la fuente de energía solar para recuperar la información cuantitativa así como la profundidad del defecto. Las imágenes térmicas se obtuvieron mediante el análisis de la fachada de la Iglesia de Santa María Collemaggio (L’Aquila, Italia, mientras que los resultados cuantitativos inherentes a las discontinuidades sub-superficiales se obtuvieron gracias al uso de otras técnicas avanzadas. Los resultados experimentales vinculados al enfoque pasivo (es decir, el proceso de mosaico de las imágenes térmicas derivan de un conjunto de Iglesias

  9. A reactive decision-making approach to reduce instability in a Master Production Schedule

    OpenAIRE

    Herrera , Carlos; Belmokhtar Berraf , Sana; Thomas , André; Parada , Victor

    2016-01-01

    International audience; One of the primary factors that impact the master production scheduling performance is demand fluctuation, which leads to frequently updated decisions, thereby causing instability. Consequently, global cost deteriorates, and productivity decreases. A reactive approach based on parametric mixed-integer programming is proposed that aims to provide a set of plans such that a compromise between production cost and production stability is ensured. Several stability measures...

  10. Modified approach to PROMETHEE for multi-criteria decision-making

    Directory of Open Access Journals (Sweden)

    Zoran Nesic

    2013-10-01

    Full Text Available This paper presents a modification of PROMETHEE for multi -criteria decision- making. The authors of PROMETHEE have defined six generalised preference functions in order to express their preferences for particular criteria. A modified approach to PROMETHEE is based on the Universal preference function which replaces the six proposed functions and generates an unlimited number of other preference functions. By applying this method, we can express all the complexity of selecting preference functions in the problems of optimisation by PROMETHEE.

  11. Integrated assessment of the global warming problem. A decision-analytical approach

    International Nuclear Information System (INIS)

    Van Lenthe, J.; Hendrickx, L.; Vlek, C.A.J.

    1995-01-01

    The project on the title subject aims at developing a policy-oriented methodology for the integrated assessment of the global warming problem. Decision analysis in general and influence diagrams in particular appear to constitute an appropriate integrated assessment methodology. The influence-diagram approach is illustrated at a preliminary integrated modeling of the global warming problem. In next stages of the research, attention will be shifted from the methodology of integrated assessment to the contents of integrated models. 4 figs., 5 refs

  12. Incorporating historical information in biosimilar trials: Challenges and a hybrid Bayesian-frequentist approach.

    Science.gov (United States)

    Mielke, Johanna; Schmidli, Heinz; Jones, Byron

    2018-05-01

    For the approval of biosimilars, it is, in most cases, necessary to conduct large Phase III clinical trials in patients to convince the regulatory authorities that the product is comparable in terms of efficacy and safety to the originator product. As the originator product has already been studied in several trials beforehand, it seems natural to include this historical information into the showing of equivalent efficacy. Since all studies for the regulatory approval of biosimilars are confirmatory studies, it is required that the statistical approach has reasonable frequentist properties, most importantly, that the Type I error rate is controlled-at least in all scenarios that are realistic in practice. However, it is well known that the incorporation of historical information can lead to an inflation of the Type I error rate in the case of a conflict between the distribution of the historical data and the distribution of the trial data. We illustrate this issue and confirm, using the Bayesian robustified meta-analytic-predictive (MAP) approach as an example, that simultaneously controlling the Type I error rate over the complete parameter space and gaining power in comparison to a standard frequentist approach that only considers the data in the new study, is not possible. We propose a hybrid Bayesian-frequentist approach for binary endpoints that controls the Type I error rate in the neighborhood of the center of the prior distribution, while improving the power. We study the properties of this approach in an extensive simulation study and provide a real-world example. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Tackling Complex Emergency Response Solutions Evaluation Problems in Sustainable Development by Fuzzy Group Decision Making Approaches with Considering Decision Hesitancy and Prioritization among Assessing Criteria.

    Science.gov (United States)

    Qi, Xiao-Wen; Zhang, Jun-Ling; Zhao, Shu-Ping; Liang, Chang-Yong

    2017-10-02

    In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE) as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM) approaches to ERSE have been facing simultaneous challenging characteristics of decision hesitancy and prioritization relations among assessing criteria, due to the complexity in practical ERSE problems. Therefore, aiming at the special type of ERSE problems that hold the two characteristics, we investigate effective MCGDM approaches by hiring interval-valued dual hesitant fuzzy set (IVDHFS) to comprehensively depict decision hesitancy. To exploit decision information embedded in prioritization relations among criteria, we firstly define an fuzzy entropy measure for IVDHFS so that its derivative decision models can avoid potential information distortion in models based on classic IVDHFS distance measures with subjective supplementing mechanism; further, based on defined entropy measure, we develop two fundamental prioritized operators for IVDHFS by extending Yager's prioritized operators. Furthermore, on the strength of above methods, we construct two hesitant fuzzy MCGDM approaches to tackle complex scenarios with or without known weights for decision makers, respectively. Finally, case studies have been conducted to show effectiveness and practicality of our proposed approaches.

  14. Tackling Complex Emergency Response Solutions Evaluation Problems in Sustainable Development by Fuzzy Group Decision Making Approaches with Considering Decision Hesitancy and Prioritization among Assessing Criteria

    Directory of Open Access Journals (Sweden)

    Xiao-Wen Qi

    2017-10-01

    Full Text Available In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM approaches to ERSE have been facing simultaneous challenging characteristics of decision hesitancy and prioritization relations among assessing criteria, due to the complexity in practical ERSE problems. Therefore, aiming at the special type of ERSE problems that hold the two characteristics, we investigate effective MCGDM approaches by hiring interval-valued dual hesitant fuzzy set (IVDHFS to comprehensively depict decision hesitancy. To exploit decision information embedded in prioritization relations among criteria, we firstly define an fuzzy entropy measure for IVDHFS so that its derivative decision models can avoid potential information distortion in models based on classic IVDHFS distance measures with subjective supplementing mechanism; further, based on defined entropy measure, we develop two fundamental prioritized operators for IVDHFS by extending Yager’s prioritized operators. Furthermore, on the strength of above methods, we construct two hesitant fuzzy MCGDM approaches to tackle complex scenarios with or without known weights for decision makers, respectively. Finally, case studies have been conducted to show effectiveness and practicality of our proposed approaches.

  15. A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

    Science.gov (United States)

    Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

    2016-09-01

    In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic

  16. Comparative approaches to studying strategy: towards an evolutionary account of primate decision making.

    Science.gov (United States)

    Brosnan, Sarah F; Beran, Michael J; Parrish, Audrey E; Price, Sara A; Wilson, Bart J

    2013-07-18

    How do primates, humans included, deal with novel problems that arise in interactions with other group members? Despite much research regarding how animals and humans solve social problems, few studies have utilized comparable procedures, outcomes, or measures across different species. Thus, it is difficult to piece together the evolution of decision making, including the roots from which human economic decision making emerged. Recently, a comparative body of decision making research has emerged, relying largely on the methodology of experimental economics in order to address these questions in a cross-species fashion. Experimental economics is an ideal method of inquiry for this approach. It is a well-developed method for distilling complex decision making involving multiple conspecifics whose decisions are contingent upon one another into a series of simple decision choices. This allows these decisions to be compared across species and contexts. In particular, our group has used this approach to investigate coordination in New World monkeys, Old World monkeys, and great apes (including humans), using identical methods. We find that in some cases there are remarkable continuities of outcome, as when some pairs in all species solved a coordination game, the Assurance game. On the other hand, we also find that these similarities in outcomes are likely driven by differences in underlying cognitive mechanisms. New World monkeys required exogenous information about their partners' choices in order to solve the task, indicating that they were using a matching strategy. Old World monkeys, on the other hand, solved the task without exogenous cues, leading to investigations into what mechanisms may be underpinning their responses (e.g., reward maximization, strategy formation, etc.). Great apes showed a strong experience effect, with cognitively enriched apes following what appears to be a strategy. Finally, humans were able to solve the task with or without exogenous cues

  17. A multi-criteria optimization and decision-making approach for improvement of food engineering processes

    Directory of Open Access Journals (Sweden)

    Alik Abakarov

    2013-04-01

    Full Text Available The objective of this study was to propose a multi-criteria optimization and decision-making technique to solve food engineering problems. This technique was demonstrated using experimental data obtained on osmotic dehydration of carrot cubes in a sodium chloride solution. The Aggregating Functions Approach, the Adaptive Random Search Algorithm, and the Penalty Functions Approach were used in this study to compute the initial set of non-dominated or Pareto-optimal solutions. Multiple non-linear regression analysis was performed on a set of experimental data in order to obtain particular multi-objective functions (responses, namely water loss, solute gain, rehydration ratio, three different colour criteria of rehydrated product, and sensory evaluation (organoleptic quality. Two multi-criteria decision-making approaches, the Analytic Hierarchy Process (AHP and the Tabular Method (TM, were used simultaneously to choose the best alternative among the set of non-dominated solutions. The multi-criteria optimization and decision-making technique proposed in this study can facilitate the assessment of criteria weights, giving rise to a fairer, more consistent, and adequate final compromised solution or food process. This technique can be useful to food scientists in research and education, as well as to engineers involved in the improvement of a variety of food engineering processes.

  18. Near-Earth object hazardous impact: A Multi-Criteria Decision Making approach.

    Science.gov (United States)

    Sánchez-Lozano, J M; Fernández-Martínez, M

    2016-11-16

    The impact of a near-Earth object (NEO) may release large amounts of energy and cause serious damage. Several NEO hazard studies conducted over the past few years provide forecasts, impact probabilities and assessment ratings, such as the Torino and Palermo scales. These high-risk NEO assessments involve several criteria, including impact energy, mass, and absolute magnitude. The main objective of this paper is to provide the first Multi-Criteria Decision Making (MCDM) approach to classify hazardous NEOs. Our approach applies a combination of two methods from a widely utilized decision making theory. Specifically, the Analytic Hierarchy Process (AHP) methodology is employed to determine the criteria weights, which influence the decision making, and the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is used to obtain a ranking of alternatives (potentially hazardous NEOs). In addition, NEO datasets provided by the NASA Near-Earth Object Program are utilized. This approach allows the classification of NEOs by descending order of their TOPSIS ratio, a single quantity that contains all of the relevant information for each object.

  19. A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

    Science.gov (United States)

    Clark, Renee M; Besterfield-Sacre, Mary E

    2009-03-01

    We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

  20. Frame-based safety analysis approach for decision-based errors

    International Nuclear Information System (INIS)

    Fan, Chin-Feng; Yihb, Swu

    1997-01-01

    A frame-based approach is proposed to analyze decision-based errors made by automatic controllers or human operators due to erroneous reference frames. An integrated framework, Two Frame Model (TFM), is first proposed to model the dynamic interaction between the physical process and the decision-making process. Two important issues, consistency and competing processes, are raised. Consistency between the physical and logic frames makes a TFM-based system work properly. Loss of consistency refers to the failure mode that the logic frame does not accurately reflect the state of the controlled processes. Once such failure occurs, hazards may arise. Among potential hazards, the competing effect between the controller and the controlled process is the most severe one, which may jeopardize a defense-in-depth design. When the logic and physical frames are inconsistent, conventional safety analysis techniques are inadequate. We propose Frame-based Fault Tree; Analysis (FFTA) and Frame-based Event Tree Analysis (FETA) under TFM to deduce the context for decision errors and to separately generate the evolution of the logical frame as opposed to that of the physical frame. This multi-dimensional analysis approach, different from the conventional correctness-centred approach, provides a panoramic view in scenario generation. Case studies using the proposed techniques are also given to demonstrate their usage and feasibility

  1. Resilience thinking and a decision-analytic approach to conservation: strange bedfellows or essential partners?

    Science.gov (United States)

    Johnson, Fred A.; Williams, Byron K.; Nichols, James D.

    2013-01-01

    There has been some tendency to view decision science and resilience theory as opposing approaches, or at least as contending perspectives, for natural resource management. Resilience proponents have been especially critical of optimization in decision science, at least for those cases where it is focused on the aggressive pursuit of efficiency. In general, optimization of resource systems is held to reduce spatial, temporal, or organizational heterogeneity that would otherwise limit efficiency, leading to homogenization of a system and making it less able to cope with unexpected changes or disturbances. For their part, decision analysts have been critical of resilience proponents for not providing much practical advice to decision makers. We believe a key source of tension between resilience thinking and application of decision science is the pursuit of efficiency in the latter (i.e., choosing the “best” management action or strategy option to maximize productivity of one or few resource components), vs. a desire in the former to keep options open (i.e., maintaining and enhancing diversity). It seems obvious, however, that with managed natural systems, there must be a principle by which to guide decision making, which at a minimumallows for a comparison of projected outcomes associated with decision alternatives. This is true even if the primary concern of decision making is the preservation of system resilience. We describe how a careful framing of conservation problems, especially in terms of management objectives and predictive models, can help reduce the purported tension between resiliencethinking and decision analysis. In particular, objective setting in conservation problems needs to be more attuned to the dynamics of ecological systems and to the possibility of deep uncertainties that underlie the risk of unintended, if not irreversible, outcomes. Resilience thinking also leads to the suggestion that model development should focus more on process

  2. Resilience Thinking and a Decision-Analytic Approach to Conservation: Strange Bedfellows or Essential Partners?

    Directory of Open Access Journals (Sweden)

    Fred A. Johnson

    2013-06-01

    Full Text Available There has been some tendency to view decision science and resilience theory as opposing approaches, or at least as contending perspectives, for natural resource management. Resilience proponents have been especially critical of optimization in decision science, at least for those cases where it is focused on the aggressive pursuit of efficiency. In general, optimization of resource systems is held to reduce spatial, temporal, or organizational heterogeneity that would otherwise limit efficiency, leading to homogenization of a system and making it less able to cope with unexpected changes or disturbances. For their part, decision analysts have been critical of resilience proponents for not providing much practical advice to decision makers. We believe a key source of tension between resilience thinking and application of decision science is the pursuit of efficiency in the latter (i.e., choosing the "best" management action or strategy option to maximize productivity of one or few resource components, vs. a desire in the former to keep options open (i.e., maintaining and enhancing diversity. It seems obvious, however, that with managed natural systems, there must be a principle by which to guide decision making, which at a minimum allows for a comparison of projected outcomes associated with decision alternatives. This is true even if the primary concern of decision making is the preservation of system resilience. We describe how a careful framing of conservation problems, especially in terms of management objectives and predictive models, can help reduce the purported tension between resilience thinking and decision analysis. In particular, objective setting in conservation problems needs to be more attuned to the dynamics of ecological systems and to the possibility of deep uncertainties that underlie the risk of unintended, if not irreversible, outcomes. Resilience thinking also leads to the suggestion that model development should focus more

  3. Hybrid Air Quality Modeling Approach for use in the Hear-road Exposures to Urban air pollutant Study(NEXUS)

    Science.gov (United States)

    The paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associa...

  4. A hybrid regional approach to model discharge at multiple sub-basins within the Calapooia Watershed, Oregon, USA

    Science.gov (United States)

    Modeling is a useful tool for quantifying ecosystem services and understanding their temporal dynamics. Here we describe a hybrid regional modeling approach for sub-basins of the Calapooia watershed that incorporates both a precipitation-runoff model and an indexed regression mo...

  5. Comparing Hybrid Learning with Traditional Approaches on Learning the Microsoft Office Power Point 2003 Program in Tertiary Education

    Science.gov (United States)

    Vernadakis, Nikolaos; Antoniou, Panagiotis; Giannousi, Maria; Zetou, Eleni; Kioumourtzoglou, Efthimis

    2011-01-01

    The purpose of this study was to determine the effectiveness of a hybrid learning approach to deliver a computer science course concerning the Microsoft office PowerPoint 2003 program in comparison to delivering the same course content in the form of traditional lectures. A hundred and seventy-two first year university students were randomly…

  6. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.

    Science.gov (United States)

    Murat, Miraemiliana; Chang, Siow-Wee; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

    2017-01-01

    Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99

  7. Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

    Science.gov (United States)

    Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.

    2017-11-01

    The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general

  8. A complex systems approach to planning, optimization and decision making for energy networks

    International Nuclear Information System (INIS)

    Beck, Jessica; Kempener, Ruud; Cohen, Brett; Petrie, Jim

    2008-01-01

    This paper explores a new approach to planning and optimization of energy networks, using a mix of global optimization and agent-based modeling tools. This approach takes account of techno-economic, environmental and social criteria, and engages explicitly with inherent network complexity in terms of the autonomous decision-making capability of individual agents within the network, who may choose not to act as economic rationalists. This is an important consideration from the standpoint of meeting sustainable development goals. The approach attempts to set targets for energy planning, by determining preferred network development pathways through multi-objective optimization. The viability of such plans is then explored through agent-based models. The combined approach is demonstrated for a case study of regional electricity generation in South Africa, with biomass as feedstock

  9. A Computational Approach to Characterizing the Impact of Social Influence on Individuals’ Vaccination Decision Making

    Science.gov (United States)

    Xia, Shang; Liu, Jiming

    2013-01-01

    In modeling individuals vaccination decision making, existing studies have typically used the payoff-based (e.g., game-theoretical) approaches that evaluate the risks and benefits of vaccination. In reality, whether an individual takes vaccine or not is also influenced by the decisions of others, i.e., due to the impact of social influence. In this regard, we present a dual-perspective view on individuals decision making that incorporates both the cost analysis of vaccination and the impact of social influence. In doing so, we consider a group of individuals making their vaccination decisions by both minimizing the associated costs and evaluating the decisions of others. We apply social impact theory (SIT) to characterize the impact of social influence with respect to individuals interaction relationships. By doing so, we propose a novel modeling framework that integrates an extended SIT-based characterization of social influence with a game-theoretical analysis of cost minimization. We consider the scenario of voluntary vaccination against an influenza-like disease through a series of simulations. We investigate the steady state of individuals’ decision making, and thus, assess the impact of social influence by evaluating the coverage of vaccination for infectious diseases control. Our simulation results suggest that individuals high conformity to social influence will increase the vaccination coverage if the cost of vaccination is low, and conversely, will decrease it if the cost is high. Interestingly, if individuals are social followers, the resulting vaccination coverage would converge to a certain level, depending on individuals’ initial level of vaccination willingness rather than the associated costs. We conclude that social influence will have an impact on the control of an infectious disease as they can affect the vaccination coverage. In this respect, our work can provide a means for modeling the impact of social influence as well as for estimating

  10. A computational approach to characterizing the impact of social influence on individuals' vaccination decision making.

    Science.gov (United States)

    Xia, Shang; Liu, Jiming

    2013-01-01

    In modeling individuals vaccination decision making, existing studies have typically used the payoff-based (e.g., game-theoretical) approaches that evaluate the risks and benefits of vaccination. In reality, whether an individual takes vaccine or not is also influenced by the decisions of others, i.e., due to the impact of social influence. In this regard, we present a dual-perspective view on individuals decision making that incorporates both the cost analysis of vaccination and the impact of social influence. In doing so, we consider a group of individuals making their vaccination decisions by both minimizing the associated costs and evaluating the decisions of others. We apply social impact theory (SIT) to characterize the impact of social influence with respect to individuals interaction relationships. By doing so, we propose a novel modeling framework that integrates an extended SIT-based characterization of social influence with a game-theoretical analysis of cost minimization. We consider the scenario of voluntary vaccination against an influenza-like disease through a series of simulations. We investigate the steady state of individuals' decision making, and thus, assess the impact of social influence by evaluating the coverage of vaccination for infectious diseases control. Our simulation results suggest that individuals high conformity to social influence will increase the vaccination coverage if the cost of vaccination is low, and conversely, will decrease it if the cost is high. Interestingly, if individuals are social followers, the resulting vaccination coverage would converge to a certain level, depending on individuals' initial level of vaccination willingness rather than the associated costs. We conclude that social influence will have an impact on the control of an infectious disease as they can affect the vaccination coverage. In this respect, our work can provide a means for modeling the impact of social influence as well as for estimating the

  11. Optimization of approximate decision rules relative to number of misclassifications: Comparison of greedy and dynamic programming approaches

    KAUST Repository

    Amin, Talha

    2013-01-01

    In the paper, we present a comparison of dynamic programming and greedy approaches for construction and optimization of approximate decision rules relative to the number of misclassifications. We use an uncertainty measure that is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. Experimental results with decision tables from the UCI Machine Learning Repository are also presented. © 2013 Springer-Verlag.

  12. Shaping the Future Landscape: Catchment Systems Engineering and the Decision Support Matrix Approach

    Science.gov (United States)

    Hewett, Caspar; Quinn, Paul; Wilkinson, Mark; Wainwright, John

    2017-04-01

    Land degradation is widely recognised as one of the great environmental challenges facing humanity today, much of which is directly associated with human activity. The negative impacts of climate change and of the way in which we have engineered the landscape through, for example, agriculture intensification and deforestation, need to be addressed. However, the answer is not a simple matter of doing the opposite of current practice. Nor is non-intervention a viable option. There is a need to bring together approaches from the natural and social sciences both to understand the issues and to act to solve real problems. We propose combining a Catchment Systems Engineering (CSE) approach that builds on existing approaches such as Natural Water Retention Measures, Green infrastructure and Nature-Based Solutions with a multi-scale framework for decision support that has been successfully applied to diffuse pollution and flood risk management. The CSE philosophy follows that of Earth Systems Engineering and Management, which aims to engineer and manage complex coupled human-natural systems in a highly integrated, rational manner. CSE is multi-disciplinary, and necessarily involves a wide range of subject areas including anthropology, engineering, environmental science, ethics and philosophy. It offers a rational approach which accepts the fact that we need to engineer and act to improve the functioning of the existing catchment entity on which we rely. The decision support framework proposed draws on physical and mathematical modelling; Participatory Action Research; and demonstration sites at which practical interventions are implemented. It is predicated on the need to work with stakeholders to co-produce knowledge that leads to proactive interventions to reverse the land degradation we observe today while sustaining the agriculture humanity needs. The philosophy behind CSE and examples of where it has been applied successfully are presented. The Decision Support Matrix

  13. A hybrid deterministic-probabilistic approach to model the mechanical response of helically arranged hierarchical strands

    Science.gov (United States)

    Fraldi, M.; Perrella, G.; Ciervo, M.; Bosia, F.; Pugno, N. M.

    2017-09-01

    Very recently, a Weibull-based probabilistic strategy has been successfully applied to bundles of wires to determine their overall stress-strain behaviour, also capturing previously unpredicted nonlinear and post-elastic features of hierarchical strands. This approach is based on the so-called "Equal Load Sharing (ELS)" hypothesis by virtue of which, when a wire breaks, the load acting on the strand is homogeneously redistributed among the surviving wires. Despite the overall effectiveness of the method, some discrepancies between theoretical predictions and in silico Finite Element-based simulations or experimental findings might arise when more complex structures are analysed, e.g. helically arranged bundles. To overcome these limitations, an enhanced hybrid approach is proposed in which the probability of rupture is combined with a deterministic mechanical model of a strand constituted by helically-arranged and hierarchically-organized wires. The analytical model is validated comparing its predictions with both Finite Element simulations and experimental tests. The results show that generalized stress-strain responses - incorporating tension/torsion coupling - are naturally found and, once one or more elements break, the competition between geometry and mechanics of the strand microstructure, i.e. the different cross sections and helical angles of the wires in the different hierarchical levels of the strand, determines the no longer homogeneous stress redistribution among the surviving wires whose fate is hence governed by a "Hierarchical Load Sharing" criterion.

  14. A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings.

    Science.gov (United States)

    Liu, Jie; Hu, Youmin; Wu, Bo; Wang, Yan; Xie, Fengyun

    2017-05-18

    The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD). Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features' information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components.

  15. A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings

    Directory of Open Access Journals (Sweden)

    Jie Liu

    2017-05-01

    Full Text Available The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD. Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features’ information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components.

  16. A hybrid modelling approach to develop scenarios for China's carbon dioxide emissions to 2050

    International Nuclear Information System (INIS)

    Gambhir, Ajay; Schulz, Niels; Napp, Tamaryn; Tong, Danlu; Munuera, Luis; Faist, Mark; Riahi, Keywan

    2013-01-01

    This paper describes a hybrid modelling approach to assess the future development of China's energy system, for both a “hypothetical counterfactual baseline” (HCB) scenario and low carbon (“abatement”) scenarios. The approach combines a technology-rich integrated assessment model (MESSAGE) of China's energy system with a set of sector-specific, bottom-up, energy demand models for the transport, buildings and industrial sectors developed by the Grantham Institute for Climate Change at Imperial College London. By exploring technology-specific solutions in all major sectors of the Chinese economy, we find that a combination of measures, underpinned by low-carbon power options based on a mix of renewables, nuclear and carbon capture and storage, would fundamentally transform the Chinese energy system, when combined with increasing electrification of demand-side sectors. Energy efficiency options in these demand sectors are also important. - Highlights: • Combining energy supply and demand models reveals low-carbon technology choices across China's economy. • China could reduce its CO 2 emissions to close to 3 Gt in 2050, costing around 2% of GDP. • Decarbonising the power sector underpins the energy system transformation. • Electrification of industrial processes, building heating and transport is required. • Energy efficiency across the demand side is also important

  17. A Two-Step Hybrid Approach for Modeling the Nonlinear Dynamic Response of Piezoelectric Energy Harvesters

    Directory of Open Access Journals (Sweden)

    Claudio Maruccio

    2018-01-01

    Full Text Available An effective hybrid computational framework is described here in order to assess the nonlinear dynamic response of piezoelectric energy harvesting devices. The proposed strategy basically consists of two steps. First, fully coupled multiphysics finite element (FE analyses are performed to evaluate the nonlinear static response of the device. An enhanced reduced-order model is then derived, where the global dynamic response is formulated in the state-space using lumped coefficients enriched with the information derived from the FE simulations. The electromechanical response of piezoelectric beams under forced vibrations is studied by means of the proposed approach, which is also validated by comparing numerical predictions with some experimental results. Such numerical and experimental investigations have been carried out with the main aim of studying the influence of material and geometrical parameters on the global nonlinear response. The advantage of the presented approach is that the overall computational and experimental efforts are significantly reduced while preserving a satisfactory accuracy in the assessment of the global behavior.

  18. Covercrete with hybrid functions - A novel approach to durable reinforced concrete structures

    Energy Technology Data Exchange (ETDEWEB)

    Tang, L.; Zhang, E.Q. [Chalmers University of Technology, SE-412 96 Gothenburg (Sweden); Fu, Y. [KTH Royal Institute of Technology, SE-106 91 Stockholm (Sweden); Schouenborg, B.; Lindqvist, J.E. [CBI Swedish Cement and Concrete Research Institute, c/o SP, Box 857, SE-501 15 Boraas (Sweden)

    2012-12-15

    Due to the corrosion of steel in reinforced concrete structures, the concrete with low water-cement ratio (w/c), high cement content, and large cover thickness is conventionally used for prolonging the passivation period of steel. Obviously, this conventional approach to durable concrete structures is at the sacrifice of more CO{sub 2} emission and natural resources through consuming higher amount of cement and more constituent materials, which is against sustainability. By placing an economically affordable conductive mesh made of carbon fiber or conductive polymer fiber in the near surface zone of concrete acting as anode we can build up a cathodic prevention system with intermittent low current density supplied by, e.g., the solar cells. In such a way, the aggressive negative ions such as Cl{sup -}, CO{sub 3}{sup 2-}, and SO{sub 4}{sup 2-} can be stopped near the cathodic (steel) zone. Thus the reinforcement steel is prevented from corrosion even in the concrete with relatively high w/c and small cover thickness. This conductive mesh functions not only as electrode, but also as surface reinforcement to prevent concrete surface from cracking. Therefore, this new type of covercrete has hybrid functions. This paper presents the theoretical analysis of feasibility of this approach and discusses the potential durability problems and possible solutions to the potential problems. (Copyright copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  19. A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

    Science.gov (United States)

    Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

    2015-06-01

    The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

  20. Developing hybrid approaches to predict pKa values of ionizable groups

    Science.gov (United States)

    Witham, Shawn; Talley, Kemper; Wang, Lin; Zhang, Zhe; Sarkar, Subhra; Gao, Daquan; Yang, Wei

    2011-01-01

    Accurate predictions of pKa values of titratable groups require taking into account all relevant processes associated with the ionization/deionization. Frequently, however, the ionization does not involve significant structural changes and the dominating effects are purely electrostatic in origin allowing accurate predictions to be made based on the electrostatic energy difference between ionized and neutral forms alone using a static structure. On another hand, if the change of the charge state is accompanied by a structural reorganization of the target protein, then the relevant conformational changes have to be taken into account in the pKa calculations. Here we report a hybrid approach that first predicts the titratable groups, which ionization is expected to cause conformational changes, termed “problematic” residues, then applies a special protocol on them, while the rest of the pKa’s are predicted with rigid backbone approach as implemented in multi-conformation continuum electrostatics (MCCE) method. The backbone representative conformations for “problematic” groups are generated with either molecular dynamics simulations with charged and uncharged amino acid or with ab-initio local segment modeling. The corresponding ensembles are then used to calculate the pKa of the “problematic” residues and then the results are averaged. PMID:21744395

  1. Hybrid approaches to clinical trial monitoring: Practical alternatives to 100% source data verification

    Directory of Open Access Journals (Sweden)

    Sourabh De

    2011-01-01

    Full Text Available For years, a vast majority of clinical trial industry has followed the tenet of 100% source data verification (SDV. This has been driven partly by the overcautious approach to linking quality of data to the extent of monitoring and SDV and partly by being on the safer side of regulations. The regulations however, do not state any upper or lower limits of SDV. What it expects from researchers and the sponsors is methodologies which ensure data quality. How the industry does it is open to innovation and application of statistical methods, targeted and remote monitoring, real time reporting, adaptive monitoring schedules, etc. In short, hybrid approaches to monitoring. Coupled with concepts of optimum monitoring and SDV at site and off-site monitoring techniques, it should be possible to save time required to conduct SDV leading to more available time for other productive activities. Organizations stand to gain directly or indirectly from such savings, whether by diverting the funds back to the R&D pipeline; investing more in technology infrastructure to support large trials; or simply increasing sample size of trials. Whether it also affects the work-life balance of monitors who may then need to travel with a less hectic schedule for the same level of quality and productivity can be predicted only when there is more evidence from field.

  2. Hybrid approaches to clinical trial monitoring: Practical alternatives to 100% source data verification.

    Science.gov (United States)

    De, Sourabh

    2011-07-01

    For years, a vast majority of clinical trial industry has followed the tenet of 100% source data verification (SDV). This has been driven partly by the overcautious approach to linking quality of data to the extent of monitoring and SDV and partly by being on the safer side of regulations. The regulations however, do not state any upper or lower limits of SDV. What it expects from researchers and the sponsors is methodologies which ensure data quality. How the industry does it is open to innovation and application of statistical methods, targeted and remote monitoring, real time reporting, adaptive monitoring schedules, etc. In short, hybrid approaches to monitoring. Coupled with concepts of optimum monitoring and SDV at site and off-site monitoring techniques, it should be possible to save time required to conduct SDV leading to more available time for other productive activities. Organizations stand to gain directly or indirectly from such savings, whether by diverting the funds back to the R&D pipeline; investing more in technology infrastructure to support large trials; or simply increasing sample size of trials. Whether it also affects the work-life balance of monitors who may then need to travel with a less hectic schedule for the same level of quality and productivity can be predicted only when there is more evidence from field.

  3. A New Hybrid Approach for Augmented Reality Maintenance in Scientific Facilities

    Directory of Open Access Journals (Sweden)

    Héctor Martínez

    2013-09-01

    Full Text Available Maintenance in scientific facilities is a difficult issue, especially in large and hazardous facilities, due to the complexity of tasks and equipment. Augmented reality is a technology that has already shown great promise in the maintenance field. With the help of augmented reality applications, maintenance tasks can be carried out faster and more safely. The problem with current applications is that they are small-scale prototypes that do not easily scale to large facility maintenance applications. This paper presents a new hybrid approach that enables the creation of augmented reality maintenance applications for large and hazardous scientific facilities. In this paper, a new augmented reality marker and the algorithm for its recognition is proposed. The performance of the algorithm is verified in three test cases, showing promising results in two of them. Improvements in robustness in the third test case in which the camera is moving quickly or when light conditions are extreme are subject to further studies. The proposed new approach will be integrated into an existing augmented reality maintenance system.

  4. A hybrid stochastic approach for self-location of wireless sensors in indoor environments.

    Science.gov (United States)

    Lloret, Jaime; Tomas, Jesus; Garcia, Miguel; Canovas, Alejandro

    2009-01-01

    Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS) in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

  5. A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments

    Directory of Open Access Journals (Sweden)

    Alejandro Canovas

    2009-05-01

    Full Text Available Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

  6. Critical care physicians’ approaches to negotiating with surrogate decision makers: a qualitative study

    Science.gov (United States)

    Brush, David R.; Brown, Crystal E.; Alexander, G. Caleb

    2013-01-01

    Objective To describe how critical care physicians manage conflicts with surrogates about withdrawing or withholding patients’ life support. Design Qualitative analysis of key informant interviews with critical care physicians during 2010. We transcribed interviews verbatim and used grounded theory to code and revise a taxonomy of themes and to identify illustrative quotes. Setting 3 academic medical centers, 1 academic-affiliated medical center and 4 private practice groups or private hospitals in a large Midwestern city Subjects 14 critical care physicians Measurements and main results Physicians reported tailoring their approach to address specific reasons for disagreement with surrogates. Five common approaches were identified: (1) building trust, (2) educating and informing, (3) providing surrogates more time, (4) adjusting surrogate and physician roles, and (5) highlighting specific values. When mistrust was an issue, physicians endeavored to build a more trusting relationship with the surrogate before re-addressing decision making. Physicians also reported correcting misunderstandings by providing targeted education, and some reported highlighting specific patient, surrogate, or physician values that they hoped would guide surrogates to agree with them. When surrogates struggled with decision making roles, physicians attempted to reinforce the concept of substituted judgment. Physicians noted that some surrogates needed time to “come to terms” with the patent’s illness before agreeing with physicians. Many physicians had witnessed colleagues negotiate in ways they found objectionable, such as providing misleading information, injecting their own values into the negotiation, or behaving unprofessionally towards surrogates. While some physicians viewed their efforts to encourage surrogates’ agreement as persuasive, others strongly denied persuading surrogates and described their actions as “guiding” or “negotiating.” Conclusions Physicians

  7. Improved hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW)

    Science.gov (United States)

    Zaiwani, B. E.; Zarlis, M.; Efendi, S.

    2018-03-01

    In this research, the improvement of hybridization algorithm of Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) in selecting the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. To improve the performance of the above research, FAHP algorithm hybridization with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW) algorithm was adopted, which applied FAHP algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee at a government institution. The result of improvement of the average value of Efficiency Rate (ER) is 85.24%, which means that this research has succeeded in improving the previous research that is equal to 77.82%. Keywords: Ranking and Selection, Fuzzy AHP, Fuzzy TOPSIS, FMADM-SAW.

  8. Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis

    International Nuclear Information System (INIS)

    Jesneck, Jonathan L.; Nolte, Loren W.; Baker, Jay A.; Floyd, Carey E.; Lo, Joseph Y.

    2006-01-01

    As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p<0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets

  9. “ELEPHANT TRUNK” AND ENDOVASCULAR STENTGRAFTING – A HYBRID APPROACH TO THE TREATMENT OF EXTENSIVE THORACIC AORTIC ANEURYSM

    Directory of Open Access Journals (Sweden)

    Tomáš Holubec

    2013-01-01

    Full Text Available A hybrid approach to elephant trunk technique for treatment of thoracic aortic aneurysms combines a conventional surgical and endovascular therapy. Compared to surgery alone, there is a presumption that mortality and morbidity is reduced. We present a case report of a 42-year-old man with a giant aneurysm of the entire thoracic aorta, significant aortic and tricuspid regurgitation and ventricular septum defect. The patient underwent multiple consecutive operations and interventions having, among others, finally replaced the entire thoracic aorta with the use of the hybrid elephant trunk technique.

  10. Cloud E-Learning Service Strategies for Improving E-Learning Innovation Performance in a Fuzzy Environment by Using a New Hybrid Fuzzy Multiple Attribute Decision-Making Model

    Science.gov (United States)

    Su, Chiu Hung; Tzeng, Gwo-Hshiung; Hu, Shu-Kung

    2016-01-01

    The purpose of this study was to address this problem by applying a new hybrid fuzzy multiple criteria decision-making model including (a) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to construct the fuzzy scope influential network relationship map (FSINRM) and determine the fuzzy influential weights of the…

  11. Training in Decision-making Strategies: An approach to enhance students' competence to deal with socio-scientific issues

    Science.gov (United States)

    Gresch, Helge; Hasselhorn, Marcus; Bögeholz, Susanne

    2013-10-01

    Dealing with socio-scientific issues in science classes enables students to participate productively in controversial discussions concerning ethical topics, such as sustainable development. In this respect, well-structured decision-making processes are essential for elaborate reasoning. To foster decision-making competence, a computer-based programme was developed that trains secondary school students (grades 11-13) in decision-making strategies. The main research question is: does training students to use these strategies foster decision-making competence? In addition, the influence of meta-decision aids was examined. Students conducted a task analysis to select an appropriate strategy prior to the decision-making process. Hence, the second research question is: does combining decision-making training with a task analysis enhance decision-making competence at a higher rate? To answer these questions, 386 students were tested in a pre-post-follow-up control-group design that included two training groups (decision-making strategies/decision-making strategies combined with a task analysis) and a control group (decision-making with additional ecological information instead of strategic training). An open-ended questionnaire was used to assess decision-making competence in situations related to sustainable development. The decision-making training led to a significant improvement in the post-test and the follow-up, which was administered three months after the training. Long-term effects on the quality of the students' decisions were evident for both training groups. Gains in competence when reflecting upon the decision-making processes of others were found, to a lesser extent, in the training group that received the additional meta-decision training. In conclusion, training in decision-making strategies is a promising approach to deal with socio-scientific issues related to sustainable development.

  12. Innovative molecular approach to the identification of Colossoma macropomum and its hybrids

    Directory of Open Access Journals (Sweden)

    Fátima Gomes

    2012-06-01

    Full Text Available Tambaqui (Colossoma macropomum is the fish species most commonly raised in the Brazilian fish farms. The species is highly adaptable to captive conditions, and is both fast-growing and relatively fecund. In recent years, artificial breeding has produced hybrids with Characiform species, known as "Tambacu" and "Tambatinga". Identifying hybrids is a difficult process, given their morphological similarities with the parent species. This study presents an innovative molecular approach to the identification of hybrids based primarily on Multiplex PCR of a nuclear gene (α-Tropomyosin, which was tested on 93 specimens obtained from fish farms in northern Brazil. The sequencing of a 505-bp fragment of the Control Region (CR permitted the identification of the maternal lineage of the specimen, all of which corresponded to C. macropomum. Unexpectedly, only two CR haplotype were found in 93 samples, a very low genetic diversity for the pisciculture of Tambaqui. Multiplex PCR identified 42 hybrids, in contrast with 23 identified by the supplier on the basis of external morphology. This innovative tool has considerable potential for the development of the Brazilian aquaculture, given the possibility of the systematic identification of the genetic traits of both fry-producing stocks, and the fry and juveniles raised in farms.O Tambaqui (Colossoma macropomum é a espécie de peixe mais comumente cultivada em pisciculturas no Brasil. A espécie é altamente adaptada às condições de cativeiro, apresentando rápido crescimento e alta fecundidade. Nos últimos anos tem ocorrido o cruzamento artificial entre espécies de Characiformes, produzindo os híbridos "Tambacu" e "Tambatinga". A identificação de híbridos é uma tarefa difícil, em virtude da grande similaridade morfológica entre as espécies parentais. O presente estudo apresenta uma abordagem molecular inovadora para identificação de híbridos com base em PCR Multiplex de um gene nuclear (

  13. An approach to siting nuclear power plants: the relevance of earthquakes, faults and decision analysis

    International Nuclear Information System (INIS)

    Nair, K.; Brogan, G.E.; Cluff, L.S.; Idriss, I.M.; Mao, K.T.

    1975-01-01

    The regional approach to nuclear power plant siting described in this paper identifies candidate sites within the region and ranks these sites by using decision-analysis concepts. The approach uses exclusionary criteria to eliminate areas from consideration and to identify those areas which are most likely to contain candidate sites. These areas are then examined in greater detail to identify candidate sites, and the number of sites under consideration is reduced to a reasonably manageable number, approximately 15. These sites are then ranked using concepts of decision analysis. The exclusionary criteria applied relate primarily to regulatory-agency safety requirements and essential functional requirements. Examples of such criteria include proximity to population centres, presence of active faults, and the availability of cooling water. In many areas of the world, the presence of active faults and potential negative effects of earthquakes are dominant exclusionary criteria. To apply the 'active fault' criterion the region must be studied to locate and assess the activity of all potentially active faults. This requires complementary geologic (including geomorphic), historical, seismological, geodetic and geophysical investigations of the entire region. Site response studies or empirical attenuation correlations can be used to determine the relevant parameters of anticipated shaking from postulated earthquakes, and analytical testing and evaluation can be used to assess the potential extent of ground failure during an earthquake. After candidate sites are identified, an approach based on decision analysis is used to rank them. This approach uses the preferences and judgements of consumers, utility companies, the government, and other groups concerned with siting and licensing issues in the ranking process. Both subjective and objective factors are processed in a logical manner, as are the monetary and non-monetary factors and achievement of competing environmental

  14. Hybrid Design Thinking in a Consummate Marriage of People and Technology

    NARCIS (Netherlands)

    Wendrich, Robert E.; Sugiyama, K.

    2013-01-01

    In this paper we take a hybrid design tool approach to integrate existing and new advances in HCI, problem-solving, decision-making, mind-mapping, universal access in conjunction with multi-disciplinary and cross-domain areas based on holistic and interactive systems. Our hybrid approach constitutes

  15. Recent Development in Pulmonary Valve Replacement after Tetralogy of Fallot Repair: The Emergence of Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Tariq eSuleiman

    2015-06-01

    Full Text Available In the current era approximately 90% of infants born with tetralogy of Fallot (ToF are expected to live beyond 40 years of age making it the fastest growing population amongst patients with congenital heart disease. One of the most common late consequences after repair of ToF, is pulmonary valve regurgitation (PVR. Significant PVR results in progressive dilatation and dysfunction of the right ventricle, decrease in exercise tolerance, arrhythmias, heart failure, and increased risk of sudden death. The conventional approach of dealing with this problem is to perform pulmonary valve replacement using cardiopulmonary bypass (CPB and cardioplegic arrest. However, this approach is associated not only with long operative times but also side effects related to the use of CPB. Development of percutaneous approaches to valve disease is one of the most exciting areas of research and clinical innovation in cardiovascular research. The main development has been that of transcatheter pulmonary valve replacement for the rehabilitation of conduits between the right ventricle and pulmonary artery in patients after surgery for ToF. However, with the percutaneous technique, a limited size of prosthesis can be inserted. Moreover, the technique does not offer the opportunity of treating additional defects that are frequently associated with severe PR, such as pulmonary artery dilatation, and it cannot be used in the significantly dilated native right ventricular outlet tract (RVOT. The advent of the hybrid surgical options for treating cardiac disease has integrated the techniques of interventional cardiology with the techniques of cardiac surgery to provide a form of therapy that combines the respective strengths of both fields.In this review, we present and compare recent advances in procedures to replace the pulmonary valve in patients with ToF presenting with severe PVR and dilated RVOT.

  16. A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.

    Science.gov (United States)

    Xue, Xiaoming; Zhou, Jianzhong

    2017-01-01

    To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Super-resolution nanofabrication with metal-ion doped hybrid material through an optical dual-beam approach

    International Nuclear Information System (INIS)

    Cao, Yaoyu; Li, Xiangping; Gu, Min

    2014-01-01

    We apply an optical dual-beam approach to a metal-ion doped hybrid material to achieve nanofeatures beyond the optical diffraction limit. By spatially inhibiting the photoreduction and the photopolymerization, we realize a nano-line, consisting of polymer matrix and in-situ generated gold nanoparticles, with a lateral size of sub 100 nm, corresponding to a factor of 7 improvement compared to the diffraction limit. With the existence of gold nanoparticles, a plasmon enhanced super-resolution fabrication mechanism in the hybrid material is observed, which benefits in a further reduction in size of the fabricated feature. The demonstrated nanofeature in hybrid materials paves the way for realizing functional nanostructures

  18. A MOORA based fuzzy multi-criteria decision making approach for supply chain strategy selection

    Directory of Open Access Journals (Sweden)

    Bijan Sarkar

    2012-08-01

    Full Text Available To acquire the competitive advantages in order to survive in the global business scenario, modern companies are now facing the problems of selecting key supply chain strategies. Strategy selection becomes difficult as the number of alternatives and conflicting criteria increases. Multi criteria decision making (MCDM methodologies help the supply chain managers take a lead in a complex industrial set-up. The present investigation applies fuzzy MCDM technique entailing multi-objective optimization on the basis of ratio analysis (MOORA in selection of alternatives in a supply chain. The MOORA method is utilized to three suitable numerical examples for the selection of supply chain strategies (warehouse location selection and vendor/supplier selection. The results obtained by using current approach almost match with those of previous research works published in various open journals. The empirical study has demonstrated the simplicity and applicability of this method as a strategic decision making tool in a supply chain.

  19. The Bayes linear approach to inference and decision-making for a reliability programme

    International Nuclear Information System (INIS)

    Goldstein, Michael; Bedford, Tim

    2007-01-01

    In reliability modelling it is conventional to build sophisticated models of the probabilistic behaviour of the component lifetimes in a system in order to deduce information about the probabilistic behaviour of the system lifetime. Decision modelling of the reliability programme requires a priori, therefore, an even more sophisticated set of models in order to capture the evidence the decision maker believes may be obtained from different types of data acquisition. Bayes linear analysis is a methodology that uses expectation rather than probability as the fundamental expression of uncertainty. By working only with expected values, a simpler level of modelling is needed as compared to full probability models. In this paper we shall consider the Bayes linear approach to the estimation of a mean time to failure MTTF of a component. The model built will take account of the variance in our estimate of the MTTF, based on a variety of sources of information

  20. Decision-making in environmental radiation protection: using the ERICA Integrated Approach

    International Nuclear Information System (INIS)

    Zinger, I.; Copplestone, D.; Howard, B.J.

    2008-01-01

    The ERICA Integrated Approach and its associated tool and databases provide a method by which the likely impact of radioactive discharges on the environment can be evaluated, see Fig. 1. The various factors, which should be taken into account when making decisions both during and after an assessment has been made, are discussed for each stage in the assessment process for a hypothetical case study. The assessment will demonstrate the issues associated with the decision-making process at Tiers 1 and 2 within the ERICA Tool and how they may vary. The case study, set in England, evaluates the environmental impact of radioactive substances released under authorisation in response primarily to conservation legislation, because of the need to demonstrate that no adverse impacts will occur on Natura 2000 sites as a result of the release of an authorised substance