WorldWideScience

Sample records for hybrid model previously

  1. Hybrid Unifying Variable Supernetwork Model

    Institute of Scientific and Technical Information of China (English)

    LIU; Qiang; FANG; Jin-qing; LI; Yong

    2015-01-01

    In order to compare new phenomenon of topology change,evolution,hybrid ratio and network characteristics of unified hybrid network theoretical model with unified hybrid supernetwork model,this paper constructed unified hybrid variable supernetwork model(HUVSM).The first layer introduces a hybrid ratio dr,the

  2. Large Unifying Hybrid Supernetwork Model

    Institute of Scientific and Technical Information of China (English)

    LIU; Qiang; FANG; Jin-qing; LI; Yong

    2015-01-01

    For depicting multi-hybrid process,large unifying hybrid network model(so called LUHNM)has two sub-hybrid ratios except dr.They are deterministic hybrid ratio(so called fd)and random hybrid ratio(so called gr),respectively.

  3. Interspecific hybridization transfers a previously unknown glyphosate resistance mechanism in Amaranthus species.

    Science.gov (United States)

    Gaines, Todd A; Ward, Sarah M; Bukun, Bekir; Preston, Christopher; Leach, Jan E; Westra, Philip

    2012-01-01

    A previously unknown glyphosate resistance mechanism, amplification of the 5-enolpyruvyl shikimate-3-phosphate synthase gene, was recently reported in Amaranthus palmeri. This evolved mechanism could introgress to other weedy Amaranthus species through interspecific hybridization, representing an avenue for acquisition of a novel adaptive trait. The objective of this study was to evaluate the potential for this glyphosate resistance trait to transfer via pollen from A. palmeri to five other weedy Amaranthus species (Amaranthus hybridus, Amaranthus powellii, Amaranthus retroflexus, Amaranthus spinosus, and Amaranthus tuberculatus). Field and greenhouse crosses were conducted using glyphosate-resistant male A. palmeri as pollen donors and the other Amaranthus species as pollen recipients. Hybridization between A. palmeri and A. spinosus occurred with frequencies in the field studies ranging from <0.01% to 0.4%, and 1.4% in greenhouse crosses. A majority of the A. spinosus × A. palmeri hybrids grown to flowering were monoecious and produced viable seed. Hybridization occurred in the field study between A. palmeri and A. tuberculatus (<0.2%), and between A. palmeri and A. hybridus (<0.01%). This is the first documentation of hybridization between A. palmeri and both A. spinosus and A. hybridus.

  4. Unified Hybrid Network Theoretical Model Trilogy

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The first of the unified hybrid network theoretical model trilogy (UHNTF) is the harmonious unification hybrid preferential model (HUHPM), seen in the inner loop of Fig. 1, the unified hybrid ratio is defined.

  5. Model Reduction of Hybrid Systems

    DEFF Research Database (Denmark)

    Shaker, Hamid Reza

    systems are derived in this thesis. The results are used for output feedback control of switched nonlinear systems. Model reduction of piecewise affine systems is also studied in this thesis. The proposed method is based on the reduction of linear subsystems inside the polytopes. The methods which......High-Technological solutions of today are characterized by complex dynamical models. A lot of these models have inherent hybrid/switching structure. Hybrid/switched systems are powerful models for distributed embedded systems design where discrete controls are applied to continuous processes...... of hybrid systems, designing controllers and implementations is very high so that the use of these models is limited in applications where the size of the state space is large. To cope with complexity, model reduction is a powerful technique. This thesis presents methods for model reduction and stability...

  6. Hybrid Model of Content Extraction

    DEFF Research Database (Denmark)

    Qureshi, Pir Abdul Rasool; Memon, Nasrullah

    2012-01-01

    We present a hybrid model for content extraction from HTML documents. The model operates on Document Object Model (DOM) tree of the corresponding HTML document. It evaluates each tree node and associated statistical features like link density and text distribution across the node to predict signi...

  7. Hybrid models for complex fluids

    CERN Document Server

    Tronci, Cesare

    2010-01-01

    This paper formulates a new approach to complex fluid dynamics, which accounts for microscopic statistical effects in the micromotion. While the ordinary fluid variables (mass density and momentum) undergo usual dynamics, the order parameter field is replaced by a statistical distribution on the order parameter space. This distribution depends also on the point in physical space and its dynamics retains the usual fluid transport features while containing the statistical information on the order parameter space. This approach is based on a hybrid moment closure for Yang-Mills Vlasov plasmas, which replaces the usual cold-plasma assumption. After presenting the basic properties of the hybrid closure, such as momentum map features, singular solutions and Casimir invariants, the effect of Yang-Mills fields is considered and a direct application to ferromagnetic fluids is presented. Hybrid models are also formulated for complex fluids with symmetry breaking. For the special case of liquid crystals, a hybrid formul...

  8. Hybrid Model of Content Extraction

    DEFF Research Database (Denmark)

    Qureshi, Pir Abdul Rasool; Memon, Nasrullah

    2012-01-01

    We present a hybrid model for content extraction from HTML documents. The model operates on Document Object Model (DOM) tree of the corresponding HTML document. It evaluates each tree node and associated statistical features like link density and text distribution across the node to predict...... model outperformed other existing content extraction models. We present a browser based implementation of the proposed model as proof of concept and compare the implementation strategy with various state of art implementations. We also discuss various applications of the proposed model with special...

  9. Presumable incipient hybrid speciation of door snails in previously glaciated areas in the Caucasus.

    Science.gov (United States)

    Koch, Eva L; Neiber, Marco T; Walther, Frank; Hausdorf, Bernhard

    2016-04-01

    Homoploid hybrid speciation, speciation by hybridization without a change in chromosome number, may be the result of an encounter of closely related species in a habitat that is different from that usually occupied by these species. In the northwestern Caucasus the land snail species Micropontica caucasica and M. circassica form two distinct entities with little admixture at low and intermediate altitudes. However, at higher altitudes in the Lagonaki plateau, which were repeatedly glaciated, Micropontica populations with intermediate characters occur. Admixture analyses based on AFLP data demonstrated that the populations from the Lagonaki plateau are homoploid hybrids that now form a cluster separate from the parental species. The Lagonaki populations are characterized by a mtDNA haplotype clade that has been found in the parental species only once. The fixation of this haplotype clade in most hybrid populations suggests that these haplotypes are better adapted to the cooler conditions in high altitude habitats and have replaced the haplotypes of the parental species in a selective sweep. The fixation of a presumably adaptive mitochondrial haplotype clade in the Lagonaki populations is an important step towards speciation under the differential fitness species concept.

  10. Hybrid2 - The hybrid power system simulation model

    Energy Technology Data Exchange (ETDEWEB)

    Baring-Gould, E.I.; Green, H.J.; Dijk, V.A.P. van [National Renewable Energy Lab., Golden, CO (United States); Manwell, J.F. [Univ. of Massachusetts, Amherst, MA (United States)

    1996-12-31

    There is a large-scale need and desire for energy in remote communities, especially in the developing world; however the lack of a user friendly, flexible performance prediction model for hybrid power systems incorporating renewables hindered the analysis of hybrids as options to conventional solutions. A user friendly model was needed with the versatility to simulate the many system locations, widely varying hardware configurations, and differing control options for potential hybrid power systems. To meet these ends, researchers from the National Renewable Energy Laboratory (NREL) and the University of Massachusetts (UMass) developed the Hybrid2 software. This paper provides an overview of the capabilities, features, and functionality of the Hybrid2 code, discusses its validation and future plans. Model availability and technical support provided to Hybrid2 users are also discussed. 12 refs., 3 figs., 4 tabs.

  11. Modeling and analysis using hybrid Petri nets

    CERN Document Server

    Ghomri, Latéfa

    2007-01-01

    This paper is devoted to the use of hybrid Petri nets (PNs) for modeling and control of hybrid dynamic systems (HDS). Modeling, analysis and control of HDS attract ever more of researchers' attention and several works have been devoted to these topics. We consider in this paper the extensions of the PN formalism (initially conceived for modeling and analysis of discrete event systems) in the direction of hybrid modeling. We present, first, the continuous PN models. These models are obtained from discrete PNs by the fluidification of the markings. They constitute the first steps in the extension of PNs toward hybrid modeling. Then, we present two hybrid PN models, which differ in the class of HDS they can deal with. The first one is used for deterministic HDS modeling, whereas the second one can deal with HDS with nondeterministic behavior. Keywords: Hybrid dynamic systems; D-elementary hybrid Petri nets; Hybrid automata; Controller synthesis

  12. Hybrid Atlas Models

    CERN Document Server

    Ichiba, Tomoyuki; Banner, Adrian; Karatzas, Ioannis; Fernholz, Robert

    2009-01-01

    We study Atlas-type models of equity markets with local characteristics that depend on both name and rank, and in ways that induce a stability of the capital distribution. Ergodic properties and rankings of processes are examined with reference to the theory of reflected Brownian motions in polyhedral domains. In the context of such models, we discuss properties of various investment strategies, including the so-called growth-optimal and universal portfolios.

  13. A Hybrid Model. DEMETER

    Energy Technology Data Exchange (ETDEWEB)

    Gerlagh, Reyer [University of Manchester, Manchester (United Kingdom); Van der Zwaan, Bob [ECN Policy Studies, Petten (Netherlands)

    2009-11-15

    This insightful book explores the issue of sustainable development in its more operative and applied sense. Although a great deal of research has addressed potential interpretations and definitions of sustainable development, much of this work is too abstract to offer policy-makers and researchers the feasible and effective guidelines they require. This book redresses the balance. The authors highlight how various indicators and aggregate measures can be included in models that are used for decision-making support and sustainability assessment. They also demonstrate the importance of identifying practical means to assess whether policy proposals, specific decisions or targeted scenarios are sustainable. With discussions of basic concepts relevant to understanding applied sustainability analysis, such as definitions of costs and revenue recycling, this book provides policy-makers, researchers and graduate students with feasible and effective principles for measuring sustainable development.

  14. In situ hybridization of bat chromosomes with human (TTAGGGn probe, after previous digestion with Alu I

    Directory of Open Access Journals (Sweden)

    Karina de Cassia Faria

    2002-01-01

    Full Text Available The purpose of this work was to verify the ability of the enzyme Alu I to cleave and/or remove satellite DNA sequences from heterochromatic regions in chromosomes of bats, by identifying the occurrence of modifications in the pattern of fluorescence in situ hybridization with telomeric DNA. The localization and fluorescence intensity of the telomeric DNA sites of the Alu-digested and undigested chromosomes of species Eumops glaucinus, Carollia perspicillata, and Platyrrhinus lineatus were analyzed. Telomeric sequences were detected at the termini of chromosomes of all three species, although, in C. perspicillata, the signals were very faint or absent in most chromosomes. This finding was interpreted as being due to a reduced number of copies of the telomeric repeat, resulting from extensive telomeric association and/or rearrangements undergone by the chromosomes of Carollia. Fluorescent signals were also observed in centromeric and pericentromeric regions in several two-arm chromosomes of E. glaucinus and C. perspicillata. In E. glaucinus and P. lineatus, some interstitial and terminal telomeric sites were observed to be in association with regions of constitutive heterochromatin and ribosomal DNA (NORs. After digestion, these telomeric sites showed a significant decrease in signal intensity, indicating that enzyme Alu I cleaves and/or removes part of the satellite DNA present in these regions. These results suggest that the telomeric sequence is a component of the heterochromatin, and that the C-band- positive regions of bat chromosomes have a different DNA composition.

  15. Travelling waves in hybrid chemotaxis models

    CERN Document Server

    Franz, Benjamin; Painter, Kevin J; Erban, Radek

    2013-01-01

    Hybrid models of chemotaxis combine agent-based models of cells with partial differential equation models of extracellular chemical signals. In this paper, travelling wave properties of hybrid models of bacterial chemotaxis are investigated. Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death. Cells consume the extracellular nutrient field (chemoattractant) which is modelled using a partial differential equation. Mesoscopic and macroscopic equations representing the behaviour of the hybrid model are derived and the existence of travelling wave solutions for these models is established. It is shown that cell proliferation is necessary for the existence of non-transient (stationary) travelling waves in hybrid models. Additionally, a numerical comparison between the wave speeds of the continuum models and the hybr...

  16. Hadron rapidity spectra within a hybrid model

    CERN Document Server

    Khvorostukhin, A S

    2016-01-01

    A 2-stage hybrid model is proposed that joins the fast initial state of interaction, described by the hadron string dynamics (HSD) model, to subsequent evolution of the expanding system at the second stage, treated within ideal hydrodynamics. The developed hybrid model is assigned to describe heavy-ion collisions in the energy range of the NICA collider under construction in Dubna. Generally, the model is in reasonable agreement with the available data on proton rapidity spectra. However, reproducing proton rapidity spectra, our hybrid model cannot describe the rapidity distributions of pions. The model should be improved by taking into consideration viscosity effects at the hydrodynamical stage of system evolution.

  17. Statistical Model Checking for Stochastic Hybrid Systems

    DEFF Research Database (Denmark)

    David, Alexandre; Du, Dehui; Larsen, Kim Guldstrand

    2012-01-01

    This paper presents novel extensions and applications of the UPPAAL-SMC model checker. The extensions allow for statistical model checking of stochastic hybrid systems. We show how our race-based stochastic semantics extends to networks of hybrid systems, and indicate the integration technique ap...

  18. Hybrid neural network models of transducers

    Science.gov (United States)

    Xie, Shilin; Zhang, Xinong; Chen, Shenglai; Zhu, Changchun

    2011-10-01

    A hybrid neural network (NN) approach is proposed and applied to modeling of transducers in the paper. The modeling procedures are also presented in detail. First, the simulated studies on the modeling of single input-single output and multi input-multi output transducers are conducted respectively by use of the developed hybrid NN scheme. Secondly, the hybrid NN modeling approach is utilized to characterize a six-axis force sensor prototype based on the measured data. The results show that the hybrid NN approach can significantly improve modeling precision in comparison with the conventional modeling method. In addition, the method is superior to NN black-box modeling because the former possesses smaller network scale, higher convergence speed, higher model precision and better generalization performance.

  19. Evaluating the Pedagogical Potential of Hybrid Models

    Science.gov (United States)

    Levin, Tzur; Levin, Ilya

    2013-01-01

    The paper examines how the use of hybrid models--that consist of the interacting continuous and discrete processes--may assist in teaching system thinking. We report an experiment in which undergraduate students were asked to choose between a hybrid and a continuous solution for a number of control problems. A correlation has been found between…

  20. Harmonious Unifying Hybrid Preferential Supernetwork Model

    Institute of Scientific and Technical Information of China (English)

    LIU; Qiang; FANG; Jin-qing; LI; Yong

    2015-01-01

    The basic concepts and methods for harmonious unifying hybrid preferential model(HUHPM)are based on random preferential attachment(RPA)mixed with deterministic preferential attachment(DPA),so there is only one unified hybrid ratio dr,which is defined as:

  1. Towards Modelling of Hybrid Systems

    DEFF Research Database (Denmark)

    Wisniewski, Rafal

    2006-01-01

    The article is an attempt to use methods of category theory and topology for analysis of hybrid systems. We use the notion of a directed topological space; it is a topological space together with a set of privileged paths. Dynamical systems are examples of directed topological spaces. A hybrid...... system consists of a number of dynamical systems that are glued together according to information encoded in the discrete part of the system. We develop a definition of a hybrid system as a functor from the category generated by a transition system to the category of directed topological spaces. Its...... directed homotopy colimit (geometric realization) is a single directed topological space. The behavior of hybrid systems can be then understood in terms of the behavior of dynamical systems through the directed homotopy colimit....

  2. Modeling hybrid perovskites by molecular dynamics.

    Science.gov (United States)

    Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia

    2017-02-01

    The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.

  3. Modeling hybrid perovskites by molecular dynamics

    Science.gov (United States)

    Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia

    2017-02-01

    The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.

  4. Travelling Waves in Hybrid Chemotaxis Models

    KAUST Repository

    Franz, Benjamin

    2013-12-18

    Hybrid models of chemotaxis combine agent-based models of cells with partial differential equation models of extracellular chemical signals. In this paper, travelling wave properties of hybrid models of bacterial chemotaxis are investigated. Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death. Cells consume the extracellular nutrient field (chemoattractant), which is modelled using a partial differential equation. Mesoscopic and macroscopic equations representing the behaviour of the hybrid model are derived and the existence of travelling wave solutions for these models is established. It is shown that cell proliferation is necessary for the existence of non-transient (stationary) travelling waves in hybrid models. Additionally, a numerical comparison between the wave speeds of the continuum models and the hybrid models shows good agreement in the case of weak chemotaxis and qualitative agreement for the strong chemotaxis case. In the case of slow cell adaptation, we detect oscillating behaviour of the wave, which cannot be explained by mean-field approximations. © 2013 Society for Mathematical Biology.

  5. HYbrid Coordinate Ocean Model (HYCOM): Global

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Global HYbrid Coordinate Ocean Model (HYCOM) and U.S. Navy Coupled Ocean Data Assimilation (NCODA) 3-day, daily forecast at approximately 9-km (1/12-degree)...

  6. A muscle model for hybrid muscle activation

    Directory of Open Access Journals (Sweden)

    Klauer Christian

    2015-09-01

    Full Text Available To develop model-based control strategies for Functional Electrical Stimulation (FES in order to support weak voluntary muscle contractions, a hybrid model for describing joint motions induced by concurrent voluntary-and FES induced muscle activation is proposed. It is based on a Hammerstein model – as commonly used in feedback controlled FES – and exemplarily applied to describe the shoulder abduction joint angle. Main component of a Hammerstein muscle model is usually a static input nonlinearity depending on the stimulation intensity. To additionally incorporate voluntary contributions, we extended the static non-linearity by a second input describing the intensity of the voluntary contribution that is estimated by electromyography (EMG measurements – even during active FES. An Artificial Neural Network (ANN is used to describe the static input non-linearity. The output of the ANN drives a second-order linear dynamical system that describes the combined muscle activation and joint angle dynamics. The tunable parameters are adapted to the individual subject by a system identification approach using previously recorded I/O-data. The model has been validated in two healthy subjects yielding RMS values for the joint angle error of 3.56° and 3.44°, respectively.

  7. Boltzmann Transport in Hybrid PIC HET Modeling

    Science.gov (United States)

    2015-07-01

    Paper 3. DATES COVERED (From - To) July 2015-July 2015 4. TITLE AND SUBTITLE Boltzmann transport in hybrid PIC HET modeling 5a. CONTRACT NUMBER In...produced a variety of self-consistent electron swarm codes, such as the Magboltz code, focused on directly solving the steady Boltzmann trans-port...Std. 239.18 Boltzmann transport in hybrid PIC HET modeling IEPC-2015- /ISTS-2015-b- Presented at Joint Conference of 30th International

  8. Statistical Model Checking for Stochastic Hybrid Systems

    DEFF Research Database (Denmark)

    David, Alexandre; Du, Dehui; Larsen, Kim Guldstrand

    2012-01-01

    This paper presents novel extensions and applications of the UPPAAL-SMC model checker. The extensions allow for statistical model checking of stochastic hybrid systems. We show how our race-based stochastic semantics extends to networks of hybrid systems, and indicate the integration technique...... applied for implementing this semantics in the UPPAAL-SMC simulation engine. We report on two applications of the resulting tool-set coming from systems biology and energy aware buildings....

  9. A novel simplified model for torsional vibration analysis of a series-parallel hybrid electric vehicle

    Science.gov (United States)

    Tang, Xiaolin; Yang, Wei; Hu, Xiaosong; Zhang, Dejiu

    2017-02-01

    In this study, based on our previous work, a novel simplified torsional vibration dynamic model is established to study the torsional vibration characteristics of a compound planetary hybrid propulsion system. The main frequencies of the hybrid driveline are determined. In contrast to vibration characteristics of the previous 16-degree of freedom model, the simplified model can be used to accurately describe the low-frequency vibration property of this hybrid powertrain. This study provides a basis for further vibration control of the hybrid powertrain during the process of engine start/stop.

  10. A Mathematical Model for Suppression Subtractive Hybridization

    OpenAIRE

    2002-01-01

    Suppression subtractive hybridization (SSH) is frequently used to unearth differentially expressed genes on a whole-genome scale. Its versatility is based on combining cDNA library subtraction and normalization, which allows the isolation of sequences of varying degrees of abundance and differential expression. SSH is a complex process with many adjustable parameters that affect the outcome of gene isolation.We present a mathematical model of SSH based on DNA hybridization kinetics for assess...

  11. Diagnosing Hybrid Systems: a Bayesian Model Selection Approach

    Science.gov (United States)

    McIlraith, Sheila A.

    2005-01-01

    In this paper we examine the problem of monitoring and diagnosing noisy complex dynamical systems that are modeled as hybrid systems-models of continuous behavior, interleaved by discrete transitions. In particular, we examine continuous systems with embedded supervisory controllers that experience abrupt, partial or full failure of component devices. Building on our previous work in this area (MBCG99;MBCG00), our specific focus in this paper ins on the mathematical formulation of the hybrid monitoring and diagnosis task as a Bayesian model tracking algorithm. The nonlinear dynamics of many hybrid systems present challenges to probabilistic tracking. Further, probabilistic tracking of a system for the purposes of diagnosis is problematic because the models of the system corresponding to failure modes are numerous and generally very unlikely. To focus tracking on these unlikely models and to reduce the number of potential models under consideration, we exploit logic-based techniques for qualitative model-based diagnosis to conjecture a limited initial set of consistent candidate models. In this paper we discuss alternative tracking techniques that are relevant to different classes of hybrid systems, focusing specifically on a method for tracking multiple models of nonlinear behavior simultaneously using factored sampling and conditional density propagation. To illustrate and motivate the approach described in this paper we examine the problem of monitoring and diganosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12 thrusters that enable both linear and rotational motion.

  12. A Hybrid 3D Indoor Space Model

    Science.gov (United States)

    Jamali, Ali; Rahman, Alias Abdul; Boguslawski, Pawel

    2016-10-01

    GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM), Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.

  13. A Hybrid 3D Indoor Space Model

    Directory of Open Access Journals (Sweden)

    A. Jamali

    2016-10-01

    Full Text Available GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM, Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.

  14. Hybrid simulation models of production networks

    CERN Document Server

    Kouikoglou, Vassilis S

    2001-01-01

    This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.

  15. Hybrid Models in Loop Quantum Cosmology

    CERN Document Server

    Navascués, B Elizaga; Marugán, G A Mena

    2016-01-01

    In the framework of Loop Quantum Cosmology, inhomogeneous models are usually quantized by means of a hybrid approach that combines loop quantization techniques with standard quantum field theory methods. This approach is based on a splitting of the phase space in a homogeneous sector, formed by global, zero-modes, and an inhomogeneous sector, formed by the remaining, infinite number of modes, that describe the local degrees of freedom. Then, the hybrid quantization is attained by adopting a loop representation for the homogeneous gravitational sector, while a Fock representation is used for the inhomogeneities. The zero-mode of the Hamiltonian constraint operator couples the homogeneous and inhomogeneous sectors. The hybrid approach, therefore, is expected to provide a suitable quantum theory in regimes where the main quantum effects of the geometry are those affecting the zero-modes, while the inhomogeneities, still being quantum, can be treated in a more conventional way. This hybrid strategy was first prop...

  16. Hybrid modelling of anaerobic wastewater treatment processes.

    Science.gov (United States)

    Karama, A; Bernard, O; Genovesi, A; Dochain, D; Benhammou, A; Steyer, J P

    2001-01-01

    This paper presents a hybrid approach for the modelling of an anaerobic digestion process. The hybrid model combines a feed-forward network, describing the bacterial kinetics, and the a priori knowledge based on the mass balances of the process components. We have considered an architecture which incorporates the neural network as a static model of unmeasured process parameters (kinetic growth rate) and an integrator for the dynamic representation of the process using a set of dynamic differential equations. The paper contains a description of the neural network component training procedure. The performance of this approach is illustrated with experimental data.

  17. A New Hybrid Model of Amino Acid Substitution for Protein Functional Classification

    Institute of Scientific and Technical Information of China (English)

    Ke Long WANG; Zhi Ning WEN; Fu Sheng NIE; Meng Long LI

    2005-01-01

    In this paper, a new hybrid model of amino acid substitution is developed and compared with the others in previous works. The results show that the new hybrid model can characterize the protein sequences very well by calculating Fisher weights, which can denote how much the variants contribute to the classification.

  18. Weather forecasting based on hybrid neural model

    Science.gov (United States)

    Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.

    2017-02-01

    Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.

  19. MODA - A hybrid atmospheric pollutant dispersion model

    Energy Technology Data Exchange (ETDEWEB)

    Favaron, M.; Oliveti Selmi, O. [Servizi Territorio srl, Milan (Italy); Sozzi, R. [Agenzia Regionale Protezione Ambiente (ARPA) Lazio, Rieti (Italy)

    2004-07-01

    MODA is a Gaussian-hybrid atmospheric dispersion model, intended for regulatory applications, and designed to meet the following requirements: ability to operate in complex terrain, standard use of a refined description of turbulence, operational efficiency (in terms of both speed and ease to change simulation parameters), ease of integration in modelling interfaces, output compatibility with the widely-used ISC3. MODA can operate in two modes: a standard mode, in which the pollutant dispersion is treated as Gaussian, and an advanced mode, in which the hybrid relations are used to compute the pollutant concentrations. (orig.)

  20. A hybrid wind farm parameterization for mesoscale and climate models

    Science.gov (United States)

    Pan, Y.; Archer, C. L.

    2016-12-01

    To better understand the potential impacts of wind farms on weather and climate at the local to regional scale, a new hybrid wind farm parameterization is proposed here for mesoscale models, such as the Weather Research and Forecasting Model (WRF), or climate models, such as the Community Atmosphere Model (CAM). All previous wind farm parameterizations treat all the wind turbines in the same grid cell as identical (i.e., they all share the same upstream wind velocity) and ignore the effect of wind direction. By contrast, the new hybrid model considers each individual wind turbine, based on its position in the layout and on wind direction. The new parameterization is developed starting from large eddy simulations (LES) of existing wind farms, in which the local flow around each wind turbine is directly simulated at high spatial ( 3.5 m) and temporal ( 0.1 s) resolutions and the effects of subgrid-scale processes are modeled. Based on analytic and statistical relationships between the LES results and several geometric properties of the wind farm layout (such as blockage ratio and blocking distance), the new hybrid parameterization predicts the local upstream wind speed of each individual wind turbine in the same grid cell, and thus successfully account for the effects of layout and wind direction with little computational cost. With the newly predicted upstream velocity, the turbine-induced forces and added turbulence kinetic energy (TKE) in the atmosphere are derived analytically. The wind speed, wind speed deficit, and TKE profiles and power production obtained with the hybrid parameterization for the test case (the 48-turbine Lillgrund wind farm in Sweden) are in better agreement with the LES results than previous parameterizations. Future work includes the insertion of the hybrid parameterization into the WRF code to assess impacts on near-surface properties, such as temperature and heat and momentum fluxes, in the region surrounding the wind farm.

  1. SCAN-based hybrid and double-hybrid density functionals from models without fitted parameters

    OpenAIRE

    Hui, Kerwin; Chai, Jeng-Da

    2015-01-01

    By incorporating the nonempirical SCAN semilocal density functional [Sun, Ruzsinszky, and Perdew, Phys. Rev. Lett. 115, 036402 (2015)] in the underlying expression of four existing hybrid and double-hybrid models, we propose one hybrid (SCAN0) and three double-hybrid (SCAN0-DH, SCAN-QIDH, and SCAN0-2) density functionals, which are free from any fitted parameters. The SCAN-based double-hybrid functionals consistently outperform their parent SCAN semilocal functional for self-interaction probl...

  2. Hybrid Modeling of Elastic Wave Scattering in a Welded Cylinder

    Science.gov (United States)

    Mahmoud, A.; Shah, A. H.; Popplewell, N.

    2003-03-01

    In the present study, a 3D hybrid method, which couples the finite element region with guided elastic wave modes, is formulated to investigate the scattering by a non-axisymmetric crack in a welded steel pipe. The algorithm is implemented on a parallel computing platform. Implementation is facilitated by the dynamic memory allocation capabilities of Fortran 90™ and the parallel processing directives of OpenMp™. The algorithm is validated against available numerical results. The agreement with a previous 2D hybrid model is excellent. Novel results are presented for the scattering of the first longitudinal mode from different non-axisymmetric cracks. The trend of the new results is consistent with the previous findings for the axisymmetric case. The developed model has potential application in ultrasonic nondestructive evaluation of welded steel pipes.

  3. 75 FR 91 - Airworthiness Directives; Bombardier, Inc. (Type Certificate Previously Held by Canadair) Model...

    Science.gov (United States)

    2010-01-04

    ... Directives; Bombardier, Inc. (Type Certificate Previously Held by Canadair) Model CL-600-2B16 (CL-604...: Bombardier, Inc. (Type Certificate Previously Held by Canadair): Docket No. FAA-2009-1227; Directorate... (b) None. Applicability (c) This AD applies to Bombardier, Inc. (Type Certificate previously held...

  4. Hybrid models in loop quantum cosmology

    Science.gov (United States)

    Elizaga Navascués, Beatriz; Martín-Benito, Mercedes; Mena Marugán, Guillermo A.

    2016-06-01

    In the framework of Loop Quantum Cosmology (LQC), inhomogeneous models are usually quantized by means of a hybrid approach that combines loop quantization techniques with standard quantum field theory methods. This approach is based on a splitting of the phase space in a homogeneous sector, formed by global, zero-modes and an inhomogeneous sector, formed by the remaining, infinite number of modes, that describe the local degrees of freedom. Then, the hybrid quantization is attained by adopting a loop representation for the homogeneous gravitational sector, while a Fock representation is used for the inhomogeneities. The zero-mode of the Hamiltonian constraint operator couples the homogeneous and inhomogeneous sectors. The hybrid approach, therefore, is expected to provide a suitable quantum theory in regimes where the main quantum effects of the geometry are those affecting the zero-modes, while the inhomogeneities, still being quantum, can be treated in a more conventional way. This hybrid strategy was first proposed for the simplest cosmological midisuperspaces: the Gowdy models, and it has been later applied to the case of cosmological perturbations. This paper reviews the construction and main applications of hybrid LQC.

  5. Incorporating RTI in a Hybrid Model of Reading Disability

    OpenAIRE

    2014-01-01

    The present study seeks to evaluate a hybrid model of identification that incorporates response-to-intervention (RTI) as a one of the key symptoms of reading disability. The one-year stability of alternative operational definitions of reading disability was examined in a large scale sample of students who were followed longitudinally from first to second grade. The results confirmed previous findings of limited stability for single-criterion based operational definitions of reading disability...

  6. Hybrid quantum teleportation: A theoretical model

    Energy Technology Data Exchange (ETDEWEB)

    Takeda, Shuntaro; Mizuta, Takahiro; Fuwa, Maria; Yoshikawa, Jun-ichi; Yonezawa, Hidehiro; Furusawa, Akira [Department of Applied Physics, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan)

    2014-12-04

    Hybrid quantum teleportation – continuous-variable teleportation of qubits – is a promising approach for deterministically teleporting photonic qubits. We propose how to implement it with current technology. Our theoretical model shows that faithful qubit transfer can be achieved for this teleportation by choosing an optimal gain for the teleporter’s classical channel.

  7. Novel Hybrid Model: Integrating Scrum and XP

    Directory of Open Access Journals (Sweden)

    Zaigham Mushtaq

    2012-06-01

    Full Text Available Scrum does not provide any direction about how to engineer a software product. The project team has to adopt suitable agile process model for the engineering of software. XP process model is mainly focused on engineering practices rather than management practices. The design of XP process makes it suitable for simple and small size projects and not appropriate for medium and large projects. A fine integration of management and engineering practices is desperately required to build quality product to make it valuable for customers. In this research a novel framework hybrid model is proposed to achieve this integration. The proposed hybrid model is actually an express version of Scrum model. It possesses features of engineering practices that are necessary to develop quality software as per customer requirements and company objectives. A case study is conducted to validate the proposal of hybrid model. The results of the case study reveal that proposed model is an improved version of XP and Scrum model.

  8. CORSICA modelling of ITER hybrid operation scenarios

    Science.gov (United States)

    Kim, S. H.; Bulmer, R. H.; Campbell, D. J.; Casper, T. A.; LoDestro, L. L.; Meyer, W. H.; Pearlstein, L. D.; Snipes, J. A.

    2016-12-01

    The hybrid operating mode observed in several tokamaks is characterized by further enhancement over the high plasma confinement (H-mode) associated with reduced magneto-hydro-dynamic (MHD) instabilities linked to a stationary flat safety factor (q ) profile in the core region. The proposed ITER hybrid operation is currently aiming at operating for a long burn duration (>1000 s) with a moderate fusion power multiplication factor, Q , of at least 5. This paper presents candidate ITER hybrid operation scenarios developed using a free-boundary transport modelling code, CORSICA, taking all relevant physics and engineering constraints into account. The ITER hybrid operation scenarios have been developed by tailoring the 15 MA baseline ITER inductive H-mode scenario. Accessible operation conditions for ITER hybrid operation and achievable range of plasma parameters have been investigated considering uncertainties on the plasma confinement and transport. ITER operation capability for avoiding the poloidal field coil current, field and force limits has been examined by applying different current ramp rates, flat-top plasma currents and densities, and pre-magnetization of the poloidal field coils. Various combinations of heating and current drive (H&CD) schemes have been applied to study several physics issues, such as the plasma current density profile tailoring, enhancement of the plasma energy confinement and fusion power generation. A parameterized edge pedestal model based on EPED1 added to the CORSICA code has been applied to hybrid operation scenarios. Finally, fully self-consistent free-boundary transport simulations have been performed to provide information on the poloidal field coil voltage demands and to study the controllability with the ITER controllers. Extended from Proc. 24th Int. Conf. on Fusion Energy (San Diego, 2012) IT/P1-13.

  9. Modeling lithium/hybrid-cathode batteries

    Energy Technology Data Exchange (ETDEWEB)

    Gomadam, Parthasarathy M.; Merritt, Don R.; Scott, Erik R.; Schmidt, Craig L.; Skarstad, Paul M. [Medtronic Energy and Component Center, 6700 Shingle Creek Pkwy, Brooklyn Center, MN 55430 (United States); Weidner, John W. [Center for Electrochemical Engineering, Department of Chemical Engineering, University of South Carolina, Columbia, SC 29208 (United States)

    2007-12-06

    This document describes a first-principles-based mathematical model developed to predict the voltage-capacity behavior of batteries having hybrid cathodes comprising a mixture of carbon monofluoride (CF{sub x}) and silver vanadium oxide (SVO). These batteries typically operate at moderate rates of discharge, lasting several years. The model presented here is an accurate tool for design optimization and performance prediction of batteries under current drains that encompass both the application rate and accelerated testing. (author)

  10. Influence of Deterministic Attachments for Large Unifying Hybrid Network Model

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Large unifying hybrid network model (LUHPM) introduced the deterministic mixing ratio fd on the basis of the harmonious unification hybrid preferential model, to describe the influence of deterministic attachment to the network topology characteristics,

  11. Hybrid model for QCD deconfining phase boundary

    Science.gov (United States)

    Srivastava, P. K.; Singh, C. P.

    2012-06-01

    Intensive search for a proper and realistic equations of state (EOS) is still continued for studying the phase diagram existing between quark gluon plasma (QGP) and hadron gas (HG) phases. Lattice calculations provide such EOS for the strongly interacting matter at finite temperature (T) and vanishing baryon chemical potential (μB). These calculations are of limited use at finite μB due to the appearance of notorious sign problem. In the recent past, we had constructed a hybrid model description for the QGP as well as HG phases where we make use of a new excluded-volume model for HG and a thermodynamically-consistent quasiparticle model for the QGP phase and used them further to get QCD phase boundary and a critical point. Since then many lattice calculations have appeared showing various thermal and transport properties of QCD matter at finite T and μB=0. We test our hybrid model by reproducing the entire data for strongly interacting matter and predict our results at finite μB so that they can be tested in future. Finally we demonstrate the utility of the model in fixing the precise location, the order of the phase transition and the nature of CP existing on the QCD phase diagram. We thus emphasize the suitability of the hybrid model as formulated here in providing a realistic EOS for the strongly interacting matter.

  12. Hybrid modeling and prediction of dynamical systems

    Science.gov (United States)

    Lloyd, Alun L.; Flores, Kevin B.

    2017-01-01

    Scientific analysis often relies on the ability to make accurate predictions of a system’s dynamics. Mechanistic models, parameterized by a number of unknown parameters, are often used for this purpose. Accurate estimation of the model state and parameters prior to prediction is necessary, but may be complicated by issues such as noisy data and uncertainty in parameters and initial conditions. At the other end of the spectrum exist nonparametric methods, which rely solely on data to build their predictions. While these nonparametric methods do not require a model of the system, their performance is strongly influenced by the amount and noisiness of the data. In this article, we consider a hybrid approach to modeling and prediction which merges recent advancements in nonparametric analysis with standard parametric methods. The general idea is to replace a subset of a mechanistic model’s equations with their corresponding nonparametric representations, resulting in a hybrid modeling and prediction scheme. Overall, we find that this hybrid approach allows for more robust parameter estimation and improved short-term prediction in situations where there is a large uncertainty in model parameters. We demonstrate these advantages in the classical Lorenz-63 chaotic system and in networks of Hindmarsh-Rose neurons before application to experimentally collected structured population data. PMID:28692642

  13. Hybrid Energy System Modeling in Modelica

    Energy Technology Data Exchange (ETDEWEB)

    William R. Binder; Christiaan J. J. Paredis; Humberto E. Garcia

    2014-03-01

    In this paper, a Hybrid Energy System (HES) configuration is modeled in Modelica. Hybrid Energy Systems (HES) have as their defining characteristic the use of one or more energy inputs, combined with the potential for multiple energy outputs. Compared to traditional energy systems, HES provide additional operational flexibility so that high variability in both energy production and consumption levels can be absorbed more effectively. This is particularly important when including renewable energy sources, whose output levels are inherently variable, determined by nature. The specific HES configuration modeled in this paper include two energy inputs: a nuclear plant, and a series of wind turbines. In addition, the system produces two energy outputs: electricity and synthetic fuel. The models are verified through simulations of the individual components, and the system as a whole. The simulations are performed for a range of component sizes, operating conditions, and control schemes.

  14. Mathematical Modeling of Hybrid Electrical Engineering Systems

    Directory of Open Access Journals (Sweden)

    A. A. Lobaty

    2016-01-01

    Full Text Available A large class of systems that have found application in various industries and households, electrified transportation facilities and energy sector has been classified as electrical engineering systems. Their characteristic feature is a combination of continuous and discontinuous modes of operation, which is reflected in the appearance of a relatively new term “hybrid systems”. A wide class of hybrid systems is pulsed DC converters operating in a pulse width modulation, which are non-linear systems with variable structure. Using various methods for linearization it is possible to obtain linear mathematical models that rather accurately simulate behavior of such systems. However, the presence in the mathematical models of exponential nonlinearities creates considerable difficulties in the implementation of digital hardware. The solution can be found while using an approximation of exponential functions by polynomials of the first order, that, however, violates the rigor accordance of the analytical model with characteristics of a real object. There are two practical approaches to synthesize algorithms for control of hybrid systems. The first approach is based on the representation of the whole system by a discrete model which is described by difference equations that makes it possible to synthesize discrete algorithms. The second approach is based on description of the system by differential equations. The equations describe synthesis of continuous algorithms and their further implementation in a digital computer included in the control loop system. The paper considers modeling of a hybrid electrical engineering system using differential equations. Neglecting the pulse duration, it has been proposed to describe behavior of vector components in phase coordinates of the hybrid system by stochastic differential equations containing generally non-linear differentiable random functions. A stochastic vector-matrix equation describing dynamics of the

  15. Petascale computation performance of lightweight multiscale cardiac models using hybrid programming models.

    Science.gov (United States)

    Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias

    2011-01-01

    Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models.

  16. Hybrid optimization model of product concepts

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Deficiencies of applying the simple genetic algorithm to generate concepts were specified. Based on analyzing conceptual design and the morphological matrix of an excavator, the hybrid optimization model of generating its concepts was proposed, viz. an improved adaptive genetic algorithm was applied to explore the excavator concepts in the searching space of conceptual design, and a neural network was used to evaluate the fitness of the population. The optimization of generating concepts was finished through the "evolution - evaluation" iteration. The results show that by using the hybrid optimization model, not only the fitness evaluation and constraint conditions are well processed, but also the search precision and convergence speed of the optimization process are greatly improved. An example is presented to demonstrate the advantages of the proposed method and associated algorithms.

  17. Hamiltonian approach to hybrid plasma models

    CERN Document Server

    Tronci, Cesare

    2010-01-01

    The Hamiltonian structures of several hybrid kinetic-fluid models are identified explicitly, upon considering collisionless Vlasov dynamics for the hot particles interacting with a bulk fluid. After presenting different pressure-coupling schemes for an ordinary fluid interacting with a hot gas, the paper extends the treatment to account for a fluid plasma interacting with an energetic ion species. Both current-coupling and pressure-coupling MHD schemes are treated extensively. In particular, pressure-coupling schemes are shown to require a transport-like term in the Vlasov kinetic equation, in order for the Hamiltonian structure to be preserved. The last part of the paper is devoted to studying the more general case of an energetic ion species interacting with a neutralizing electron background (hybrid Hall-MHD). Circulation laws and Casimir functionals are presented explicitly in each case.

  18. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

    Science.gov (United States)

    Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed

    2017-05-01

    Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

  19. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

    Science.gov (United States)

    Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed

    2016-02-01

    Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

  20. 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.

  1. A hybrid double-observer sightability model for aerial surveys

    Science.gov (United States)

    Griffin, Paul C.; Lubow, Bruce C.; Jenkins, Kurt J.; Vales, David J.; Moeller, Barbara J.; Reid, Mason; Happe, Patricia J.; Mccorquodale, Scott M.; Tirhi, Michelle J.; Schaberi, Jim P.; Beirne, Katherine

    2013-01-01

    Raw counts from aerial surveys make no correction for undetected animals and provide no estimate of precision with which to judge the utility of the counts. Sightability modeling and double-observer (DO) modeling are 2 commonly used approaches to account for detection bias and to estimate precision in aerial surveys. We developed a hybrid DO sightability model (model MH) that uses the strength of each approach to overcome the weakness in the other, for aerial surveys of elk (Cervus elaphus). The hybrid approach uses detection patterns of 2 independent observer pairs in a helicopter and telemetry-based detections of collared elk groups. Candidate MH models reflected hypotheses about effects of recorded covariates and unmodeled heterogeneity on the separate front-seat observer pair and back-seat observer pair detection probabilities. Group size and concealing vegetation cover strongly influenced detection probabilities. The pilot's previous experience participating in aerial surveys influenced detection by the front pair of observers if the elk group was on the pilot's side of the helicopter flight path. In 9 surveys in Mount Rainier National Park, the raw number of elk counted was approximately 80–93% of the abundance estimated by model MH. Uncorrected ratios of bulls per 100 cows generally were low compared to estimates adjusted for detection bias, but ratios of calves per 100 cows were comparable whether based on raw survey counts or adjusted estimates. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to DO modeling.

  2. Fluid and hybrid models for streamers

    Science.gov (United States)

    Bonaventura, Zdeněk

    2016-09-01

    Streamers are contracted ionizing waves with self-generated field enhancement that propagate into a low-ionized medium exposed to high electric field leaving filamentary trails of plasma behind. The widely used model to study streamer dynamics is based on drift-diffusion equations for electrons and ions, assuming local field approximation, coupled with Poisson's equation. For problems where presence of energetic electrons become important a fluid approach needs to be extended by a particle model, accompanied also with Monte Carlo Collision technique, that takes care of motion of these electrons. A combined fluid-particle approach is used to study an influence of surface emission processes on a fast-pulsed dielectric barrier discharge in air at atmospheric pressure. It is found that fluid-only model predicts substantially faster reignition dynamics compared to coupled fluid-particle model. Furthermore, a hybrid model can be created in which the population of electrons is divided in the energy space into two distinct groups: (1) low energy `bulk' electrons that are treated with fluid model, and (2) high energy `beam' electrons, followed as particles. The hybrid model is then capable not only to deal with streamer discharges in laboratory conditions, but also allows us to study electron acceleration in streamer zone of lighting leaders. There, the production of fast electrons from streamers is investigated, since these (runaway) electrons act as seeds for the relativistic runaway electron avalanche (RREA) mechanism, important for high-energy atmospheric physics phenomena. Results suggest that high energy electrons effect the streamer propagation, namely the velocity, the peak electric field, and thus also the production rate of runaway electrons. This work has been supported by the Czech Science Foundation research project 15-04023S.

  3. New hybrid model of proton exchange membrane fuel cell

    Institute of Scientific and Technical Information of China (English)

    WANG Rui-min; CAO Guang-yi; ZHU Xin-jian

    2007-01-01

    Model and simulation are good tools for design optimization of fuel cell systems. This paper proposes a new hybrid model of proton exchange membrane fuel cell (PEMFC). The hybrid model includes physical component and black-box component. The physical component represents the well-known part of PEMFC, while artificial neural network (ANN) component estimates the poorly known part of PEMFC. The ANN model can compensate the performance of the physical model. This hybrid model is implemented on Matlab/Simulink software. The hybrid model shows better accuracy than that of the physical model and ANN model. Simulation results suggest that the hybrid model can be used as a suitable and accurate model for PEMFC.

  4. Modeling of renewable hybrid energy sources

    Directory of Open Access Journals (Sweden)

    Dumitru Cristian Dragos

    2009-12-01

    Full Text Available Recent developments and trends in the electric power consumption indicate an increasing use of renewable energy. Renewable energy technologies offer the promise of clean, abundant energy gathered from self-renewing resources such as the sun, wind, earth and plants. Virtually all regions of the world have renewable resources of one type or another. By this point of view studies on renewable energies focuses more and more attention. The present paper intends to present different mathematical models related to different types of renewable energy sources such as: solar energy and wind energy. It is also presented the validation and adaptation of such models to hybrid systems working in geographical and meteorological conditions specific to central part of Transylvania region. The conclusions based on validation of such models are also shown.

  5. Hybrid2: The hybrid system simulation model, Version 1.0, user manual

    Energy Technology Data Exchange (ETDEWEB)

    Baring-Gould, E.I.

    1996-06-01

    In light of the large scale desire for energy in remote communities, especially in the developing world, the need for a detailed long term performance prediction model for hybrid power systems was seen. To meet these ends, engineers from the National Renewable Energy Laboratory (NREL) and the University of Massachusetts (UMass) have spent the last three years developing the Hybrid2 software. The Hybrid2 code provides a means to conduct long term, detailed simulations of the performance of a large array of hybrid power systems. This work acts as an introduction and users manual to the Hybrid2 software. The manual describes the Hybrid2 code, what is included with the software and instructs the user on the structure of the code. The manual also describes some of the major features of the Hybrid2 code as well as how to create projects and run hybrid system simulations. The Hybrid2 code test program is also discussed. Although every attempt has been made to make the Hybrid2 code easy to understand and use, this manual will allow many organizations to consider the long term advantages of using hybrid power systems instead of conventional petroleum based systems for remote power generation.

  6. Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites

    Science.gov (United States)

    2016-03-09

    AFRL-AFOSR-VA-TR-2016-0154 Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites Gregory Odegard MICHIGAN TECHNOLOGICAL UNIVERSITY Final Report...SUBTITLE Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-13-1-0030 5c. PROGRAM ELEMENT NUMBER...DISTRIBUTION A: Distribution approved for public release. Final Report Multiscale Modeling of Graphite/CNT/Epoxy Hybrid Composites Grant FA9550-13-1-0030 PI

  7. Hybrid Models of Alternative Current Filter for Hvdc

    Directory of Open Access Journals (Sweden)

    Ufa Ruslan A.

    2017-01-01

    Full Text Available Based on a hybrid simulation concept of HVDC, the developed hybrid AC filter models, providing the sufficiently full and adequate modeling of all single continuous spectrum of quasi-steady-state and transient processes in the filter, are presented. The obtained results suggest that usage of the hybrid simulation approach is carried out a methodically accurate with guaranteed instrumental error solution of differential equation systems of mathematical models of HVDC.

  8. Modeling and Analysis of Hybrid Dynamic Systems Using Hybrid Petri Nets

    OpenAIRE

    GHOMRI Latefa; Alla, Hassane

    2008-01-01

    Some extensions of PNs permitting HDS modeling were presented here. The first models to be presented are continuous PNs. This model may be used for modeling either a continuous system or a discrete system. In this case, it is an approximation that is often satisfactory. Hybrid PNs combine in the same formalism a discrete PN and a continuous PN. Two hybrid PN models were considered in this chapter. The first, called the hybrid PN, has a deterministic behavior; this means that we can predict th...

  9. Hybrid Modeling Improves Health and Performance Monitoring

    Science.gov (United States)

    2007-01-01

    Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.

  10. Analysis of chromosome aberration data by hybrid-scale models

    Energy Technology Data Exchange (ETDEWEB)

    Indrawati, Iwiq [Research and Development on Radiation and Nuclear Biomedical Center, National Nuclear Energy Agency (Indonesia); Kumazawa, Shigeru [Nuclear Technology and Education Center, Japan Atomic Energy Research Institute, Honkomagome, Tokyo (Japan)

    2000-02-01

    This paper presents a new methodology for analyzing data of chromosome aberrations, which is useful to understand the characteristics of dose-response relationships and to construct the calibration curves for the biological dosimetry. The hybrid scale of linear and logarithmic scales brings a particular plotting paper, where the normal section paper, two types of semi-log papers and the log-log paper are continuously connected. The hybrid-hybrid plotting paper may contain nine kinds of linear relationships, and these are conveniently called hybrid scale models. One can systematically select the best-fit model among the nine models by among the conditions for a straight line of data points. A biological interpretation is possible with some hybrid-scale models. In this report, the hybrid scale models were applied to separately reported data on chromosome aberrations in human lymphocytes as well as on chromosome breaks in Tradescantia. The results proved that the proposed models fit the data better than the linear-quadratic model, despite the demerit of the increased number of model parameters. We showed that the hybrid-hybrid model (both variables of dose and response using the hybrid scale) provides the best-fit straight lines to be used as the reliable and readable calibration curves of chromosome aberrations. (author)

  11. Modelling supervisory controller for hybrid power systems

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, A.; Bindner, H.; Lundsager, P. [Risoe National Lab., Roskilde (Denmark); Jannerup, O. [Technical Univ. of Denmark, Dept. of Automation, Lyngby (Denmark)

    1999-03-01

    Supervisory controllers are important to achieve optimal operation of hybrid power systems. The performance and economics of such systems depend mainly on the control strategy for switching on/off components. The modular concept described in this paper is an attempt to design standard supervisory controllers that could be used in different applications, such as village power and telecommunication applications. This paper presents some basic aspects of modelling and design of modular supervisory controllers using the object-oriented modelling technique. The functional abstraction hierarchy technique is used to formulate the control requirements and identify the functions of the control system. The modular algorithm is generic and flexible enough to be used with any system configuration and several goals (different applications). The modularity includes accepting modification of system configuration and goals during operation with minor or no changes in the supervisory controller. (au)

  12. A Hybrid Teaching and Learning Model

    Science.gov (United States)

    Juhary, Jowati Binti

    This paper aims at analysing the needs for a specific teaching and learning model for the National Defence University of Malaysia (NDUM). The main argument is that whether there are differences between teaching and learning for academic component versus military component at the university. It is further argued that in order to achieve excellence, there should be one teaching and learning culture. Data were collected through interviews with military cadets. It is found that there are variations of teaching and learning strategies for academic courses, in comparison to a dominant teaching and learning style for military courses. Thus, in the interest of delivering quality education and training for students at the university, the paper argues that possibly a hybrid model for teaching and learning is fundamental in order to generate a one culture of academic and military excellence for the NDUM.

  13. Hybrid adaptive control of a dragonfly model

    Science.gov (United States)

    Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro

    2012-02-01

    Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.

  14. Hybrid Perturbation methods based on Statistical Time Series models

    CERN Document Server

    San-Juan, Juan Félix; Pérez, Iván; López, Rosario

    2016-01-01

    In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of a...

  15. Hybrid perturbation methods based on statistical time series models

    Science.gov (United States)

    San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario

    2016-04-01

    In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.

  16. Modelling of Natural and Hybrid Ventilation

    DEFF Research Database (Denmark)

    Heiselberg, Per

    be installed in existing buildings after a few modifications. In contrast, ventilation systems using only natural forces such as wind and thermal buoyancy need to be designed together with the building, since the building itself and its components are the elements that can reduce or increase air movement...... as well as influence the air content (dust, pollution etc.). Architects and engineers need to acquire qualitative and quantitative information about the interactions between building characteristics and natural ventilation in order to design buildings and systems consistent with a passive low......-energy approach. These lecture notes focus on modelling of natural and hybrid ventilation driven by thermal buoyancy, wind and/or mechanical driving forces for a single zone with one, two or several openings....

  17. Activity recognition using hybrid generative/discriminative models on home environments using binary sensors.

    Science.gov (United States)

    Ordóñez, Fco Javier; de Toledo, Paula; Sanchis, Araceli

    2013-04-24

    Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network) and SVM (Support Vector Machines), within the framework of HMM (Hidden Markov Model) in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0.05, proving that the hybrid approach is better suited for the addressed domain.

  18. Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

    Directory of Open Access Journals (Sweden)

    Araceli Sanchis

    2013-04-01

    Full Text Available Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network and SVM (Support Vector Machines, within the framework of HMM (Hidden Markov Model in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0:05, proving that the hybrid approach is better suited for the addressed domain.

  19. A hybrid Fermi-Ulam-bouncer model

    Energy Technology Data Exchange (ETDEWEB)

    Leonel, Edson D; McClintock, P V E [Department of Physics, Lancaster University, Lancaster LA1 4YB (United Kingdom)

    2005-01-28

    Some dynamical and chaotic properties are studied for a classical particle bouncing between two rigid walls, one of which is fixed and the other moves in time, in the presence of an external field. The system is a hybrid, behaving not as a purely Fermi-Ulam model, nor as a bouncer, but as a combination of the two. We consider two different kinds of motion of the moving wall: (i) periodic and (ii) random. The dynamics of the model is studied via a two-dimensional nonlinear area-preserving map. We confirm that, for periodic oscillations, our model recovers the well-known results of the Fermi-Ulam model in the limit of zero external field. For intense external fields, we establish the range of control parameters values within which invariant spanning curves are observed below the chaotic sea in the low energy domain. We characterize this chaotic low energy region in terms of Lyapunov exponents. We also show that the velocity of the particle, and hence also its kinetic energy, grow according to a power law when the wall moves randomly, yielding clear evidence of Fermi acceleration.

  20. A Hybrid Model of a Brushless DC Motor

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Hansen, Hans Brink; Kallesøe, Carsten Skovmose

    2007-01-01

    This paper presents a novel approach to modeling of a Brush-Less Direct Current Motor (BLDCM) driven by an inverter using hybrid systems theory. Hybrid systems combine continuous and discrete (event-based) dynamics, which is exactly the case in an inverter-driven BLDCM. The model presented in thi...

  1. Hybrid Scheduling Model for Independent Grid Tasks

    Directory of Open Access Journals (Sweden)

    J. Shanthini

    2015-01-01

    Full Text Available Grid computing facilitates the resource sharing through the administrative domains which are geographically distributed. Scheduling in a distributed heterogeneous environment is intrinsically very hard because of the heterogeneous nature of resource collection. Makespan and tardiness are two different measures of scheduling, and many of the previous researches concentrated much on reduction of makespan, which measures the machine utilization. In this paper, we propose a hybrid scheduling algorithm for scheduling independent grid tasks with the objective of reducing total weighted tardiness of grid tasks. Tardiness is to measure the due date performance, which has a direct impact on cost for executing the jobs. In this paper we propose BG_ATC algorithm which is a combination of best gap (BG search and Apparent Tardiness Cost (ATC indexing algorithm. Furthermore, we implemented these two algorithms in two different phases of the scheduling process. In addition to that, the comparison was made on results with various benchmark algorithms and the experimental results show that our algorithm outperforms the benchmark algorithms.

  2. Hybrid Scheduling Model for Independent Grid Tasks.

    Science.gov (United States)

    Shanthini, J; Kalaikumaran, T; Karthik, S

    2015-01-01

    Grid computing facilitates the resource sharing through the administrative domains which are geographically distributed. Scheduling in a distributed heterogeneous environment is intrinsically very hard because of the heterogeneous nature of resource collection. Makespan and tardiness are two different measures of scheduling, and many of the previous researches concentrated much on reduction of makespan, which measures the machine utilization. In this paper, we propose a hybrid scheduling algorithm for scheduling independent grid tasks with the objective of reducing total weighted tardiness of grid tasks. Tardiness is to measure the due date performance, which has a direct impact on cost for executing the jobs. In this paper we propose BG_ATC algorithm which is a combination of best gap (BG) search and Apparent Tardiness Cost (ATC) indexing algorithm. Furthermore, we implemented these two algorithms in two different phases of the scheduling process. In addition to that, the comparison was made on results with various benchmark algorithms and the experimental results show that our algorithm outperforms the benchmark algorithms.

  3. Hybrid Dynamical Systems Modeling, Stability, and Robustness

    CERN Document Server

    Goebel, Rafal; Teel, Andrew R

    2012-01-01

    Hybrid dynamical systems exhibit continuous and instantaneous changes, having features of continuous-time and discrete-time dynamical systems. Filled with a wealth of examples to illustrate concepts, this book presents a complete theory of robust asymptotic stability for hybrid dynamical systems that is applicable to the design of hybrid control algorithms--algorithms that feature logic, timers, or combinations of digital and analog components. With the tools of modern mathematical analysis, Hybrid Dynamical Systems unifies and generalizes earlier developments in continuous-time and discret

  4. A methodology for modeling photocatalytic reactors for indoor pollution control using previously estimated kinetic parameters

    Energy Technology Data Exchange (ETDEWEB)

    Passalia, Claudio; Alfano, Orlando M. [INTEC - Instituto de Desarrollo Tecnologico para la Industria Quimica, CONICET - UNL, Gueemes 3450, 3000 Santa Fe (Argentina); FICH - Departamento de Medio Ambiente, Facultad de Ingenieria y Ciencias Hidricas, Universidad Nacional del Litoral, Ciudad Universitaria, 3000 Santa Fe (Argentina); Brandi, Rodolfo J., E-mail: rbrandi@santafe-conicet.gov.ar [INTEC - Instituto de Desarrollo Tecnologico para la Industria Quimica, CONICET - UNL, Gueemes 3450, 3000 Santa Fe (Argentina); FICH - Departamento de Medio Ambiente, Facultad de Ingenieria y Ciencias Hidricas, Universidad Nacional del Litoral, Ciudad Universitaria, 3000 Santa Fe (Argentina)

    2012-04-15

    Highlights: Black-Right-Pointing-Pointer Indoor pollution control via photocatalytic reactors. Black-Right-Pointing-Pointer Scaling-up methodology based on previously determined mechanistic kinetics. Black-Right-Pointing-Pointer Radiation interchange model between catalytic walls using configuration factors. Black-Right-Pointing-Pointer Modeling and experimental validation of a complex geometry photocatalytic reactor. - Abstract: A methodology for modeling photocatalytic reactors for their application in indoor air pollution control is carried out. The methodology implies, firstly, the determination of intrinsic reaction kinetics for the removal of formaldehyde. This is achieved by means of a simple geometry, continuous reactor operating under kinetic control regime and steady state. The kinetic parameters were estimated from experimental data by means of a nonlinear optimization algorithm. The second step was the application of the obtained kinetic parameters to a very different photoreactor configuration. In this case, the reactor is a corrugated wall type using nanosize TiO{sub 2} as catalyst irradiated by UV lamps that provided a spatially uniform radiation field. The radiative transfer within the reactor was modeled through a superficial emission model for the lamps, the ray tracing method and the computation of view factors. The velocity and concentration fields were evaluated by means of a commercial CFD tool (Fluent 12) where the radiation model was introduced externally. The results of the model were compared experimentally in a corrugated wall, bench scale reactor constructed in the laboratory. The overall pollutant conversion showed good agreement between model predictions and experiments, with a root mean square error less than 4%.

  5. Synchronizability Analysis of Harmonious Unification Hybrid Preferential Model

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The harmonious unification hybrid preferential model uses the dr ratio to adjust the proportion of deterministic preferential attachment and random preferential attachment, enriched the only deterministic preferential network model,

  6. Hybrid Information Retrieval Model For Web Images

    CERN Document Server

    Bassil, Youssef

    2012-01-01

    The Bing Bang of the Internet in the early 90's increased dramatically the number of images being distributed and shared over the web. As a result, image information retrieval systems were developed to index and retrieve image files spread over the Internet. Most of these systems are keyword-based which search for images based on their textual metadata; and thus, they are imprecise as it is vague to describe an image with a human language. Besides, there exist the content-based image retrieval systems which search for images based on their visual information. However, content-based type systems are still immature and not that effective as they suffer from low retrieval recall/precision rate. This paper proposes a new hybrid image information retrieval model for indexing and retrieving web images published in HTML documents. The distinguishing mark of the proposed model is that it is based on both graphical content and textual metadata. The graphical content is denoted by color features and color histogram of ...

  7. Modelling of data uncertainties on hybrid computers

    Energy Technology Data Exchange (ETDEWEB)

    Schneider, Anke (ed.)

    2016-06-15

    The codes d{sup 3}f and r{sup 3}t are well established for modelling density-driven flow and nuclide transport in the far field of repositories for hazardous material in deep geological formations. They are applicable in porous media as well as in fractured rock or mudstone, for modelling salt- and heat transport as well as a free groundwater surface. Development of the basic framework of d{sup 3}f and r{sup 3}t had begun more than 20 years ago. Since that time significant advancements took place in the requirements for safety assessment as well as for computer hardware development. The period of safety assessment for a repository of high-level radioactive waste was extended to 1 million years, and the complexity of the models is steadily growing. Concurrently, the demands on accuracy increase. Additionally, model and parameter uncertainties become more and more important for an increased understanding of prediction reliability. All this leads to a growing demand for computational power that requires a considerable software speed-up. An effective way to achieve this is the use of modern, hybrid computer architectures which requires basically the set-up of new data structures and a corresponding code revision but offers a potential speed-up by several orders of magnitude. The original codes d{sup 3}f and r{sup 3}t were applications of the software platform UG /BAS 94/ whose development had begun in the early nineteennineties. However, UG had recently been advanced to the C++ based, substantially revised version UG4 /VOG 13/. To benefit also in the future from state-of-the-art numerical algorithms and to use hybrid computer architectures, the codes d{sup 3}f and r{sup 3}t were transferred to this new code platform. Making use of the fact that coupling between different sets of equations is natively supported in UG4, d{sup 3}f and r{sup 3}t were combined to one conjoint code d{sup 3}f++. A direct estimation of uncertainties for complex groundwater flow models with the

  8. Estimating hybrid choice models with the new version of Biogeme

    OpenAIRE

    Bierlaire, Michel

    2010-01-01

    Hybrid choice models integrate many types of discrete choice modeling methods, including latent classes and latent variables, in order to capture concepts such as perceptions, attitudes, preferences, and motivatio (Ben-Akiva et al., 2002). Although they provide an excellent framework to capture complex behavior patterns, their use in applications remains rare in the literature due to the difficulty of estimating the models. In this talk, we provide a short introduction to hybrid choice model...

  9. Hybrids of Gibbs Point Process Models and Their Implementation

    Directory of Open Access Journals (Sweden)

    Adrian Baddeley

    2013-11-01

    Full Text Available We describe a simple way to construct new statistical models for spatial point pattern data. Taking two or more existing models (finite Gibbs spatial point processes we multiply the probability densities together and renormalise to obtain a new probability density. We call the resulting model a hybrid. We discuss stochastic properties of hybrids, their statistical implications, statistical inference, computational strategies and software implementation in the R package spatstat. Hybrids are particularly useful for constructing models which exhibit interaction at different spatial scales. The methods are demonstrated on a real data set on human social interaction. Software and data are provided.

  10. Cyclostratigraphy for Chinese red clay sequences: Implications to changing previous age models and paleoclimate interpretations

    Science.gov (United States)

    Anwar, T.; Kravchinsky, V. A.; Zhang, R.

    2015-12-01

    The Chinese Loess Plateau contains red clay sequence which has continuous alternation of sedimentary cycles with recurrent paleoclimatic fluctuations. Absence of abundant fossils and inability of radiometric dating method made magnetostratigraphy a leading method to build age model for the red clay. Here magnetostratigraphic age model in red clay sequence is tested using cyclostratigraphy as orbital parameters of Earth are known. Milankovitch periodicities recorded in magnetic susceptibility and grain size in the Shilou red clay section are investigated and previously found age of 11 Ma for this section is re-evaluated. Magnetostratigraphy dating based on only visual correlation could potentially lead to erroneous age model. In this study the correlation is executed through the iteration procedure until it is supported by cyclostratigraphy; i.e. Milankovitch cycles are resolved in the best possible manner. Our new approach provides an age of 5.2 Ma for the Shilou profile. Wavelet analysis reveals that a 400 kyr eccentricity cycle is well preserved and the existence of a 100 kyr eccentricity in the red clay sequence on the eastern Chinese Loess Plateau suggests that eccentricity plays a vital role in Pliocene climate evolution. Paleomonsoon evolution is reconstructed and divided into three intervals (5.2-4.5 Ma, 4.5-3.6 Ma and 3.6-2.58 Ma). The earliest stage indicates that summer and winter monsoon cycles may rapidly alter, whereas the middle stage reflects an intensification of winter monsoon and aridification in Asia, and the youngest stage is characterized by relatively intensified summer monsoon. This study demonstrates that cyclostratigraphy can greatly assist magnetostratigraphy in dating the red clay sequences, and implies that many published age models for the red clay sequences should likely be re-assessed where possible. An evaluation of the monsoon system and climate change in eastern Asia might prominently benefit from this approach.

  11. Hybrid nonlinear model of the angular vestibulo-ocular reflex.

    Science.gov (United States)

    Ranjbaran, Mina; Galiana, Henrietta L

    2013-01-01

    A hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) is presented in this paper. The model relies on known interconnections between saccadic burst circuits in the brainstem and ocular premotor areas in the vestibular nuclei during slow and fast phase intervals. A viable switching strategy for the timing of nystagmus events is proposed. Simulations show that this hybrid model replicates AVOR nystagmus patterns that are observed in experimentally recorded data.

  12. Design, analysis and modeling of a novel hybrid powertrain system based on hybridized automated manual transmission

    Science.gov (United States)

    Wu, Guang; Dong, Zuomin

    2017-09-01

    Hybrid electric vehicles are widely accepted as a promising short to mid-term technical solution due to noticeably improved efficiency and lower emissions at competitive costs. In recent years, various hybrid powertrain systems were proposed and implemented based on different types of conventional transmission. Power-split system, including Toyota Hybrid System and Ford Hybrid System, are well-known examples. However, their relatively low torque capacity, and the drive of alternative and more advanced designs encouraged other innovative hybrid system designs. In this work, a new type of hybrid powertrain system based hybridized automated manual transmission (HAMT) is proposed. By using the concept of torque gap filler (TGF), this new hybrid powertrain type has the potential to overcome issue of torque gap during gearshift. The HAMT design (patent pending) is described in details, from gear layout and design of gear ratios (EV mode and HEV mode) to torque paths at different gears. As an analytical tool, mutli-body model of vehicle equipped with this HAMT was built to analyze powertrain dynamics at various steady and transient modes. A gearshift was decomposed and analyzed based basic modes. Furthermore, a Simulink-SimDriveline hybrid vehicle model was built for the new transmission, driveline and vehicle modular. Control strategy has also been built to harmonically coordinate different powertrain components to realize TGF function. A vehicle launch simulation test has been completed under 30% of accelerator pedal position to reveal details during gearshift. Simulation results showed that this HAMT can eliminate most torque gap that has been persistent issue of traditional AMT, improving both drivability and performance. This work demonstrated a new type of transmission that features high torque capacity, high efficiency and improved drivability.

  13. Treatment with intranasal iloprost reduces disease manifestations in a murine model of previously established COPD.

    Science.gov (United States)

    Lammi, Matthew R; Ghonim, Mohamed A; Pyakurel, Kusma; Naura, Amarjit S; Ibba, Salome V; Davis, Christian J; Okpechi, Samuel C; Happel, Kyle I; deBoisblanc, Bennett P; Shellito, Judd; Boulares, A Hamid

    2016-04-01

    Pulmonary endothelial prostacyclin appears to be involved in the pathogenesis of chronic obstructive pulmonary disease (COPD). The effect of treatment with a prostacyclin analog in animal models of previously established COPD is unknown. We evaluated the short- and long-term effect of iloprost on inflammation and airway hyperresponsiveness (AHR) in a murine model of COPD. Nineteen mice were exposed to LPS/elastase, followed by either three doses of intranasal iloprost or saline. In the long-term treatment experiment, 18 mice were exposed to LPS/elastase and then received 6 wk of iloprost or were left untreated as controls. In the short-term experiment, iloprost did not change AHR but significantly reduced serum IL-5 and IFN-γ. Long-term treatment with iloprost for both 2 and 6 wk significantly improved AHR. After 6 wk of iloprost, there was a reduction in bronchoalveolar lavage (BALF) neutrophils, serum IL-1β (30.0 ± 9.2 vs. 64.8 ± 7.4 pg/ml, P = 0.045), IL-2 (36.5 ± 10.6 vs. 83.8 ± 0.4 pg/ml, P = 0.01), IL-10 (75.7 ± 9.3 vs. 96.5 ± 3.5 pg/ml, P = 0.02), and nitrite (15.1 ± 5.4 vs. 30.5 ± 10.7 μmol, P = 0.01). Smooth muscle actin (SMA) in the lung homogenate was also significantly reduced after iloprost treatment (P = 0.02), and SMA thickness was reduced in the small and medium blood vessels after iloprost (P iloprost significantly reduced systemic inflammation in an LPS/elastase COPD model. Long-term iloprost treatment also reduced AHR, serum nitrite, SMA, and BALF neutrophilia. These data encourage future investigations of prostanoid therapy as a novel treatment for COPD patients. Copyright © 2016 the American Physiological Society.

  14. Bond graph model-based fault diagnosis of hybrid systems

    CERN Document Server

    Borutzky, Wolfgang

    2015-01-01

    This book presents a bond graph model-based approach to fault diagnosis in mechatronic systems appropriately represented by a hybrid model. The book begins by giving a survey of the fundamentals of fault diagnosis and failure prognosis, then recalls state-of-art developments referring to latest publications, and goes on to discuss various bond graph representations of hybrid system models, equations formulation for switched systems, and simulation of their dynamic behavior. The structured text: • focuses on bond graph model-based fault detection and isolation in hybrid systems; • addresses isolation of multiple parametric faults in hybrid systems; • considers system mode identification; • provides a number of elaborated case studies that consider fault scenarios for switched power electronic systems commonly used in a variety of applications; and • indicates that bond graph modelling can also be used for failure prognosis. In order to facilitate the understanding of fault diagnosis and the presented...

  15. A hybrid model of a subminiature helicopter in horizontal turn

    Institute of Scientific and Technical Information of China (English)

    Chen Li; Gong Zhenbang; Liu Liang

    2007-01-01

    A hybrid model of a subminiature helicopter in horizontal turn is presented. This model is based on a mechanism model and its compensated neural network (NN). First, the nonlinear dynamics of a subminiature helicopter is established. Through the linearization of the nonlinear dynamics on a trim point, the linear time-invariant mechanism model in horizontal turn is obtained. Then a diagonal recursive neural network is used to compensate the model error between the mechanism model and the nonlinear model, thus the hybrid model of a subminiature helicopter in horizontal turn is achieved. Simulation results show that the hybrid model has higher accuracy than the mechanism model and the obtained compensated-NN has good generalization capability.

  16. Discovery of previously unrecognised local faults in London, UK, using detailed 3D geological modelling

    Science.gov (United States)

    Aldiss, Don; Haslam, Richard

    2013-04-01

    In parts of London, faulting introduces lateral heterogeneity to the local ground conditions, especially where construction works intercept the Palaeogene Lambeth Group. This brings difficulties to the compilation of a ground model that is fully consistent with the ground investigation data, and so to the design and construction of engineering works. However, because bedrock in the London area is rather uniform at outcrop, and is widely covered by Quaternary deposits, few faults are shown on the geological maps of the area. This paper discusses a successful resolution of this problem at a site in east central London, where tunnels for a new underground railway station are planned. A 3D geological model was used to provide an understanding of the local geological structure, in faulted Lambeth Group strata, that had not been possible by other commonly-used methods. This model includes seven previously unrecognised faults, with downthrows ranging from about 1 m to about 12 m. The model was constructed in the GSI3D geological modelling software using about 145 borehole records, including many legacy records, in an area of 850 m by 500 m. The basis of a GSI3D 3D geological model is a network of 2D cross-sections drawn by a geologist, generally connecting borehole positions (where the borehole records define the level of the geological units that are present), and outcrop and subcrop lines for those units (where shown by a geological map). When the lines tracing the base of each geological unit within the intersecting cross-sections are complete and mutually consistent, the software is used to generate TIN surfaces between those lines, so creating a 3D geological model. Even where a geological model is constructed as if no faults were present, changes in apparent dip between two data points within a single cross-section can indicate that a fault is present in that segment of the cross-section. If displacements of similar size with the same polarity are found in a series

  17. Modelling the Noise-Robustness of Infants' Word Representations: The Impact of Previous Experience.

    Directory of Open Access Journals (Sweden)

    Christina Bergmann

    Full Text Available During language acquisition, infants frequently encounter ambient noise. We present a computational model to address whether specific acoustic processing abilities are necessary to detect known words in moderate noise--an ability attested experimentally in infants. The model implements a general purpose speech encoding and word detection procedure. Importantly, the model contains no dedicated processes for removing or cancelling out ambient noise, and it can replicate the patterns of results obtained in several infant experiments. In addition to noise, we also addressed the role of previous experience with particular target words: does the frequency of a word matter, and does it play a role whether that word has been spoken by one or multiple speakers? The simulation results show that both factors affect noise robustness. We also investigated how robust word detection is to changes in speaker identity by comparing words spoken by known versus unknown speakers during the simulated test. This factor interacted with both noise level and past experience, showing that an increase in exposure is only helpful when a familiar speaker provides the test material. Added variability proved helpful only when encountering an unknown speaker. Finally, we addressed whether infants need to recognise specific words, or whether a more parsimonious explanation of infant behaviour, which we refer to as matching, is sufficient. Recognition involves a focus of attention on a specific target word, while matching only requires finding the best correspondence of acoustic input to a known pattern in the memory. Attending to a specific target word proves to be more noise robust, but a general word matching procedure can be sufficient to simulate experimental data stemming from young infants. A change from acoustic matching to targeted recognition provides an explanation of the improvements observed in infants around their first birthday. In summary, we present a

  18. Hybrid Modelling of Individual Movement and Collective Behaviour

    KAUST Repository

    Franz, Benjamin

    2013-01-01

    Mathematical models of dispersal in biological systems are often written in terms of partial differential equations (PDEs) which describe the time evolution of population-level variables (concentrations, densities). A more detailed modelling approach is given by individual-based (agent-based) models which describe the behaviour of each organism. In recent years, an intermediate modelling methodology - hybrid modelling - has been applied to a number of biological systems. These hybrid models couple an individual-based description of cells/animals with a PDE-model of their environment. In this chapter, we overview hybrid models in the literature with the focus on the mathematical challenges of this modelling approach. The detailed analysis is presented using the example of chemotaxis, where cells move according to extracellular chemicals that can be altered by the cells themselves. In this case, individual-based models of cells are coupled with PDEs for extracellular chemical signals. Travelling waves in these hybrid models are investigated. In particular, we show that in contrary to the PDEs, hybrid chemotaxis models only develop a transient travelling wave. © 2013 Springer-Verlag Berlin Heidelberg.

  19. Hybrid ODE/SSA methods and the cell cycle model

    Science.gov (United States)

    Wang, S.; Chen, M.; Cao, Y.

    2017-07-01

    Stochastic effect in cellular systems has been an important topic in systems biology. Stochastic modeling and simulation methods are important tools to study stochastic effect. Given the low efficiency of stochastic simulation algorithms, the hybrid method, which combines an ordinary differential equation (ODE) system with a stochastic chemically reacting system, shows its unique advantages in the modeling and simulation of biochemical systems. The efficiency of hybrid method is usually limited by reactions in the stochastic subsystem, which are modeled and simulated using Gillespie's framework and frequently interrupt the integration of the ODE subsystem. In this paper we develop an efficient implementation approach for the hybrid method coupled with traditional ODE solvers. We also compare the efficiency of hybrid methods with three widely used ODE solvers RADAU5, DASSL, and DLSODAR. Numerical experiments with three biochemical models are presented. A detailed discussion is presented for the performances of three ODE solvers.

  20. A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

    Science.gov (United States)

    Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

    2015-01-01

    Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

  1. Hybrid Computational Model for High-Altitude Aeroassist Vehicles Project

    Data.gov (United States)

    National Aeronautics and Space Administration — A hybrid continuum/noncontinuum computational model will be developed for analyzing the aerodynamics and heating on aeroassist vehicles. Unique features of this...

  2. Nuclear Hybrid Energy System Modeling: RELAP5 Dynamic Coupling Capabilities

    Energy Technology Data Exchange (ETDEWEB)

    Piyush Sabharwall; Nolan Anderson; Haihua Zhao; Shannon Bragg-Sitton; George Mesina

    2012-09-01

    The nuclear hybrid energy systems (NHES) research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation.

  3. DEVELOPMENT OF A HYBRID MODEL FOR THREE-DIMENSIONAL GIS

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This paper presents a hybrid model for three-dimensional Geographical Information Systems which is an integration of surface- and volume-based models. The Triangulat ed Irregular Network (TIN) and octree models are integrated in this hybrid model. The TIN model works as a surface-based model which mainly serves for surface presentation and visualization. On the other hand, the octree encoding supports volumetric analysis. The designed data structure brings a major advantage in the three-dimensional selective retrieval. This technique increases the efficiency of three-dimensional data operation.

  4. Two-compartment model for competitive hybridization on molecular biochips

    Science.gov (United States)

    Chechetkin, V. R.

    2007-01-01

    During competitive hybridization the specific and non-specific fractions of tested biomolecules in solution bind jointly with the specific probes immobilized in a separate cell of a microchip. The application of two-compartment model to the two-component hybridization allows analytically investigating the underlying kinetics. It is shown that the behaviour with the non-monotonous growth of complexes formed by the non-specific fraction on a probe cell is a typical feature of competitive hybridization for both diffusion-limited and reaction-limited kinetics. The physical reason behind such an evolution consists in the fact that the characteristic hybridization time for the perfect complexes turns out longer with respect to that for the mismatch complexes. This behaviour should be taken into account for the choice of optimum hybridization and washing conditions for the analysis of specific fraction.

  5. Two-compartment model for competitive hybridization on molecular biochips

    Energy Technology Data Exchange (ETDEWEB)

    Chechetkin, V.R. [Theoretical Department of Division for Perspective Investigations, Troitsk Institute of Innovation and Thermonuclear Investigations (TRINITI), Troitsk, 142190 Moscow Region (Russian Federation)]. E-mail: chechet@biochip.ru

    2007-01-08

    During competitive hybridization the specific and non-specific fractions of tested biomolecules in solution bind jointly with the specific probes immobilized in a separate cell of a microchip. The application of two-compartment model to the two-component hybridization allows analytically investigating the underlying kinetics. It is shown that the behaviour with the non-monotonous growth of complexes formed by the non-specific fraction on a probe cell is a typical feature of competitive hybridization for both diffusion-limited and reaction-limited kinetics. The physical reason behind such an evolution consists in the fact that the characteristic hybridization time for the perfect complexes turns out longer with respect to that for the mismatch complexes. This behaviour should be taken into account for the choice of optimum hybridization and washing conditions for the analysis of specific fraction.

  6. A hybrid Scatter/Transform cloaking model

    Directory of Open Access Journals (Sweden)

    Gad Licht

    2015-01-01

    Full Text Available A new Scatter/Transform cloak is developed that combines the light bending of refraction characteristic of a Transform cloak with the scatter cancellation characteristic of a Scatter cloak. The hybrid cloak incorporates both Transform’s variable index of refraction with modified linear intrusions to maximize the Scatter cloak effect. Scatter/Transform improved the scattering cross-section of cloaking in a 2-dimensional space to 51.7% compared to only 39.6% or 45.1% respectively with either Scatter or Transform alone. Metamaterials developed with characteristics based on the new ST hybrid cloak will exhibit superior cloaking capabilities.

  7. The development of a mathematical model of a hybrid airship

    Science.gov (United States)

    Abdul Ghaffar, Alia Farhana

    The mathematical model of a winged hybrid airship is developed for the analysis of its dynamic stability characteristics. A full nonlinear equation of motion that describes the dynamics of the hybrid airship is determined and for completeness, some of the components in the equations are estimated using the appropriate methods that has been established and used in the past. Adequate assumptions are made in order to apply any relevant computation and estimation methods. While this hybrid airship design is unique, its modeling and stability analysis were done according to the typical procedure of conventional airships and aircrafts. All computations pertaining to the hybrid airship's equation of motion are carried out and any issues related to the integration of the wing to the conventional airship design are discussed in this thesis. The design of the hybrid airship is also slightly modified to suit the demanding requirement of a complete and feasible mathematical model. Then, linearization is performed under a chosen trim condition, and eigenvalue analysis is carried out to determine the general dynamic stability characteristics of the winged hybrid airship. The result shows that the winged hybrid airship possesses dynamic instability in longitudinal pitch motion and lateral-directional slow roll motion. This is due to the strong coupling between the aerostatic lift from the buoyant gas and aerodynamic lift from the wing.

  8. Exploratory Topology Modelling of Form-Active Hybrid Structures

    DEFF Research Database (Denmark)

    Holden Deleuran, Anders; Pauly, Mark; Tamke, Martin;

    2016-01-01

    The development of novel form-active hybrid structures (FAHS) is impeded by a lack of modelling tools that allow for exploratory topology modelling of shaped assemblies. We present a flexible and real-time computational design modelling pipeline developed for the exploratory modelling of FAHS tha...

  9. Data assimilation using a hybrid ice flow model

    Directory of Open Access Journals (Sweden)

    D. N. Goldberg

    2010-10-01

    Full Text Available Hybrid models, or depth-integrated flow models that include the effect of both longitudinal stresses and vertical shearing, are becoming more prevalent in dynamical ice modeling. Under a wide range of conditions they closely approximate the well-known First Order stress balance, yet are of computationally lower dimension, and thus require less intensive resources. Concomitant with the development and use of these models is the need to perform inversions of observed data. Here, an inverse control method is extended to use a hybrid flow model as a forward model. We derive an adjoint of a hybrid model and use it for inversion of ice-stream basal traction from observed surface velocities. A novel aspect of the adjoint derivation is a retention of non-linearities in Glen's flow law. Experiments show that including those nonlinearities is advantageous in minimization of the cost function, yielding a more efficient inversion procedure.

  10. Hybrid modeling of xanthan gum bioproduction in batch bioreactor.

    Science.gov (United States)

    Zabot, Giovani L; Mecca, Jaqueline; Mesomo, Michele; Silva, Marceli F; Prá, Valéria Dal; de Oliveira, Débora; Oliveira, J Vladimir; Castilhos, Fernanda; Treichel, Helen; Mazutti, Marcio A

    2011-10-01

    This work is focused on hybrid modeling of xanthan gum bioproduction process by Xanthomonas campestris pv. mangiferaeindicae. Experiments were carried out to evaluate the effects of stirred speed and superficial gas velocity on the kinetics of cell growth, lactose consumption and xanthan gum production in a batch bioreactor using cheese whey as substrate. A hybrid model was employed to simulate the bio-process making use of an artificial neural network (ANN) as a kinetic parameter estimator for the phenomenological model. The hybrid modeling of the process provided a satisfactory fitting quality of the experimental data, since this approach makes possible the incorporation of the effects of operational variables on model parameters. The applicability of the validated model was investigated, using the model as a process simulator to evaluate the effects of initial cell and lactose concentration in the xanthan gum production.

  11. Hybrid reliability model for fatigue reliability analysis of steel bridges

    Institute of Scientific and Technical Information of China (English)

    曹珊珊; 雷俊卿

    2016-01-01

    A kind of hybrid reliability model is presented to solve the fatigue reliability problems of steel bridges. The cumulative damage model is one kind of the models used in fatigue reliability analysis. The parameter characteristics of the model can be described as probabilistic and interval. The two-stage hybrid reliability model is given with a theoretical foundation and a solving algorithm to solve the hybrid reliability problems. The theoretical foundation is established by the consistency relationships of interval reliability model and probability reliability model with normally distributed variables in theory. The solving process is combined with the definition of interval reliability index and the probabilistic algorithm. With the consideration of the parameter characteristics of theS−N curve, the cumulative damage model with hybrid variables is given based on the standards from different countries. Lastly, a case of steel structure in the Neville Island Bridge is analyzed to verify the applicability of the hybrid reliability model in fatigue reliability analysis based on the AASHTO.

  12. A hybrid random field model for scalable statistical learning.

    Science.gov (United States)

    Freno, A; Trentin, E; Gori, M

    2009-01-01

    This paper introduces hybrid random fields, which are a class of probabilistic graphical models aimed at allowing for efficient structure learning in high-dimensional domains. Hybrid random fields, along with the learning algorithm we develop for them, are especially useful as a pseudo-likelihood estimation technique (rather than a technique for estimating strict joint probability distributions). In order to assess the generality of the proposed model, we prove that the class of pseudo-likelihood distributions representable by hybrid random fields strictly includes the class of joint probability distributions representable by Bayesian networks. Once we establish this result, we develop a scalable algorithm for learning the structure of hybrid random fields, which we call 'Markov Blanket Merging'. On the one hand, we characterize some complexity properties of Markov Blanket Merging both from a theoretical and from the experimental point of view, using a series of synthetic benchmarks. On the other hand, we evaluate the accuracy of hybrid random fields (as learned via Markov Blanket Merging) by comparing them to various alternative statistical models in a number of pattern classification and link-prediction applications. As the results show, learning hybrid random fields by the Markov Blanket Merging algorithm not only reduces significantly the computational cost of structure learning with respect to several considered alternatives, but it also leads to models that are highly accurate as compared to the alternative ones.

  13. 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.

  14. Hybrid Aging Delay Model Considering the PBTI and TDDB

    Institute of Scientific and Technical Information of China (English)

    Yong Miao; Mao-Xiang Yi; Gui-Mao Zhang; Da-Wen Xu

    2015-01-01

    Abstract-With a 45nm process technique, the shrinking silicon feature size brings in a high-k/metal gate which significantly exacerbates the positive bias temperature instability (PBTI) and time-dependent dielectric breakdown (TDDB) effects of a NMOS transistor. However, previous works presented delay models to characterize the PBTI or TDDB individually. This paper demonstrates that the delay caused by the joint effects of PBTI and TDDB widely differs from the cumulated result of the delay caused by the PBTI and TDDB, respectively, with the experiments on an inverter chain. This paper proposes a hybrid aging delay model comprising both the PBTI and TDDB effects by analyzing the relationship between the aging propagation delay and the inherent delay of the gate. Experimental results on the logic gates under 45nm, 32 nm, 22nm, and 16nm CMOS technologies show that the maximum error between the proposed model and the actual value is less than 2.5%, meanwhile the average error is about 1.5%.

  15. Fluid Survival Tool: A Model Checker for Hybrid Petri Nets

    NARCIS (Netherlands)

    Postema, Björn; Remke, Anne; Haverkort, Boudewijn R.; Ghasemieh, Hamed

    2014-01-01

    Recently, algorithms for model checking Stochastic Time Logic (STL) on Hybrid Petri nets with a single general one-shot transition (HPNG) have been introduced. This paper presents a tool for model checking HPNG models against STL formulas. A graphical user interface (GUI) not only helps to demonstra

  16. Nuclear Hybrid Energy System Model Stability Testing

    Energy Technology Data Exchange (ETDEWEB)

    Greenwood, Michael Scott [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-04-01

    A Nuclear Hybrid Energy System (NHES) uses a nuclear reactor as the basic power generation unit, and the power generated is used by multiple customers as combinations of thermal power or electrical power. The definition and architecture of a particular NHES can be adapted based on the needs and opportunities of different localities and markets. For example, locations in need of potable water may be best served by coupling a desalination plant to the NHES. Similarly, a location near oil refineries may have a need for emission-free hydrogen production. Using the flexible, multi-domain capabilities of Modelica, Argonne National Laboratory, Idaho National Laboratory, and Oak Ridge National Laboratory are investigating the dynamics (e.g., thermal hydraulics and electrical generation/consumption) and cost of a hybrid system. This paper examines the NHES work underway, emphasizing the control system developed for individual subsystems and the overall supervisory control system.

  17. Nonlinear lower hybrid modeling in tokamak plasmas

    Energy Technology Data Exchange (ETDEWEB)

    Napoli, F.; Schettini, G. [Università Roma Tre, Dipartimento di Ingegneria, Roma (Italy); Castaldo, C.; Cesario, R. [Associazione EURATOM/ENEA sulla Fusione, Centro Ricerche Frascati (Italy)

    2014-02-12

    We present here new results concerning the nonlinear mechanism underlying the observed spectral broadening produced by parametric instabilities occurring at the edge of tokamak plasmas in present day LHCD (lower hybrid current drive) experiments. Low frequency (LF) ion-sound evanescent modes (quasi-modes) are the main parametric decay channel which drives a nonlinear mode coupling of lower hybrid (LH) waves. The spectrum of the LF fluctuations is calculated here considering the beating of the launched LH wave at the radiofrequency (RF) operating line frequency (pump wave) with the noisy background of the RF power generator. This spectrum is calculated in the frame of the kinetic theory, following a perturbative approach. Numerical solutions of the nonlinear LH wave equation show the evolution of the nonlinear mode coupling in condition of a finite depletion of the pump power. The role of the presence of heavy ions in a Deuterium plasma in mitigating the nonlinear effects is analyzed.

  18. Pseudospectral Model for Hybrid PIC Hall-effect Thruster Simulation

    Science.gov (United States)

    2015-07-01

    1149. 8Goebel, D. M. and Katz, I., Fundamentals of Electric Propulsion : Ion and Hall Thrusters, John Wiley & Sons, Inc., 2008. 9Martin, R., J.W., K...Bilyeu, D., and Tran, J., “Dynamic Particle Weight Remapping in Hybrid PIC Hall -effect Thruster Simulation,” 34th Int. Electric Propulsion Conf...Paper 3. DATES COVERED (From - To) July 2015-July 2015 4. TITLE AND SUBTITLE Pseudospectral model for hybrid PIC Hall -effect thruster simulationect

  19. Hybrid Modeling and Optimization of Yogurt Starter Culture Continuous Fermentation

    Directory of Open Access Journals (Sweden)

    Silviya Popova

    2009-10-01

    Full Text Available The present paper presents a hybrid model of yogurt starter mixed culture fermentation. The main nonlinearities within a classical structure of continuous process model are replaced by neural networks. The new hybrid model accounts for the dependence of the two microorganisms' kinetics from the on-line measured characteristics of the culture medium - pH. Then the model was used further for calculation of the optimal time profile of pH. The obtained results are with agreement with the experimental once.

  20. Mechanisms Underlying Mammalian Hybrid Sterility in Two Feline Interspecies Models.

    Science.gov (United States)

    Davis, Brian W; Seabury, Christopher M; Brashear, Wesley A; Li, Gang; Roelke-Parker, Melody; Murphy, William J

    2015-10-01

    The phenomenon of male sterility in interspecies hybrids has been observed for over a century, however, few genes influencing this recurrent phenotype have been identified. Genetic investigations have been primarily limited to a small number of model organisms, thus limiting our understanding of the underlying molecular basis of this well-documented "rule of speciation." We utilized two interspecies hybrid cat breeds in a genome-wide association study employing the Illumina 63 K single-nucleotide polymorphism array. Collectively, we identified eight autosomal genes/gene regions underlying associations with hybrid male sterility (HMS) involved in the function of the blood-testis barrier, gamete structural development, and transcriptional regulation. We also identified several candidate hybrid sterility regions on the X chromosome, with most residing in close proximity to complex duplicated regions. Differential gene expression analyses revealed significant chromosome-wide upregulation of X chromosome transcripts in testes of sterile hybrids, which were enriched for genes involved in chromatin regulation of gene expression. Our expression results parallel those reported in Mus hybrids, supporting the "Large X-Effect" in mammalian HMS and the potential epigenetic basis for this phenomenon. These results support the value of the interspecies feline model as a powerful tool for comparison to rodent models of HMS, demonstrating unique aspects and potential commonalities that underpin mammalian reproductive isolation.

  1. Constraining hybrid inflation models with WMAP three-year results

    CERN Document Server

    Cardoso, A

    2006-01-01

    We reconsider the original model of quadratic hybrid inflation in light of the WMAP three-year results and study the possibility of obtaining a spectral index of primordial density perturbations, $n_s$, smaller than one from this model. The original hybrid inflation model naturally predicts $n_s\\geq1$ in the false vacuum dominated regime but it is also possible to have $n_s<1$ when the quadratic term dominates. We therefore investigate whether there is also an intermediate regime compatible with the latest constraints, where the scalar field value during the last 50 e-folds of inflation is less than the Planck scale.

  2. Runoff prediction using an integrated hybrid modelling scheme

    Science.gov (United States)

    Remesan, Renji; Shamim, Muhammad Ali; Han, Dawei; Mathew, Jimson

    2009-06-01

    SummaryRainfall runoff is a very complicated process due to its nonlinear and multidimensional dynamics, and hence difficult to model. There are several options for a modeller to consider, for example: the type of input data to be used, the length of model calibration (training) data and whether or not the input data be treated as signals with different frequency bands so that they can be modelled separately. This paper describes a new hybrid modelling scheme to answer the above mentioned questions. The proposed methodology is based on a hybrid model integrating wavelet transformation, a modelling engine (Artificial Neural Network) and the Gamma Test. First, the Gamma Test is used to decide the required input data dimensions and its length. Second, the wavelet transformation decomposes the input signals into different frequency bands. Finally, a modelling engine (ANN in this study) is used to model the decomposed signals separately. The proposed scheme was tested using the Brue catchment, Southwest England, as a case study and has produced very positive results. The hybrid model outperforms all other models tested. This study has a wider implication in the hydrological modelling field since its general framework could be applied to other model combinations (e.g., model engine could be Support Vector Machines, neuro-fuzzy systems, or even a conceptual model. The signal decomposition could be carried out by Fourier transformation).

  3. Hybrid continuum-atomistic approach to model electrokinetics in nanofluidics

    Energy Technology Data Exchange (ETDEWEB)

    Amani, Ehsan, E-mail: eamani@aut.ac.ir; Movahed, Saeid, E-mail: smovahed@aut.ac.ir

    2016-06-07

    In this study, for the first time, a hybrid continuum-atomistic based model is proposed for electrokinetics, electroosmosis and electrophoresis, through nanochannels. Although continuum based methods are accurate enough to model fluid flow and electric potential in nanofluidics (in dimensions larger than 4 nm), ionic concentration is too low in nanochannels for the continuum assumption to be valid. On the other hand, the non-continuum based approaches are too time-consuming and therefore is limited to simple geometries, in practice. Here, to propose an efficient hybrid continuum-atomistic method of modelling the electrokinetics in nanochannels; the fluid flow and electric potential are computed based on continuum hypothesis coupled with an atomistic Lagrangian approach for the ionic transport. The results of the model are compared to and validated by the results of the molecular dynamics technique for a couple of case studies. Then, the influences of bulk ionic concentration, external electric field, size of nanochannel, and surface electric charge on the electrokinetic flow and ionic mass transfer are investigated, carefully. The hybrid continuum-atomistic method is a promising approach to model more complicated geometries and investigate more details of the electrokinetics in nanofluidics. - Highlights: • A hybrid continuum-atomistic model is proposed for electrokinetics in nanochannels. • The model is validated by molecular dynamics. • This is a promising approach to model more complicated geometries and physics.

  4. Feller Property for a Special Hybrid Jump-Diffusion Model

    Directory of Open Access Journals (Sweden)

    Jinying Tong

    2014-01-01

    Full Text Available We consider the stochastic stability for a hybrid jump-diffusion model, where the switching here is a phase semi-Markovian process. We first transform the process into a corresponding jump-diffusion with Markovian switching by the supplementary variable technique. Then we prove the Feller and strong Feller properties of the model under some assumptions.

  5. Support for the 7-factor hybrid model of PTSD in a community sample.

    Science.gov (United States)

    Seligowski, Antonia V; Orcutt, Holly K

    2016-03-01

    Research suggests that 4-factor models of posttraumatic stress disorder (PTSD) may be improved upon by the addition of novel factors, such as Dysphoric Arousal, Externalizing Behaviors, and Anhedonia. However, a novel 7-factor hybrid model has demonstrated superior fit in veteran and undergraduate samples. The current study sought to replicate this finding in a trauma-exposed community sample and examined relations with positive (PA) and negative affect (NA). Participants included 403 adults (M(age) = 37.75) recruited through Amazon's MTurk. PTSD was measured using the PTSD Checklist-5 (PCL-5). Confirmatory factor analyses were conducted in Mplus. The 7-factor hybrid model demonstrated good fit: CFI = .96, TLI = .95, RMSEA = .06 (90% CI [.05, .07]), SRMR = .03. This model was superior to the 5- and 6-factor models. All factors demonstrated significant relations with PA and NA, the largest of which were the Externalizing Behaviors (with NA) and Anhedonia (with PA) factors. Results provide support for the 7-factor hybrid model of PTSD using the PCL-5 in a community sample. Findings replicate previous research suggesting that PTSD is highly related to NA, which has been purported as an underlying dimension of PTSD. It is recommended that future research use clinical measures to further examine the hybrid model. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  6. Hybrid programming model for implicit PDE simulations on multicore architectures

    KAUST Repository

    Kaushik, Dinesh K.

    2011-01-01

    The complexity of programming modern multicore processor based clusters is rapidly rising, with GPUs adding further demand for fine-grained parallelism. This paper analyzes the performance of the hybrid (MPI+OpenMP) programming model in the context of an implicit unstructured mesh CFD code. At the implementation level, the effects of cache locality, update management, work division, and synchronization frequency are studied. The hybrid model presents interesting algorithmic opportunities as well: the convergence of linear system solver is quicker than the pure MPI case since the parallel preconditioner stays stronger when hybrid model is used. This implies significant savings in the cost of communication and synchronization (explicit and implicit). Even though OpenMP based parallelism is easier to implement (with in a subdomain assigned to one MPI process for simplicity), getting good performance needs attention to data partitioning issues similar to those in the message-passing case. © 2011 Springer-Verlag.

  7. Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

    Science.gov (United States)

    Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

    2012-08-01

    A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three

  8. A structured modeling approach for dynamic hybrid fuzzy-first principles models

    NARCIS (Netherlands)

    Lith, van Pascal F.; Betlem, Ben H.L.; Roffel, Brian

    2002-01-01

    Hybrid fuzzy-first principles models can be attractive if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented with fuzzy submodels describing additional equations, such as mass transformation and transfer rate

  9. Nuclear Hybrid Energy Systems FY16 Modeling Efforts at ORNL

    Energy Technology Data Exchange (ETDEWEB)

    Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Greenwood, Michael Scott [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Harrison, Thomas J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Qualls, A. L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Guler Yigitoglu, Askin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2016-09-01

    A nuclear hybrid system uses a nuclear reactor as the basic power generation unit. The power generated by the nuclear reactor is utilized by one or more power customers as either thermal power, electrical power, or both. In general, a nuclear hybrid system will couple the nuclear reactor to at least one thermal power user in addition to the power conversion system. The definition and architecture of a particular nuclear hybrid system is flexible depending on local markets needs and opportunities. For example, locations in need of potable water may be best served by coupling a desalination plant to the nuclear system. Similarly, an area near oil refineries may have a need for emission free hydrogen production. A nuclear hybrid system expands the nuclear power plant from its more familiar central power station role by diversifying its immediately and directly connected customer base. The definition, design, analysis, and optimization work currently performed with respect to the nuclear hybrid systems represents the work of three national laboratories. Idaho National Laboratory (INL) is the lead lab working with Argonne National Laboratory (ANL) and Oak Ridge National Laboratory. Each laboratory is providing modeling and simulation expertise for the integration of the hybrid system.

  10. Emotional Belief-Desire-Intention Agent Model: Previous Work And Proposed Architecture

    Directory of Open Access Journals (Sweden)

    Mihaela- Alexandra Puica

    2013-02-01

    Full Text Available Research in affective computing shows that agents cannot be truly intelligent, nor believable or realistic without emotions. In this paper, we present a model of emotional agents that is based on a BDI architecture. We show how we can integrate emotions, resources and personality features into an artificial intelligent agent so as to obtain a human-like behavior of this agent. We place our work in the general context of existing research in emotional agents, with emphasis on BDI emotional models.

  11. MODEL OF LASER-TIG HYBRID WELDING HEAT SOURCE

    Institute of Scientific and Technical Information of China (English)

    Chen Yanbin; Li Liqun; Feng Xiaosong; Fang Junfei

    2004-01-01

    The welding mechanism of laser-TIG hybrid welding process is analyzed. With the variation of arc current, the welding process is divided into two patterns: deep-penetration welding and heat conductive welding. The heat flow model of hybrid welding is presented. As to deep-penetration welding, the heat source includes a surface heat flux and a volume heat flux. The heat source of heat conductive welding is composed of two Gaussian distribute surface heat sources. With this heat source model, a temperature field is calculated. The finite element code MARC is employed for this purpose. The calculation results show a good agreement with the experimental data.

  12. Modeling of hybrid vehicle fuel economy and fuel engine efficiency

    Science.gov (United States)

    Wu, Wei

    "Near-CV" (i.e., near-conventional vehicle) hybrid vehicles, with an internal combustion engine, and a supplementary storage with low-weight, low-energy but high-power capacity, are analyzed. This design avoids the shortcoming of the "near-EV" and the "dual-mode" hybrid vehicles that need a large energy storage system (in terms of energy capacity and weight). The small storage is used to optimize engine energy management and can provide power when needed. The energy advantage of the "near-CV" design is to reduce reliance on the engine at low power, to enable regenerative braking, and to provide good performance with a small engine. The fuel consumption of internal combustion engines, which might be applied to hybrid vehicles, is analyzed by building simple analytical models that reflect the engines' energy loss characteristics. Both diesel and gasoline engines are modeled. The simple analytical models describe engine fuel consumption at any speed and load point by describing the engine's indicated efficiency and friction. The engine's indicated efficiency and heat loss are described in terms of several easy-to-obtain engine parameters, e.g., compression ratio, displacement, bore and stroke. Engine friction is described in terms of parameters obtained by fitting available fuel measurements on several diesel and spark-ignition engines. The engine models developed are shown to conform closely to experimental fuel consumption and motored friction data. A model of the energy use of "near-CV" hybrid vehicles with different storage mechanism is created, based on simple algebraic description of the components. With powertrain downsizing and hybridization, a "near-CV" hybrid vehicle can obtain a factor of approximately two in overall fuel efficiency (mpg) improvement, without considering reductions in the vehicle load.

  13. Literature Survey of previous research work in Models and Methodologies in Project Management

    OpenAIRE

    Ravinder Singh; Dr. Kevin Lano

    2014-01-01

    This paper provides a survey of the existing literature and research carried out in the area of project management using different models, methodologies, and frameworks. Project Management (PM) broadly means programme management, portfolio management, practice management, project management office, etc. A project management system has a set of processes, procedures, framework, methods, tools, methodologies, techniques, resources, etc. which are used to manage the full life cycle of projects. ...

  14. Literature Survey of previous research work in Models and Methodologies in Project Management

    Directory of Open Access Journals (Sweden)

    Ravinder Singh

    2014-09-01

    Full Text Available This paper provides a survey of the existing literature and research carried out in the area of project management using different models, methodologies, and frameworks. Project Management (PM broadly means programme management, portfolio management, practice management, project management office, etc. A project management system has a set of processes, procedures, framework, methods, tools, methodologies, techniques, resources, etc. which are used to manage the full life cycle of projects. This also means to create risk, quality, performance, and other management plans to monitor and manage the projects efficiently and effectively.

  15. Third metacarpal condylar fatigue fractures in equine athletes occur within previously modelled subchondral bone.

    Science.gov (United States)

    Whitton, R Christopher; Trope, Gareth D; Ghasem-Zadeh, Ali; Anderson, Garry A; Parkin, Timothy D H; Mackie, Eleanor J; Seeman, Ego

    2010-10-01

    Bone modelling and remodelling reduce the risk of fatigue fractures; the former by adapting bone to its loading circumstances, the latter by replacing fatigued bone. Remodelling transiently increases porosity because of the normal delay in onset of the formation phase of the remodelling sequence. Protracted intense loading suppresses remodelling leaving modelling as the only means of maintaining bone strength. We therefore hypothesized that race horses with fatigue fractures of the distal third metacarpal bone (MC3) will have reduced porosity associated with suppressed remodelling while continued adaptive modelling will result in higher volume fraction (BV/TV) at this site. Using high resolution peripheral quantitative computed tomography (HR-pQCT), we measured the distal aspect of the MC3 obtained at postmortem from 13 thoroughbred race horses with condylar fractures of the MC3 (cases), 8 horses without fractures (training controls), 14 horses with a fracture at another site (fractured controls) and 9 horses resting from training (resting controls). Porosity of the subchondral bone of MC3 was lower in cases than resting controls (12±1.4% vs. 18±1.6%, P=0.017) although areas of focal porosity were observed adjacent to fractures in 6/13 horses. BV/TV of the distal metacarpal epiphysis tended to be higher in horses with condylar fractures (0.79±0.015) than training controls (0.74±0.019, P=0.070), but also higher in controls with a fracture elsewhere (0.79±0.014) than the training controls (0.74±0.019, P=0.040). BV/TV was higher in horses over three years of age than those aged two or three years (0.79±0.01 vs. 0.74±0.01, P=0.016). All metacarpal condylar fractures occurred within focal areas of high BV/TV. We infer that intense training in equine athletes suppresses remodelling of third metacarpal subchondral bone limiting damage repair while modelling increases regional bone volume in an attempt to minimise local stresses but may fail to offset bone

  16. The innovative concept of three-dimensional hybrid receptor modeling

    Science.gov (United States)

    Stojić, A.; Stanišić Stojić, S.

    2017-09-01

    The aim of this study was to improve the current understanding of air pollution transport processes at regional and long-range scale. For this purpose, three-dimensional (3D) potential source contribution function and concentration weighted trajectory models, as well as new hybrid receptor model, concentration weighted boundary layer (CWBL), which uses a two-dimensional grid and a planetary boundary layer height as a frame of reference, are presented. The refined approach to hybrid receptor modeling has two advantages. At first, it considers whether each trajectory endpoint meets the inclusion criteria based on planetary boundary layer height, which is expected to provide a more realistic representation of the spatial distribution of emission sources and pollutant transport pathways. Secondly, it includes pollutant time series preprocessing to make hybrid receptor models more applicable for suburban and urban locations. The 3D hybrid receptor models presented herein are designed to identify altitude distribution of potential sources, whereas CWBL can be used for analyzing the vertical distribution of pollutant concentrations along the transport pathway.

  17. Fatigue reliability based on residual strength model with hybrid uncertain parameters

    Institute of Scientific and Technical Information of China (English)

    Jun Wang; Zhi-Ping Qiu

    2012-01-01

    The aim of this paper is to evaluate the fatigue reliability with hybrid uncertain parameters based on a residual strength model.By solving the non-probabilistic setbased reliability problem and analyzing the reliability with randomness,the fatigue reliability with hybrid parameters can be obtained.The presented hybrid model can adequately consider all uncertainties affecting the fatigue reliability with hybrid uncertain parameters.A comparison among the presented hybrid model,non-probabilistic set-theoretic model and the conventional random model is made through two typical numerical examples.The results show that the presented hybrid model,which can ensure structural security,is effective and practical.

  18. Battery thermal models for hybrid vehicle simulations

    Science.gov (United States)

    Pesaran, Ahmad A.

    This paper summarizes battery thermal modeling capabilities for: (1) an advanced vehicle simulator (ADVISOR); and (2) battery module and pack thermal design. The National Renewable Energy Laboratory's (NREL's) ADVISOR is developed in the Matlab/Simulink environment. There are several battery models in ADVISOR for various chemistry types. Each one of these models requires a thermal model to predict the temperature change that could affect battery performance parameters, such as resistance, capacity and state of charges. A lumped capacitance battery thermal model in the Matlab/Simulink environment was developed that included the ADVISOR battery performance models. For thermal evaluation and design of battery modules and packs, NREL has been using various computer aided engineering tools including commercial finite element analysis software. This paper will discuss the thermal ADVISOR battery model and its results, along with the results of finite element modeling that were presented at the workshop on "Development of Advanced Battery Engineering Models" in August 2001.

  19. Mechanical and histological characterization of the abdominal muscle. A previous step to modelling hernia surgery.

    Science.gov (United States)

    Hernández, B; Peña, E; Pascual, G; Rodríguez, M; Calvo, B; Doblaré, M; Bellón, J M

    2011-04-01

    The aims of this study are to experimentally characterize the passive elastic behaviour of the rabbit abdominal wall and to develop a mechanical constitutive law which accurately reproduces the obtained experimental results. For this purpose, tissue samples from New Zealand White rabbits 2150±50 (g) were mechanically tested in vitro. Mechanical tests, consisting of uniaxial loading on tissue samples oriented along the craneo-caudal and the perpendicular directions, respectively, revealed the anisotropic non-linear mechanical behaviour of the abdominal tissues. Experiments were performed considering the composite muscle (including external oblique-EO, internal oblique-IO and transverse abdominis-TA muscle layers), as well as separated muscle layers (i.e., external oblique, and the bilayer formed by internal oblique and transverse abdominis). Both the EO muscle layer and the IO-TA bilayer demonstrated a stiffer behaviour along the transversal direction to muscle fibres than along the longitudinal one. The fibre arrangement was measured by means of a histological study which confirmed that collagen fibres are mainly responsible for the passive mechanical strength and stiffness. Furthermore, the degree of anisotropy of the abdominal composite muscle turned out to be less pronounced than those obtained while studying the EO and IO-TA separately. Moreover, a phenomenological constitutive law was used to capture the measured experimental curves. A Levenberg-Marquardt optimization algorithm was used to fit the model constants to reproduce the experimental curves. Copyright © 2010 Elsevier Ltd. All rights reserved.

  20. A linear dispersion relation for the hybrid kinetic-ion/fluid-electron model of plasma physics

    CERN Document Server

    Told, Daniel; Astfalk, Patrick; Jenko, Frank

    2016-01-01

    A dispersion relation for a commonly used hybrid model of plasma physics is developed, which combines fully kinetic ions and a massless-electron fluid description. Although this model and variations of it have been used to describe plasma phenomena for about 40 years, to date there exists no general dispersion relation to describe the linear wave physics contained in the model. Previous efforts along these lines are extended here to retain arbitrary wave propagation angles, temperature anisotropy effects, as well as additional terms in the generalized Ohm's law which determines the electric field. A numerical solver for the dispersion relation is developed, and linear wave physics is benchmarked against solutions of a full Vlasov-Maxwell dispersion relation solver. This work opens the door to a more accurate interpretation of existing and future wave and turbulence simulations using this type of hybrid model.

  1. Efficient Proof Engines for Bounded Model Checking of Hybrid Systems

    DEFF Research Database (Denmark)

    Fränzle, Martin; Herde, Christian

    2005-01-01

    In this paper we present HySat, a new bounded model checker for linear hybrid systems, incorporating a tight integration of a DPLL-based pseudo-Boolean SAT solver and a linear programming routine as core engine. In contrast to related tools like MathSAT, ICS, or CVC, our tool exploits all...

  2. 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.

  3. (Hybrid) Baryons in the Flux-Tube Model

    CERN Document Server

    Page, P R

    1999-01-01

    We construct baryons and hybrid baryons in the non-relativistic flux-tube model of Isgur and Paton. The motion of the flux-tube with the three quark positions fixed, except for centre of mass corrections, is discussed. It is shown that the problem can to an excellent approximation be reduced to the independent motion of a junction and strings.

  4. New Models of Hybrid Leadership in Global Higher Education

    Science.gov (United States)

    Tonini, Donna C.; Burbules, Nicholas C.; Gunsalus, C. K.

    2016-01-01

    This manuscript highlights the development of a leadership preparation program known as the Nanyang Technological University Leadership Academy (NTULA), exploring the leadership challenges unique to a university undergoing rapid growth in a highly multicultural context, and the hybrid model of leadership it developed in response to globalization.…

  5. Incorporating RTI in a Hybrid Model of Reading Disability

    Science.gov (United States)

    Spencer, Mercedes; Wagner, Richard K.; Schatschneider, Christopher; Quinn, Jamie M.; Lopez, Danielle; Petscher, Yaacov

    2014-01-01

    The present study seeks to evaluate a hybrid model of identification that incorporates response to instruction and intervention (RTI) as one of the key symptoms of reading disability. The 1-year stability of alternative operational definitions of reading disability was examined in a large-scale sample of students who were followed longitudinally…

  6. Liver growth factor treatment reverses emphysema previously established in a cigarette smoke exposure mouse model.

    Science.gov (United States)

    Pérez-Rial, Sandra; Del Puerto-Nevado, Laura; Girón-Martínez, Alvaro; Terrón-Expósito, Raúl; Díaz-Gil, Juan J; González-Mangado, Nicolás; Peces-Barba, Germán

    2014-11-01

    Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disease largely associated with cigarette smoke exposure (CSE) and characterized by pulmonary and extrapulmonary manifestations, including systemic inflammation. Liver growth factor (LGF) is an albumin-bilirubin complex with demonstrated antifibrotic, antioxidant, and antihypertensive actions even at extrahepatic sites. We aimed to determine whether short LGF treatment (1.7 μg/mouse ip; 2 times, 2 wk), once the lung damage was established through the chronic CSE, contributes to improvement of the regeneration of damaged lung tissue, reducing systemic inflammation. We studied AKR/J mice, divided into three groups: control (air-exposed), CSE (chronic CSE), and CSE + LGF (LGF-treated CSE mice). We assessed pulmonary function, morphometric data, and levels of various systemic inflammatory markers to test the LGF regenerative capacity in this system. Our results revealed that the lungs of the CSE animals showed pulmonary emphysema and inflammation, characterized by increased lung compliance, enlargement of alveolar airspaces, systemic inflammation (circulating leukocytes and serum TNF-α level), and in vivo lung matrix metalloproteinase activity. LGF treatment was able to reverse all these parameters, decreasing total cell count in bronchoalveolar lavage fluid and T-lymphocyte infiltration in peripheral blood observed in emphysematous mice and reversing the decrease in monocytes observed in chronic CSE mice, and tends to reduce the neutrophil population and serum TNF-α level. In conclusion, LGF treatment normalizes the physiological and morphological parameters and levels of various systemic inflammatory biomarkers in a chronic CSE AKR/J model, which may have important pathophysiological and therapeutic implications for subjects with stable COPD.

  7. Hybrid multiscale modeling and prediction of cancer cell behavior.

    Science.gov (United States)

    Zangooei, Mohammad Hossein; Habibi, Jafar

    2017-01-01

    Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.

  8. Brain anatomical structure segmentation by hybrid discriminative/generative models.

    Science.gov (United States)

    Tu, Z; Narr, K L; Dollar, P; Dinov, I; Thompson, P M; Toga, A W

    2008-04-01

    In this paper, a hybrid discriminative/generative model for brain anatomical structure segmentation is proposed. The learning aspect of the approach is emphasized. In the discriminative appearance models, various cues such as intensity and curvatures are combined to locally capture the complex appearances of different anatomical structures. A probabilistic boosting tree (PBT) framework is adopted to learn multiclass discriminative models that combine hundreds of features across different scales. On the generative model side, both global and local shape models are used to capture the shape information about each anatomical structure. The parameters to combine the discriminative appearance and generative shape models are also automatically learned. Thus, low-level and high-level information is learned and integrated in a hybrid model. Segmentations are obtained by minimizing an energy function associated with the proposed hybrid model. Finally, a grid-face structure is designed to explicitly represent the 3-D region topology. This representation handles an arbitrary number of regions and facilitates fast surface evolution. Our system was trained and tested on a set of 3-D magnetic resonance imaging (MRI) volumes and the results obtained are encouraging.

  9. Hybrid modelling of a sugar boiling process

    CERN Document Server

    Lauret, Alfred Jean Philippe; Gatina, Jean Claude

    2012-01-01

    The first and maybe the most important step in designing a model-based predictive controller is to develop a model that is as accurate as possible and that is valid under a wide range of operating conditions. The sugar boiling process is a strongly nonlinear and nonstationary process. The main process nonlinearities are represented by the crystal growth rate. This paper addresses the development of the crystal growth rate model according to two approaches. The first approach is classical and consists of determining the parameters of the empirical expressions of the growth rate through the use of a nonlinear programming optimization technique. The second is a novel modeling strategy that combines an artificial neural network (ANN) as an approximator of the growth rate with prior knowledge represented by the mass balance of sucrose crystals. The first results show that the first type of model performs local fitting while the second offers a greater flexibility. The two models were developed with industrial data...

  10. Hybrid Sludge Modeling in Water Treatment Processes

    OpenAIRE

    Brenda, Marian

    2015-01-01

    Sludge occurs in many waste water and drinking water treatment processes. The numeric modeling of sludge is therefore crucial for developing and optimizing water treatment processes. Numeric single-phase sludge models mainly include settling and viscoplastic behavior. Even though many investigators emphasize the importance of modeling the rheology of sludge for good simulation results, it is difficult to measure, because of settling and the viscoplastic behavior. In this thesis, a new method ...

  11. Modelling and analysis of real-time and hybrid systems

    Energy Technology Data Exchange (ETDEWEB)

    Olivero, A.

    1994-09-29

    This work deals with the modelling and analysis of real-time and hybrid systems. We first present the timed-graphs as model for the real-time systems and we recall the basic notions of the analysis of real-time systems. We describe the temporal properties on the timed-graphs using TCTL formulas. We consider two methods for property verification: in one hand we study the symbolic model-checking (based on backward analysis) and in the other hand we propose a verification method derived of the construction of the simulation graph (based on forward analysis). Both methods have been implemented within the KRONOS verification tool. Their application for the automatic verification on several real-time systems confirms the practical interest of our approach. In a second part we study the hybrid systems, systems combining discrete components with continuous ones. As in the general case the analysis of this king of systems is not decidable, we identify two sub-classes of hybrid systems and we give a construction based method for the generation of a timed-graph from an element into the sub-classes. We prove that in one case the timed-graph obtained is bi-similar with the considered system and that there exists a simulation in the other case. These relationships allow the application of the described technics on the hybrid systems into the defined sub-classes. (authors). 60 refs., 43 figs., 8 tabs., 2 annexes.

  12. A hybrid parallel framework for the cellular Potts model simulations

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Yi [Los Alamos National Laboratory; He, Kejing [SOUTH CHINA UNIV; Dong, Shoubin [SOUTH CHINA UNIV

    2009-01-01

    The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approach achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).

  13. QCD Phase Transition in a new Hybrid Model Formulation

    CERN Document Server

    Srivastava, P K

    2013-01-01

    Search of a proper and realistic equations of state (EOS) for strongly interacting matter used in the study of QCD phase diagram still appears as a challenging task. Recently, we have constructed a hybrid model description for the quark gluon plasma (QGP) as well as hadron gas (HG) phases where we use a new excluded-volume model for HG and a thermodynamically-consistent quasiparticle model for the QGP phase. We attempt to use them to get a QCD phase boundary and a critical point. We test our hybrid model by reproducing the entire lattice QCD data for strongly interacting matter at zero baryon chemical potential ($\\mu_{B}$)and predict the results at finite $\\mu_{B}$ and $T$.

  14. Strongly Interacting Matter at Finite Chemical Potential: Hybrid Model Approach

    Science.gov (United States)

    Srivastava, P. K.; Singh, C. P.

    2013-06-01

    Search for a proper and realistic equation of state (EOS) for strongly interacting matter used in the study of the QCD phase diagram still appears as a challenging problem. Recently, we constructed a hybrid model description for the quark-gluon plasma (QGP) as well as hadron gas (HG) phases where we used an excluded volume model for HG and a thermodynamically consistent quasiparticle model for the QGP phase. The hybrid model suitably describes the recent lattice results of various thermodynamical as well as transport properties of the QCD matter at zero baryon chemical potential (μB). In this paper, we extend our investigations further in obtaining the properties of QCD matter at finite value of μB and compare our results with the most recent results of lattice QCD calculation.

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

    OpenAIRE

    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 faulty outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeate...

  16. Hybrid Neuro-Fuzzy Classifier Based On Nefclass Model

    Directory of Open Access Journals (Sweden)

    Bogdan Gliwa

    2011-01-01

    Full Text Available The paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which wasmodified. The presented classifier was compared to popular classifiers – neural networks andk-nearest neighbours. Efficiency of modifications in classifier was compared with methodsused in original model NEFCLASS (learning methods. Accuracy of classifier was testedusing 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wisconsin.Moreover, influence of ensemble classification methods on classification accuracy waspresented.

  17. Advanced Geometric Modeler with Hybrid Representation

    Institute of Scientific and Technical Information of China (English)

    杨长贵; 陈玉健; 等

    1996-01-01

    An advanced geometric modeler GEMS4.0 has been developed,in which feature representation is used at the highest level abstraction of a product model.Boundary representation is used at the bottom level,while CSG model is adopted at the median level.A BRep data structure capable of modeling non-manifold is adopted.UNRBS representation is used for all curved surfaces,Quadric surfaces have dual representations consisting of their geometric data such as radius,center point,and center axis.Boundary representation of free form surfaces is easily built by sweeping and skinning method with NURBS geometry.Set operations on curved solids with boundary representation are performed by an evaluation process consisting of four steps.A file exchange facility is provided for the conversion between product data described by STEP and product information generated by GEMS4.0.

  18. Long-wave approximation for hybridization modeling of local surface plasmonic resonance in nanoshells.

    Science.gov (United States)

    Li, Ben Q; Liu, Changhong

    2011-01-15

    A hybridization model for the localized surface plasmon resonance of a nanoshell is developed within the framework of long-wave approximation. Compared with the existing hybridization model derived from the hydrodynamic simulation of free electron gas, this approach is much simpler and gives identical results for a concentric nanoshell. Also, with this approach, the limitations associated with the original hybridization model are succinctly stated. Extension of this approach to hybridization modeling of more complicated structures such as multiplayered nanoshells is straightforward.

  19. Enhanced hybrid search algorithm for protein structure prediction using the 3D-HP lattice model.

    Science.gov (United States)

    Zhou, Changjun; Hou, Caixia; Zhang, Qiang; Wei, Xiaopeng

    2013-09-01

    The problem of protein structure prediction in the hydrophobic-polar (HP) lattice model is the prediction of protein tertiary structure. This problem is usually referred to as the protein folding problem. This paper presents a method for the application of an enhanced hybrid search algorithm to the problem of protein folding prediction, using the three dimensional (3D) HP lattice model. The enhanced hybrid search algorithm is a combination of the particle swarm optimizer (PSO) and tabu search (TS) algorithms. Since the PSO algorithm entraps local minimum in later evolution extremely easily, we combined PSO with the TS algorithm, which has properties of global optimization. Since the technologies of crossover and mutation are applied many times to PSO and TS algorithms, so enhanced hybrid search algorithm is called the MCMPSO-TS (multiple crossover and mutation PSO-TS) algorithm. Experimental results show that the MCMPSO-TS algorithm can find the best solutions so far for the listed benchmarks, which will help comparison with any future paper approach. Moreover, real protein sequences and Fibonacci sequences are verified in the 3D HP lattice model for the first time. Compared with the previous evolutionary algorithms, the new hybrid search algorithm is novel, and can be used effectively to predict 3D protein folding structure. With continuous development and changes in amino acids sequences, the new algorithm will also make a contribution to the study of new protein sequences.

  20. Hybrid grey model to forecast monitoring series with seasonality

    Institute of Scientific and Technical Information of China (English)

    WANG Qi-jie; LIAO Xin-hao; ZHOU Yong-hong; ZOU Zheng-rong; ZHU Jian-jun; PENG Yue

    2005-01-01

    The grey forecasting model has been successfully applied to many fields. However, the precision of GM(1,1) model is not high. In order to remove the seasonal fluctuations in monitoring series before building GM(1,1) model, the forecasting series of GM(1,1) was built, and an inverse process was used to resume the seasonal fluctuations. Two deseasonalization methods were presented , i.e., seasonal index-based deseasonalization and standard normal distribution-based deseasonalization. They were combined with the GM(1,1) model to form hybrid grey models. A simple but practical method to further improve the forecasting results was also suggested. For comparison, a conventional periodic function model was investigated. The concept and algorithms were tested with four years monthly monitoring data. The results show that on the whole the seasonal index-GM(1,1) model outperform the conventional periodic function model and the conventional periodic function model outperform the SND-GM(1,1) model. The mean absolute error and mean square error of seasonal index-GM(1,1) are 30.69% and 54.53% smaller than that of conventional periodic function model, respectively. The high accuracy, straightforward and easy implementation natures of the proposed hybrid seasonal index-grey model make it a powerful analysis technique for seasonal monitoring series.

  1. Multiview coding mode decision with hybrid optimal stopping model.

    Science.gov (United States)

    Zhao, Tiesong; Kwong, Sam; Wang, Hanli; Wang, Zhou; Pan, Zhaoqing; Kuo, C-C Jay

    2013-04-01

    In a generic decision process, optimal stopping theory aims to achieve a good tradeoff between decision performance and time consumed, with the advantages of theoretical decision-making and predictable decision performance. In this paper, optimal stopping theory is employed to develop an effective hybrid model for the mode decision problem, which aims to theoretically achieve a good tradeoff between the two interrelated measurements in mode decision, as computational complexity reduction and rate-distortion degradation. The proposed hybrid model is implemented and examined with a multiview encoder. To support the model and further promote coding performance, the multiview coding mode characteristics, including predicted mode probability and estimated coding time, are jointly investigated with inter-view correlations. Exhaustive experimental results with a wide range of video resolutions reveal the efficiency and robustness of our method, with high decision accuracy, negligible computational overhead, and almost intact rate-distortion performance compared to the original encoder.

  2. Whispered speaker identification based on feature and model hybrid compensation

    Institute of Scientific and Technical Information of China (English)

    GU Xiaojiang; ZHAO Heming; Lu Gang

    2012-01-01

    In order to increase short time whispered speaker recognition rate in variable chan- nel conditions, the hybrid compensation in model and feature domains was proposed. This method is based on joint factor analysis in training model stage. It extracts speaker factor and eliminates channel factor by estimating training speech speaker and channel spaces. Then in the test stage, the test speech channel factor is projected into feature space to engage in feature compensation, so it can remove channel information both in model and feature domains in order to improve recognition rate. The experiment result shows that the hybrid compensation can obtain the similar recognition rate in the three different training channel conditions and this method is more effective than joint factor analysis in the test of short whispered speech.

  3. Cranio-orbito-zygomatic approach for a previously coiled/recurrent giant MCA aneurysm in a hybrid angio/OR suite.

    Science.gov (United States)

    Arko, Leopold; Quach, Eric; Sukul, Vishad; Desai, Anuj; Gassie, Kelly; Erkmen, Kadir

    2015-07-01

    We present surgical clipping of a giant middle cerebral artery aneurysm. The patient is a 64-year-old woman who suffered subarachnoid hemorrhage in 2005. She was treated with coiling of the aneurysm at an outside institution. She presented to our clinic with headaches and was found on angiography to have giant recurrence of the aneurysm. To allow adequate exposure for clipping, we performed the surgery through a cranio-orbito-zygomatic (COZ) skull base approach, which is demonstrated. The surgery was performed in an operating room/angiography hybrid suite allowing for high quality intraoperative angiography. The technique and room flow are also demonstrated. The video can be found here: http://youtu.be/eePcyOMi85M.

  4. Credit Scoring Model Hybridizing Artificial Intelligence with Logistic Regression

    Directory of Open Access Journals (Sweden)

    Han Lu

    2013-01-01

    Full Text Available Today the most commonly used techniques for credit scoring are artificial intelligence and statistics. In this paper, we started a new way to use these two kinds of models. Through logistic regression filters the variables with a high degree of correlation, artificial intelligence models reduce complexity and accelerate convergence, while these models hybridizing logistic regression have better explanations in statistically significance, thus improve the effect of artificial intelligence models. With experiments on German data set, we find an interesting phenomenon defined as ‘Dimensional interference’ with support vector machine and from cross validation it can be seen that the new method gives a lot of help with credit scoring.

  5. A Hybrid Tool for User Interface Modeling and Prototyping

    Science.gov (United States)

    Trætteberg, Hallvard

    Although many methods have been proposed, model-based development methods have only to some extent been adopted for UI design. In particular, they are not easy to combine with user-centered design methods. In this paper, we present a hybrid UI modeling and GUI prototyping tool, which is designed to fit better with IS development and UI design traditions. The tool includes a diagram editor for domain and UI models and an execution engine that integrates UI behavior, live UI components and sample data. Thus, both model-based user interface design and prototyping-based iterative design are supported

  6. IMPLICIT REPRESENTATION FOR THE MODELLING OF HYBRID DYNAMIC SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Hybrid systems can be represented by a discrete event model interacting with a continuous model, and the interface by ideal switching components which modify the topology of a system at the switching time. This paper deals with the modelling of such systems using the bond graph approach. The paper shows the interest of the implicit representation: to derive a unique state equation with jumping parameters, to derive the implicit state equation with index of nilpotency one corresponding to each configuration, to analyze the properties of those models and to compute the discontinuity.

  7. HYBRID TRUST MODEL FOR INTERNET ROUTING

    Directory of Open Access Journals (Sweden)

    Pekka Rantala

    2011-05-01

    Full Text Available The current Internet is based on a fundamental assumption of reliability and good intent among actors inthe network. Unfortunately, unreliable and malicious behaviour is becoming a major obstacle forInternet communication. In order to improve the trustworthiness and reliability of the networkinfrastructure, we propose a novel trust model to be incorporated into BGP routing. In our approach,trust model is defined by combining voting and recommendation to direct trust estimation for neighbourrouters located in different autonomous systems. We illustrate the impact of our approach with cases thatdemonstrate the indication of distrusted paths beyond the nearest neighbours and the detection of adistrusted neighbour advertising a trusted path. We simulated the impact of weighting voted and directtrust in a rectangular grid of 15*15 nodes (autonomous systems with a randomly connected topology.

  8. Hybrid Trust Model for Internet Routing

    CERN Document Server

    Rantala, Pekka; Isoaho, Jouni

    2011-01-01

    The current Internet is based on a fundamental assumption of reliability and good intent among actors in the network. Unfortunately, unreliable and malicious behaviour is becoming a major obstacle for Internet communication. In order to improve the trustworthiness and reliability of the network infrastructure, we propose a novel trust model to be incorporated into BGP routing. In our approach, trust model is defined by combining voting and recommendation to direct trust estimation for neighbour routers located in different autonomous systems. We illustrate the impact of our approach with cases that demonstrate the indication of distrusted paths beyond the nearest neighbours and the detection of a distrusted neighbour advertising a trusted path. We simulated the impact of weighting voted and direct trust in a rectangular grid of 15*15 nodes (autonomous systems) with a randomly connected topology.

  9. A New Hybrid Model Rotor Flux Observer and Its Application

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A new hybrid model rotor flux observer, based on a new voltage model, is presented. In the first place, the voltage model of an induction machine was constructed by using the modeling method discussed in this paper and then the current model using a flux feedback was adopted in this flux observer. Secondly, the two models were combined via a filter and then the rotor flux observer was established. In the M-T synchronous coordinate, the observer was analyzed theoretically and several important functions were derived. A comparison between the observer and the traditional models was made using Matlab software. The simulation results show that the observer model had a better performance than the traditional model.

  10. A Secured Hybrid Architecture Model for Internet Banking (e - Banking

    Directory of Open Access Journals (Sweden)

    Ganesan R

    2009-05-01

    Full Text Available Internet banking has made it easy to carry out the personal or business financial trans action without going to bank and at any suitable time. This facility enables to transfer money to other accounts and checking current balance alongside the status of any financial transaction made in the account. However, in order to maintain privacy and t o avoid any misuse of transactions, it is necessary to follow a secured architecture model which ensures the privacy and integrity of the transactions and provides confidence on internet banking is stable. In this research paper, a secured hybrid architect ure model for the internet banking using Hyperelliptic curve cryptosystem and MD5 is described. This hybrid model is implemented with the hyperelliptic curve cryptosystem and it performs the encryption and decryption processes in an efficient way merely wi th an 80 - bit key size. The various screen shots given in this contribution shows that the hybrid model which encompasses HECC and MD5 can be considered in the internet banking environment to enrich the privacy and integrity of the sensitive data transmitte d between the clients and the application server

  11. Reverse engineering cellular decisions for hybrid reconfigurable network modeling

    Science.gov (United States)

    Blair, Howard A.; Saranak, Jureepan; Foster, Kenneth W.

    2011-06-01

    Cells as microorganisms and within multicellular organisms make robust decisions. Knowing how these complex cells make decisions is essential to explain, predict or mimic their behavior. The discovery of multi-layer multiple feedback loops in the signaling pathways of these modular hybrid systems suggests their decision making is sophisticated. Hybrid systems coordinate and integrate signals of various kinds: discrete on/off signals, continuous sensory signals, and stochastic and continuous fluctuations to regulate chemical concentrations. Such signaling networks can form reconfigurable networks of attractors and repellors giving them an extra level of organization that has resilient decision making built in. Work on generic attractor and repellor networks and on the already identified feedback networks and dynamic reconfigurable regulatory topologies in biological cells suggests that biological systems probably exploit such dynamic capabilities. We present a simple behavior of the swimming unicellular alga Chlamydomonas that involves interdependent discrete and continuous signals in feedback loops. We show how to rigorously verify a hybrid dynamical model of a biological system with respect to a declarative description of a cell's behavior. The hybrid dynamical systems we use are based on a unification of discrete structures and continuous topologies developed in prior work on convergence spaces. They involve variables of discrete and continuous types, in the sense of type theory in mathematical logic. A unification such as afforded by convergence spaces is necessary if one wants to take account of the affect of the structural relationships within each type on the dynamics of the system.

  12. Modelling hybrid stars in quark-hadron approaches

    Energy Technology Data Exchange (ETDEWEB)

    Schramm, S. [FIAS, Frankfurt am Main (Germany); Dexheimer, V. [Kent State University, Department of Physics, Kent, OH (United States); Negreiros, R. [Federal Fluminense University, Gragoata, Niteroi (Brazil)

    2016-01-15

    The density in the core of neutron stars can reach values of about 5 to 10 times nuclear matter saturation density. It is, therefore, a natural assumption that hadrons may have dissolved into quarks under such conditions, forming a hybrid star. This star will have an outer region of hadronic matter and a core of quark matter or even a mixed state of hadrons and quarks. In order to investigate such phases, we discuss different model approaches that can be used in the study of compact stars as well as being applicable to a wider range of temperatures and densities. One major model ingredient, the role of quark interactions in the stability of massive hybrid stars is discussed. In this context, possible conflicts with lattice QCD simulations are investigated. (orig.)

  13. A hybrid neural network model for consciousness

    Institute of Scientific and Technical Information of China (English)

    蔺杰; 金小刚; 杨建刚

    2004-01-01

    A new framework for consciousness is introduced based upon traditional artificial neural network models. This framework reflects explicit connections between two parts of the brain: one global working memory and distributed modular cerebral networks relating to specific brain functions. Accordingly this framework is composed of three layers,physical mnemonic layer and abstract thinking layer,which cooperate together through a recognition layer to accomplish information storage and cognition using algorithms of how these interactions contribute to consciousness:(1)the reception process whereby cerebral subsystems group distributed signals into coherent object patterns;(2)the partial recognition process whereby patterns from particular subsystems are compared or stored as knowledge; and(3)the resonant learning process whereby global workspace stably adjusts its structure to adapt to patterns' changes. Using this framework,various sorts of human actions can be explained,leading to a general approach for analyzing brain functions.

  14. A hybrid neural network model for consciousness

    Institute of Scientific and Technical Information of China (English)

    蔺杰; 金小刚; 杨建刚

    2004-01-01

    A new framework for consciousness is introduced based upon traditional artificial neural network models. This framework reflects explicit connections between two parts of the brain: one global working memory and distributed modular cerebral networks relating to specific brain functions. Accordingly this framework is composed of three layers, physical mnemonic layer and abstract thinking layer, which cooperate together through a recognition layer to accomplish information storage and cognition using algorithms of how these interactions contribute to consciousness: (l) the reception process whereby cerebral subsystems group distributed signals into coherent object patterns; (2) the partial recognition process whereby patterns from particular subsystems are compared or stored as knowledge; and (3) the resonant learning process whereby global workspace stably adjusts its structure to adapt to patterns' changes. Using this framework, various sorts of human actions can be explained, leading to a general approach for analyzing brain functions.

  15. Recent progress in battery models for hybrid wind power systems

    Energy Technology Data Exchange (ETDEWEB)

    Manwell, J.F.; McGowan, J.G.; Baring-Gould, I.; Stein, W. [Univ. of Massachusetts, Amherst, MA (United States)

    1995-12-31

    This paper summarizes the latest University of Massachusetts work on the analytical modeling and experimental testing of battery component models for hybrid power systems. An extension of the Kinetic Battery Model (KiBaM), developed at the University of Massachusetts is presented. The original model was based on a combination of phenomenological and physical considerations. As described in this paper, the modified KiBaM can now model the sharp increase in voltage near the end of charging, and the sharp drop in voltage when the battery is nearly empty. This model may readily be coupled with a DC load or charging source (such as a DC wind turbine or photovoltaic panels) to determine the corresponding DC bus voltage. For example, it is now an integral part of the DC bus section of the University of Massachusetts HYBRID simulation models. The paper describes the development of the extensions to the KiBaM model and the method of determining the constants from test data. On the experimental/applications side, it includes an illustration of how the constants are obtained from representative data (using a specially developed testing apparatus), and an example of how the model can be used.

  16. A light neutralino in hybrid models of supersymmetry breaking

    CERN Document Server

    Dudas, Emilian; Parmentier, Jeanne; 10.1016

    2008-01-01

    We show that in gauge mediation models where heavy messenger masses are provided by the adjoint Higgs field of an underlying SU(5) theory, a generalized gauge mediation spectrum arises with the characteristic feature of having a neutralino much lighter than in the standard gauge or gravity mediation schemes. This naturally fits in a hybrid scenario where gravity mediation, while subdominant with respect to gauge mediation, provides mu and B mu parameters in the TeV range.

  17. A Novel of Hybrid Maintenance Management Models for Industrial Applications

    OpenAIRE

    Tahir, Zulkifli

    2010-01-01

    It is observed through empirical studies that the effectiveness of industrial process have been increased by a well organized of machines maintenance structure. In current research, a novel of maintenance concept has been designed by hybrid several maintenance management models with Decision Making Grid (DMG), Analytic Hierarchy Process (AHP) and Fuzzy Logic. The concept is designed for maintenance personnel to evaluate and benchmark the maintenance operations and to reveal important maintena...

  18. Controllability in hybrid kinetic equations modeling nonequilibrium multicellular systems.

    Science.gov (United States)

    Bianca, Carlo

    2013-01-01

    This paper is concerned with the derivation of hybrid kinetic partial integrodifferential equations that can be proposed for the mathematical modeling of multicellular systems subjected to external force fields and characterized by nonconservative interactions. In order to prevent an uncontrolled time evolution of the moments of the solution, a control operator is introduced which is based on the Gaussian thermostat. Specifically, the analysis shows that the moments are solution of a Riccati-type differential equation.

  19. Statics of levitated vehicle model with hybrid magnets

    Institute of Scientific and Technical Information of China (English)

    Desheng LI; Zhiyuan LU; Tianwu DONG

    2009-01-01

    By studying the special characteristics of permanent and electronic magnets, a levitated vehicle model with hybrid magnets is established. The mathematical model of the vehicle is built based on its dynamics equation by studying its machine structure and working principle. Based on the model, the basic characteristics and the effect between the excluding forces from permanent magnets in three different spatial directions are analyzed, statics characteristics of the interference forces in three different spatial directions are studied, and self-adjusting equilibrium characteristics and stabilization are analyzed. Based on the structure above, the vehicle can levitate steadily by control system adjustment.

  20. Hybrid Surface Mesh Adaptation for Climate Modeling

    Institute of Scientific and Technical Information of China (English)

    Ahmed Khamayseh; Valmor de Almeida; Glen Hansen

    2008-01-01

    Solution-driven mesh adaptation is becoming quite popular for spatial error control in the numerical simulation of complex computational physics applications, such as climate modeling. Typically, spatial adaptation is achieved by element subdivision (h adaptation) with a primary goal of resolving the local length scales of interest. A second, lesspopular method of spatial adaptivity is called "mesh motion" (r adaptation); the smooth repositioning of mesh node points aimed at resizing existing elements to capture the local length scales. This paper proposes an adaptation method based on a combination of both element subdivision and node point repositioning (rh adaptation). By combining these two methods using the notion of a mobility function, the proposed approach seeks to increase the flexibility and extensibility of mesh motion algorithms while providing a somewhat smoother transition between refined regions than is pro-duced by element subdivision alone. Further, in an attempt to support the requirements of a very general class of climate simulation applications, the proposed method is de-signed to accommodate unstructured, polygonal mesh topologies in addition to the most popular mesh types.

  1. Hybrid LCA model for assessing the embodied environmental impacts of buildings in South Korea

    Energy Technology Data Exchange (ETDEWEB)

    Jang, Minho, E-mail: minmin40@hanmail.net [Asset Management Division, Mate Plus Co., Ltd., 9th Fl., Financial News Bldg. 24-5 Yeouido-dong, Yeongdeungpo-gu, Seoul, 150-877 (Korea, Republic of); Hong, Taehoon, E-mail: hong7@yonsei.ac.kr [Department of Architectural Engineering, Yonsei University, Seoul, 120-749 (Korea, Republic of); Ji, Changyoon, E-mail: chnagyoon@yonsei.ac.kr [Department of Architectural Engineering, Yonsei University, Seoul, 120-749 (Korea, Republic of)

    2015-01-15

    The assessment of the embodied environmental impacts of buildings can help decision-makers plan environment-friendly buildings and reduce environmental impacts. For a more comprehensive assessment of the embodied environmental impacts of buildings, a hybrid life cycle assessment model was developed in this study. The developed model can assess the embodied environmental impacts (global warming, ozone layer depletion, acidification, eutrophication, photochemical ozone creation, abiotic depletion, and human toxicity) generated directly and indirectly in the material manufacturing, transportation, and construction phases. To demonstrate the application and validity of the developed model, the environmental impacts of an elementary school building were assessed using the developed model and compared with the results of a previous model used in a case study. The embodied environmental impacts from the previous model were lower than those from the developed model by 4.6–25.2%. Particularly, human toxicity potential (13 kg C{sub 6}H{sub 6} eq.) calculated by the previous model was much lower (1965 kg C{sub 6}H{sub 6} eq.) than what was calculated by the developed model. The results indicated that the developed model can quantify the embodied environmental impacts of buildings more comprehensively, and can be used by decision-makers as a tool for selecting environment-friendly buildings. - Highlights: • The model was developed to assess the embodied environmental impacts of buildings. • The model evaluates GWP, ODP, AP, EP, POCP, ADP, and HTP as environmental impacts. • The model presents more comprehensive results than the previous model by 4.6–100%. • The model can present the HTP of buildings, which the previous models cannot do. • Decision-makers can use the model for selecting environment-friendly buildings.

  2. Magnetic equivalent circuit model for unipolar hybrid excitation synchronous machine

    Directory of Open Access Journals (Sweden)

    Kupiec Emil

    2015-03-01

    Full Text Available Lately, there has been increased interest in hybrid excitation electrical machines. Hybrid excitation is a construction that combines permanent magnet excitation with wound field excitation. Within the general classification, these machines can be classified as modified synchronous machines or inductor machines. These machines may be applied as motors and generators. The complexity of electromagnetic phenomena which occur as a result of coupling of magnetic fluxes of separate excitation systems with perpendicular magnetic axis is a motivation to formulate various mathematical models of these machines. The presented paper discusses the construction of a unipolar hybrid excitation synchronous machine. The magnetic equivalent circuit model including nonlinear magnetization curves is presented. Based on this model, it is possible to determine the multi-parameter relationships between the induced voltage and magnetomotive force in the excitation winding. Particular attention has been paid to the analysis of the impact of additional stator and rotor yokes on above relationship. Induced voltage determines the remaining operating parameters of the machine, both in the motor and generator mode of operation. The analysis of chosen correlations results in an identification of the effective control range of electromotive force of the machine.

  3. Hybrid and adaptive meta-model-based global optimization

    Science.gov (United States)

    Gu, J.; Li, G. Y.; Dong, Z.

    2012-01-01

    As an efficient and robust technique for global optimization, meta-model-based search methods have been increasingly used in solving complex and computation intensive design optimization problems. In this work, a hybrid and adaptive meta-model-based global optimization method that can automatically select appropriate meta-modelling techniques during the search process to improve search efficiency is introduced. The search initially applies three representative meta-models concurrently. Progress towards a better performing model is then introduced by selecting sample data points adaptively according to the calculated values of the three meta-models to improve modelling accuracy and search efficiency. To demonstrate the superior performance of the new algorithm over existing search methods, the new method is tested using various benchmark global optimization problems and applied to a real industrial design optimization example involving vehicle crash simulation. The method is particularly suitable for design problems involving computation intensive, black-box analyses and simulations.

  4. An isentropic and sigma coordinate hybrid numerical model - Model development and some initial tests. [for atmospheric simulations

    Science.gov (United States)

    Uccellini, L. W.; Johnson, D. R.; Schlesinger, R. E.

    1979-01-01

    A solution is presented for matching boundary conditions across the interface of an isentropic and sigma coordinate hybrid model. A hybrid model based on the flux form of the primitive equations is developed which allows direct vertical exchange between the model domains, satisfies conservation principles with respect to transport processes, and maintains a smooth transition across the interface without need for artificial adjustment or parameterization schemes. The initial hybrid model simulations of a jet streak propagating in a zonal channel are used to test the feasibility of the hybrid model approach. High efficiency of the hybrid model is demonstrated.

  5. Modeling of plasma and thermo-fluid transport in hybrid welding

    Science.gov (United States)

    Ribic, Brandon D.

    processes parameters on heat transfer, fluid flow, and plasma characteristics for arc and laser welding. However, numerical modeling of laser/GTA hybrid welding is just beginning. Arc and laser welding plasmas have been previously analyzed successfully using optical emission spectroscopy in order to better understand arc and laser plasma properties as a function of plasma radius. Variation of hybrid welding plasma properties with radial distance is not known. Since plasma properties can affect arc and laser energy absorption and weld integrity, a better understanding of the change in hybrid welding plasma properties as a function of plasma radius is important and necessary. Material composition influences welding plasma properties, arc and laser energy absorption, heat transfer, and fluid flow. The presence of surface active elements such as oxygen and sulfur can affect weld pool fluid flow and bead geometry depending upon the significance of heat transfer by convection. Easily vaporized and ionized alloying elements can influence arc plasma characteristics and arc energy absorption. The effects of surface active elements on heat transfer and fluid flow are well understood in the case of arc and conduction mode laser welding. However, the influence of surface active elements on heat transfer and fluid flow during keyhole mode laser welding and laser/arc hybrid welding are not well known. Modeling has been used to successfully analyze the influence of surface active elements during arc and conduction mode laser welding in the past and offers promise in the case of laser/arc hybrid welding. A critical review of the literature revealed several important areas for further research and unanswered questions. (1) The understanding of heat transfer and fluid flow during hybrid welding is still beginning and further research is necessary. (2) Why hybrid welding weld bead width is greater than that of laser or arc welding is not well understood. (3) The influence of arc power and

  6. A Novel Software Simulator Model Based on Active Hybrid Architecture

    Directory of Open Access Journals (Sweden)

    Amr AbdElHamid

    2015-01-01

    Full Text Available The simulated training is an important issue for any type of missions such as aerial, ground, sea, or even space missions. In this paper, a new flexible aerial simulator based on active hybrid architecture is introduced. The simulator infrastructure is applicable to any type of training missions and research activities. This software-based simulator is tested on aerial missions to prove its applicability within time critical systems. The proposed active hybrid architecture is introduced via using the VB.NET and MATLAB in the same simulation loop. It exploits the remarkable computational power of MATLAB as a backbone aircraft model, and such mathematical model provides realistic dynamics to the trainee. Meanwhile, the Human-Machine Interface (HMI, the mission planning, the hardware interfacing, data logging, and MATLAB interfacing are developed using VB.NET. The proposed simulator is flexible enough to perform navigation and obstacle avoidance training missions. The active hybrid architecture is used during the simulated training, and also through postmission activities (like the generation of signals playback reports for evaluation purposes. The results show the ability of the proposed architecture to fulfill the aerial simulator demands and to provide a flexible infrastructure for different simulated mission requirements. Finally, a comparison with some existing simulators is introduced.

  7. MODEL APLIKASI FIKIH MUAMALAH PADA FORMULASI HYBRID CONTRACT

    Directory of Open Access Journals (Sweden)

    Ali Murtadho

    2013-10-01

    Full Text Available Modern literatures of fiqh mu’āmalah talk alot about various contract formulation with capability of maximizing profit in shariah finance industry. This new contract modification is the synthesis among existing contracts which is formulated in such a way to be an integrated contract. This formulation is known as a hybrid contract or multicontract (al-'uqūd al-murakkabah. Some of them are, bay' bi thaman 'ājil, Ijārah muntahiyah bi ’l-tamlīk dan mushārakah mutanāqiṣah. This study intends to further describe models of hybrid contract, and explore the shari'ah principles in modern financial institutions. This study found a potential shift from the ideal values of the spirit of shari'ah into the spirit of competition based shari'ah formally.

  8. System Modeling and Diagnostics for Liquefying-Fuel Hybrid Rockets

    Science.gov (United States)

    Poll, Scott; Iverson, David; Ou, Jeremy; Sanderfer, Dwight; Patterson-Hine, Ann

    2003-01-01

    A Hybrid Combustion Facility (HCF) was recently built at NASA Ames Research Center to study the combustion properties of a new fuel formulation that burns approximately three times faster than conventional hybrid fuels. Researchers at Ames working in the area of Integrated Vehicle Health Management recognized a good opportunity to apply IVHM techniques to a candidate technology for next generation launch systems. Five tools were selected to examine various IVHM techniques for the HCF. Three of the tools, TEAMS (Testability Engineering and Maintenance System), L2 (Livingstone2), and RODON, are model-based reasoning (or diagnostic) systems. Two other tools in this study, ICS (Interval Constraint Simulator) and IMS (Inductive Monitoring System) do not attempt to isolate the cause of the failure but may be used for fault detection. Models of varying scope and completeness were created, both qualitative and quantitative. In each of the models, the structure and behavior of the physical system are captured. In the qualitative models, the temporal aspects of the system behavior and the abstraction of sensor data are handled outside of the model and require the development of additional code. In the quantitative model, less extensive processing code is also necessary. Examples of fault diagnoses are given.

  9. A Simple Hybrid Model for Short-Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Suseelatha Annamareddi

    2013-01-01

    Full Text Available The paper proposes a simple hybrid model to forecast the electrical load data based on the wavelet transform technique and double exponential smoothing. The historical noisy load series data is decomposed into deterministic and fluctuation components using suitable wavelet coefficient thresholds and wavelet reconstruction method. The variation characteristics of the resulting series are analyzed to arrive at reasonable thresholds that yield good denoising results. The constitutive series are then forecasted using appropriate exponential adaptive smoothing models. A case study performed on California energy market data demonstrates that the proposed method can offer high forecasting precision for very short-term forecasts, considering a time horizon of two weeks.

  10. 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 faulty...... outputs constrained by tolerable performance requirements. As in standard model predictive control, the first element of the optimal input is applied to the system and the whole procedure is repeated until the fault is detected by a passive diagnoser. It is demonstrated how the generated excitation signal...

  11. A Hybrid Approach for Co-Channel Speech Segregation based on CASA, HMM Multipitch Tracking, and Medium Frame Harmonic Model

    Directory of Open Access Journals (Sweden)

    Ashraf M. Mohy Eldin

    2013-08-01

    Full Text Available This paper proposes a hybrid approach for co-channel speech segregation. HMM (hidden Markov model is used to track the pitches of 2 talkers. The resulting pitch tracks are then enriched with the prominent pitch. The enriched tracks are correctly grouped using pitch continuity. Medium frame harmonics are used to extract the second pitch for frames with only one pitch deduced using the previous steps. Finally, the pitch tracks are input to CASA (computational auditory scene analysis to segregate the mixed speech. The center frequency range of the gamma tone filter banks is maximized to reduce the overlap between the channels filtered for better segregation. Experiments were conducted using this hybrid approach on the speech separation challenge database and compared to the single (non-hybrid approaches, i.e. signal processing and CASA. Results show that using the hybrid approach outperforms the single approaches.

  12. Hybrid models for hydrological forecasting: integration of data-driven and conceptual modelling techniques

    NARCIS (Netherlands)

    Corzo Perez, G.A.

    2009-01-01

    This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following top

  13. Hybrid models for hydrological forecasting: Integration of data-driven and conceptual modelling techniques

    NARCIS (Netherlands)

    Corzo Perez, G.A.

    2009-01-01

    This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following top

  14. Hybrid models for hydrological forecasting: integration of data-driven and conceptual modelling techniques

    NARCIS (Netherlands)

    Corzo Perez, G.A.

    2009-01-01

    This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following

  15. Hybrid models for hydrological forecasting: Integration of data-driven and conceptual modelling techniques

    NARCIS (Netherlands)

    Corzo Perez, G.A.

    2009-01-01

    This book presents the investigation of different architectures of integrating hydrological knowledge and models with data-driven models for the purpose of hydrological flow forecasting. The models resulting from such integration are referred to as hybrid models. The book addresses the following

  16. Multiobjective muffler shape optimization with hybrid acoustics modeling.

    Science.gov (United States)

    Airaksinen, Tuomas; Heikkola, Erkki

    2011-09-01

    This paper considers the combined use of a hybrid numerical method for the modeling of acoustic mufflers and a genetic algorithm for multiobjective optimization. The hybrid numerical method provides accurate modeling of sound propagation in uniform waveguides with non-uniform obstructions. It is based on coupling a wave based modal solution in the uniform sections of the waveguide to a finite element solution in the non-uniform component. Finite element method provides flexible modeling of complicated geometries, varying material parameters, and boundary conditions, while the wave based solution leads to accurate treatment of non-reflecting boundaries and straightforward computation of the transmission loss (TL) of the muffler. The goal of optimization is to maximize TL at multiple frequency ranges simultaneously by adjusting chosen shape parameters of the muffler. This task is formulated as a multiobjective optimization problem with the objectives depending on the solution of the simulation model. NSGA-II genetic algorithm is used for solving the multiobjective optimization problem. Genetic algorithms can be easily combined with different simulation methods, and they are not sensitive to the smoothness properties of the objective functions. Numerical experiments demonstrate the accuracy and feasibility of the model-based optimization method in muffler design.

  17. Hybrid model decomposition of speech and noise in a radial basis function neural model framework

    DEFF Research Database (Denmark)

    Sørensen, Helge Bjarup Dissing; Hartmann, Uwe

    1994-01-01

    applied is based on a combination of the hidden Markov model (HMM) decomposition method, for speech recognition in noise, developed by Varga and Moore (1990) from DRA and the hybrid (HMM/RBF) recognizer containing hidden Markov models and radial basis function (RBF) neural networks, developed by Singer...... and Lippmann (1992) from MIT Lincoln Lab. The present authors modified the hybrid recognizer to fit into the decomposition method to achieve high performance speech recognition in noisy environments. The approach has been denoted the hybrid model decomposition method and it provides an optimal method...... for decomposition of speech and noise by using a set of speech pattern models and a noise model(s), each realized as an HMM/RBF pattern model...

  18. Experimental Validation of a Thermoelastic Model for SMA Hybrid Composites

    Science.gov (United States)

    Turner, Travis L.

    2001-01-01

    This study presents results from experimental validation of a recently developed model for predicting the thermomechanical behavior of shape memory alloy hybrid composite (SMAHC) structures, composite structures with an embedded SMA constituent. The model captures the material nonlinearity of the material system with temperature and is capable of modeling constrained, restrained, or free recovery behavior from experimental measurement of fundamental engineering properties. A brief description of the model and analysis procedures is given, followed by an overview of a parallel effort to fabricate and characterize the material system of SMAHC specimens. Static and dynamic experimental configurations for the SMAHC specimens are described and experimental results for thermal post-buckling and random response are presented. Excellent agreement is achieved between the measured and predicted results, fully validating the theoretical model for constrained recovery behavior of SMAHC structures.

  19. SCAN-based hybrid and double-hybrid density functionals from parameter-free models

    CERN Document Server

    Hui, Kerwin

    2015-01-01

    By incorporating the nonempirical SCAN semilocal density functional [Sun, Ruzsinszky, and Perdew, Phys. Rev. Lett. 115, 036402 (2015)] in the underlying expression, we propose one hybrid (SCAN0) and three double-hybrid (SCAN0-DH, SCAN-QIDH, and SCAN0-2) density functionals, which are free of any empirical parameter. The SCAN-based hybrid and double-hybrid functionals consistently outperform their parent SCAN semilocal functional for a wide range of applications. The SCAN-based semilocal, hybrid, and double-hybrid functionals generally perform better than the corresponding PBE-based functionals. In addition, the SCAN0-2 and SCAN-QIDH double-hybrid functionals significantly reduce the qualitative failures of the SCAN semilocal functional, such as the self-interaction error and noncovalent interaction error, extending the applicability of the SCAN-based functionals to a very diverse range of systems.

  20. Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields

    Science.gov (United States)

    Weller, Daniel; Shiwakoti, Suvash; Bergholz, Peter; Grohn, Yrjo; Wiedmann, Martin

    2015-01-01

    Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce. PMID:26590280

  1. A Hybrid Model for QCD Deconfining Phase Boundary

    CERN Document Server

    Srivastava, P K

    2012-01-01

    Intensive search for a proper and realistic equations of state (EOS) is still continued for studying the phase diagram existing between quark gluon plasma (QGP) and hadron gas (HG) phases. Lattice calculations provide such EOS for the strongly interacting matter at finite temperature ($T$) and vanishing baryon chemical potential ($\\mu_{B}$). These calculations are of limited use at finite $\\mu_{B}$ due to the appearance of notorious sign problem. In the recent past, we had constructed a hybrid model description for the QGP as well as HG phases where we make use of a new excluded-volume model for HG and a thermodynamically-consistent quasiparticle model for the QGP phase and used them further to get QCD phase boundary and a critical point. Since then many lattice calculations have appeared showing various thermal and transport properties of QCD matter at finite $T$ and $\\mu_{B}=0$. We test our hybrid model by reproducing the entire data for strongly interacting matter and predict our results at finite $\\mu_{B}...

  2. Description of Strongly Interacting Matter in A Hybrid Model

    CERN Document Server

    Srivastava, P K

    2014-01-01

    Search for a proper and realistic equation of state (EOS) for strongly interacting matter used in the study of the QCD phase diagram still appears as a challenging problem. Recently, we constructed a hybrid model description for the quark gluon plasma (QGP) as well as hadron gas (HG) phases where we used an excluded volume model for HG and a thermodynamically consistent quasiparticle model for the QGP phase. The hybrid model suitably describes the recent lattice results of various thermodynamical as well as transport properties of the QCD matter at zero baryon chemical potential ($\\mu_{B}$). In this paper, we extend our investigations further in obtaining the properties of QCD matter at finite value of $\\mu_{B}$ and compare our results with the most recent results of lattice QCD calculation. Finally we demonstrate the existence of two different limiting energy regimes and propose that the connection point of these two limiting regimes would foretell the existence of critical point (CP) of the deconfining phas...

  3. Interval forecasts of a novelty hybrid model for wind speeds

    Directory of Open Access Journals (Sweden)

    Shanshan Qin

    2015-11-01

    Full Text Available The utilization of wind energy, as a booming technology in the field of renewable energies, has been highly regarded around the world. Quantification of uncertainties associated with accurate wind speed forecasts is essential for regulating wind power generation and integration. However, it remains difficult work primarily due to the stochastic and nonlinear characteristics of wind speed series. Traditional models for wind speed forecasting mostly focus on generating certain predictive values, which cannot properly handle uncertainties. For quantifying potential uncertainties, a hybrid model constructed by the Cuckoo Search Optimization (CSO-based Back Propagation Neural Network (BPNN is proposed to establish wind speed interval forecasts (IFs by estimating the lower and upper bounds. The quality of IFs is assessed quantitatively using IFs coverage probability (IFCP and IFs normalized average width (IFNAW. Moreover, to assess the overall quality of IFs comprehensively, a tradeoff between informativeness (IFNAW and validity (IFCP of IFs is examined by coverage width-based criteria (CWC. As an applicative study, wind speeds from the Xinjiang Region in China are used to validate the proposed hybrid model. The results demonstrate that the proposed model can construct higher quality IFs for short-term wind speed forecasts.

  4. A site dependent top height growth model for hybrid aspen

    Institute of Scientific and Technical Information of China (English)

    Tord Johansson

    2013-01-01

    In this study height growth models for hybrid aspen were developed using three growth equations. The mean age of the hybrid aspen was 21 years (range 15−51 years) with a mean stand density of 946 stems ha-1 (87−2374) and a mean diameter at breast height (over bark) of 19.6 cm (8.5−40.8 cm). Site index was also examined in relation to soil type. Multiple samples were collected for three types of soil: light clay, medium clay and till. Site index curves were constructed using the col-lected data and compared with published reports. A number of dynamic equations were assessed for modeling top-height growth from total age. A Generalized Algebraic Difference Approach model derived by Cieszewski (2001) performed the best. This model explained 99% of the observed variation in tree height growth and exhibited no apparent bias across the range of predicted site indices. There were no significant differences between the soil types and site indices.

  5. KNGEOID14: A national hybrid geoid model in Korea

    Science.gov (United States)

    Kang, S.; Sung, Y. M.; KIM, H.; Kim, Y. S.

    2016-12-01

    This study describes in brief the construction of a national hybrid geoid model in Korea, KNGEOID14, which can be used as an accurate vertical datum in/around Korea. The hybrid geoid model should be determined by fitting the gravimetric geoid to the geometric geoid undulations from GNSS/Leveling data which were presented the local vertical level. For developing the gravimetric geoid model, we determined all frequency parts (long, middle and short-frequency) of gravimetric geoid using all available data with optimal remove-restore technique based on EGM2008 reference surface. In remove-restore technique, the EGM2008 model to degree 360, RTM reduction method were used for calculating the long, middle and short-frequency part of gravimetric geoid, respectively. A number of gravity data compiled for modeling the middle-frequency part, residual geoid, containing 8,866 points gravity data on land and ocean areas. And, the DEM data gridded by 100m×100m were used for short-frequency part, is the topographic effect on the geoid generated by RTM method. The accuracy of gravimetric geoid model were evaluated by comparison with GNSS/Leveling data was about -0.362m ± 0.055m. Finally, we developed the national hybrid geoid model in Korea, KNGEOID14, corrected to gravimetric geoid with the correction term by fitting the about 1,200 GNSS/Leveling data on Korean bench marks. The correction term is modeled using the difference between GNSS/Leveling derived geoidal heights and gravimetric geoidal heights. The stochastic model used in the calculation of correction term is the LSC technique based on second-order Markov covariance function. The post-fit error (mean and std. dev.) of the KNGEOID14 model was evaluated as 0.001m ± 0.033m. Concerning the result of this study, the accurate orthometric height at any points in Korea will be easily and precisely calculated by combining the geoidal height from KNGEOID14 and ellipsoidal height from GPS observation technique.

  6. Ionocovalency and Applications 1. Ionocovalency Model and Orbital Hybrid Scales

    Directory of Open Access Journals (Sweden)

    Yonghe Zhang

    2010-11-01

    Full Text Available Ionocovalency (IC, a quantitative dual nature of the atom, is defined and correlated with quantum-mechanical potential to describe quantitatively the dual properties of the bond. Orbiotal hybrid IC model scale, IC, and IC electronegativity scale, XIC, are proposed, wherein the ionicity and the covalent radius are determined by spectroscopy. Being composed of the ionic function I and the covalent function C, the model describes quantitatively the dual properties of bond strengths, charge density and ionic potential. Based on the atomic electron configuration and the various quantum-mechanical built-up dual parameters, the model formed a Dual Method of the multiple-functional prediction, which has much more versatile and exceptional applications than traditional electronegativity scales and molecular properties. Hydrogen has unconventional values of IC and XIC, lower than that of boron. The IC model can agree fairly well with the data of bond properties and satisfactorily explain chemical observations of elements throughout the Periodic Table.

  7. Nonlinear Thermoelastic Model for SMAs and SMA Hybrid Composites

    Science.gov (United States)

    Turner, Travis L.

    2004-01-01

    A constitutive mathematical model has been developed that predicts the nonlinear thermomechanical behaviors of shape-memory-alloys (SMAs) and of shape-memory-alloy hybrid composite (SMAHC) structures, which are composite-material structures that contain embedded SMA actuators. SMAHC structures have been investigated for their potential utility in a variety of applications in which there are requirements for static or dynamic control of the shapes of structures, control of the thermoelastic responses of structures, or control of noise and vibrations. The present model overcomes deficiencies of prior, overly simplistic or qualitative models that have proven ineffective or intractable for engineering of SMAHC structures. The model is sophisticated enough to capture the essential features of the mechanics of SMAHC structures yet simple enough to accommodate input from fundamental engineering measurements and is in a form that is amenable to implementation in general-purpose structural analysis environments.

  8. Hierarchical modeling and control of hybrid systems with two layers; Hierarchische Modellierung und Regelung hybrider Systeme auf zwei Ebenen

    Energy Technology Data Exchange (ETDEWEB)

    Stursberg, Olaf; Paschedag, Tina; Rungger, Matthias; Ding, Hao [Kassel Univ. (Germany). Fachgebiet Regelungs- und Systemtheorie

    2010-08-15

    While hybrid dynamic models are, to a certain degree, established for modeling systems with heterogeneous dynamics, most approaches for design and analysis of hybrid systems are restricted to monolithic models without hierarchy. This contribution first shows, how modular hybrid systems with two layers of decision, as appropriate for representing manufacturing systems for example, can be modeled systematically. The second part proposes a technique for fixing discrete inputs (for coordinating control) and continuous inputs (for embedded continuous controllers) in combination. The method uses a graph-based search on the upper decision layer, while principles of predictive control are used on the lower layer. The procedure of modeling and control is illustrated for a manufacturing process. (orig.)

  9. A hybrid model of mammalian cell cycle regulation.

    Directory of Open Access Journals (Sweden)

    Rajat Singhania

    Full Text Available The timing of DNA synthesis, mitosis and cell division is regulated by a complex network of biochemical reactions that control the activities of a family of cyclin-dependent kinases. The temporal dynamics of this reaction network is typically modeled by nonlinear differential equations describing the rates of the component reactions. This approach provides exquisite details about molecular regulatory processes but is hampered by the need to estimate realistic values for the many kinetic constants that determine the reaction rates. It is difficult to estimate these kinetic constants from available experimental data. To avoid this problem, modelers often resort to 'qualitative' modeling strategies, such as Boolean switching networks, but these models describe only the coarsest features of cell cycle regulation. In this paper we describe a hybrid approach that combines the best features of continuous differential equations and discrete Boolean networks. Cyclin abundances are tracked by piecewise linear differential equations for cyclin synthesis and degradation. Cyclin synthesis is regulated by transcription factors whose activities are represented by discrete variables (0 or 1 and likewise for the activities of the ubiquitin-ligating enzyme complexes that govern cyclin degradation. The discrete variables change according to a predetermined sequence, with the times between transitions determined in part by cyclin accumulation and degradation and as well by exponentially distributed random variables. The model is evaluated in terms of flow cytometry measurements of cyclin proteins in asynchronous populations of human cell lines. The few kinetic constants in the model are easily estimated from the experimental data. Using this hybrid approach, modelers can quickly create quantitatively accurate, computational models of protein regulatory networks in cells.

  10. A hybrid model for improving response time in distributed data mining.

    Science.gov (United States)

    Krishnaswamy, Shonali; Loke, Seng W; Zaslasvky, Arkady

    2004-12-01

    This paper presents a hybrid distributed data mining (DDM) model for optimization of response time. The model combines a mobile agent approach with client server strategies to reduce the overall response time. The hybrid model proposes and develops accurate a priori estimates of the computation and communication components of response time as the costing strategy to support optimization. Experimental evaluation of the hybrid model is presented.

  11. Chromosome mapping radiation hybrid data and stochastic spin models

    CERN Document Server

    Falk, C T

    1995-01-01

    This work approaches human chromosome mapping by developing algorithms for ordering markers associated with radiation hybrid data. Motivated by recent work of Boehnke et al. [1], we formulate the ordering problem by developing stochastic spin models to search for minimum-break marker configurations. As a particular application, the methods developed are applied to 14 human chromosome-21 markers tested by Cox et al. [2]. The methods generate configurations consistent with the best found by others. Additionally, we find that the set of low-lying configurations is described by a Markov-like ordering probability distribution. The distribution displays cluster correlations reflecting closely linked loci.

  12. Software development infrastructure for the HYBRID modeling and simulation project

    Energy Technology Data Exchange (ETDEWEB)

    Aaron S. Epiney; Robert A. Kinoshita; Jong Suk Kim; Cristian Rabiti; M. Scott Greenwood

    2016-09-01

    One of the goals of the HYBRID modeling and simulation project is to assess the economic viability of hybrid systems in a market that contains renewable energy sources like wind. The idea is that it is possible for the nuclear plant to sell non-electric energy cushions, which absorb (at least partially) the volatility introduced by the renewable energy sources. This system is currently modeled in the Modelica programming language. To assess the economics of the system, an optimization procedure is trying to find the minimal cost of electricity production. The RAVEN code is used as a driver for the whole problem. It is assumed that at this stage, the HYBRID modeling and simulation framework can be classified as non-safety “research and development” software. The associated quality level is Quality Level 3 software. This imposes low requirements on quality control, testing and documentation. The quality level could change as the application development continues.Despite the low quality requirement level, a workflow for the HYBRID developers has been defined that include a coding standard and some documentation and testing requirements. The repository performs automated unit testing of contributed models. The automated testing is achieved via an open-source python script called BuildingsP from Lawrence Berkeley National Lab. BuildingsPy runs Modelica simulation tests using Dymola in an automated manner and generates and runs unit tests from Modelica scripts written by developers. In order to assure effective communication between the different national laboratories a biweekly videoconference has been set-up, where developers can report their progress and issues. In addition, periodic face-face meetings are organized intended to discuss high-level strategy decisions with management. A second means of communication is the developer email list. This is a list to which everybody can send emails that will be received by the collective of the developers and managers

  13. Exploring The Lambda Model Of The Hybrid Superstring

    CERN Document Server

    Schmidtt, David M

    2016-01-01

    The purpose of this contribution is to initiate the study of integrable deformations for different superstring theory formalisms that manifest the property of (classical) integrability. In this paper we choose the hybrid formalism of the superstring in the background AdS_{2}xS^{2} and explore in detail the most immediate consequences of its lambda-deformation. The resulting action functional corresponds to the lambda-model of the matter part of the fairly more sophisticated pure spinor formalism, which is also known to be classical integrable. In particular, the deformation preserves the integrability and the one-loop conformal invariance of its parent theory, hence being a marginal deformation.

  14. On The Modelling Of Hybrid Aerostatic - Gas Journal Bearings

    DEFF Research Database (Denmark)

    Morosi, Stefano; Santos, Ilmar

    2011-01-01

    Gas journal bearing have been increasingly adopted in modern turbo-machinery applications, as they meet the demands of operation at higher rotational speeds, in clean environment and great efficiency. Due to the fact that gaseous lubricants, typically air, have much lower viscosity than more...... modeling for hybrid lubrication of a compressible fluid film journal bearing. Additional forces are generated by injecting pressurized air into the bearing gap through orifices located on the bearing walls. A modified form of the compressible Reynolds equation for active lubrication is derived. By solving...

  15. Photoionization models of the CALIFA H II regions. I. Hybrid models

    Science.gov (United States)

    Morisset, C.; Delgado-Inglada, G.; Sánchez, S. F.; Galbany, L.; García-Benito, R.; Husemann, B.; Marino, R. A.; Mast, D.; Roth, M. M.

    2016-10-01

    Photoionization models of H ii regions require as input a description of the ionizing spectral energy distribution (SED) and of the gas distribution, in terms of ionization parameter U and chemical abundances (e.g., O/H and N/O).A strong degeneracy exists between the hardness of the SED and U, which in turn leads to high uncertainties in the determination of the other parameters, including abundances. One way to resolve the degeneracy is to fix one of the parameters using additional information. For each of the ~20 000 sources of the CALIFA H ii regions catalog, a grid of photoionization models is computed assuming the ionizing SED to be described by the underlying stellar population obtained from spectral synthesis modeling. The ionizing SED is then defined as the sum of various stellar bursts of different ages and metallicities. This solves the degeneracy between the shape of the ionizing SED and U. The nebular metallicity (associated with O/H) is defined using the classical strong line method O3N2 (which gives our models the status of "hybrids"). The remaining free parameters are the abundance ratio N/O and the ionization parameter U, which are determined by looking for the model fitting [N ii]/Hα and [O iii]/Hβ. The models are also selected to fit [O ii]/Hβ. This process leads to a set of ~3200 models that reproduce the three observations simultaneously. We find that the regions associated with young stellar bursts (i.e., ionized by OB stars) are affected by leaking of ionizing photons,the proportion of escaping photons having a median of 80%. The set of photoionization models satisfactorily reproduces the electron temperature derived from the [O iii]λ4363/5007 line ratio. We determine new relations between the nebular parameters, like the ionization parameter U and the [O ii]/[O iii] or [S ii]/[S iii] line ratios. A new relation between N/O and O/H is obtained, mostly compatible with previous empirical determinations (and not with previous results obtained

  16. Causality in Psychiatry: A Hybrid Symptom Network Construct Model

    Directory of Open Access Journals (Sweden)

    Gerald eYoung

    2015-11-01

    Full Text Available Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved that inform approaches to nosology, or classification, such as in the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; American Psychiatric Association, 2013. However, network approaches to symptom interaction (i.e., symptoms are formative of the construct; e.g., McNally, Robinaugh, Wu, Wang, Deserno, & Borsboom, 2014, for PTSD (posttraumatic stress disorder are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth nonlinear dynamical systems theory (NLDST. The article applies the concept of emergent circular causality (Young, 2011 to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning and universal (e.g., causal processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments.

  17. A hybrid neural network model for noisy data regression.

    Science.gov (United States)

    Lee, Eric W M; Lim, Chee Peng; Yuen, Richard K K; Lo, S M

    2004-04-01

    A hybrid neural network model, based on the fusion of fuzzy adaptive resonance theory (FA ART) and the general regression neural network (GRNN), is proposed in this paper. Both FA and the GRNN are incremental learning systems and are very fast in network training. The proposed hybrid model, denoted as GRNNFA, is able to retain these advantages and, at the same time, to reduce the computational requirements in calculating and storing information of the kernels. A clustering version of the GRNN is designed with data compression by FA for noise removal. An adaptive gradient-based kernel width optimization algorithm has also been devised. Convergence of the gradient descent algorithm can be accelerated by the geometric incremental growth of the updating factor. A series of experiments with four benchmark datasets have been conducted to assess and compare effectiveness of GRNNFA with other approaches. The GRNNFA model is also employed in a novel application task for predicting the evacuation time of patrons at typical karaoke centers in Hong Kong in the event of fire. The results positively demonstrate the applicability of GRNNFA in noisy data regression problems.

  18. Hybrid CFD/CAA Modeling for Liftoff Acoustic Predictions

    Science.gov (United States)

    Strutzenberg, Louise L.; Liever, Peter A.

    2011-01-01

    This paper presents development efforts at the NASA Marshall Space flight Center to establish a hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) simulation system for launch vehicle liftoff acoustics environment analysis. Acoustic prediction engineering tools based on empirical jet acoustic strength and directivity models or scaled historical measurements are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. CFD based modeling approaches are now able to capture the important details of vehicle specific plume flow environment, identifY the noise generation sources, and allow assessment of the influence of launch pad geometric details and sound mitigation measures such as water injection. However, CFD methodologies are numerically too dissipative to accurately capture the propagation of the acoustic waves in the large CFD models. The hybrid CFD/CAA approach combines the high-fidelity CFD analysis capable of identifYing the acoustic sources with a fast and efficient Boundary Element Method (BEM) that accurately propagates the acoustic field from the source locations. The BEM approach was chosen for its ability to properly account for reflections and scattering of acoustic waves from launch pad structures. The paper will present an overview of the technology components of the CFD/CAA framework and discuss plans for demonstration and validation against test data.

  19. Causality in Psychiatry: A Hybrid Symptom Network Construct Model

    Science.gov (United States)

    Young, Gerald

    2015-01-01

    Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved) that inform approaches to nosology, or classification, such as in the DSM-5 [Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; (1)]. However, network approaches to symptom interaction [i.e., symptoms are formative of the construct; e.g., (2), for posttraumatic stress disorder (PTSD)] are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth non-linear dynamical systems theory (NLDST). The article applies the concept of emergent circular causality (3) to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning) and universal (e.g., causal) processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments. PMID:26635639

  20. Efficient Vaccine Distribution Based on a Hybrid Compartmental Model.

    Directory of Open Access Journals (Sweden)

    Zhiwen Yu

    Full Text Available To effectively and efficiently reduce the morbidity and mortality that may be caused by outbreaks of emerging infectious diseases, it is very important for public health agencies to make informed decisions for controlling the spread of the disease. Such decisions must incorporate various kinds of intervention strategies, such as vaccinations, school closures and border restrictions. Recently, researchers have paid increased attention to searching for effective vaccine distribution strategies for reducing the effects of pandemic outbreaks when resources are limited. Most of the existing research work has been focused on how to design an effective age-structured epidemic model and to select a suitable vaccine distribution strategy to prevent the propagation of an infectious virus. Models that evaluate age structure effects are common, but models that additionally evaluate geographical effects are less common. In this paper, we propose a new SEIR (susceptible-exposed-infectious šC recovered model, named the hybrid SEIR-V model (HSEIR-V, which considers not only the dynamics of infection prevalence in several age-specific host populations, but also seeks to characterize the dynamics by which a virus spreads in various geographic districts. Several vaccination strategies such as different kinds of vaccine coverage, different vaccine releasing times and different vaccine deployment methods are incorporated into the HSEIR-V compartmental model. We also design four hybrid vaccination distribution strategies (based on population size, contact pattern matrix, infection rate and infectious risk for controlling the spread of viral infections. Based on data from the 2009-2010 H1N1 influenza epidemic, we evaluate the effectiveness of our proposed HSEIR-V model and study the effects of different types of human behaviour in responding to epidemics.

  1. Regression modeling of the North East Atlantic Spring Bloom suggests previously unrecognized biological roles for V and Mo

    Directory of Open Access Journals (Sweden)

    Nick J Klein

    2013-03-01

    Full Text Available In order to identify the biogeochemical parameters controlling pCO2, total chlorophyll a, and dimethylsulfide (DMS concentrations during the North East Atlantic Spring Bloom (NASB, we used previously unpublished particulate and dissolved elemental concentrations to construct several linear regression models; first by hypothesis-testing, and then with exhaustive stepwise linear regression followed by leave-one-out cross-validation. The field data was obtained along a latitudinal transect from the Azores Islands to the North Atlantic, and best-fit models (determined by lowest predictive error of up to three variables are presented. Total chlorophyll a is predicted best by biomass (POC, PON parameters and by pigments characteristic of picophytoplankton for the southern section of the sampling transect (from the Azores to the Rockhall-Hatton Plateau and coccolithophores in the northern portion (from the Rockhall-Hatton Plateau to the Denmark Strait. Both the pCO2 and DMS models included variables traditionally associated with the development of the NASB such as mixed-layer depth and with Fe, Si and P-deplete conditions (dissolved Fe, dissolved and biogenic silica, dissolved PO43-. However, the regressions for pCO2 and DMS also include intracellular V and Mo concentrations, respectively. Mo is involved in DMS production as a cofactor in dimethylsulfoxide reductase. No significant biological role for V has yet been determined, although intracellular V is significantly correlated (p-value < 0.05 with biogenic silica (R2 = 0.72 and total chlorophyll a (R2 = 0.49 while the same is not true for its biogeochemical analogue Mo, suggesting active uptake of V by phytoplankton. Our statistical analysis suggests these two lesser-studied metals may play more important roles in bloom dynamics than previously thought, and highlights a need for studies focused on determining their potential biological requirements and cell quotas.

  2. A novel hybrid forecasting model for PM₁₀ and SO₂ daily concentrations.

    Science.gov (United States)

    Wang, Ping; Liu, Yong; Qin, Zuodong; Zhang, Guisheng

    2015-02-01

    Air-quality forecasting in urban areas is difficult because of the uncertainties in describing both the emission and meteorological fields. The use of incomplete information in the training phase restricts practical air-quality forecasting. In this paper, we propose a hybrid artificial neural network and a hybrid support vector machine, which effectively enhance the forecasting accuracy of an artificial neural network (ANN) and support vector machine (SVM) by revising the error term of the traditional methods. The hybrid methodology can be described in two stages. First, we applied the ANN or SVM forecasting system with historical data and exogenous parameters, such as meteorological variables. Then, the forecasting target was revised by the Taylor expansion forecasting model using the residual information of the error term in the previous stage. The innovation involved in this approach is that it sufficiently and validly utilizes the useful residual information on an incomplete input variable condition. The proposed method was evaluated by experiments using a 2-year dataset of daily PM₁₀ (particles with a diameter of 10 μm or less) concentrations and SO₂ (sulfur dioxide) concentrations from four air pollution monitoring stations located in Taiyuan, China. The theoretical analysis and experimental results demonstrated that the forecasting accuracy of the proposed model is very promising.

  3. A HYBRID PETRI-NET MODEL OF GRID WORKFLOW

    Institute of Scientific and Technical Information of China (English)

    Ji Yimu; Wang Ruchuan; Ren Xunyi

    2008-01-01

    In order to effectively control the random tasks submitted and executed in grid workflow, a grid workflow model based on hybrid petri-net is presented. This model is composed of random petri-net, colored petri-net and general petri-net. Therein random petri-net declares the relationship between the number of grid users' random tasks and the size of service window and computes the server intensity of grid system. Colored petri-net sets different color for places with grid services and provides the valid interfaces for grid resource allocation and task scheduling. The experiment indicated that the model presented in this letter could compute the valve between the number of users' random tasks and the size of grid service window in grid workflow management system.

  4. Proposal: A Hybrid Dictionary Modelling Approach for Malay Tweet Normalization

    Science.gov (United States)

    Muhamad, Nor Azlizawati Binti; Idris, Norisma; Arshi Saloot, Mohammad

    2017-02-01

    Malay Twitter message presents a special deviation from the original language. Malay Tweet widely used currently by Twitter users, especially at Malaya archipelago. Thus, it is important to make a normalization system which can translated Malay Tweet language into the standard Malay language. Some researchers have conducted in natural language processing which mainly focuses on normalizing English Twitter messages, while few studies have been done for normalize Malay Tweets. This paper proposes an approach to normalize Malay Twitter messages based on hybrid dictionary modelling methods. This approach normalizes noisy Malay twitter messages such as colloquially language, novel words, and interjections into standard Malay language. This research will be used Language Model and N-grams model.

  5. Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

    CERN Document Server

    Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure

    2012-01-01

    We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly look at the Multi-Layer Perceptron. After optimizing our architecture with ALADIN and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model ANN/ARMA is 14.9% compared to 26.2% for the na\\"ive persistence predictor. Note that in the stand alone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposed

  6. A Probability-Based Hybrid User Model for Recommendation System

    Directory of Open Access Journals (Sweden)

    Jia Hao

    2016-01-01

    Full Text Available With the rapid development of information communication technology, the available information or knowledge is exponentially increased, and this causes the well-known information overload phenomenon. This problem is more serious in product design corporations because over half of the valuable design time is consumed in knowledge acquisition, which highly extends the design cycle and weakens the competitiveness. Therefore, the recommender systems become very important in the domain of product domain. This research presents a probability-based hybrid user model, which is a combination of collaborative filtering and content-based filtering. This hybrid model utilizes user ratings and item topics or classes, which are available in the domain of product design, to predict the knowledge requirement. The comprehensive analysis of the experimental results shows that the proposed method gains better performance in most of the parameter settings. This work contributes a probability-based method to the community for implement recommender system when only user ratings and item topics are available.

  7. Hybrid TS fuzzy modelling and simulation for chaotic Lorenz system

    Institute of Scientific and Technical Information of China (English)

    Li De-Quan

    2006-01-01

    The projection of the chaotic attractor observed from the Lorenz system in the X-Z plane is like a butterfly, hence the classical Lorenz system is widely known as the butterfly attractor, and has served as a prototype model for studying chaotic behaviour since it was coined. In this work we take one step further to investigate some fundamental dynamic behaviours of a novel hybrid Takagi-Sugeno (TS) fuzzy Lorenz-type system, which is essentially derived from the delta-operator-based TS fuzzy modelling for complex nonlinear systems, and contains the original Lorenz system of continuous-time TS fuzzy form as a special case. By simply and appropriately tuning the additional parametric perturbations in the two-rule hybrid TS fuzzy Lorenz-type system, complex (two-wing) butterfly attractors observed from this system in the three dimensional (3D) X-Y-Z space are created, which have not yet been reported in the literature, and the forming mechanism of the compound structures have been numerically investigated.

  8. Modelling the solar wind interaction with Mercury by a quasi-neutral hybrid model

    Directory of Open Access Journals (Sweden)

    E. Kallio

    Full Text Available Quasi-neutral hybrid model is a self-consistent modelling approach that includes positively charged particles and an electron fluid. The approach has received an increasing interest in space plasma physics research because it makes it possible to study several plasma physical processes that are difficult or impossible to model by self-consistent fluid models, such as the effects associated with the ions’ finite gyroradius, the velocity difference between different ion species, or the non-Maxwellian velocity distribution function. By now quasi-neutral hybrid models have been used to study the solar wind interaction with the non-magnetised Solar System bodies of Mars, Venus, Titan and comets. Localized, two-dimensional hybrid model runs have also been made to study terrestrial dayside magnetosheath. However, the Hermean plasma environment has not yet been analysed by a global quasi-neutral hybrid model.

    In this paper we present a new quasi-neutral hybrid model developed to study various processes associated with the Mercury-solar wind interaction. Emphasis is placed on addressing advantages and disadvantages of the approach to study different plasma physical processes near the planet. The basic assumptions of the approach and the algorithms used in the new model are thoroughly presented. Finally, some of the first three-dimensional hybrid model runs made for Mercury are presented.

    The resulting macroscopic plasma parameters and the morphology of the magnetic field demonstrate the applicability of the new approach to study the Mercury-solar wind interaction globally. In addition, the real advantage of the kinetic hybrid model approach is to study the property of individual ions, and the study clearly demonstrates the large potential of the approach to address these more detailed issues by a quasi-neutral hybrid model in the future.

    Key words. Magnetospheric physics

  9. Empirical Estimation of Hybrid Model: A Controlled Case Study

    Directory of Open Access Journals (Sweden)

    Sadaf Un Nisa

    2012-07-01

    Full Text Available Scrum and Extreme Programming (XP are frequently used models among all agile models whereas Rational Unified Process (RUP is one of the widely used conventional plan driven software development models. The agile and plan driven approaches both have their own strengths and weaknesses. Although RUP model has certain drawbacks, such as tendency to be over budgeted, slow in adaptation to rapidly changing requirements and reputation of being impractical for small and fast paced projects. XP model has certain drawbacks such as weak documentation and poor performance for medium and large development projects. XP has a concrete set of engineering practices that emphasizes on team work where managers, customers and developers are all equal partners in collaborative teams. Scrum is more concerned with the project management. It has seven practices namely Scrum Master, Scrum teams, Product Backlog, Sprint, Sprint Planning Meeting, Daily Scrum Meeting and Sprint Review. Keeping above mentioned context in view, this paper intends to propose a hybrid model naming SPRUP model by combining strengths of Scrum, XP and RUP by eliminating their weaknesses to produce high quality software. The proposed SPRUP model is validated through a controlled case study.

  10. Hybrid turbulence models for atmospheric flow: A proper comparison with RANS models

    Directory of Open Access Journals (Sweden)

    Bautista Mary C.

    2015-01-01

    Full Text Available A compromise between the required accuracy and the need for affordable simulations for the wind industry might be achieved with the use of hybrid turbulence models. Detached-Eddy Simulation (DES [1] is a hybrid technique that yields accurate results only if it is used according to its original formulation [2]. Due to its particular characteristics (i.e., the type of mesh required, the modeling of the atmospheric flow might always fall outside the original scope of DES. An enhanced version of DES called Simplify Improved Delayed Detached-Eddy Simulation (SIDDES [3] can overcome this and other disadvantages of DES. In this work the neutrally stratified atmospheric flow over a flat terrain with homogeneous roughness will be analyzed using a Reynolds-Averaged Navier–Stokes (RANS model called k – ω SST (shear stress transport [4], and the hybrids k – ω SST-DES and k – ω SST-SIDDES models. An obvious test is to validate these hybrid approaches and asses their advantages and disadvantages over the pure RANS model. However, for several reasons the technique to drive the atmospheric flow is generally different for RANS and LES or hybrid models. The flow in a RANS simulation is usually driven by a constant shear stress imposed at the top boundary [5], therefore modeling only the atmospheric surface layer. On the contrary the LES and hybrid simulations are usually driven by a constant pressure gradient, thus a whole atmospheric boundary layer is simulated. Rigorously, this represents two different simulated cases making the model comparison not trivial. Nevertheless, both atmospheric flow cases are studied with the mentioned models. The results prove that a simple comparison of the time average turbulent quantities obtained by RANS and hybrid simulations is not easily achieved. The RANS simulations yield consistent results for the atmospheric surface layer case, while the hybrid model results are not correct. As for the atmospheric boundary

  11. Buckling induced delamination of graphene composites through hybrid molecular modeling

    Science.gov (United States)

    Cranford, Steven W.

    2013-01-01

    The efficiency of graphene-based composites relies on mechanical stability and cooperativity, whereby separation of layers (i.e., delamination) can severely hinder performance. Here we study buckling induced delamination of mono- and bilayer graphene-based composites, utilizing a hybrid full atomistic and coarse-grained molecular dynamics approach. The coarse-grain model allows exploration of an idealized model material to facilitate parametric variation beyond any particular molecular structure. Through theoretical and simulation analyses, we show a critical delamination condition, where ΔD∝kL4, where ΔD is the change in bending stiffness (eV), k the stiffness of adhesion (eV/Å4), and L the length of the adhered section (Å).

  12. A Hybrid Program Projects Selection Model for Nonprofit TV Stations

    Directory of Open Access Journals (Sweden)

    Kuei-Lun Chang

    2015-01-01

    Full Text Available This study develops a hybrid multiple criteria decision making (MCDM model to select program projects for nonprofit TV stations on the basis of managers’ perceptions. By the concept of balanced scorecard (BSC and corporate social responsibility (CSR, we collect criteria for selecting the best program project. Fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Next, considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain the weights of them. To avoid calculation and additional pairwise comparisons of ANP, technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. A case study is presented to demonstrate the applicability of the proposed model.

  13. 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.

  14. Designing e-learning cognitively: TSOI Hybrid Learning Model

    Directory of Open Access Journals (Sweden)

    Mun Fie Tsoi

    2008-08-01

    Full Text Available Research on learning has proposed various models for learning. However, generally, there has been an inadequate research of the application of these models for learning for example the Kolb’s experiential learning cycle or the Jarvis’s model of reflection and learning to the development of e-learning materials. This is more so especially due to lack of effective yet practical design model for designing interactive e-learning materials. Having this in mind, the TSOI Hybrid Learning Model can be used as a pedagogic model for the cognitive design of e-learning. This Model represents learning as a cyclical cognitive process. A major feature is to promote active cognitive processing in the learner for meaningful learning proceeding from inductive to deductive. Design specificity in science and chemistry education is illustrated in terms of instructional storyboarding and the research-based e-learning product developed. Learners’ cognitive abilities will be addressed as part of the research data collected.

  15. OFF-LINE HANDWRITING RECOGNITION USING VARIOUS HYBRID MODELING TECHNIQUES AND CHARACTER N-GRAMS

    NARCIS (Netherlands)

    Brakensiek, A.; Rottland, J.; Kosmala, A.; Rigoll, G.

    2004-01-01

    In this paper a system for on-line cursive handwriting recognition is described. The system is based on Hidden Markov Models (HMMs) using discrete and hybrid modeling techniques. Here, we focus on two aspects of the recognition system. First, we present different hybrid modeling techniques, whereas

  16. Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation

    Directory of Open Access Journals (Sweden)

    Göran Ståhl

    2016-02-01

    Full Text Available This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where models play a core role: model-assisted, model-based, and hybrid estimation. The first two are well known, whereas the third has only recently been introduced in forest surveys. Hybrid inference mixes designbased and model-based inference, since it relies on a probability sample of auxiliary data and a model predicting the target variable from the auxiliary data..We review studies on large-area forest surveys based on model-assisted, modelbased, and hybrid estimation, and discuss advantages and disadvantages of the approaches. We conclude that no general recommendations can be made about whether model-assisted, model-based, or hybrid estimation should be preferred. The choice depends on the objective of the survey and the possibilities to acquire appropriate field and remotely sensed data. We also conclude that modelling approaches can only be successfully applied for estimating target variables such as growing stock volume or biomass, which are adequately related to commonly available remotely sensed data, and thus purely field based surveys remain important for several important forest parameters. Keywords: Design-based inference, Model-assisted estimation, Model-based inference, Hybrid inference, National forest inventory, Remote sensing, Sampling

  17. Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks

    Science.gov (United States)

    Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

    2013-01-01

    The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more

  18. Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

    Directory of Open Access Journals (Sweden)

    Natalie Berestovsky

    Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them

  19. Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

    Directory of Open Access Journals (Sweden)

    Natalie Berestovsky

    Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them

  20. Transcriptomic analysis in a Drosophila model identifies previously implicated and novel pathways in the therapeutic mechanism in neuropsychiatric disorders

    Directory of Open Access Journals (Sweden)

    Priyanka eSingh

    2011-03-01

    Full Text Available We have taken advantage of a newly described Drosophila model to gain insights into the potential mechanism of antiepileptic drugs (AEDs, a group of drugs that are widely used in the treatment of several neurological and psychiatric conditions besides epilepsy. In the recently described Drosophila model that is inspired by pentylenetetrazole (PTZ induced kindling epileptogenesis in rodents, chronic PTZ treatment for seven days causes a decreased climbing speed and an altered CNS transcriptome, with the latter mimicking gene expression alterations reported in epileptogenesis. In the model, an increased climbing speed is further observed seven days after withdrawal from chronic PTZ. We used this post-PTZ withdrawal regime to identify potential AED mechanism. In this regime, treatment with each of the five AEDs tested, namely, ethosuximide (ETH, gabapentin (GBP, vigabatrin (VGB, sodium valproate (NaVP and levetiracetam (LEV, resulted in rescuing of the altered climbing behavior. The AEDs also normalized PTZ withdrawal induced transcriptomic perturbation in fly heads; whereas AED untreated flies showed a large number of up- and down-regulated genes which were enriched in several processes including gene expression and cell communication, the AED treated flies showed differential expression of only a small number of genes that did not enrich gene expression and cell communication processes. Gene expression and cell communication related upregulated genes in AED untreated flies overrepresented several pathways - spliceosome, RNA degradation, and ribosome in the former category, and inositol phosphate metabolism, phosphatidylinositol signaling, endocytosis and hedgehog signaling in the latter. Transcriptome remodeling effect of AEDs was overall confirmed by microarray clustering that clearly separated the profiles of AED treated and untreated flies. Besides being consistent with previously implicated pathways, our results provide evidence for a role of

  1. Hybrid Soft Soil Tire Model (HSSTM). Part 1: Tire Material and Structure Modeling

    Science.gov (United States)

    2015-04-28

    HYBRID SOFT SOIL TIRE MODEL (HSSTM). PART I: TIRE MATERIAL AND STRUCTURE MODELING Taheri, Sh.a,1, Sandu, C.a...model the dynamic behavior of the tire on soft soil , a lumped mass discretized tire model using Kelvin-Voigt elements is developed. To optimize the...terrains (such as sandy loam) and tire force and moments, soil sinkage, and tire deformation data were collected for various case studies based on a

  2. A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis

    Directory of Open Access Journals (Sweden)

    Juliana Yim

    2009-06-01

    Full Text Available This paper looks at the ability of a relatively new technique, hybrid ANN’s, to predict corporate distress in Brazil. These models are compared with traditional statistical techniques and conventional ANN models. The results suggest that hybrid neural networks outperform all other models in predicting firms in financial distress one year prior to the event. This suggests that for researchers, policymakers and others interested in early warning systems, hybrid networks may be a useful tool for predicting firm failure.

  3. A comparison of corporate distress prediction models in Brazil: hybrid neural networks, logit models and discriminant analysis

    Directory of Open Access Journals (Sweden)

    Juliana Yim

    2005-01-01

    Full Text Available This paper looks at the ability of a relatively new technique, hybrid ANN's, to predict corporate distress in Brazil. These models are compared with traditional statistical techniques and conventional ANN models. The results suggest that hybrid neural networks outperform all other models in predicting firms in financial distress one year prior to the event. This suggests that for researchers, policymakers and others interested in early warning systems, hybrid networks may be a useful tool for predicting firm failure.

  4. A Hybrid EAV-Relational Model for Consistent and Scalable Capture of Clinical Research Data.

    Science.gov (United States)

    Khan, Omar; Lim Choi Keung, Sarah N; Zhao, Lei; Arvanitis, Theodoros N

    2014-01-01

    Many clinical research databases are built for specific purposes and their design is often guided by the requirements of their particular setting. Not only does this lead to issues of interoperability and reusability between research groups in the wider community but, within the project itself, changes and additions to the system could be implemented using an ad hoc approach, which may make the system difficult to maintain and even more difficult to share. In this paper, we outline a hybrid Entity-Attribute-Value and relational model approach for modelling data, in light of frequently changing requirements, which enables the back-end database schema to remain static, improving the extensibility and scalability of an application. The model also facilitates data reuse. The methods used build on the modular architecture previously introduced in the CURe project.

  5. Modeling and simulation of a hybrid ship power system

    Science.gov (United States)

    Doktorcik, Christopher J.

    2011-12-01

    Optimizing the performance of naval ship power systems requires integrated design and coordination of the respective subsystems (sources, converters, and loads). A significant challenge in the system-level integration is solving the Power Management Control Problem (PMCP). The PMCP entails deciding on subsystem power usages for achieving a trade-off between the error in tracking a desired position/velocity profile, minimizing fuel consumption, and ensuring stable system operation, while at the same time meeting performance limitations of each subsystem. As such, the PMCP naturally arises at a supervisory level of a ship's operation. In this research, several critical steps toward the solution of the PMCP for surface ships have been undertaken. First, new behavioral models have been developed for gas turbine engines, wound rotor synchronous machines, DC super-capacitors, induction machines, and ship propulsion systems. Conventional models describe system inputs and outputs in terms of physical variables such as voltage, current, torque, and force. In contrast, the behavioral models developed herein express system inputs and outputs in terms of power whenever possible. Additionally, the models have been configured to form a hybrid system-level power model (HSPM) of a proposed ship electrical architecture. Lastly, several simulation studies have been completed to expose the capabilities and limitations of the HSPM.

  6. Simulation of hybrid vehicle propulsion with an advanced battery model

    Energy Technology Data Exchange (ETDEWEB)

    Nallabolu, S.; Kostetzer, L.; Rudnyi, E. [CADFEM GmbH, Grafing (Germany); Geppert, M.; Quinger, D. [LION Smart GmbH, Frieding (Germany)

    2011-07-01

    In the recent years there has been observed an increasing concern about global warming and greenhouse gas emissions. In addition to the environmental issues the predicted scarcity of oil supplies and the dramatic increase in oil price puts new demands on vehicle design. As a result energy efficiency and reduced emission have become one of main selling point for automobiles. Hybrid electric vehicles (HEV) have therefore become an interesting technology for the governments and automotive industries. HEV are more complicated compared to conventional vehicles due to the fact that these vehicles contain more electrical components such as electric machines, power electronics, electronic continuously variable transmissions (CVT), and embedded powertrain controllers. Advanced energy storage devices and energy converters, such as Li-ion batteries, ultracapacitors, and fuel cells are also considered. A detailed vehicle model used for an energy flow analysis and vehicle performance simulation is necessary. Computer simulation is indispensible to facilitate the examination of the vast hybrid electric vehicle design space with the aim to predict the vehicle performance over driving profiles, estimate fuel consumption and the pollution emissions. There are various types of mathematical models and simulators available to perform system simulation of vehicle propulsion. One of the standard methods to model the complete vehicle powertrain is ''backward quasistatic modeling''. In this method vehicle subsystems are defined based on experiential models in the form of look-up tables and efficiency maps. The interaction between adjacent subsystems of the vehicle is defined through the amount of power flow. Modeling the vehicle subsystems like motor, engine, gearbox and battery is under this technique is based on block diagrams. The vehicle model is applied in two case studies to evaluate the vehicle performance and fuel consumption. In the first case study the affect

  7. Lumiproxy: A Hybrid Representation of Image-Based Models

    Institute of Scientific and Technical Information of China (English)

    Bin Sheng; Jian Zhu; En-Hua; Yan-Ci Zhang

    2009-01-01

    In this paper, we present a hybrid representation of image-based models combining the textured planes and the hierarchical points. Taking a set of depth images as input, our method starts from classifying input pixels into two categories, indicating the planar and non-planar surfaces respectively. For the planar surfaces, the geometric coefficients are reconstructed to form the uniformly sampled textures. For nearly planar surfaces, some textured planes, called lumiproxies,are constructed to represent the equivalent visual appearance. The Hough transform is used to find the positions of these textured planes, and optic flow measures are used to determine their textures. For remaining pixels corresponding to the non-planar geometries, the point primitive is applied, reorganized as the OBB-tree structure. Then, texture mapping and point splatting are employed together to render the novel views, with the hardware acceleration.

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

    Directory of Open Access Journals (Sweden)

    Fu-Kwun Wang

    2014-01-01

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

  9. Two dimensional cellular automaton for evacuation modeling: hybrid shuffle update

    CERN Document Server

    Arita, Chikashi; Appert-Rolland, Cécile

    2015-01-01

    We consider a cellular automaton model with a static floor field for pedestrians evacuating a room. After identifying some properties of real pedestrian flows, we discuss various update schemes, and we introduce a new one, the hybrid shuffle update. The properties specific to pedestrians are incorporated in variables associated to particles called phases, that represent their step cycles. The dynamics of the phases gives naturally raise to some friction, and allows to reproduce several features observed in experiments. We study in particular the crossover between a low- and a high-density regime that occurs when the density of pedestrian increases, the dependency of the outflow in the strength of the floor field, and the shape of the queue in front of the exit.

  10. Exploring the lambda model of the hybrid superstring

    Energy Technology Data Exchange (ETDEWEB)

    Schmidtt, David M. [Instituto de Física Teórica IFT/UNESP,Rua Dr. Bento Teobaldo Ferraz 271, Bloco II, CEP 01140-070, São Paulo-SP (Brazil)

    2016-10-26

    The purpose of this contribution is to initiate the study of integrable deformations for different superstring theory formalisms that manifest the property of (classical) integrability. In this paper we choose the hybrid formalism of the superstring in the background AdS{sub 2}×S{sup 2} and explore in detail the most immediate consequences of its λ-deformation. The resulting action functional corresponds to the λ-model of the matter part of the fairly more sophisticated pure spinor formalism, which is also known to be classical integrable. In particular, the deformation preserves the integrability and the one-loop conformal invariance of its parent theory, hence being a marginal deformation.

  11. Modelling hybrid Beta Cephei/SPB pulsations: Gamma Pegasi

    CERN Document Server

    Zdravkov, T

    2009-01-01

    Recent photometric and spectroscopic observations of the hybrid variable Gamma Pegasi (Handler et al. 2009, Handler 2009) revealed 6 frequencies of the SPB type and 8 of the Beta Cep type pulsations. Standard seismic models, which have been constructed with OPAL (Iglesias & Rogers 1996) and OP (Seaton 2005) opacities by fitting three frequencies (those of the radial fundamental and two dipole modes), do not reproduce the frequency range of observed pulsations and do not fit the observed individual frequencies with a satisfactory accuracy. We argue that better fitting can be achieved with opacity enhancements, over the OP data, by about 20-50 percent around the opacity bumps produced by excited ions of the iron-group elements at temperatures of about 200 000 K (Z bump) and 2 million K (Deep Opacity Bump).

  12. Hybrid Modelling Approach to Prairie hydrology: Fusing Data-driven and Process-based Hydrological Models

    Science.gov (United States)

    Mekonnen, B.; Nazemi, A.; Elshorbagy, A.; Mazurek, K.; Putz, G.

    2012-04-01

    Modeling the hydrological response in prairie regions, characterized by flat and undulating terrain, and thus, large non-contributing areas, is a known challenge. The hydrological response (runoff) is the combination of the traditional runoff from the hydrologically contributing area and the occasional overflow from the non-contributing area. This study provides a unique opportunity to analyze the issue of fusing the Soil and Water Assessment Tool (SWAT) and Artificial Neural Networks (ANNs) in a hybrid structure to model the hydrological response in prairie regions. A hybrid SWAT-ANN model is proposed, where the SWAT component and the ANN module deal with the effective (contributing) area and the non-contributing area, respectively. The hybrid model is applied to the case study of Moose Jaw watershed, located in southern Saskatchewan, Canada. As an initial exploration, a comparison between ANN and SWAT models is established based on addressing the daily runoff (streamflow) prediction accuracy using multiple error measures. This is done to identify the merits and drawbacks of each modeling approach. It has been found out that the SWAT model has better performance during the low flow periods but with degraded efficiency during periods of high flows. The case is different for the ANN model as ANNs exhibit improved simulation during high flow periods but with biased estimates during low flow periods. The modelling results show that the new hybrid SWAT-ANN model is capable of exploiting the strengths of both SWAT and ANN models in an integrated framrwork. The new hybrid SWAT-ANN model simulates daily runoff quite satisfactorily with NSE measures of 0.80 and 0.83 during calibration and validation periods, respectively. Furthermore, an experimental assessment was performed to identify the effects of the ANN training method on the performance of the hybrid model as well as the parametric identifiability. Overall, the results obtained in this study suggest that the fusion

  13. Photoionization models of the CALIFA HII regions. I. Hybrid models

    CERN Document Server

    Morisset, C; Sánchez, S F; Galbany, L; Garcia-Benito, R; Husemann, B; Marino, R A; Mast, D; Roth, M M; Colaboration, CALIFA

    2016-01-01

    Photoionization models of HII regions require as input a description of the ionizing SED and of the gas distribution, in terms of ionization parameter U and chemical abundances (e.g. O/H and N/O). A strong degeneracy exists between the hardness of the SED and U, which in turn leads to high uncertainties in the determination of the other parameters, including abundances. One way to resolve the degeneracy is to fix one of the parameters using additional information. For each of the ~ 20000 sources of the CALIFA HII regions catalog, a grid of photoionization models is computed assuming the ionizing SED being described by the underlying stellar population obtained from spectral synthesis modeling. The ionizing SED is then defined as the sum of various stellar bursts of different ages and metallicities. This solves the degeneracy between the shape of the ionizing SED and U. The nebular metallicity (associated to O/H) is defined using the classical strong line method O3N2 (which gives to our models the status of "h...

  14. Hybrid Models for Trajectory Error Modelling in Urban Environments

    Science.gov (United States)

    Angelatsa, E.; Parés, M. E.; Colomina, I.

    2016-06-01

    This paper tackles the first step of any strategy aiming to improve the trajectory of terrestrial mobile mapping systems in urban environments. We present an approach to model the error of terrestrial mobile mapping trajectories, combining deterministic and stochastic models. Due to urban specific environment, the deterministic component will be modelled with non-continuous functions composed by linear shifts, drifts or polynomial functions. In addition, we will introduce a stochastic error component for modelling residual noise of the trajectory error function. First step for error modelling requires to know the actual trajectory error values for several representative environments. In order to determine as accurately as possible the trajectories error, (almost) error less trajectories should be estimated using extracted nonsemantic features from a sequence of images collected with the terrestrial mobile mapping system and from a full set of ground control points. Once the references are estimated, they will be used to determine the actual errors in terrestrial mobile mapping trajectory. The rigorous analysis of these data sets will allow us to characterize the errors of a terrestrial mobile mapping system for a wide range of environments. This information will be of great use in future campaigns to improve the results of the 3D points cloud generation. The proposed approach has been evaluated using real data. The data originate from a mobile mapping campaign over an urban and controlled area of Dortmund (Germany), with harmful GNSS conditions. The mobile mapping system, that includes two laser scanner and two cameras, was mounted on a van and it was driven over a controlled area around three hours. The results show the suitability to decompose trajectory error with non-continuous deterministic and stochastic components.

  15. A hybrid multiview stereo algorithm for modeling urban scenes.

    Science.gov (United States)

    Lafarge, Florent; Keriven, Renaud; Brédif, Mathieu; Vu, Hoang-Hiep

    2013-01-01

    We present an original multiview stereo reconstruction algorithm which allows the 3D-modeling of urban scenes as a combination of meshes and geometric primitives. The method provides a compact model while preserving details: Irregular elements such as statues and ornaments are described by meshes, whereas regular structures such as columns and walls are described by primitives (planes, spheres, cylinders, cones, and tori). We adopt a two-step strategy consisting first in segmenting the initial meshbased surface using a multilabel Markov Random Field-based model and second in sampling primitive and mesh components simultaneously on the obtained partition by a Jump-Diffusion process. The quality of a reconstruction is measured by a multi-object energy model which takes into account both photo-consistency and semantic considerations (i.e., geometry and shape layout). The segmentation and sampling steps are embedded into an iterative refinement procedure which provides an increasingly accurate hybrid representation. Experimental results on complex urban structures and large scenes are presented and compared to state-of-the-art multiview stereo meshing algorithms.

  16. Control-relevant modeling and simulation of a SOFC-GT hybrid system

    Directory of Open Access Journals (Sweden)

    Rambabu Kandepu

    2006-07-01

    Full Text Available In this paper, control-relevant models of the most important components in a SOFC-GT hybrid system are described. Dynamic simulations are performed on the overall hybrid system. The model is used to develop a simple control structure, but the simulations show that more elaborate control is needed.

  17. Partitioning and interpolation based hybrid ARIMA–ANN model for time series forecasting

    Indian Academy of Sciences (India)

    C NARENDRA BABU; PALLAVIRAM SURE

    2016-07-01

    Time series data (TSD) originating from different applications have dissimilar characteristics. Hence for prediction of TSD, diversified varieties of prediction models exist. In many applications, hybrid models provide more accurate predictions than individual models. One such hybrid model, namely auto regressive integrated moving average – artificial neural network (ARIMA–ANN) is devised in many different ways in the literature. However, the prediction accuracy of hybrid ARIMA–ANN model can be further improved by devising suitable processing techniques. In this paper, a hybrid ARIMA–ANN model is proposed, which combines the concepts of the recently developed moving average (MA) filter based hybrid ARIMA–ANN model, with a processing technique involving a partitioning–interpolation (PI) step. The improved prediction accuracy of the proposed PI based hybrid ARIMA–ANN model is justified using a simulation experiment.Further, on different experimental TSD like sunspots TSD and electricity price TSD, the proposed hybrid model is applied along with four existing state-of-the-art models and it is found that the proposed model outperforms all the others, and hence is a promising model for TSD prediction

  18. Status and modeling improvements of hybrid wind/PV/diesel power systems for Brazilian applications

    Energy Technology Data Exchange (ETDEWEB)

    McGowan, J.G.; Manwell, J.F.; Avelar, C. [Univ. of Massachusetts, Amherst, MA (United States); Taylor, R. [National Renewable Energy Lab., Golden, CO (United States)

    1997-12-31

    This paper present a summary of the ongoing work on the modeling and system design of hybrid wind/PV/diesel systems for two different sites in the Amazonia region of Brazil. The work incorporates the latest resource data and is based on the use of the Hybrid2 simulation code developed by the University of Massachusetts and NREL. Details of the baseline operating hybrid systems are reviewed, and the results of the latest detailed hybrid system evaluation for each site are summarized. Based on the system modeling results, separate recommendations for system modification and improvements are made.

  19. Modelling the response of stable water isotopes in Greenland precipitation to orbital configurations of the previous interglacial

    Directory of Open Access Journals (Sweden)

    Jesper Sjolte

    2014-09-01

    Full Text Available The relation between δ 18O of precipitation and temperature has been used in numerous studies to reconstruct past temperatures at ice core sites in Greenland and Antarctica. During the past two decades, it has become clear that the slope between δ 18O and temperature varies in both space and time. Here, we use a general circulation model driven by changes in orbital parameters to investigate the Greenland δ 18O–temperature relation for the previous interglacial, the Eemian. In our analysis, we focus on changes in the moisture source regions, and the results underline the importance of taking the seasonality of climate change into account. The orbitally driven experiments show that continental evaporation over North America increases during summer in the warm parts of the Eemian, while marine evaporation decreases. This likely flattens the Greenland δ 18O response to temperature during summer. Since the main climate change in the experiments occurs during summer this adds to a limited response of δ 18O, which is more strongly tied to temperature during winter than during summer. A south–west to north–east gradient in the δ 18O–temperature slope is also evident for Greenland, with low slopes in the south–west and steeper slopes in the north–east. This probably reflects the proportion of continental moisture and Arctic moisture arriving in Greenland, with more continental moisture in the south–west and less in the north–east, and vice versa for the Arctic moisture.

  20. Hybrid Baryons

    CERN Document Server

    Page, P R

    2003-01-01

    We review the status of hybrid baryons. The only known way to study hybrids rigorously is via excited adiabatic potentials. Hybrids can be modelled by both the bag and flux-tube models. The low-lying hybrid baryon is N 1/2^+ with a mass of 1.5-1.8 GeV. Hybrid baryons can be produced in the glue-rich processes of diffractive gamma N and pi N production, Psi decays and p pbar annihilation.

  1. Tracer Modeling with the Hybrid Coordinates Ocean Model (hycom)

    Science.gov (United States)

    Garraffo, Z. D.; Kim, H.; Li, B.; Mehra, A.; Rivin, I.; Spindler, T.; Tolman, H. L.

    2012-12-01

    A series of tracer simulations have been started at NCEP/NWS aiming to a variety of applications, from dispersion of contaminants in estimations motivated by the Japanese nuclear accident near Fukushima, to nutrient estimations. The tracer capabilities of HYCOM are used, in regional domains, nested to daily nowcast/forecast fields from 1/12 HYCOM (RTOFS-Global) model output. A Fukushima Cs-137 simulation is now run in operational mode (RTOFS_ET). The simulation was initialized at the time of the Fukushima nuclear accident, and includes atmospheric deposition of Cs-137 and coastal discharge from a high resolution coastal model (ROMS done at NOAA/NOS). Almost all tracer moved offshore before the end of the first year after the accident. The tracer initially deposited in the Pacific ocean through the atmosphere slowly moves eastward and to deeper waters following the 3D ocean circulation. A series of simulations were started for nutrient estimations in the Gulf Stream and Mid Atlantic Bight region. Initially the capabilities implemented in HYCOM are used. The work aims to monitoring nutrients in the chosen region. Work is done in collaboration with Victoria Coles of U. Maryland.

  2. A logistical model for performance evaluations of hybrid generation systems

    Energy Technology Data Exchange (ETDEWEB)

    Bonanno, F.; Consoli, A.; Raciti, A. [Univ. of Catania (Italy). Dept. of Electrical, Electronic, and Systems Engineering; Lombardo, S. [Schneider Electric SpA, Torino (Italy)

    1998-11-01

    In order to evaluate the fuel and energy savings, and to focus on the problems related to the exploitation of combined renewable and conventional energies, a logistical model for hybrid generation systems (HGS`s) has been prepared. A software package written in ACSL, allowing easy handling of the models and data of the HGS components, is presented. A special feature of the proposed model is that an auxiliary fictitious source is introduced in order to obtain the power electric balance at the busbars during the simulation state and, also, in the case of ill-sized components. The observed imbalance powers are then used to update the system design. As a case study, the simulation program is applied to evaluate the energetic performance of a power plant relative to a small isolated community, and island in the Mediterranean Sea, in order to establish the potential improvement achievable via an optimal integration of renewable energy sources in conventional plants. Evaluations and comparisons among different-sized wind, photovoltaic, and diesel groups, as well as of different management strategies have been performed using the simulation package and are reported and discussed in order to present the track followed to select the final design.

  3. Weighted Hybrid Decision Tree Model for Random Forest Classifier

    Science.gov (United States)

    Kulkarni, Vrushali Y.; Sinha, Pradeep K.; Petare, Manisha C.

    2016-06-01

    Random Forest is an ensemble, supervised machine learning algorithm. An ensemble generates many classifiers and combines their results by majority voting. Random forest uses decision tree as base classifier. In decision tree induction, an attribute split/evaluation measure is used to decide the best split at each node of the decision tree. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation among them. The work presented in this paper is related to attribute split measures and is a two step process: first theoretical study of the five selected split measures is done and a comparison matrix is generated to understand pros and cons of each measure. These theoretical results are verified by performing empirical analysis. For empirical analysis, random forest is generated using each of the five selected split measures, chosen one at a time. i.e. random forest using information gain, random forest using gain ratio, etc. The next step is, based on this theoretical and empirical analysis, a new approach of hybrid decision tree model for random forest classifier is proposed. In this model, individual decision tree in Random Forest is generated using different split measures. This model is augmented by weighted voting based on the strength of individual tree. The new approach has shown notable increase in the accuracy of random forest.

  4. 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.

  5. A hybrid moment equation approach to gas-grain chemical modeling

    CERN Document Server

    Du, Fujun

    2011-01-01

    [Context] The stochasticity of grain chemistry requires special care in modeling. Previously methods based on the modified rate equation, the master equation, the moment equation, and Monte Carlo simulations have been used. [Aims] We attempt to develop a systematic and efficient way to model the gas-grain chemistry with a large reaction network as accurately as possible. [Methods] We present a hybrid moment equation approach which is a general and automatic method where the generating function is used to generate the moment equations. For large reaction networks, the moment equation is cut off at the second order, and a switch scheme is used when the average population of certain species reaches 1. For small networks, the third order moments can also be utilized to achieve a higher accuracy. [Results] For physical conditions in which the surface reactions are important, our method provides a major improvement over the rate equation approach, when benchmarked against the rigorous Monte Carlo results. For eithe...

  6. Modeling, hybridization, and optimal charging of electrical energy storage systems

    Science.gov (United States)

    Parvini, Yasha

    The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electrified vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the first step, the supercapacitor cell is modeled in order to gain fundamental understanding of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40°C to 60°C was embedded in this computationally efficient model. The coupled electro-thermal model was parameterized using specifically designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the benefits of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hardware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (muC) to implement the power management strategy, 12V lead-acid battery, and a 16.2V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efficient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efficiency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems

  7. 40 CFR 60.4236 - What is the deadline for importing or installing stationary SI ICE produced in the previous model...

    Science.gov (United States)

    2010-07-01

    ... installing stationary SI ICE produced in the previous model year? 60.4236 Section 60.4236 Protection of... installing stationary SI ICE produced in the previous model year? (a) After July 1, 2010, owners and operators may not install stationary SI ICE with a maximum engine power of less than 500 HP that do not...

  8. Forecasting Stock Exchange Movements Using Artificial Neural Network Models and Hybrid Models

    Science.gov (United States)

    Güreşen, Erkam; Kayakutlu, Gülgün

    Forecasting stock exchange rates is an important financial problem that is receiving increasing attention. During the last few years, a number of neural network models and hybrid models have been proposed for obtaining accurate prediction results, in an attempt to outperform the traditional linear and nonlinear approaches. This paper evaluates the effectiveness of neural network models; recurrent neural network (RNN), dynamic artificial neural network (DAN2) and the hybrid neural networks which use generalized autoregressive conditional heteroscedasticity (GARCH) and exponential generalized autoregressive conditional heteroscedasticity (EGARCH) to extract new input variables. The comparison for each model is done in two view points: MSE and MAD using real exchange daily rate values of Istanbul Stock Exchange (ISE) index XU10).

  9. Thermal-mechanical modeling of laser ablation hybrid machining

    Science.gov (United States)

    Matin, Mohammad Kaiser

    2001-08-01

    Hard, brittle and wear-resistant materials like ceramics pose a problem when being machined using conventional machining processes. Machining ceramics even with a diamond cutting tool is very difficult and costly. Near net-shape processes, like laser evaporation, produce micro-cracks that require extra finishing. Thus it is anticipated that ceramic machining will have to continue to be explored with new-sprung techniques before ceramic materials become commonplace. This numerical investigation results from the numerical simulations of the thermal and mechanical modeling of simultaneous material removal from hard-to-machine materials using both laser ablation and conventional tool cutting utilizing the finite element method. The model is formulated using a two dimensional, planar, computational domain. The process simulation acronymed, LAHM (Laser Ablation Hybrid Machining), uses laser energy for two purposes. The first purpose is to remove the material by ablation. The second purpose is to heat the unremoved material that lies below the ablated material in order to ``soften'' it. The softened material is then simultaneously removed by conventional machining processes. The complete solution determines the temperature distribution and stress contours within the material and tracks the moving boundary that occurs due to material ablation. The temperature distribution is used to determine the distance below the phase change surface where sufficient ``softening'' has occurred, so that a cutting tool may be used to remove additional material. The model incorporated for tracking the ablative surface does not assume an isothermal melt phase (e.g. Stefan problem) for laser ablation. Both surface absorption and volume absorption of laser energy as function of depth have been considered in the models. LAHM, from the thermal and mechanical point of view is a complex machining process involving large deformations at high strain rates, thermal effects of the laser, removal of

  10. Modeling and Simulation for Hybrid of PV-Wind system

    Directory of Open Access Journals (Sweden)

    Maged N. F. Nashed

    2015-04-01

    Full Text Available The rising consumption rate of fossil fuels causes a significant pollution impact on the atmosphere, unwanted greenhouse gases has drawn worldwide attention towards renewable energy sources. Moreover, in recent year’s generation of electricity using the different types of renewable sources are specifically evaluated in the economical performance of the overall equipment. This paper focuses on the modeling and analysis of a Standalone Photovoltaic (PV- wind energy hybrid generation system under different conditions using MATLAB. The proposed system consists of two renewable sources i.e. wind and solar energy. Modeling of PV array and wind turbine is explained. The wind subsystem is equipped of an induction generator. In photovoltaic system, the variable DC output voltage is controlled using buck-boost converter for the MPPT. These two systems are combined to operate in parallel and the common bus collects the total energy from the wind and PV systems are uses it to the load and with change the load

  11. A Hybrid Fuzzy Model for Lean Product Development Performance Measurement

    Science.gov (United States)

    Osezua Aikhuele, Daniel; Mohd Turan, Faiz

    2016-02-01

    In the effort for manufacturing companies to meet up with the emerging consumer demands for mass customized products, many are turning to the application of lean in their product development process, and this is gradually moving from being a competitive advantage to a necessity. However, due to lack of clear understanding of the lean performance measurements, many of these companies are unable to implement and fully integrated the lean principle into their product development process. Extensive literature shows that only few studies have focus systematically on the lean product development performance (LPDP) evaluation. In order to fill this gap, the study therefore proposed a novel hybrid model based on Fuzzy Reasoning Approach (FRA), and the extension of Fuzzy-AHP and Fuzzy-TOPSIS methods for the assessment of the LPDP. Unlike the existing methods, the model considers the importance weight of each of the decision makers (Experts) since the performance criteria/attributes are required to be rated, and these experts have different level of expertise. The rating is done using a new fuzzy Likert rating scale (membership-scale) which is designed such that it can address problems resulting from information lost/distortion due to closed-form scaling and the ordinal nature of the existing Likert scale.

  12. A hybrid simulation model for a stable auroral arc

    Directory of Open Access Journals (Sweden)

    P. Janhunen

    Full Text Available We present a new type of hybrid simulation model, intended to simulate a single stable auroral arc in the latitude/altitude plane. The ionospheric ions are treated as particles, the electrons are assumed to follow a Boltzmann response and the magnetospheric ions are assumed to be so hot that they form a background population unaffected by the electric fields that arise. The system is driven by assumed parallel electron energisation causing a primary negative charge cloud and an associated potential structure to build up. The results show how a closed potential structure and density depletion of an auroral arc build up and how they decay after the driver is turned off. The model also produces upgoing energetic ion beams and predicts strong static perpendicular electric fields to be found in a relatively narrow altitude range (~ 5000–11 000 km.

    Key words. Magnetospheric physics (magnetosphere-ionosphere interactions; auroral phenomena – Space plasma physics (numerical simulation studies

  13. Chern-Simons production during preheating in hybrid inflation models

    CERN Document Server

    García-Bellido, J; González-Arroyo, A; Garcia-Bellido, Juan; Perez, Margarita Garcia; Gonzalez-Arroyo, Antonio

    2004-01-01

    We study the onset of symmetry breaking after hybrid inflation in a model having the field content of the SU(2) gauge-scalar sector of the standard model, coupled to a singlet inflaton. This process is studied in (3+1)-dimensions in a fully non-perturbative way with the help of lattice techniques within the classical approximation. We focus on the role played by gauge fields and, in particular, on the generation of Chern-Simons number. Our results are shown to be insensitive to the various cut-offs introduced in our numerical approach. The spectra preserves a large hierarchy between long and short-wavelength modes during the whole period of symmetry breaking and Chern-Simons generation, confirming that the dynamics is driven by the low momentum sector of the theory. We establish that the Chern-Simons production mechanism is associated with local sphaleron-like structures. The corresponding sphaleron rates are of order 10^{-5} m^{-4}, which, within certain scenarios of electroweak baryogenesis and a (not unnat...

  14. Hybrid Network Defense Model Based on Fuzzy Evaluation

    Directory of Open Access Journals (Sweden)

    Ying-Chiang Cho

    2014-01-01

    Full Text Available With sustained and rapid developments in the field of information technology, the issue of network security has become increasingly prominent. The theme of this study is network data security, with the test subject being a classified and sensitive network laboratory that belongs to the academic network. The analysis is based on the deficiencies and potential risks of the network’s existing defense technology, characteristics of cyber attacks, and network security technologies. Subsequently, a distributed network security architecture using the technology of an intrusion prevention system is designed and implemented. In this paper, first, the overall design approach is presented. This design is used as the basis to establish a network defense model, an improvement over the traditional single-technology model that addresses the latter’s inadequacies. Next, a distributed network security architecture is implemented, comprising a hybrid firewall, intrusion detection, virtual honeynet projects, and connectivity and interactivity between these three components. Finally, the proposed security system is tested. A statistical analysis of the test results verifies the feasibility and reliability of the proposed architecture. The findings of this study will potentially provide new ideas and stimuli for future designs of network security architecture.

  15. Dynamic Hybrid Model for Short-Term Electricity Price Forecasting

    Directory of Open Access Journals (Sweden)

    Marin Cerjan

    2014-05-01

    Full Text Available Accurate forecasting tools are essential in the operation of electric power systems, especially in deregulated electricity markets. Electricity price forecasting is necessary for all market participants to optimize their portfolios. In this paper we propose a hybrid method approach for short-term hourly electricity price forecasting. The paper combines statistical techniques for pre-processing of data and a multi-layer (MLP neural network for forecasting electricity price and price spike detection. Based on statistical analysis, days are arranged into several categories. Similar days are examined by correlation significance of the historical data. Factors impacting the electricity price forecasting, including historical price factors, load factors and wind production factors are discussed. A price spike index (CWI is defined for spike detection and forecasting. Using proposed approach we created several forecasting models of diverse model complexity. The method is validated using the European Energy Exchange (EEX electricity price data records. Finally, results are discussed with respect to price volatility, with emphasis on the price forecasting accuracy.

  16. Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States); Troch, Peter [Univ. of Arizona, Tucson, AZ (United States); Pelletier, Jon [Univ. of Arizona, Tucson, AZ (United States); Niu, Guo-Yue [Univ. of Arizona, Tucson, AZ (United States); Gochis, David [NCAR Research Applications Lab., Boulder, CO (United States)

    2015-11-15

    This is the Final Report of our four-year (3-year plus one-year no cost extension) collaborative project between the University of Arizona (UA) and the National Center for Atmospheric Research (NCAR). The overall objective of our project is to develop and evaluate the first hybrid 3-D hydrological model with a horizontal grid spacing of 1 km for the NCAR Community Earth System Model (CESM).

  17. A Hybrid Analytical/Simulation Modeling Approach for Planning and Optimizing Mass Tactical Airborne Operations

    Science.gov (United States)

    1995-05-01

    A HYBRID ANALYTICAL/ SIMULATION MODELING APPROACH FOR PLANNING AND OPTIMIZING MASS TACTICAL AIRBORNE OPERATIONS by DAVID DOUGLAS BRIGGS M.S.B.A...COVERED MAY 1995 TECHNICAL REPORT THESIS 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS A HYBRID ANALYTICAL SIMULATION MODELING APPROACH FOR PLANNING AND...are present. Thus, simulation modeling presents itself as an excellent alternate tool for planning because it allows for the modeling of highly complex

  18. Hybrid Simulation Modeling to Estimate U.S. Energy Elasticities

    Science.gov (United States)

    Baylin-Stern, Adam C.

    This paper demonstrates how an U.S. application of CIMS, a technologically explicit and behaviourally realistic energy-economy simulation model which includes macro-economic feedbacks, can be used to derive estimates of elasticity of substitution (ESUB) and autonomous energy efficiency index (AEEI) parameters. The ability of economies to reduce greenhouse gas emissions depends on the potential for households and industry to decrease overall energy usage, and move from higher to lower emissions fuels. Energy economists commonly refer to ESUB estimates to understand the degree of responsiveness of various sectors of an economy, and use estimates to inform computable general equilibrium models used to study climate policies. Using CIMS, I have generated a set of future, 'pseudo-data' based on a series of simulations in which I vary energy and capital input prices over a wide range. I then used this data set to estimate the parameters for transcendental logarithmic production functions using regression techniques. From the production function parameter estimates, I calculated an array of elasticity of substitution values between input pairs. Additionally, this paper demonstrates how CIMS can be used to calculate price-independent changes in energy-efficiency in the form of the AEEI, by comparing energy consumption between technologically frozen and 'business as usual' simulations. The paper concludes with some ideas for model and methodological improvement, and how these might figure into future work in the estimation of ESUBs from CIMS. Keywords: Elasticity of substitution; hybrid energy-economy model; translog; autonomous energy efficiency index; rebound effect; fuel switching.

  19. Further validation of artificial neural network-based emissions simulation models for conventional and hybrid electric vehicles.

    Science.gov (United States)

    Tóth-Nagy, Csaba; Conley, John J; Jarrett, Ronald P; Clark, Nigel N

    2006-07-01

    With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NO(x)]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NO(x) in the case of a class-8 truck but were more accurate as the truck weight increased.

  20. Modeling and design of a high-performance hybrid actuator

    Science.gov (United States)

    Aloufi, Badr; Behdinan, Kamran; Zu, Jean

    2016-12-01

    This paper presents the model and design of a novel hybrid piezoelectric actuator which provides high active and passive performances for smart structural systems. The actuator is composed of a pair of curved pre-stressed piezoelectric actuators, so-called commercially THUNDER actuators, installed opposite each other using two clamping mechanisms constructed of in-plane fixable hinges, grippers and solid links. A fully mathematical model is developed to describe the active and passive dynamics of the actuator and investigate the effects of its geometrical parameters on the dynamic stiffness, free displacement and blocked force properties. Among the literature that deals with piezoelectric actuators in which THUNDER elements are used as a source of electromechanical power, the proposed study is unique in that it presents a mathematical model that has the ability to predict the actuator characteristics and achieve other phenomena, such as resonances, mode shapes, phase shifts, dips, etc. For model validation, the measurements of the free dynamic response per unit voltage and passive acceleration transmissibility of a particular actuator design are used to check the accuracy of the results predicted by the model. The results reveal that there is a good agreement between the model and experiment. Another experiment is performed to teste the linearity of the actuator system by examining the variation of the output dynamic responses with varying forces and voltages at different frequencies. From the results, it can be concluded that the actuator acts approximately as a linear system at frequencies up to 1000 Hz. A parametric study is achieved here by applying the developed model to analyze the influence of the geometrical parameters of the fixable hinges on the active and passive actuator properties. The model predictions in the frequency range of 0-1000 Hz show that the hinge thickness, radius, and opening angle parameters have great effects on the frequency dynamic

  1. Three hybridization models based on local search scheme for job shop scheduling problem

    Science.gov (United States)

    Balbi Fraga, Tatiana

    2015-05-01

    This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

  2. Advances in modeling of lower hybrid current drive

    Science.gov (United States)

    Peysson, Y.; Decker, J.; Nilsson, E.; Artaud, J.-F.; Ekedahl, A.; Goniche, M.; Hillairet, J.; Ding, B.; Li, M.; Bonoli, P. T.; Shiraiwa, S.; Madi, M.

    2016-04-01

    First principle modeling of the lower hybrid (LH) current drive in tokamak plasmas is a longstanding activity, which is gradually gaining in accuracy thanks to quantitative comparisons with experimental observations. The ability to reproduce simulatenously the plasma current and the non-thermal bremsstrahlung radial profiles in the hard x-ray (HXR) photon energy range represents in this context a significant achievement. Though subject to limitations, ray tracing calculations are commonly used for describing wave propagation in conjunction with Fokker-Planck codes, as it can capture prominent features of the LH wave dynamics in a tokamak plasma-like toroidal refraction. This tool has been validated on several machines when the full absorption of the LH wave requires the transfer of a small fraction of power from the main lobes of the launched power spectrum to a tail at a higher parallel refractive index. Conversely, standard modeling based on toroidal refraction only becomes more challenging when the spectral gap is large, except if other physical mechanisms may dominate to bridge it, like parametric instabilities, as suggested for JET LH discharges (Cesario et al 2004 Phys. Rev. Lett. 92 175002), or fast fluctuations of the launched power spectrum or ‘tail’ LH model, as shown for Tore Supra (Decker et al 2014 Phys. Plasma 21 092504). The applicability of the heuristic ‘tail’ LH model is investigated for a broader range of plasma parameters as compared to the Tore Supra study and with different LH wave characteristics. Discrepancies and agreements between simulations and experiments depending upon the different models used are discussed. The existence of a ‘tail’ in the launched power spectrum significantly improves the agreement between modeling and experiments in plasma conditions for which the spectral gap is large in EAST and Alcator C-Mod tokamaks. For the Alcator C-Mod tokamak, the experimental evolution of the HXR profiles with density suggests

  3. Control and verification of industrial hybrid systems using models specified with the formalism $ chi $

    NARCIS (Netherlands)

    J.J.H. Fey

    1996-01-01

    textabstractControl and verification of hybrid systems is studied using two industrial examples. The hybrid models of a conveyor-belt and of a biochemical plant for the production of ethanol are specified in the formalism $chi .$ A verification of the closed-loop systems for those examples,

  4. Thermal equilibrium solution to new model of bipolar hybrid quantum hydrodynamics

    Science.gov (United States)

    Di Michele, Federica; Mei, Ming; Rubino, Bruno; Sampalmieri, Rosella

    2017-08-01

    In this paper we study the hybrid quantum hydrodynamic model for nano-sized bipolar semiconductor devices in thermal equilibrium. By introducing a hybrid version of the Bhom potential, we derive a bipolar hybrid quantum hydrodynamic model, which is able to account for quantum effects in a localized region of the device for both electrons and holes. Coupled with Poisson equation for the electric potential, the steady-state system is regionally degenerate in its ellipticity, due to the quantum effect only in part of the device. This regional degeneracy of ellipticity makes the study more challenging. The main purpose of the paper is to investigate the existence and uniqueness of the weak solutions to this new type of equations. We first establish the uniform boundedness of the smooth solutions to the modified bipolar quantum hydrodynamic model by the variational method, then we use the compactness technique to prove the existence of weak solutions to the original hybrid system by taking hybrid limit. In particular, we account for two different kinds of hybrid behaviour. We perform the first hybrid limit when both electrons and holes behave quantum in a given region of the device, and the second one when only one carrier exhibits hybrid behaviour, whereas the other one is presented classically in the whole domain. The semi-classical limit results are also obtained. Finally, the theoretical results are tested numerically on a simple toy model.

  5. A global hybrid coupled model based on Atmosphere-SST feedbacks

    CERN Document Server

    Cimatoribus, Andrea A; Dijkstra, Henk A

    2011-01-01

    A global hybrid coupled model is developed, with the aim of studying the effects of ocean-atmosphere feedbacks on the stability of the Atlantic meridional overturning circulation. The model includes a global ocean general circulation model and a statistical atmosphere model. The statistical atmosphere model is based on linear regressions of data from a fully coupled climate model on sea surface temperature both locally and hemispherically averaged, being the footprint of Atlantic meridional overturning variability. It provides dynamic boundary conditions to the ocean model for heat, freshwater and wind-stress. A basic but consistent representation of ocean-atmosphere feedbacks is captured in the hybrid coupled model and it is more than ten times faster than the fully coupled climate model. The hybrid coupled model reaches a steady state with a climate close to the one of the fully coupled climate model, and the two models also have a similar response (collapse) of the Atlantic meridional overturning circulati...

  6. Hybrid model for forecasting time series with trend, seasonal and salendar variation patterns

    Science.gov (United States)

    Suhartono; Rahayu, S. P.; Prastyo, D. D.; Wijayanti, D. G. P.; Juliyanto

    2017-09-01

    Most of the monthly time series data in economics and business in Indonesia and other Moslem countries not only contain trend and seasonal, but also affected by two types of calendar variation effects, i.e. the effect of the number of working days or trading and holiday effects. The purpose of this research is to develop a hybrid model or a combination of several forecasting models to predict time series that contain trend, seasonal and calendar variation patterns. This hybrid model is a combination of classical models (namely time series regression and ARIMA model) and/or modern methods (artificial intelligence method, i.e. Artificial Neural Networks). A simulation study was used to show that the proposed procedure for building the hybrid model could work well for forecasting time series with trend, seasonal and calendar variation patterns. Furthermore, the proposed hybrid model is applied for forecasting real data, i.e. monthly data about inflow and outflow of currency at Bank Indonesia. The results show that the hybrid model tend to provide more accurate forecasts than individual forecasting models. Moreover, this result is also in line with the third results of the M3 competition, i.e. the hybrid model on average provides a more accurate forecast than the individual model.

  7. Modeling, control, and simulation of grid connected intelligent hybrid battery/photovoltaic system using new hybrid fuzzy-neural method.

    Science.gov (United States)

    Rezvani, Alireza; Khalili, Abbas; Mazareie, Alireza; Gandomkar, Majid

    2016-07-01

    Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current-voltage or power-voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.

  8. Field Test of a Hybrid Finite-Difference and Analytic Element Regional Model.

    Science.gov (United States)

    Abrams, D B; Haitjema, H M; Feinstein, D T; Hunt, R J

    2016-01-01

    Regional finite-difference models often have cell sizes that are too large to sufficiently model well-stream interactions. Here, a steady-state hybrid model is applied whereby the upper layer or layers of a coarse MODFLOW model are replaced by the analytic element model GFLOW, which represents surface waters and wells as line and point sinks. The two models are coupled by transferring cell-by-cell leakage obtained from the original MODFLOW model to the bottom of the GFLOW model. A real-world test of the hybrid model approach is applied on a subdomain of an existing model of the Lake Michigan Basin. The original (coarse) MODFLOW model consists of six layers, the top four of which are aggregated into GFLOW as a single layer, while the bottom two layers remain part of MODFLOW in the hybrid model. The hybrid model and a refined "benchmark" MODFLOW model simulate similar baseflows. The hybrid and benchmark models also simulate similar baseflow reductions due to nearby pumping when the well is located within the layers represented by GFLOW. However, the benchmark model requires refinement of the model grid in the local area of interest, while the hybrid approach uses a gridless top layer and is thus unaffected by grid discretization errors. The hybrid approach is well suited to facilitate cost-effective retrofitting of existing coarse grid MODFLOW models commonly used for regional studies because it leverages the strengths of both finite-difference and analytic element methods for predictions in mildly heterogeneous systems that can be simulated with steady-state conditions.

  9. The effect of food related personality traits and lifestyle orientation on consumer’s behaviour related to extra virgin olive oil: estimation of an extended hybrid choice model.

    OpenAIRE

    Yangui, Ahmed1; Font, Montserrat Costa; Gil, José María

    2013-01-01

    Due to the increasing interest on understanding the formation of consumer’s food choice process, the hybrid choice model (HCM) has been developed. HCM represents a promising new class of models which merge classic choice models with structural equations models (SEM) for latent variables (LV). Regardless of their conceptual appeal, up to date the application of HCM in agro food marketing remains very scarce. The present work extends previous HCM applications by first estimating a random parame...

  10. Polarization of Inclusive $\\Lambda_{c}$'s in a Hybrid Model

    CERN Document Server

    Goldstein, G R

    2000-01-01

    A hybrid model is presented for hyperon polarization that is based on perturbative QCD subprocesses and the recombination of polarized quarks with scalar diquarks. The updated hybrid model is applied to $p+p\\to \\Lambda +X$ and successfully reproduces the detailed kinematic dependence shown by the data. The hybrid model is extended to include pion beams and polarized $\\Lambda_c$'s. The resulting polarization is found to be in fair agreement with recent experiments. Predictions for the polarization dependence on $x_F$ and $p_T$ is given.

  11. Modeling a Hybrid Microgrid Using Probabilistic Reconfiguration under System Uncertainties

    Directory of Open Access Journals (Sweden)

    Hadis Moradi

    2017-09-01

    Full Text Available A novel method for a day-ahead optimal operation of a hybrid microgrid system including fuel cells, photovoltaic arrays, a microturbine, and battery energy storage in order to fulfill the required load demand is presented in this paper. In the proposed system, the microgrid has access to the main utility grid in order to exchange power when required. Available municipal waste is utilized to produce the hydrogen required for running the fuel cells, and natural gas will be used as the backup source. In the proposed method, an energy scheduling is introduced to optimize the generating unit power outputs for the next day, as well as the power flow with the main grid, in order to minimize the operational costs and produced greenhouse gases emissions. The nature of renewable energies and electric power consumption is both intermittent and unpredictable, and the uncertainty related to the PV array power generation and power consumption has been considered in the next-day energy scheduling. In order to model uncertainties, some scenarios are produced according to Monte Carlo (MC simulations, and microgrid optimal energy scheduling is analyzed under the generated scenarios. In addition, various scenarios created by MC simulations are applied in order to solve unit commitment (UC problems. The microgrid’s day-ahead operation and emission costs are considered as the objective functions, and the particle swarm optimization algorithm is employed to solve the optimization problem. Overall, the proposed model is capable of minimizing the system costs, as well as the unfavorable influence of uncertainties on the microgrid’s profit, by generating different scenarios.

  12. Identification of differentially expressed genes in rat silicosis model by suppression subtractive hybridization analysis

    Institute of Scientific and Technical Information of China (English)

    Zhongyuan Jin; Chunyan Fu; Jifang Wen; Baoan Liu; Deyun Feng; Chen Chen; Xiang Li; Yongbin Hu; Jinwu Peng; Yu Liu; Jing Du

    2008-01-01

    The critical molecular mechanism in the development of the pulmonary fibrosis remains unknown, leaving diagnosed patients with a poor prognosis. To isolate the genes specifi-cally up-regulated in pulmonary fibrosis, we established a rat silicosis model 360 d after treatment with crystalline silica suspension. Radiographs of chests showed that some scattered high-density shadows appeared in the lung field.Typical microscopic fibrosing silicotic nodules formed in the lung,alveolar epithelial cells and bronchial epithelial cells,particularly around the partial fibrosing silicotic nodules;some of them showed atypical hyperplasia that suggested a correlation between silicosis and lung cancer.Suppression subtractive hybridization analysis was performed to compare gene expression in lung tissue with silicosis and normal lung tissue.Reverse transcription-polymerase chain rection showed that the expressions of seven novel cDNA sequences identified by suppression subtractive hybridization in lung tissue with silicosis differed from normal lung tissue. Bioinformatics analysis showed that 47 positive clones rep-resented 35 genes containing two putative proteins and four predicted similar proteins.The analysis also showed that some screened genes in silicosis,such as prolyl 4-hydroxylases,actin-related protein-2/3 complex and acidic mammalian chitinase,have not been previously reported.These genes may provide new clues for investigating the molecular mechanisms in the development of pulmonary fibrosis.

  13. HyLTL: a temporal logic for model checking hybrid systems

    Directory of Open Access Journals (Sweden)

    Davide Bresolin

    2013-08-01

    Full Text Available The model-checking problem for hybrid systems is a well known challenge in the scientific community. Most of the existing approaches and tools are limited to safety properties only, or operates by transforming the hybrid system to be verified into a discrete one, thus loosing information on the continuous dynamics of the system. In this paper we present a logic for specifying complex properties of hybrid systems called HyLTL, and we show how it is possible to solve the model checking problem by translating the formula into an equivalent hybrid automaton. In this way the problem is reduced to a reachability problem on hybrid automata that can be solved by using existing tools.

  14. Dynamic Modeling and Simulation on a Hybrid Power System for Electric Vehicle Applications

    Directory of Open Access Journals (Sweden)

    Hong-Wen He

    2010-11-01

    Full Text Available Hybrid power systems, formed by combining high-energy-density batteries and high-power-density ultracapacitors in appropriate ways, provide high-performance and high-efficiency power systems for electric vehicle applications. This paper first establishes dynamic models for the ultracapacitor, the battery and a passive hybrid power system, and then based on the dynamic models a comparative simulation between a battery only power system and the proposed hybrid power system was done under the UDDS (Urban Dynamometer Driving Schedule. The simulation results showed that the hybrid power system could greatly optimize and improve the efficiency of the batteries and their dynamic current was also decreased due to the participation of the ultracapacitors, which would have a good influence on batteries’ cycle life. Finally, the parameter matching for the passive hybrid power system was studied by simulation and comparisons.

  15. Hybrid Modeling for Soft Sensing of Molten Steel Temperature in LF

    Institute of Scientific and Technical Information of China (English)

    TIAN Hui-xin; MAO Zhi-zhong; WANG An-na

    2009-01-01

    Aiming at the limitations of traditional thermal model and intelligent model, a new hybrid model is established for soft sensing of the molten steel temperature in LF. Firstly, a thermal model based on energy conservation is described; and then, an improved intelligent model based on process data is presented by ensemble ELM (extreme learning machine) for predicting the molten steel temperature in LF. Secondly, the self-adaptive data fusion is proposed as a hybrid modeling method to combine the thermal model with the intelligent model. The new hybrid model could complement mutual advantage of two models by combination. It can overcome the shortcoming of parameters obtained on-line hardly in a thermal model and the disadvantage of lacking the analysis of ladle furnace metallurgical process in an intelligent model. The new hybrid model is applied to a 300 t LF in Baoshan Iron and Steel Co Ltd for predicting the molten steel temperature. The experiments demonstrate that the hybrid model has good generalization performance and high accuracy.

  16. Singularity avoidance in the hybrid quantization of the Gowdy model

    CERN Document Server

    Tarrío, Paula; Marugán, Guillermo A Mena

    2013-01-01

    One of the most remarkable phenomena in Loop Quantum Cosmology is that, at least for homogeneous cosmological models, the Big Bang is replaced with a Big Bounce that connects our universe with a previous branch without passing through a cosmological singularity. The goal of this work is to study the existence of singularities in Loop Quantum Cosmology including inhomogeneities and check whether the behavior obtained in the purely homogeneous setting continues to be valid. With this aim, we focus our attention on the three-torus Gowdy cosmologies with linearly polarized gravitational waves and use effective dynamics to carry out the analysis. For this model, we prove that all the potential cosmological singularities are avoided, generalizing the results about resolution of singularities to this scenario with inhomogeneities. We also demonstrate that, if a bounce in the (Bianchi background) volume occurs, the inhomogeneities increase the value of this volume at the bounce with respect to its counterpart in the ...

  17. Application of a New Hybrid Fuzzy AHP Model to the Location Choice

    Directory of Open Access Journals (Sweden)

    Chien-Chang Chou

    2013-01-01

    Full Text Available The purpose of this paper is to propose a new hybrid fuzzy Analytic Hierarchy Process (AHP algorithm to deal with the decision-making problems in an uncertain and multiple-criteria environment. In this study, the proposed hybrid fuzzy AHP model is applied to the location choices of international distribution centers in international ports from the view of multiple-nation corporations. The results show that the proposed new hybrid fuzzy AHP model is an appropriate tool to solve the decision-making problems in an uncertain and multiple-criteria environment.

  18. DESIGNING A FORECAST MODEL FOR ECONOMIC GROWTH OF JAPAN USING COMPETITIVE (HYBRID ANN VS MULTIPLE REGRESSION MODELS

    Directory of Open Access Journals (Sweden)

    Ahmet DEMIR

    2015-07-01

    Full Text Available Artificial neural network models have been already used on many different fields successfully. However, many researches show that ANN models provide better optimum results than other competitive models in most of the researches. But does it provide optimum solutions in case ANN is proposed as hybrid model? The answer of this question is given in this research by using these models on modelling a forecast for GDP growth of Japan. Multiple regression models utilized as competitive models versus hybrid ANN (ANN + multiple regression models. Results have shown that hybrid model gives better responds than multiple regression models. However, variables, which were significantly affecting GDP growth, were determined and some of the variables, which were assumed to be affecting GDP growth of Japan, were eliminated statistically.

  19. Dynamic modeling of hybrid energy storage systems coupled to photovoltaic generation in residential applications

    OpenAIRE

    Maclay, JD; J. Brouwer; Samuelsen, GS

    2007-01-01

    A model of a photovoltaic (PV) powered residence in stand-alone configuration was developed and evaluated. The model assesses the sizing, capital costs, control strategies, and efficiencies of reversible fuel cells (RFC), batteries, and ultra-capacitors (UC) both individually, and in combination, as hybrid energy storage devices. The choice of control strategy for a hybrid energy storage system is found to have a significant impact on system efficiency, hydrogen production and component utili...

  20. Hybrid Electric Vehicle Experimental Model with CAN Network Real Time Control

    Directory of Open Access Journals (Sweden)

    RATOI, M.

    2010-05-01

    Full Text Available In this paper an experimental model with a distributed control system of a hybrid electrical vehicle is presented. A communication CAN network of high speed (1 Mbps assures a distributed control of the all components. The modeling and the control of different operating regimes are realized on an experimental test-bench of a hybrid electrical vehicle. The experimental results concerning the variations of the mains variables (currents, torques, speeds are presented.

  1. Hybrid systems modelling and simulation in DESTECS: a co-simulation approach

    NARCIS (Netherlands)

    Ni, Yunyun; Broenink, Johannes F.; Klumpp, M.

    2012-01-01

    This paper introduces the modelling methodology and tooling in DESTECS (www.destecs.org) - Design Support and Tooling for Embedded Control Software - project as a novel modelling approach for hybrid systems from an executable model perspective. It provides a top-level structure for the system model

  2. Synthesis of a hybrid model of the VSC FACTS devices and HVDC technologies

    Science.gov (United States)

    Borovikov, Yu S.; Gusev, A. S.; Sulaymanov, A. O.; Ufa, R. A.

    2014-10-01

    The motivation of the presented research is based on the need for development of new methods and tools for adequate simulation of FACTS devices and HVDC systems as part of real electric power systems (EPS). The Research object: An alternative hybrid approach for synthesizing VSC-FACTS and -HVDC hybrid model is proposed. The results: the VSC- FACTS and -HVDC hybrid model is designed in accordance with the presented concepts of hybrid simulation. The developed model allows us to carry out adequate simulation in real time of all the processes in HVDC, FACTS devices and EPS as a whole without any decomposition and limitation on their duration, and also use the developed tool for effective solution of a design, operational and research tasks of EPS containing such devices.

  3. Prediction of melting temperatures in fluorescence in situ hybridization (FISH) procedures using thermodynamic models

    DEFF Research Database (Denmark)

    Fontenete, Sílvia; Guimarães, Nuno; Wengel, Jesper

    2016-01-01

    Abstract The thermodynamics and kinetics of DNA hybridization, i.e. the process of self-assembly of one, two or more complementary nucleic acid strands, has been studied for many years. The appearance of the nearest-neighbor model led to several theoretical and experimental papers on DNA thermody......Abstract The thermodynamics and kinetics of DNA hybridization, i.e. the process of self-assembly of one, two or more complementary nucleic acid strands, has been studied for many years. The appearance of the nearest-neighbor model led to several theoretical and experimental papers on DNA...... thermodynamics that provide reasonably accurate thermodynamic information on nucleic acid duplexes and allow estimation of the melting temperature. Because there are no thermodynamic models specifically developed to predict the hybridization temperature of a probe used in a fluorescence in situ hybridization...

  4. Mathematical Modeling of the Three Phase Induction Motor Couple to DC Motor in Hybrid Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Zulkarnain Lubis

    2009-01-01

    Full Text Available Problem statement: With emphasis on a cleaner environment and efficient operation, vehicles today rely more and more heavily on electrical power generation for success. Approach: Mathematical modeling the components of the HEV as the three phase induction motor couple to DC motor in hybrid electric vehicle was introduced. The controller of Induction Motor (IM was designed based on input-output feedback linearization technique. It allowed greater electrical generation capacity and the fuel economy and emissions benefits of hybrid electric automotive propulsion. Results: A typical series hybrid electric vehicle was modeled and investigated. Conclusion: Various tests, such as acceleration traversing ramp and fuel consumption and emission were performed on the proposed model of 3 phase induction motor coupler DC motor in electric hybrid vehicles drive.

  5. A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting

    Directory of Open Access Journals (Sweden)

    Zongxi Qu

    2016-01-01

    Full Text Available As a type of clean and renewable energy, the superiority of wind power has increasingly captured the world’s attention. Reliable and precise wind speed prediction is vital for wind power generation systems. Thus, a more effective and precise prediction model is essentially needed in the field of wind speed forecasting. Most previous forecasting models could adapt to various wind speed series data; however, these models ignored the importance of the data preprocessing and model parameter optimization. In view of its importance, a novel hybrid ensemble learning paradigm is proposed. In this model, the original wind speed data is firstly divided into a finite set of signal components by ensemble empirical mode decomposition, and then each signal is predicted by several artificial intelligence models with optimized parameters by using the fruit fly optimization algorithm and the final prediction values were obtained by reconstructing the refined series. To estimate the forecasting ability of the proposed model, 15 min wind speed data for wind farms in the coastal areas of China was performed to forecast as a case study. The empirical results show that the proposed hybrid model is superior to some existing traditional forecasting models regarding forecast performance.

  6. Two new prediction rules for spontaneous pregnancy leading to live birth among subfertile couples, based on the synthesis of three previous models.

    NARCIS (Netherlands)

    C.C. Hunault; J.D.F. Habbema (Dik); M.J.C. Eijkemans (René); J.A. Collins (John); J.L.H. Evers (Johannes); E.R. te Velde (Egbert)

    2004-01-01

    textabstractBACKGROUND: Several models have been published for the prediction of spontaneous pregnancy among subfertile patients. The aim of this study was to broaden the empirical basis for these predictions by making a synthesis of three previously published models. METHODS: We u

  7. Two new prediction rules for spontaneous pregnancy leading to live birth among subfertile couples, based on the synthesis of three previous models.

    NARCIS (Netherlands)

    C.C. Hunault; J.D.F. Habbema (Dik); M.J.C. Eijkemans (René); J.A. Collins (John); J.L.H. Evers (Johannes); E.R. te Velde (Egbert)

    2004-01-01

    textabstractBACKGROUND: Several models have been published for the prediction of spontaneous pregnancy among subfertile patients. The aim of this study was to broaden the empirical basis for these predictions by making a synthesis of three previously published models. METHODS: We u

  8. Stability Analysis of a Hybrid Cellular Automaton Model of Cell Colony Growth

    CERN Document Server

    Gerlee, P

    2007-01-01

    Cell colonies of bacteria, tumour cells and fungi, under nutrient limited growth conditions, exhibit complex branched growth patterns. In order to investigate this phenomenon we present a simple hybrid cellular automaton model of cell colony growth. In the model the growth of the colony is limited by a nutrient that is consumed by the cells and which inhibits cell division if it falls below a certain threshold. Using this model we have investigated how the nutrient consumption rate of the cells affects the growth dynamics of the colony. We found that for low consumption rates the colony takes on a Eden-like morphology, while for higher consumption rates the morphology of the colony is branched with a fractal geometry. These findings are in agreement with previous results, but the simplicity of the model presented here allows for a linear stability analysis of the system. By observing that the local growth of the colony is proportional to the flux of the nutrient we derive an approximate dispersion relation fo...

  9. Hierarchical hybrid testability modeling and evaluation method based on information fusion

    Institute of Scientific and Technical Information of China (English)

    Xishan Zhang; Kaoli Huang; Pengcheng Yan; Guangyao Lian

    2015-01-01

    In order to meet the demand of testability analysis and evaluation for complex equipment under a smal sample test in the equipment life cycle, the hierarchical hybrid testability model-ing and evaluation method (HHTME), which combines the testabi-lity structure model (TSM) with the testability Bayesian networks model (TBNM), is presented. Firstly, the testability network topo-logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob-ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in-formation. Final y, the learned hierarchical hybrid testability model (HHTM) is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accurate.

  10. Hybrid multiple attribute decision making model based on entropy

    Institute of Scientific and Technical Information of China (English)

    Wang Wei; Cui Mingming

    2007-01-01

    From the viewpoint of entropy, this paper investigates a hybrid multiple attribute decision making problem with precision number, interval number and fuzzy number. It defines a new concept: project entropy and the decision is taken according to the values. The validity and scientific nature of the given is proven.

  11. Model-based health monitoring of hybrid systems

    CERN Document Server

    Wang, Danwei; Low, Chang Boon; Arogeti, Shai

    2013-01-01

    Offers in-depth comprehensive study on health monitoring for hybrid systems Includes new concepts, such as GARR, mode tracking and multiple failure prognosis Contains many examples, making the developed techniques easily understandable and accessible Introduces state-of-the-art algorithms and methodologies from experienced researchers

  12. A Hybrid Method for Modeling and Solving Supply Chain Optimization Problems with Soft and Logical Constraints

    Directory of Open Access Journals (Sweden)

    Paweł Sitek

    2016-01-01

    Full Text Available This paper presents a hybrid method for modeling and solving supply chain optimization problems with soft, hard, and logical constraints. Ability to implement soft and logical constraints is a very important functionality for supply chain optimization models. Such constraints are particularly useful for modeling problems resulting from commercial agreements, contracts, competition, technology, safety, and environmental conditions. Two programming and solving environments, mathematical programming (MP and constraint logic programming (CLP, were combined in the hybrid method. This integration, hybridization, and the adequate multidimensional transformation of the problem (as a presolving method helped to substantially reduce the search space of combinatorial models for supply chain optimization problems. The operation research MP and declarative CLP, where constraints are modeled in different ways and different solving procedures are implemented, were linked together to use the strengths of both. This approach is particularly important for the decision and combinatorial optimization models with the objective function and constraints, there are many decision variables, and these are summed (common in manufacturing, supply chain management, project management, and logistic problems. The ECLiPSe system with Eplex library was proposed to implement a hybrid method. Additionally, the proposed hybrid transformed model is compared with the MILP-Mixed Integer Linear Programming model on the same data instances. For illustrative models, its use allowed finding optimal solutions eight to one hundred times faster and reducing the size of the combinatorial problem to a significant extent.

  13. Hybrid model predictive control for speed control of permanent magnet synchronous motor with saturation

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    A discrete-time hybrid model of a permanent magnet synchronous motor (PMSM) with saturation in voltage and current is formulated.The controller design with incorporated constraints is achieved in a systematic way from modeling to control synthesis and implementation.The Hybrid System Description Language is used to obtain a mixed-logical dynamical (MLD) model.Based on the MLD model,a model predictive controller is designed for an optimal speed regulation of the motor.For reducing computation complexity and ...

  14. Hybrid Model for Early Onset Prediction of Driver Fatigue with Observable Cues

    Directory of Open Access Journals (Sweden)

    Mingheng Zhang

    2014-01-01

    Full Text Available This paper presents a hybrid model for early onset prediction of driver fatigue, which is the major reason of severe traffic accidents. The proposed method divides the prediction problem into three stages, that is, SVM-based model for predicting the early onset driver fatigue state, GA-based model for optimizing the parameters in the SVM, and PCA-based model for reducing the dimensionality of the complex features datasets. The model and algorithm are illustrated with driving experiment data and comparison results also show that the hybrid method can generally provide a better performance for driver fatigue state prediction.

  15. Hybrid computational phantoms of the male and female newborn patient: NURBS-based whole-body models

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Choonsik [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Lodwick, Daniel [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Hasenauer, Deanna [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States); Williams, Jonathan L [Department of Radiology, University of Florida, Gainesville, FL 32611 (United States); Lee, Choonik [MD Anderson Cancer Center-Orlando, Orlando, FL 32806 (United States); Bolch, Wesley E [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL 32611 (United States)

    2007-07-21

    Anthropomorphic computational phantoms are computer models of the human body for use in the evaluation of dose distributions resulting from either internal or external radiation sources. Currently, two classes of computational phantoms have been developed and widely utilized for organ dose assessment: (1) stylized phantoms and (2) voxel phantoms which describe the human anatomy via mathematical surface equations or 3D voxel matrices, respectively. Although stylized phantoms based on mathematical equations can be very flexible in regard to making changes in organ position and geometrical shape, they are limited in their ability to fully capture the anatomic complexities of human internal anatomy. In turn, voxel phantoms have been developed through image-based segmentation and correspondingly provide much better anatomical realism in comparison to simpler stylized phantoms. However, they themselves are limited in defining organs presented in low contrast within either magnetic resonance or computed tomography images-the two major sources in voxel phantom construction. By definition, voxel phantoms are typically constructed via segmentation of transaxial images, and thus while fine anatomic features are seen in this viewing plane, slice-to-slice discontinuities become apparent in viewing the anatomy of voxel phantoms in the sagittal or coronal planes. This study introduces the concept of a hybrid computational newborn phantom that takes full advantage of the best features of both its stylized and voxel counterparts: flexibility in phantom alterations and anatomic realism. Non-uniform rational B-spline (NURBS) surfaces, a mathematical modeling tool traditionally applied to graphical animation studies, was adopted to replace the limited mathematical surface equations of stylized phantoms. A previously developed whole-body voxel phantom of the newborn female was utilized as a realistic anatomical framework for hybrid phantom construction. The construction of a hybrid

  16. Hybrid computational phantoms of the male and female newborn patient: NURBS-based whole-body models

    Science.gov (United States)

    Lee, Choonsik; Lodwick, Daniel; Hasenauer, Deanna; Williams, Jonathan L.; Lee, Choonik; Bolch, Wesley E.

    2007-07-01

    Anthropomorphic computational phantoms are computer models of the human body for use in the evaluation of dose distributions resulting from either internal or external radiation sources. Currently, two classes of computational phantoms have been developed and widely utilized for organ dose assessment: (1) stylized phantoms and (2) voxel phantoms which describe the human anatomy via mathematical surface equations or 3D voxel matrices, respectively. Although stylized phantoms based on mathematical equations can be very flexible in regard to making changes in organ position and geometrical shape, they are limited in their ability to fully capture the anatomic complexities of human internal anatomy. In turn, voxel phantoms have been developed through image-based segmentation and correspondingly provide much better anatomical realism in comparison to simpler stylized phantoms. However, they themselves are limited in defining organs presented in low contrast within either magnetic resonance or computed tomography images—the two major sources in voxel phantom construction. By definition, voxel phantoms are typically constructed via segmentation of transaxial images, and thus while fine anatomic features are seen in this viewing plane, slice-to-slice discontinuities become apparent in viewing the anatomy of voxel phantoms in the sagittal or coronal planes. This study introduces the concept of a hybrid computational newborn phantom that takes full advantage of the best features of both its stylized and voxel counterparts: flexibility in phantom alterations and anatomic realism. Non-uniform rational B-spline (NURBS) surfaces, a mathematical modeling tool traditionally applied to graphical animation studies, was adopted to replace the limited mathematical surface equations of stylized phantoms. A previously developed whole-body voxel phantom of the newborn female was utilized as a realistic anatomical framework for hybrid phantom construction. The construction of a hybrid

  17. AMITIS: A 3D GPU-Based Hybrid-PIC Model for Space and Plasma Physics

    Science.gov (United States)

    Fatemi, Shahab; Poppe, Andrew R.; Delory, Gregory T.; Farrell, William M.

    2017-05-01

    We have developed, for the first time, an advanced modeling infrastructure in space simulations (AMITIS) with an embedded three-dimensional self-consistent grid-based hybrid model of plasma (kinetic ions and fluid electrons) that runs entirely on graphics processing units (GPUs). The model uses NVIDIA GPUs and their associated parallel computing platform, CUDA, developed for general purpose processing on GPUs. The model uses a single CPU-GPU pair, where the CPU transfers data between the system and GPU memory, executes CUDA kernels, and writes simulation outputs on the disk. All computations, including moving particles, calculating macroscopic properties of particles on a grid, and solving hybrid model equations are processed on a single GPU. We explain various computing kernels within AMITIS and compare their performance with an already existing well-tested hybrid model of plasma that runs in parallel using multi-CPU platforms. We show that AMITIS runs ∼10 times faster than the parallel CPU-based hybrid model. We also introduce an implicit solver for computation of Faraday’s Equation, resulting in an explicit-implicit scheme for the hybrid model equation. We show that the proposed scheme is stable and accurate. We examine the AMITIS energy conservation and show that the energy is conserved with an error < 0.2% after 500,000 timesteps, even when a very low number of particles per cell is used.

  18. Effect of nonlinearity in hybrid kinetic Monte Carlo-continuum models.

    Science.gov (United States)

    Balter, Ariel; Lin, Guang; Tartakovsky, Alexandre M

    2012-01-01

    Recently there has been interest in developing efficient ways to model heterogeneous surface reactions with hybrid computational models that couple a kinetic Monte Carlo (KMC) model for a surface to a finite-difference model for bulk diffusion in a continuous domain. We consider two representative problems that validate a hybrid method and show that this method captures the combined effects of nonlinearity and stochasticity. We first validate a simple deposition-dissolution model with a linear rate showing that the KMC-continuum hybrid agrees with both a fully deterministic model and its analytical solution. We then study a deposition-dissolution model including competitive adsorption, which leads to a nonlinear rate, and show that in this case the KMC-continuum hybrid and fully deterministic simulations do not agree. However, we are able to identify the difference as a natural result of the stochasticity coming from the KMC surface process. Because KMC captures inherent fluctuations, we consider it to be more realistic than a purely deterministic model. Therefore, we consider the KMC-continuum hybrid to be more representative of a real system.

  19. Dynamic Modeling and Simulation of a Switched Reluctance Motor in a Series Hybrid Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Siavash Sadeghi

    2010-04-01

    Full Text Available Dynamic behavior analysis of electric motors is required in order to accuratelyevaluate the performance, energy consumption and pollution level of hybrid electricvehicles. Simulation tools for hybrid electric vehicles are divided into steady state anddynamic models. Tools with steady-state models are useful for system-level analysiswhereas tools that utilize dynamic models give in-depth information about the behavior ofsublevel components. For the accurate prediction of hybrid electric vehicle performance,dynamic modeling of the motor and other components is necessary. Whereas the switchedreluctance machine is well suited for electric and hybrid electric vehicles, due to the simpleand rugged construction, low cost, and ability to operate over a wide speed range atconstant power, in this paper dynamic performance of the switched reluctance motor for eseries hybrid electric vehicles is investigated. For this purpose a switched reluctance motorwith its electrical drive is modeld and simulated first, and then the other components of aseries hybrid electric vehicle, such as battery, generator, internal combusion engine, andgearbox, are designed and linked with the electric motor. Finally a typical series hybridelectric vehicle is simulated for different drive cycles. The extensive simulation results showthe dynamic performance of SRM, battery, fuel consumption, and emissions.

  20. Hybrid Model for Cascading Outage in a Power System: A Numerical Study

    Science.gov (United States)

    Susuki, Yoshihiko; Takatsuji, Yu; Hikihara, Takashi

    Analysis of cascading outages in power systems is important for understanding why large blackouts emerge and how to prevent them. Cascading outages are complex dynamics of power systems, and one cause of them is the interaction between swing dynamics of synchronous machines and protection operation of relays and circuit breakers. This paper uses hybrid dynamical systems as a mathematical model for cascading outages caused by the interaction. Hybrid dynamical systems can combine families of flows describing swing dynamics with switching rules that are based on protection operation. This paper refers to data on a cascading outage in the September 2003 blackout in Italy and shows a hybrid dynamical system by which propagation of outages reproduced is consistent with the data. This result suggests that hybrid dynamical systems can provide an effective model for the analysis of cascading outages in power systems.

  1. Hybrid Models Based on Singular Values and Autoregressive Methods for Multistep Ahead Forecasting of Traffic Accidents

    Directory of Open Access Journals (Sweden)

    Lida Barba

    2016-01-01

    Full Text Available The traffic accidents occurrence urges the intervention of researchers and society; the human losses and material damage could be abated with scientific studies focused on supporting prevention plans. In this paper prediction strategies based on singular values and autoregressive models are evaluated for multistep ahead traffic accidents forecasting. Three time series of injured people in traffic accidents collected in Santiago de Chile from 2000:1 to 2014:12 were used, which were previously classified by causes related to the behavior of drivers, passengers, or pedestrians and causes not related to the behavior as road deficiencies, mechanical failures, and undetermined causes. A simplified form of Singular Spectrum Analysis (SSA, combined with the autoregressive linear (AR method, and a conventional Artificial Neural Network (ANN are proposed. Additionally, equivalent models that combine Hankel Singular Value Decomposition (HSVD, AR, and ANN are evaluated. The comparative analysis shows that the hybrid models SSA-AR and SSA-ANN reach the highest accuracy with an average MAPE of 1.5% and 1.9%, respectively, from 1- to 14-step ahead prediction. However, it was discovered that HSVD-AR shows a higher accuracy in the farthest horizons, from 12- to 14-step ahead prediction, which reaches an average MAPE of 2.2%.

  2. 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.

  3. Hybrid Model for Cascading Outage in a Power System: A Numerical Study

    OpenAIRE

    Susuki, Yoshihiko; Takatsuji, Yu; Hikihara, Takashi

    2009-01-01

    Analysis of cascading outages in power systems is important for understanding why large blackouts emerge and how to prevent them. Cascading outages are complex dynamics of power systems, and one cause of them is the interaction between swing dynamics of synchronous machines and protection operation of relays and circuit breakers. This paper uses hybrid dynamical systems as a mathematical model for cascading outages caused by the interaction. Hybrid dynamical systems can combine families of fl...

  4. Hybrid experimental/analytical models of structural dynamics - Creation and use for predictions

    Science.gov (United States)

    Balmes, Etienne

    1993-01-01

    An original complete methodology for the construction of predictive models of damped structural vibrations is introduced. A consistent definition of normal and complex modes is given which leads to an original method to accurately identify non-proportionally damped normal mode models. A new method to create predictive hybrid experimental/analytical models of damped structures is introduced, and the ability of hybrid models to predict the response to system configuration changes is discussed. Finally a critical review of the overall methodology is made by application to the case of the MIT/SERC interferometer testbed.

  5. Calibrated and Interactive Modelling of Form-Active Hybrid Structures

    DEFF Research Database (Denmark)

    Quinn, Gregory; Holden Deleuran, Anders; Piker, Daniel

    2016-01-01

    Form-active hybrid structures (FAHS) couple two or more different structural elements of low self weight and low or negligible bending flexural stiffness (such as slender beams, cables and membranes) into one structural assembly of high global stiffness. They offer high load-bearing capacity...... materially-informed sketching. Making use of a projection-based dynamic relaxation solver for structural analysis, explorative design has proven to be highly effective....

  6. Interspecific hybrids of dwarf hamsters and Phasianidae birds as animal models for studying the genetic and developmental basis of hybrid incompatibility.

    Science.gov (United States)

    Ishishita, Satoshi; Matsuda, Yoichi

    2016-10-13

    Hybrid incompatibility is important in speciation as it prevents gene flow between closely related populations. Reduced fitness from hybrid incompatibility may also reinforce prezygotic reproductive isolation between sympatric populations. However, the genetic and developmental basis of hybrid incompatibility in higher vertebrates remains poorly understood. Mammals and birds, both amniotes, have similar developmental processes, but marked differences in development such as the XY/ZW sex determination systems and the presence or absence of genomic imprinting. Here, we review the sterile phenotype of hybrids between the Phodopus dwarf hamsters P. campbelli and P. sungorus, and the inviable phenotype of hybrids between two birds of the family Phasianidae, chicken (Gallus gallus domesticus) and Japanese quail (Coturnix japonica). We propose hypotheses for developmental defects that are associated with these hybrid incompatibilities. In addition, we discuss the genetic and developmental basis for these defects in conjunction with recent findings from mouse and avian models of genetics, reproductive biology and genomics. We suggest that these hybrids are ideal animal models for studying the genetic and developmental basis of hybrid incompatibility in amniotes.

  7. Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes

    Energy Technology Data Exchange (ETDEWEB)

    Felice, Maria V., E-mail: maria.felice@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol, U.K. and NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom); Velichko, Alexander, E-mail: p.wilcox@bristol.ac.uk; Wilcox, Paul D., E-mail: p.wilcox@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol (United Kingdom); Barden, Tim; Dunhill, Tony [NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom)

    2015-03-31

    Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.

  8. Adaptive control using a hybrid-neural model: application to a polymerisation reactor

    Directory of Open Access Journals (Sweden)

    Cubillos F.

    2001-01-01

    Full Text Available This work presents the use of a hybrid-neural model for predictive control of a plug flow polymerisation reactor. The hybrid-neural model (HNM is based on fundamental conservation laws associated with a neural network (NN used to model the uncertain parameters. By simulations, the performance of this approach was studied for a peroxide-initiated styrene tubular reactor. The HNM was synthesised for a CSTR reactor with a radial basis function neural net (RBFN used to estimate the reaction rates recursively. The adaptive HNM was incorporated in two model predictive control strategies, a direct synthesis scheme and an optimum steady state scheme. Tests for servo and regulator control showed excellent behaviour following different setpoint variations, and rejecting perturbations. The good generalisation and training capacities of hybrid models, associated with the simplicity and robustness characteristics of the MPC formulations, make an attractive combination for the control of a polymerisation reactor.

  9. Hybrid predictions of railway induced ground vibration using a combination of experimental measurements and numerical modelling

    Science.gov (United States)

    Kuo, K. A.; Verbraken, H.; Degrande, G.; Lombaert, G.

    2016-07-01

    Along with the rapid expansion of urban rail networks comes the need for accurate predictions of railway induced vibration levels at grade and in buildings. Current computational methods for making predictions of railway induced ground vibration rely on simplifying modelling assumptions and require detailed parameter inputs, which lead to high levels of uncertainty. It is possible to mitigate against these issues using a combination of field measurements and state-of-the-art numerical methods, known as a hybrid model. In this paper, two hybrid models are developed, based on the use of separate source and propagation terms that are quantified using in situ measurements or modelling results. These models are implemented using term definitions proposed by the Federal Railroad Administration and assessed using the specific illustration of a surface railway. It is shown that the limitations of numerical and empirical methods can be addressed in a hybrid procedure without compromising prediction accuracy.

  10. Multi-trait BLUP model indicates sorghum hybrids with genetic potential for agronomic and nutritional traits.

    Science.gov (United States)

    Almeida Filho, J E; Tardin, F D; Guimarães, J F R; Resende, M D V; Silva, F F; Simeone, M L; Menezes, C B; Queiroz, V A V

    2016-02-26

    The breeding of sorghum, Sorghum bicolor (L.) Moench, aimed at improving its nutritional quality, is of great interest, since it can be used as a highly nutritive alternative food source and can possibly be cultivated in regions with low rainfall. The objective of the present study was to evaluate the potential and genetic diversity of grain-sorghum hybrids for traits of agronomic and nutritional interest. To this end, the traits grain yield and flowering, and concentrations of protein, potassium, calcium, magnesium, sulfur, iron, manganese, and zinc in the grain were evaluated in 25 grain-sorghum hybrids, comprising 18 experimental hybrids of Embrapa Milho e Sorgo and seven commercial hybrids. The genetic potential was analyzed by a multi-trait best linear unbiased prediction (BLUP) model, and cluster analysis was accomplished by squared Mahalanobis distance using the predicted genotypic values. Hybrids 0306037 and 0306034 stood out in the agronomic evaluation. The hybrids with agronomic prominence, however, did not stand out for the traits related to the nutritional quality of the grain. Three clusters were formed from the dendrogram obtained with the unweighted pair group method with arithmetic mean method. From the results of the genotypic BLUP and the analysis of the dendrogram, hybrids 0577337, 0441347, 0307651, and 0306037 were identified as having the potential to establish a population that can aggregate alleles for all the evaluated traits of interest.

  11. 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.

  12. Modeling and Simulation of Renewable Hybrid Power System using Matlab Simulink Environment

    Directory of Open Access Journals (Sweden)

    Cristian Dragoş Dumitru

    2010-12-01

    Full Text Available The paper presents the modeling of a solar-wind-hydroelectric hybrid system in Matlab/Simulink environment. The application is useful for analysis and simulation of a real hybrid solar-wind-hydroelectric system connected to a public grid. Application is built on modular architecture to facilitate easy study of each component module influence. Blocks like wind model, solar model, hydroelectric model, energy conversion and load are implemented and the results of simulation are also presented. As an example, one of the most important studies is the behavior of hybrid system which allows employing renewable and variable in time energy sources while providing a continuous supply. Application represents a useful tool in research activity and also in teaching

  13. Mechanical Properties of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composites: Multiscale Modeling and Experiments

    Science.gov (United States)

    Hadden, C. M.; Klimek-McDonald, D. R.; Pineda, E. J.; King, J. A.; Reichanadter, A. M.; Miskioglu, I.; Gowtham, S.; Odegard, G. M.

    2015-01-01

    Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

  14. Mechanical Properties of Graphene Nanoplatelet Carbon Fiber Epoxy Hybrid Composites: Multiscale Modeling and Experiments

    Science.gov (United States)

    Hadden, Cameron M.; Klimek-McDonald, Danielle R.; Pineda, Evan J.; King, Julie A.; Reichanadter, Alex M.; Miskioglu, Ibrahim; Gowtham, S.; Odegard, Gregory M.

    2015-01-01

    Because of the relatively high specific mechanical properties of carbon fiber/epoxy composite materials, they are often used as structural components in aerospace applications. Graphene nanoplatelets (GNPs) can be added to the epoxy matrix to improve the overall mechanical properties of the composite. The resulting GNP/carbon fiber/epoxy hybrid composites have been studied using multiscale modeling to determine the influence of GNP volume fraction, epoxy crosslink density, and GNP dispersion on the mechanical performance. The hierarchical multiscale modeling approach developed herein includes Molecular Dynamics (MD) and micromechanical modeling, and it is validated with experimental testing of the same hybrid composite material system. The results indicate that the multiscale modeling approach is accurate and provides physical insight into the composite mechanical behavior. Also, the results quantify the substantial impact of GNP volume fraction and dispersion on the transverse mechanical properties of the hybrid composite, while the effect on the axial properties is shown to be insignificant.

  15. Coupled thermal model of photovoltaic-thermoelectric hybrid panel for sample cities in Europe

    DEFF Research Database (Denmark)

    Rezaniakolaei, Alireza; Sera, Dezso; Rosendahl, Lasse Aistrup

    2016-01-01

    generation by the TEG is insignificant compared to electrical output by the PV panel, and the TEG plays only a small role on power generation in the hybrid PV/TEG panel. However, contribution of the TEG in the power generation can be improved via higher ZT thermoelectric materials and geometry optimization......In general, modeling of photovoltaic-thermoelectric (PV/TEG) hybrid panels have been mostly simplified and disconnected from the actual ambient conditions and thermal losses from the panel. In this study, a thermally coupled model of PV/TEG panel is established to precisely predict performance...... of the hybrid system under different weather conditions. The model takes into account solar irradiation, wind speed and ambient temperature as well as convective and radiated heat losses from the front and rear surfaces of the panel. The model is developed for three sample cities in Europe with different...

  16. A Transport Model of Mobile Agent Based on Secure Hybrid Encryption

    Institute of Scientific and Technical Information of China (English)

    SUNZhixin; CHENZhixian; WANGRuchuan

    2005-01-01

    The solution of security problems of mobile agents is a key issue, which will decide whether mobile agents can be widely used. The paper analyzes main security problems, which currently are confronted with mobile agent systems and existing protection solutions. And then the paper presents a Security Transport model of mobile agents based on a hybrid encryption algorithm (TMSHE).Meanwhile, it expatiates on implementation of the algorithm. The algorithm of TMSHE model mainly consists of two parts, i.e., employing a hybrid encryption algorithm to encrypt mobile agents and using Transport layer security (TLS) to encrypt communication channel. Mobile agents by hybrid encryption move through communication channels, which are encrypted by TLS. The simulation results indicate that the model can protect mobile agents' security effectively, and consequently the security and steadiness of the whole mobile agent system are also improved. The model has succeeded in getting application in a prototypesystem- Intrusion detection system based on mobile agents.

  17. A Method for Estimating Urban Background Concentrations in Support of Hybrid Air Pollution Modeling for Environmental Health Studies

    Directory of Open Access Journals (Sweden)

    Saravanan Arunachalam

    2014-10-01

    Full Text Available Exposure studies rely on detailed characterization of air quality, either from sparsely located routine ambient monitors or from central monitoring sites that may lack spatial representativeness. Alternatively, some studies use models of various complexities to characterize local-scale air quality, but often with poor representation of background concentrations. A hybrid approach that addresses this drawback combines a regional-scale model to provide background concentrations and a local-scale model to assess impacts of local sources. However, this approach may double-count sources in the study regions. To address these limitations, we carefully define the background concentration as the concentration that would be measured if local sources were not present, and to estimate these background concentrations we developed a novel technique that combines space-time ordinary kriging (STOK of observations with outputs from a detailed chemistry-transport model with local sources zeroed out. We applied this technique to support an exposure study in Detroit, Michigan, for several pollutants (including NOx and PM2.5, and evaluated the estimated hybrid concentrations (calculated by combining the background estimates that addresses this issue of double counting with local-scale dispersion model estimates using observations. Our results demonstrate the strength of this approach specifically by eliminating the problem of double-counting reported in previous hybrid modeling approaches leading to improved estimates of background concentrations, and further highlight the relative importance of NOx vs. PM2.5 in their relative contributions to total concentrations. While a key limitation of this approach is the requirement for another detailed model simulation to avoid double-counting, STOK improves the overall characterization of background concentrations at very fine spatial scales.

  18. A Method for Estimating Urban Background Concentrations in Support of Hybrid Air Pollution Modeling for Environmental Health Studies

    Science.gov (United States)

    Arunachalam, Saravanan; Valencia, Alejandro; Akita, Yasuyuki; Serre, Marc L.; Omary, Mohammad; Garcia, Valerie; Isakov, Vlad

    2014-01-01

    Exposure studies rely on detailed characterization of air quality, either from sparsely located routine ambient monitors or from central monitoring sites that may lack spatial representativeness. Alternatively, some studies use models of various complexities to characterize local-scale air quality, but often with poor representation of background concentrations. A hybrid approach that addresses this drawback combines a regional-scale model to provide background concentrations and a local-scale model to assess impacts of local sources. However, this approach may double-count sources in the study regions. To address these limitations, we carefully define the background concentration as the concentration that would be measured if local sources were not present, and to estimate these background concentrations we developed a novel technique that combines space-time ordinary kriging (STOK) of observations with outputs from a detailed chemistry-transport model with local sources zeroed out. We applied this technique to support an exposure study in Detroit, Michigan, for several pollutants (including NOx and PM2.5), and evaluated the estimated hybrid concentrations (calculated by combining the background estimates that addresses this issue of double counting with local-scale dispersion model estimates) using observations. Our results demonstrate the strength of this approach specifically by eliminating the problem of double-counting reported in previous hybrid modeling approaches leading to improved estimates of background concentrations, and further highlight the relative importance of NOx vs. PM2.5 in their relative contributions to total concentrations. While a key limitation of this approach is the requirement for another detailed model simulation to avoid double-counting, STOK improves the overall characterization of background concentrations at very fine spatial scales. PMID:25321872

  19. Performance modeling of hybrid MPI/OpenMP scientific applications on large-scale multicore supercomputers

    KAUST Repository

    Wu, Xingfu

    2013-12-01

    In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore supercomputers: IBM POWER4, POWER5+ and BlueGene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks and Intel\\'s MPI benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore supercomputers because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyrokinetic Toroidal Code (GTC) in magnetic fusion to validate our performance model of the hybrid application on these multicore supercomputers. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore supercomputers. © 2013 Elsevier Inc.

  20. Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control.

    Science.gov (United States)

    Deshpande, Sunil; Nandola, Naresh N; Rivera, Daniel E; Younger, Jarred W

    2014-12-01

    The term adaptive intervention is used in behavioral health to describe individually-tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health.

  1. A Mean-Variance Hybrid-Entropy Model for Portfolio Selection with Fuzzy Returns

    Directory of Open Access Journals (Sweden)

    Rongxi Zhou

    2015-05-01

    Full Text Available In this paper, we define the portfolio return as fuzzy average yield and risk as hybrid-entropy and variance to deal with the portfolio selection problem with both random uncertainty and fuzzy uncertainty, and propose a mean-variance hybrid-entropy model (MVHEM. A multi-objective genetic algorithm named Non-dominated Sorting Genetic Algorithm II (NSGA-II is introduced to solve the model. We make empirical comparisons by using the data from the Shanghai and Shenzhen stock exchanges in China. The results show that the MVHEM generally performs better than the traditional portfolio selection models.

  2. Hybrid neural modelling of an anaerobic digester with respect to biological constraints.

    Science.gov (United States)

    Karama, A; Bernard, O; Gouzé, J L; Benhammou, A; Dochain, D

    2001-01-01

    A hybrid model for an anaerobic digestion process is proposed. The fermentation is assumed to be performed in two steps, acidogenesis and methanogenesis, by two bacterial populations. The model is based on mass balance equations, and the bacterial growth rates are represented by neural networks. In order to guarantee the biological meaning of the hybrid model (positivity of the concentrations, boundedness, saturation or inhibition of the growth rates) outside the training data set, a method that imposes constraints in the neural network is proposed. The method is applied to experimental data from a fixed bed reactor.

  3. 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.

  4. A model updating method for hybrid composite/aluminum bolted joints using modal test data

    Science.gov (United States)

    Adel, Farhad; Shokrollahi, Saeed; Jamal-Omidi, Majid; Ahmadian, Hamid

    2017-05-01

    The aim of this paper is to present a simple and applicable model for predicting the dynamic behavior of bolted joints in hybrid aluminum/composite structures and its model updating using modal test data. In this regards, after investigations on bolted joints in metallic structures which led to a new concept called joint affected region (JAR) published in Shokrollahi and Adel (2016), now, a doubly connective layer is established in order to simulate the bolted joint interfaces in hybrid structures. Using the proposed model, the natural frequencies of the hybrid bolted joint structure are computed and compared to the modal test results in order to evaluate and verify the new model predictions. Because of differences in the results of two approaches, the finite element (FE) model is updated based on the genetic algorithm (GA) by minimizing the differences between analytical model and test results. This is done by identifying the parameters at the JAR including isotropic Young's modulus in metallic substructure and that of anisotropic composite substructure. The updated model compared to the initial model simulates experimental results more properly. Therefore, the proposed model can be used for modal analysis of the hybrid joint interfaces in complex and large structures.

  5. A four-stage hybrid model for hydrological time series forecasting.

    Science.gov (United States)

    Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

    2014-01-01

    Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

  6. Design and Implementation of “Many Parallel Task” Hybrid Subsurface Model

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Khushbu; Chase, Jared M.; Schuchardt, Karen L.; Scheibe, Timothy D.; Palmer, Bruce J.; Elsethagen, Todd O.

    2011-11-01

    Continuum scale models have been used to study subsurface flow, transport, and reactions for many years. Recently, pore scale models, which operate at scales of individual soil grains, have been developed to more accurately model pore scale phenomena, such as precipitation, that may not be well represented at the continuum scale. However, particle-based models become prohibitively expensive for modeling realistic domains. Instead, we are developing a hybrid model that simulates the full domain at continuum scale and applies the pore model only to areas of high reactivity. The hybrid model uses a dimension reduction approach to formulate the mathematical exchange of information across scales. Since the location, size, and number of pore regions in the model varies, an adaptive Pore Generator is being implemented to define pore regions at each iteration. A fourth code will provide data transformation from the pore scale back to the continuum scale. These components are coupled into a single hybrid model using the SWIFT workflow system. Our hybrid model workflow simulates a kinetic controlled mixing reaction in which multiple pore-scale simulations occur for every continuum scale timestep. Each pore-scale simulation is itself parallel, thus exhibiting multi-level parallelism. Our workflow manages these multiple parallel tasks simultaneously, with the number of tasks changing across iterations. It also supports dynamic allocation of job resources and visualization processing at each iteration. We discuss the design, implementation and challenges associated with building a scalable, Many Parallel Task, hybrid model to run efficiently on thousands to tens of thousands of processors.

  7. Investigation of the Magnetotail and Inner Magnetosphere with Combined Global Hybrid and CIMI Models

    Science.gov (United States)

    Lin, Y.; Wang, X.; Perez, J. D.; Fok, M. C. H.

    2014-12-01

    The interconnection between the Earth's inner and outer magnetospheric regions is calculated by coupling an existing 3-D global hybrid simulation code to an existing ring current and radiation belt code, the Comprehensive Inner Magnetosphere/Ionosphere (CIMI) model. In the hybrid simulation, the global dynamics are driven by the solar wind and a southward IMF, and the simulation domain includes the plasma regions from x=-60RE to +20RE . Evolution of the magnetotail is revealed in the hybrid simulation. The response of the ring current and radiation belts is calculated by coupling the CIMI model to the global hybrid model. The hybrid simulation results provide the CIMI model with the magnetic field and electric potential at the high-latitude ionosphere boundary and plasma density and full ion phase space distribution function at the outer boundary at the equator. Our simulation shows that the ion velocity distributions in the tail are non-Maxwellian, with the existence of multiple ion beams, which have a significant impact on the ring current and the convection electric field. Detailed results will be presented for cases with various IMF and solar wind conditions, and the simulation will be compared with satellite observations.

  8. An equity-interest rate hybrid model with stochastic volatility and the interest rate smile

    NARCIS (Netherlands)

    Grzelak, L.A.; Oosterlee, C.W.

    2010-01-01

    We define an equity-interest rate hybrid model in which the equity part is driven by the Heston stochastic volatility [Hes93], and the interest rate (IR) is generated by the displaced-diffusion stochastic volatility Libor Market Model [AA02]. We assume a non-zero correlation between the main

  9. Applying TSOI Hybrid Learning Model to Enhance Blended Learning Experience in Science Education

    Science.gov (United States)

    Tsoi, Mun Fie

    2009-01-01

    Purpose: Research on the nature of blended learning and its features has led to a variety of approaches to the practice of blended learning. The purpose of this paper is to provide an alternative practice model, the TSOI hybrid learning model (HLM) to enhance the blended learning experiences in science education. Design/methodology/approach: The…

  10. MATHEMATICAL MODEL OF HYBRID ELECTRIC VEHICLE HIGH-VOLTAGE BATTERY IDENTIFICATION

    Directory of Open Access Journals (Sweden)

    S. Serikov

    2010-01-01

    Full Text Available The mathematical model of hybrid electric vehicle NiMH high-voltage battery is obtained. This model allows to explore the interaction of vehicle tractive electric drive and high-voltage battery at the electric motive power motion and in the process of recuperation of braking kinetic energy.

  11. Multi-Zone hybrid model for failure detection of the stable ventilation systems

    DEFF Research Database (Denmark)

    Gholami, Mehdi; Schiøler, Henrik; Soltani, Mohsen;

    2010-01-01

    In this paper, a conceptual multi-zone model for climate control of a live stock building is elaborated. The main challenge of this research is to estimate the parameters of a nonlinear hybrid model. A recursive estimation algorithm, the Extended Kalman Filter (EKF) is implemented for estimation....

  12. Assessing the Therapeutic Environment in Hybrid Models of Treatment: Prisoner Perceptions of Staff

    Science.gov (United States)

    Kubiak, Sheryl Pimlott

    2009-01-01

    Hybrid treatment models within prisons are staffed by both criminal justice and treatment professionals. Because these models may be indicative of future trends, examining the perceptions of prisoners/participants may provide important information. This study examines the perceptions of male and female inmates in three prisons, comparing those in…

  13. Hybrid Continuum and Molecular Modeling of Nano-scale Flows

    Science.gov (United States)

    Povitsky, Alex; Zhao, Shunliu

    2010-11-01

    A novel hybrid method combining the continuum approach based on boundary singularity method (BSM) and the molecular approach based on the direct simulation Monte Carlo (DSMC) is developed and then used to study viscous fibrous filtration flows in the transition flow regime, Kn>0.25. The DSMC is applied to a Knudsen layer enclosing the fiber and the BSM is employed to the entire flow domain. The parameters used in the DSMC and the coupling procedure, such as the number of simulated particles, the cell size and the size of the coupling zone are determined. Results are compared to the experiments measuring pressure drop and flowfield in filters. The optimal location of singularities outside of flow domain was determined and results are compared to those obtained by regularized Stokeslets. The developed hybrid method is parallelized by using MPI and extended to multi-fiber filtration flows. The multi-fiber filter flows considered are in the partial-slip and transition regimes. For Kn˜1, the computed velocity near fibers changes significantly that confirms the need of molecular methods in evaluation of the flow slip in transitional regime.

  14. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Directory of Open Access Journals (Sweden)

    René Felix Reinhart

    2017-02-01

    Full Text Available Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  15. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †.

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-02-08

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  16. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-01-01

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697

  17. Analysis of a model of fuel cell - gas turbine hybrid power system for enhanced energy efficiency

    Science.gov (United States)

    Calay, Rajnish K.; Mustafa, Mohamad Y.; Virk, Mohammad S.; Mustafa, Mahmoud F.

    2012-11-01

    A simple mathematical model to evaluate the performance of FC-GT hybrid system is presented in this paper. The model is used to analyse the influence of various parameters on the performance of a typical hybrid system, where excess heat rejected from the solid-oxide fuel cell stack is utilised to generate additional power through a gas turbine system and to provide heat energy for space heating. The model is based on thermodynamic analysis of various components of the plant and can be adapted for various configurations of the plant components. Because there are many parameters defining the efficiency and work output of the hybrid system, the technique is based on mathematical and graphical optimisation of various parameters; to obtain the maximum efficiency for a given plant configuration.

  18. Data Fusion Modeling for an RT3102 and Dewetron System Application in Hybrid Vehicle Stability Testing

    Directory of Open Access Journals (Sweden)

    Zhibin Miao

    2015-08-01

    Full Text Available More and more hybrid electric vehicles are driven since they offer such advantages as energy savings and better active safety performance. Hybrid vehicles have two or more power driving systems and frequently switch working condition, so controlling stability is very important. In this work, a two-stage Kalman algorithm method is used to fuse data in hybrid vehicle stability testing. First, the RT3102 navigation system and Dewetron system are introduced. Second, a modeling of data fusion is proposed based on the Kalman filter. Then, this modeling is simulated and tested on a sample vehicle, using Carsim and Simulink software to test the results. The results showed the merits of this modeling.

  19. Prediction of multiaxial mechanical behavior for conventional and highly crosslinked UHMWPE using a hybrid constitutive model.

    Science.gov (United States)

    Bergström, J S; Rimnac, C M; Kurtz, S M

    2003-04-01

    The development of theoretical failure, fatigue, and wear models for ultra-high molecular weight polyethylene (UHMWPE) used in joint replacements has been hindered by the lack of a validated constitutive model that can accurately predict large deformation mechanical behavior under clinically relevant, multiaxial loading conditions. Recently, a new Hybrid constitutive model for unirradiated UHMWPE was developed Bergström et al., (Biomaterials 23 (2002) 2329) based on a physics-motivated framework which incorporates the governing micro-mechanisms of polymers into an effective and accurate continuum representation. The goal of the present study was to compare the predictive capability of the new Hybrid model with the J(2)-plasticity model for four conventional and highly crosslinked UHMWPE materials during multiaxial loading. After calibration under uniaxial loading, the predictive capabilities of the J(2)-plasticity and Hybrid model were tested by comparing the load-displacement curves from experimental multiaxial (small punch) tests with simulated load-displacement curves calculated using a finite element model of the experimental apparatus. The quality of the model predictions was quantified using the coefficient of determination (r(2)). The results of the study demonstrate that the Hybrid model outperforms the J(2)-plasticity model both for combined uniaxial tension and compression predictions and for simulating multiaxial large deformation mechanical behavior produced by the small punch test. The results further suggest that the parameters of the HM may be generalizable for a wide range of conventional, highly crosslinked, and thermally treated UHMWPE materials, based on the characterization of four material properties related to the elastic modulus, yield stress, rate of strain hardening, and locking stretch of the polymer chains. Most importantly, from a practical perspective, these four key material properties for the Hybrid constitutive model can be measured

  20. Fuzzy clustering, genetic algorithms and neuro-fuzzy methods compared for hybrid fuzzy-first principles modeling

    NARCIS (Netherlands)

    van Lith, Pascal; van Lith, P.F.; Betlem, Bernardus H.L.; Roffel, B.

    2002-01-01

    Hybrid fuzzy-first principles models can be a good alternative if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented by fuzzy submodels describing additional equations, such as mass transformation and

  1. Fuzzy Clustering, Genetic Algorithms and Neuro-Fuzzy Methods Compared for Hybrid Fuzzy-First Principles Modeling

    NARCIS (Netherlands)

    Lith, Pascal F. van; Betlem, Ben H.L.; Roffel, Brian

    2002-01-01

    Hybrid fuzzy-first principles models can be a good alternative if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented by fuzzy submodels describing additional equations, such as mass transformation and

  2. Fuzzy Clustering, Genetic Algorithms and Neuro-Fuzzy Methods Compared for Hybrid Fuzzy-First Principles Modeling

    NARCIS (Netherlands)

    Lith, Pascal F. van; Betlem, Ben H.L.; Roffel, Brian

    2002-01-01

    Hybrid fuzzy-first principles models can be a good alternative if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented by fuzzy submodels describing additional equations, such as mass transformation and transfe

  3. Fuzzy Clustering, Genetic Algorithms and Neuro-Fuzzy Methods Compared for Hybrid Fuzzy-First Principles Modeling

    NARCIS (Netherlands)

    Lith, Pascal F. van; Betlem, Ben H.L.; Roffel, Brian

    2002-01-01

    Hybrid fuzzy-first principles models can be a good alternative if a complete physical model is difficult to derive. These hybrid models consist of a framework of dynamic mass and energy balances, supplemented by fuzzy submodels describing additional equations, such as mass transformation and transfe

  4. A Hybrid LDA+gCCA Model for fMRI Data Classification and Visualization.

    Science.gov (United States)

    Afshin-Pour, Babak; Shams, Seyed-Mohammad; Strother, Stephen

    2015-05-01

    Linear predictive models are applied to functional MRI (fMRI) data to estimate boundaries that predict experimental task states for scans. These boundaries are visualized as statistical parametric maps (SPMs) and range from low to high spatial reproducibility across subjects (e.g., Strother , 2004; LaConte , 2003). Such inter-subject pattern reproducibility is an essential characteristic of interpretable SPMs that generalize across subjects. Therefore, we introduce a flexible hybrid model that optimizes reproducibility by simultaneously enhancing the prediction power and reproducibility. This hybrid model is formed by a weighted summation of the optimization functions of a linear discriminate analysis (LDA) model and a generalized canonical correlation (gCCA) model (Afshin-Pour , 2012). LDA preserves the model's ability to discriminate the fMRI scans of multiple brain states while gCCA finds a linear combination for each subject's scans such that the estimated boundary map is reproducible. The hybrid model is implemented in a split-half resampling framework (Strother , 2010) which provides reproducibility (r) and prediction (p) quality metrics. Then the model was compared with LDA, and Gaussian Naive Bayes (GNB). For simulated fMRI data, the hybrid model outperforms the other two techniques in terms of receiver operating characteristic (ROC) curves, particularly for detecting less predictable but spatially reproducible networks. These techniques were applied to real fMRI data to estimate the maps for two task contrasts. Our results indicate that compared to LDA and GNB, the hybrid model can provide maps with large increases in reproducibility for small reductions in prediction, which are jointly closer to the ideal performance point of (p=1, r=1).

  5. Modeling, analysis and control of fuel cell hybrid power systems

    Science.gov (United States)

    Suh, Kyung Won

    Transient performance is a key characteristic of fuel cells, that is sometimes more critical than efficiency, due to the importance of accepting unpredictable electric loads. To fulfill the transient requirement in vehicle propulsion and portable fuel cell applications, a fuel cell stack is typically coupled with a battery through a DC/DC converter to form a hybrid power system. Although many power management strategies already exist, they all rely on low level controllers that realize the power split. In this dissertation we design controllers that realize various power split strategies by directly manipulating physical actuators (low level commands). We maintain the causality of the electric dynamics (voltage and current) and investigate how the electric architecture affects the hybridization level and the power management. We first establish the performance limitations associated with a stand-alone and power-autonomous fuel cell system that is not supplemented by an additional energy storage and powers all its auxiliary components by itself. Specifically, we examine the transient performance in fuel cell power delivery as it is limited by the air supplied by a compressor driven by the fuel cell itself. The performance limitations arise from the intrinsic coupling in the fluid and electrical domain between the compressor and the fuel cell stack. Feedforward and feedback control strategies are used to demonstrate these limitations analytically and with simulations. Experimental tests on a small commercial fuel cell auxiliary power unit (APU) confirm the dynamics and the identified limitations. The dynamics associated with the integration of a fuel cell system and a DC/DC converter is then investigated. Decentralized and fully centralized (using linear quadratic techniques) controllers are designed to regulate the power system voltage and to prevent fuel cell oxygen starvation. Regulating these two performance variables is a difficult task and requires a compromise

  6. HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis

    Science.gov (United States)

    Narasimhan, Sriram; Brownston, Lee

    2012-01-01

    Hybrid Diagnosis Engine (HyDE) is a general framework for stochastic and hybrid model-based diagnosis that offers flexibility to the diagnosis application designer. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. Several alternative algorithms are available for the various steps in diagnostic reasoning. This approach is extensible, with support for the addition of new modeling paradigms as well as diagnostic reasoning algorithms for existing or new modeling paradigms. HyDE is a general framework for stochastic hybrid model-based diagnosis of discrete faults; that is, spontaneous changes in operating modes of components. HyDE combines ideas from consistency-based and stochastic approaches to model- based diagnosis using discrete and continuous models to create a flexible and extensible architecture for stochastic and hybrid diagnosis. HyDE supports the use of multiple paradigms and is extensible to support new paradigms. HyDE generates candidate diagnoses and checks them for consistency with the observations. It uses hybrid models built by the users and sensor data from the system to deduce the state of the system over time, including changes in state indicative of faults. At each time step when observations are available, HyDE checks each existing candidate for continued consistency with the new observations. If the candidate is consistent, it continues to remain in the candidate set. If it is not consistent, then the information about the inconsistency is used to generate successor candidates while discarding the candidate that was inconsistent. The models used by HyDE are similar to simulation models. They describe the expected behavior of the system under nominal and fault conditions. The model can be constructed in modular and hierarchical fashion by building component/subsystem models (which may themselves contain component/ subsystem models) and linking them through shared variables/parameters. The

  7. Correlation and Regressive Model Between Spikelet Fertilized Rate and Temperature in Inter-Subspecific Hybrid Rice

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    To study the sensitivity of inter-subspecific hybrid rice to climatic conditions, the spikelet fertilized rate (SFR) of four types of rice including indica-japonica hybrid, intermediate hybrid, indica and japonica were analyzed during 2000-2004. The inter-subspecific hybrids showed lower SFR, and much higher fluctuation under various climatic conditions than indica and japonica rice, showing the inter-subspecific hybrids were sensitive to ecological conditions. Among 12 climatic factors, the key factor affecting rice SFR was temperature, with the most significant factor being the average temperature of the seven days around panicle flowering (T7). A regressive equation of SFR-temperature by T7, and a comprehensive synthetic model by four important temperature indices were put forward. The optimum temperature for inter-subspecific hybrids was estimated to be 26.1-26.6 ℃, and lower limit of safe temperature to be 22.5-23.3 ℃ for panicle flowering, showing higher by averagely 0.5℃ and 1.7℃, respectively, to be compared with indica and japonica rice. This suggested that inter-subspecific hybrids require proper climatic conditions. During panicle flowering, the suitable daily average temperature was 23.3-29.0 ℃, with the fittest one at 26.1-26.6 ℃. For an application example, optimum heading season for inter-subspecific hybrids in key rice growing areas in China was as same as common pure lines, while inferior limit for safe date of heading was about a ten-day period earlier than those of common pure lines.

  8. Solving Problem of Graph Isomorphism by Membrane-Quantum Hybrid Model

    Directory of Open Access Journals (Sweden)

    Artiom Alhazov

    2015-10-01

    Full Text Available This work presents the application of new parallelization methods based on membrane-quantum hybrid computing to graph isomorphism problem solving. Applied membrane-quantum hybrid computational model was developed by authors. Massive parallelism of unconventional computing is used to implement classic brute force algorithm efficiently. This approach does not suppose any restrictions of considered graphs types. The estimated performance of the model is less then quadratic that makes a very good result for the problem of \\textbf{NP} complexity.

  9. Bounded Model Checking and Inductive Verification of Hybrid Discrete-Continuous Systems

    DEFF Research Database (Denmark)

    Becker, Bernd; Behle, Markus; Eisenbrand, Fritz

    2004-01-01

    We present a concept to signicantly advance the state of the art for bounded model checking (BMC) and inductive verication (IV) of hybrid discrete-continuous systems. Our approach combines the expertise of partners coming from dierent domains, like hybrid systems modeling and digital circuit...... verication, bounded plan- ning and heuristic search, combinatorial optimization and integer programming. Af- ter sketching the overall verication ow we present rst results indicating that the combination and tight integration of dierent verication engines is a rst step to pave the way to fully automated BMC...

  10. A New Method for Modeling and Control of Hybrid Stepper Motors

    Directory of Open Access Journals (Sweden)

    George Mihalache

    2014-09-01

    Full Text Available Over time the mathematical models of the hybrid stepper motors (HSM have been developed in various forms. In this paper we propose to use for HSM a model of a two-phase synchronous machine with permanent magnet in which the number of pole pairs is equal to the number of rotor teeth of the HSM. It analyzes the behavior of hybrid stepper motor controlled in open loop. Control signals are obtained by implementing the control sequences:one-phase-on, two-phases-on, half step.

  11. Influence of Li-ion Battery Models in the Sizing of Hybrid Storage Systems with Supercapacitors

    DEFF Research Database (Denmark)

    Pinto, Claudio; Barreras, Jorge Varela; de Castro, Ricardo

    2014-01-01

    This paper presents a comparative study of the influence of different aggregated electrical circuit battery models in the sizing process of a hybrid energy storage system (ESS), composed by Li-ion batteries and supercapacitors (SCs). The aim is to find the number of cells required to propel......-order dynamics of the battery. Simulation results demonstrate that the adoption of a more accurate battery model in the sizing of hybrid ESSs prevents over-sizing, leading to a reduction in the number of cells of up to 29%, and a cost decrease of up to 10%....

  12. Daily air quality index forecasting with hybrid models: A case in China.

    Science.gov (United States)

    Zhu, Suling; Lian, Xiuyuan; Liu, Haixia; Hu, Jianming; Wang, Yuanyuan; Che, Jinxing

    2017-09-19

    Air quality is closely related to quality of life. Air pollution forecasting plays a vital role in air pollution warnings and controlling. However, it is difficult to attain accurate forecasts for air pollution indexes because the original data are non-stationary and chaotic. The existing forecasting methods, such as multiple linear models, autoregressive integrated moving average (ARIMA) and support vector regression (SVR), cannot fully capture the information from series of pollution indexes. Therefore, new effective techniques need to be proposed to forecast air pollution indexes. The main purpose of this research is to develop effective forecasting models for regional air quality indexes (AQI) to address the problems above and enhance forecasting accuracy. Therefore, two hybrid models (EMD-SVR-Hybrid and EMD-IMFs-Hybrid) are proposed to forecast AQI data. The main steps of the EMD-SVR-Hybrid model are as follows: the data preprocessing technique EMD (empirical mode decomposition) is utilized to sift the original AQI data to obtain one group of smoother IMFs (intrinsic mode functions) and a noise series, where the IMFs contain the important information (level, fluctuations and others) from the original AQI series. LS-SVR is applied to forecast the sum of the IMFs, and then, S-ARIMA (seasonal ARIMA) is employed to forecast the residual sequence of LS-SVR. In addition, EMD-IMFs-Hybrid first separately forecasts the IMFs via statistical models and sums the forecasting results of the IMFs as EMD-IMFs. Then, S-ARIMA is employed to forecast the residuals of EMD-IMFs. To certify the proposed hybrid model, AQI data from June 2014 to August 2015 collected from Xingtai in China are utilized as a test case to investigate the empirical research. In terms of some of the forecasting assessment measures, the AQI forecasting results of Xingtai show that the two proposed hybrid models are superior to ARIMA, SVR, GRNN, EMD-GRNN, Wavelet-GRNN and Wavelet-SVR. Therefore, the

  13. Modeling of Hybrid Permanent Magnetic-Gas Bearings

    DEFF Research Database (Denmark)

    Morosi, Stefano; Santos, Ilmar

    2009-01-01

    Modern turbomachinery applications require nowadays ever-growing rotational speeds and high degree of reliability. It then becomes natural to focus the attention of the research to contact-free bearings elements. The present alternatives focus on gas lubricated journal bearings or magnetic bearings....... In the present paper both the technologies are combined with the aim of developing a new kind of hybrid permanent magnetic - gas bearing. This new kind of machine is intended to exploit the benefits of the two technologies while minimizing their drawbacks. The poor start-up and low speed operation performance...... of the gas bearing is balanced by the properties of the passive magnetic one. At high speeds the dynamic characteristics of the gas bearing are improved by offsetting the stator ring of the permanent magnetic bearing. Furthermore this design shows a kind of redundancy, which offers soft failure properties...

  14. Modeling of Hybrid Permanent Magnetic-Gas Bearings

    DEFF Research Database (Denmark)

    Morosi, Stefano; Santos, Ilmar

    2009-01-01

    Modern turbomachinery applications require nowadays ever-growing rotational speeds and high degree of reliability. It then becomes natural to focus the attention of the research to contact-free bearings elements. The present alternatives focus on gas lubricated journal bearings or magnetic bearings...... concentric rings with radial magnetic orientation - analytical expressions for the calculation of the magnetic flux density and forces are employed, opposed to the main literature trend where finite element software is utilized at least for the calculation of the B-field. Numerical analysis shows how...... the rotor equilibrium position can be made independent on the rotational speed and applied load; it becomes function of the passive magnetic bearing offset. By adjusting the offset it is possible to significantly influence the dynamic coefficients of the hybrid bearing....

  15. Rough Set Model for Discovering Hybrid Association Rules

    CERN Document Server

    Pandey, Anjana

    2009-01-01

    In this paper, the mining of hybrid association rules with rough set approach is investigated as the algorithm RSHAR.The RSHAR algorithm is constituted of two steps mainly. At first, to join the participant tables into a general table to generate the rules which is expressing the relationship between two or more domains that belong to several different tables in a database. Then we apply the mapping code on selected dimension, which can be added directly into the information system as one certain attribute. To find the association rules, frequent itemsets are generated in second step where candidate itemsets are generated through equivalence classes and also transforming the mapping code in to real dimensions. The searching method for candidate itemset is similar to apriori algorithm. The analysis of the performance of algorithm has been carried out.

  16. A global hybrid coupled model based on atmosphere-SST feedbacks

    Energy Technology Data Exchange (ETDEWEB)

    Cimatoribus, Andrea A.; Drijfhout, Sybren S. [Royal Netherlands Meteorological Institute, De Bilt (Netherlands); Dijkstra, Henk A. [Utrecht University, Institute for Marine and Atmospheric Research Utrecht, Utrecht (Netherlands)

    2012-02-15

    A global hybrid coupled model is developed, with the aim of studying the effects of ocean-atmosphere feedbacks on the stability of the Atlantic meridional overturning circulation. The model includes a global ocean general circulation model and a statistical atmosphere model. The statistical atmosphere model is based on linear regressions of data from a fully coupled climate model on sea surface temperature both locally and hemispherically averaged, being the footprint of Atlantic meridional overturning variability. It provides dynamic boundary conditions to the ocean model for heat, freshwater and wind-stress. A basic but consistent representation of ocean-atmosphere feedbacks is captured in the hybrid coupled model and it is more than 10 times faster than the fully coupled climate model. The hybrid coupled model reaches a steady state with a climate close to the one of the fully coupled climate model, and the two models also have a similar response (collapse) of the Atlantic meridional overturning circulation to a freshwater hosing applied in the northern North Atlantic. (orig.)

  17. A hybrid model for predicting carbon monoxide from vehicular exhausts in urban environments

    Science.gov (United States)

    Gokhale, Sharad; Khare, Mukesh

    Several deterministic-based air quality models evaluate and predict the frequently occurring pollutant concentration well but, in general, are incapable of predicting the 'extreme' concentrations. In contrast, the statistical distribution models overcome the above limitation of the deterministic models and predict the 'extreme' concentrations. However, the environmental damages are caused by both extremes as well as by the sustained average concentration of pollutants. Hence, the model should predict not only 'extreme' ranges but also the 'middle' ranges of pollutant concentrations, i.e. the entire range. Hybrid modelling is one of the techniques that estimates/predicts the 'entire range' of the distribution of pollutant concentrations by combining the deterministic based models with suitable statistical distribution models ( Jakeman, et al., 1988). In the present paper, a hybrid model has been developed to predict the carbon monoxide (CO) concentration distributions at one of the traffic intersections, Income Tax Office (ITO), in the Delhi city, where the traffic is heterogeneous in nature and meteorology is 'tropical'. The model combines the general finite line source model (GFLSM) as its deterministic, and log logistic distribution (LLD) model, as its statistical components. The hybrid (GFLSM-LLD) model is then applied at the ITO intersection. The results show that the hybrid model predictions match with that of the observed CO concentration data within the 5-99 percentiles range. The model is further validated at different street location, i.e. Sirifort roadway. The validation results show that the model predicts CO concentrations fairly well ( d=0.91) in 10-95 percentiles range. The regulatory compliance is also developed to estimate the probability of exceedance of hourly CO concentration beyond the National Ambient Air Quality Standards (NAAQS) of India. It consists of light vehicles, heavy vehicles, three- wheelers (auto rickshaws) and two

  18. Multiscale modeling of rapid granular flow with a hybrid discrete-continuum method

    CERN Document Server

    Chen, Xizhong; Li, Jinghai

    2015-01-01

    Both discrete and continuum models have been widely used to study rapid granular flow, discrete model is accurate but computationally expensive, whereas continuum model is computationally efficient but its accuracy is doubtful in many situations. Here we propose a hybrid discrete-continuum method to profit from the merits but discard the drawbacks of both discrete and continuum models. Continuum model is used in the regions where it is valid and discrete model is used in the regions where continuum description fails, they are coupled via dynamical exchange of parameters in the overlap regions. Simulation of granular channel flow demonstrates that the proposed hybrid discrete-continuum method is nearly as accurate as discrete model, with much less computational cost.

  19. Development of Hybrid Models for a Vapor-Phase Fungi Bioreactor

    Directory of Open Access Journals (Sweden)

    Giorgia Spigno

    2015-01-01

    Full Text Available This study is aimed at the development of a model for an experimental vapour-phase fungi bioreactor, which could be derived in a simple way using the available measurements of a pilot-plant reactor, without the development of ad hoc experiments for the evaluation of fungi kinetics and the estimation of parameters related to biofilm characteristics. The proposed approach is based on hybrid models, obtained by the connection of the mass balance equation (used in traditional phenomenological models with a feedforward neural network (used in black-box modelling, and the proper use of statistical tools for the model assessment and system understanding. Two different hybrid models were developed and compared by proper performance indexes, and their capability to predict the biological complex phenomena was demonstrated and compared to that of a first-principle model.

  20. Modelling of hybrid scenario: from present-day experiments towards ITER

    Science.gov (United States)

    Litaudon, X.; Voitsekhovitch, I.; Artaud, J. F.; Belo, P.; Bizarro, João P. S.; Casper, T.; Citrin, J.; Fable, E.; Ferreira, J.; Garcia, J.; Garzotti, L.; Giruzzi, G.; Hobirk, J.; Hogeweij, G. M. D.; Imbeaux, F.; Joffrin, E.; Koechl, F.; Liu, F.; Lönnroth, J.; Moreau, D.; Parail, V.; Schneider, M.; Snyder, P. B.; the ASDEX-Upgrade Team; Contributors, JET-EFDA; the EU-ITM ITER Scenario Modelling Group

    2013-07-01

    The ‘hybrid’ scenario is an attractive operating scenario for ITER since it combines long plasma duration with the reliability of the reference H-mode regime. We review the recent European modelling effort carried out within the Integrated Scenario Modelling group which aims at (i) understanding the underlying physics of the hybrid regime in ASDEX-Upgrade and JET and (ii) extrapolating them towards ITER. JET and ASDEX-Upgrade hybrid scenarios performed under different experimental conditions have been simulated in an interpretative and predictive way in order to address the current profile dynamics and its link with core confinement, the relative importance of magnetic shear, s, and E × B flow shear on the core turbulence, pedestal stability and H-L transition. The correlation of the improved confinement with an increased s/q at outer radii observed in JET and ASDEX-Upgrade discharges is consistent with the predictions based on the GLF23 model applied in the simulations of the ion and electron kinetic profiles. Projections to ITER hybrid scenarios have been carried out focusing on optimization of the heating/current drive schemes to reach and ultimately control the desired plasma equilibrium using ITER actuators. Firstly, access condition to the hybrid-like q-profiles during the current ramp-up phase has been investigated. Secondly, from the interpreted role of the s/q ratio, ITER hybrid scenario flat-top performance has been optimized through tailoring the q-profile shape and pedestal conditions. EPED predictions of pedestal pressure and width have been used as constraints in the interpretative modelling while the core heat transport is predicted by GLF23. Finally, model-based approach for real-time control of advanced tokamak scenarios has been applied to ITER hybrid regime for simultaneous magnetic and kinetic profile control.

  1. Two new prediction rules for spontaneous pregnancy leading to live birth among subfertile couples, based on the synthesis of three previous models.

    Science.gov (United States)

    Hunault, C C; Habbema, J D F; Eijkemans, M J C; Collins, J A; Evers, J L H; te Velde, E R

    2004-09-01

    Several models have been published for the prediction of spontaneous pregnancy among subfertile patients. The aim of this study was to broaden the empirical basis for these predictions by making a synthesis of three previously published models. We used the original data from the studies of Eimers et al. (1994), Collins et al. (1995) and Snick et al. (1997) on couples consulting for various forms of subfertility. We developed a so-called three-sample synthesis model for predicting spontaneous conception leading to live birth within 1 year after intake based on the three data sets. The predictors used are duration of subfertility, women's age, primary or secondary infertility, percentage of motile sperm, and whether the couple was referred by a general practitioner or by a gynaecologist (referral status). The performance of this model was assessed according to a 'jack-knife' analysis. Because the post-coital test (PCT) was not assessed in one of the samples, a synthesis model including the PCT was based on two samples only. The ability of the synthesis models to distinguish between women who became pregnant and those who did not was comparable to the ability of the one-sample models when applied in the other samples. The reliability of the predictions by the three-sample synthesis model was somewhat better. Predictions improved considerably by including the PCT. The synthesis models performed better and had a broader empirical basis than the original models. They are therefore better suitable for application in other centres.

  2. A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time

    Energy Technology Data Exchange (ETDEWEB)

    Korotkin, Ivan, E-mail: i.korotkin@qmul.ac.uk; Karabasov, Sergey; Markesteijn, Anton [The School of Engineering and Material Science, Queen Mary University of London, Mile End Road, E1 4NS London (United Kingdom); Nerukh, Dmitry; Scukins, Arturs [Institute of Systems Analytics, Aston University, Birmingham B4 7ET (United Kingdom); Farafonov, Vladimir [Department of Physical Chemistry, V. N. Karazin Kharkiv National University, Svobody Square 4, 61022 Kharkiv (Ukraine); Pavlov, Evgen [Institute of Systems Analytics, Aston University, Birmingham B4 7ET (United Kingdom); Faculty of Physics, Kiev National Taras Shevchenko University, Prospect Acad. Glushkova 4, Kiev 03127 (Ukraine)

    2015-07-07

    A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single “zoom-in” user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.

  3. A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes.

    Science.gov (United States)

    Chen, Cong; Zhang, Guohui; Tarefder, Rafiqul; Ma, Jianming; Wei, Heng; Guan, Hongzhi

    2015-07-01

    Rear-end crash is one of the most common types of traffic crashes in the U.S. A good understanding of its characteristics and contributing factors is of practical importance. Previously, both multinomial Logit models and Bayesian network methods have been used in crash modeling and analysis, respectively, although each of them has its own application restrictions and limitations. In this study, a hybrid approach is developed to combine multinomial logit models and Bayesian network methods for comprehensively analyzing driver injury severities in rear-end crashes based on state-wide crash data collected in New Mexico from 2010 to 2011. A multinomial logit model is developed to investigate and identify significant contributing factors for rear-end crash driver injury severities classified into three categories: no injury, injury, and fatality. Then, the identified significant factors are utilized to establish a Bayesian network to explicitly formulate statistical associations between injury severity outcomes and explanatory attributes, including driver behavior, demographic features, vehicle factors, geometric and environmental characteristics, etc. The test results demonstrate that the proposed hybrid approach performs reasonably well. The Bayesian network reference analyses indicate that the factors including truck-involvement, inferior lighting conditions, windy weather conditions, the number of vehicles involved, etc. could significantly increase driver injury severities in rear-end crashes. The developed methodology and estimation results provide insights for developing effective countermeasures to reduce rear-end crash injury severities and improve traffic system safety performance.

  4. CAD model for circuit parameters of superconducting-based hybrid planar transmission lines

    Energy Technology Data Exchange (ETDEWEB)

    Mohebbi, Hamid Reza; Hamed Majedi, A, E-mail: hmohebbi@maxwell.uwaterloo.c, E-mail: ahmajedi@maxwell.uwaterloo.c [Integrated Quantum Optoelectronics Lab (IQOL), Department of ECE, Institute for Quantum Computing (IQC), University of Waterloo, Waterloo, N2L 3G1 (Canada)

    2009-12-15

    Using the concept of surface impedance associated with a superconductor or normal conductor's plate, we extend the CAD (computer aided design) formalisms on modeling and simulation of superconducting and normal transmission lines (STL and NTL) in order to include hybrid transmission lines (HTL). STL and NTL are entirely made of superconductor or normal conductor materials, respectively. In this paper, HTL refers to a planar transmission line (TL) such as parallel plate (PPTL), microstrip ({mu}TL) and coplanar waveguide (CPW) whose ground plate is superconducting and whose top/center strip is a normal conductor or vice versa. We develop and present a set of closed-form equations in a tidy and succinct form for each configuration (STL, NTL and HTL) for widely-used planar TLs (PPTL, {mu}TL and CPW). They can be easily implemented in a systematic way by the user for the purpose of fast TL design. The results obtained with this CAD tool are compared with previously reported results in the literature, and good agreement is observed.

  5. Accuracy improvement of a hybrid robot for ITER application using POE modeling method

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yongbo, E-mail: yongbo.wang@hotmail.com [Laboratory of Intelligent Machines, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland); Wu, Huapeng; Handroos, Heikki [Laboratory of Intelligent Machines, Lappeenranta University of Technology, FIN-53851 Lappeenranta (Finland)

    2013-10-15

    Highlights: ► The product of exponential (POE) formula for error modeling of hybrid robot. ► Differential Evolution (DE) algorithm for parameter identification. ► Simulation results are given to verify the effectiveness of the method. -- Abstract: This paper focuses on the kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial–parallel hybrid robot to improve its accuracy. The robot was designed to perform the assembling and repairing tasks of the vacuum vessel (VV) of the international thermonuclear experimental reactor (ITER). By employing the product of exponentials (POEs) formula, we extended the POE-based calibration method from serial robot to redundant serial–parallel hybrid robot. The proposed method combines the forward and inverse kinematics together to formulate a hybrid calibration method for serial–parallel hybrid robot. Because of the high nonlinear characteristics of the error model and too many error parameters need to be identified, the traditional iterative linear least-square algorithms cannot be used to identify the parameter errors. This paper employs a global optimization algorithm, Differential Evolution (DE), to identify parameter errors by solving the inverse kinematics of the hybrid robot. Furthermore, after the parameter errors were identified, the DE algorithm was adopted to numerically solve the forward kinematics of the hybrid robot to demonstrate the accuracy improvement of the end-effector. Numerical simulations were carried out by generating random parameter errors at the allowed tolerance limit and generating a number of configuration poses in the robot workspace. Simulation of the real experimental conditions shows that the accuracy of the end-effector can be improved to the same precision level of the given external measurement device.

  6. Modeling of plasma in a hybrid electric propulsion for small satellites

    Science.gov (United States)

    Jugroot, Manish; Christou, Alex

    2016-09-01

    As space flight becomes more available and reliable, space-based technology is allowing for smaller and more cost-effective satellites to be produced. Working in large swarms, many small satellites can provide additional capabilities while reducing risk. These satellites require efficient, long term propulsion for manoeuvres, orbit maintenance and de-orbiting. The high exhaust velocity and propellant efficiency of electric propulsion makes it ideally suited for low thrust missions. The two dominant types of electric propulsion, namely ion thrusters and Hall thrusters, excel in different mission types. In this work, a novel electric hybrid propulsion design is modelled to enhance understanding of key phenomena and evaluate performance. Specifically, the modelled hybrid thruster seeks to overcome issues with existing Ion and Hall thruster designs. Scaling issues and optimization of the design will be discussed and will investigate a conceptual design of a hybrid spacecraft plasma engine.

  7. Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction

    Science.gov (United States)

    Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro

    Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

  8. Hybrid OPC modeling with SEM contour technique for 10nm node process

    Science.gov (United States)

    Hitomi, Keiichiro; Halle, Scott; Miller, Marshal; Graur, Ioana; Saulnier, Nicole; Dunn, Derren; Okai, Nobuhiro; Hotta, Shoji; Yamaguchi, Atsuko; Komuro, Hitoshi; Ishimoto, Toru; Koshihara, Shunsuke; Hojo, Yutaka

    2014-03-01

    Hybrid OPC modeling is investigated using both CDs from 1D and simple 2D structures and contours extracted from complex 2D structures, which are obtained by a Critical Dimension-Scanning Electron Microscope (CD-SEM). Recent studies have addressed some of key issues needed for the implementation of contour extraction, including an edge detection algorithm consistent with conventional CD measurements, contour averaging and contour alignment. Firstly, pattern contours obtained from CD-SEM images were used to complement traditional site driven CD metrology for the calibration of OPC models for both metal and contact layers of 10 nm-node logic device, developed in Albany Nano-Tech. The accuracy of hybrid OPC model was compared with that of conventional OPC model, which was created with only CD data. Accuracy of the model, defined as total error root-mean-square (RMS), was improved by 23% with the use of hybrid OPC modeling for contact layer and 18% for metal layer, respectively. Pattern specific benefit of hybrid modeling was also examined. Resist shrink correction was applied to contours extracted from CD-SEM images in order to improve accuracy of the contours, and shrink corrected contours were used for OPC modeling. The accuracy of OPC model with shrink correction was compared with that without shrink correction, and total error RMS was decreased by 0.2nm (12%) with shrink correction technique. Variation of model accuracy among 8 modeling runs with different model calibration patterns was reduced by applying shrink correction. The shrink correction of contours can improve accuracy and stability of OPC model.

  9. 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

  10. Modeling and Optimal Control of a Class of Warfare Hybrid Dynamic Systems Based on Lanchester (n,1 Attrition Model

    Directory of Open Access Journals (Sweden)

    Xiangyong Chen

    2014-01-01

    hybrid dynamic systems is established based on Lanchester equation in a (n,1 battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation, and discrete event systems (described by variable tactics. Furthermore, an expository discussion is presented on an optimal variable tactics control problem for warfare hybrid dynamic system. The optimal control strategies are designed based on dynamic programming and differential game theory. As an example of the consequences of this optimal control problem, we take the (2, 1 case and solve the optimal strategies in a (2, 1 case. Simulation results show the feasibility of warfare hybrid system model and the effectiveness of the optimal control strategies designed.

  11. Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

    Science.gov (United States)

    Mohammed, E.; Wang, S.; Yu, J.

    2017-05-01

    This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

  12. Adaptive Agent Model with Hybrid Routing Selection Strategy for Improving the Road-Network Congestion Problem

    Institute of Scientific and Technical Information of China (English)

    Bin Jiang; Chao Yang; Takao Terano

    2015-01-01

    This paper proposes an adaptive agent model with a hybrid routing selection strategy for studying the road⁃network congestion problem. We focus on improving those severely congested links. Firstly, a multi⁃agent system is built, where each agent stands for a vehicle, and it makes its routing selection by considering the shortest path and the minimum congested degree of the target link simultaneously. The agent⁃based model captures the nonlinear feedback between vehicle routing behaviors and road⁃network congestion status. Secondly, a hybrid routing selection strategy is provided, which guides the vehicle routes adapting to the real⁃time road⁃network congestion status. On this basis, we execute simulation experiments and compare the simulation results of network congestion distribution, by Floyd agent with shortest path strategy and our proposed adaptive agent with hybrid strategy. The simulation results show that our proposed model has reduced the congestion degree of those seriously congested links of road⁃network. Finally, we execute our model on a real road map. The results finds that those seriously congested roads have some common features such as located at the road junction or near the unique road connecting two areas. And, the results also show an effectiveness of our model on reduction of those seriously congested links in this actual road network. Such a bottom⁃up congestion control approach with a hybrid congestion optimization perspective will have its significance for actual traffic congestion control.

  13. Hybrid Dynamic Modeling and Control of Molten Carbonate Fuel Cell Stack Shutdown

    Institute of Scientific and Technical Information of China (English)

    LI Yong; CAO Guang-yi; ZHU Xin-jian

    2007-01-01

    A hybrid automaton modeling approach that incorporates state space partitioning, phase dynamic modeling and control law synthesis by control strategy is utilized to develop a hybrid automaton model of molten carbonate fuel cell (MCFC) stack shutdown. The shutdown operation is divided into several phases and their boundaries are decided according to a control strategy, which is a set of specifications about the dynamics of MCFC stack during shutdown. According to the control strategy, the specification of increasing stack temperature is satisfied in a phase that can be modeled accurately. The model for phase that has complex dynamic is approximated. The duration of this kind of phase is decreased to minimize the error caused by model approximation.

  14. A modeling method of semiconductor fabrication flows with extended knowledge hybrid Petri nets

    Institute of Scientific and Technical Information of China (English)

    Zhou Binghai; Jiang Shuyu; Wang Shijin; Wu bin

    2008-01-01

    A modeling method of extended knowledge hybrid Petri nets (EKHPNs), incorporating object-oriented methods into hybrid Petri nets (HPNs), was presented and used for the representation and modeling of semiconductor wafer fabrication flows. To model the discrete and continuous parts of a complex semiconductor wafer fabrication flow, the HPNs were introduced into the EKHPNs. Object-oriented methods were combined into the EKHPNs for coping with the complexity of the fabrication flow. Knowledge annotations were introduced to solve input and output conflicts of the EKHPNs.Finally, to demonstrate the validity of the EKHPN method, a real semiconductor wafer fabrication case was used to illustrate the modeling procedure. The modeling results indicate that the proposed method can be used to model a complex semiconductor wafer fabrication flow expediently.

  15. Modelling the creep behaviour of tempered martensitic steel based on a hybrid approach

    Energy Technology Data Exchange (ETDEWEB)

    Yadav, Surya Deo, E-mail: surya.yadav@tugraz.at [Institute of Materials Science and Welding, Graz University of Technology, Kopernikusgasse 24, A-8010 Graz (Austria); Sonderegger, Bernhard, E-mail: bernhard.sonderegger@tugraz.at [Institute of Materials Science and Welding, Graz University of Technology, Kopernikusgasse 24, A-8010 Graz (Austria); Stracey, Muhammad, E-mail: strmuh001@myuct.ac.za [Centre for Materials Engineering, Department of Mechanical Engineering, University of Cape Town, Cape Town (South Africa); Poletti, Cecilia, E-mail: cecilia.poletti@tugraz.at [Institute of Materials Science and Welding, Graz University of Technology, Kopernikusgasse 24, A-8010 Graz (Austria)

    2016-04-26

    In this work, we present a novel hybrid approach to describe and model the creep behaviour of tempered martensitic steels. The hybrid approach couples a physically based model with a continuum damage mechanics (CDM) model. The creep strain is modelled describing the motions of three categories of dislocations: mobile, dipole and boundary. The initial precipitate state is simulated using the thermodynamic software tool MatCalc. The particle radii and number densities are incorporated into the creep model in terms of Zener drag pressure. The Orowan's equation for creep strain rate is modified to account for tertiary creep using softening parameters related to precipitate coarsening and cavitation. For the first time the evolution of internal variables such as dislocation densities, glide velocities, effective stresses on dislocations, internal stress from the microstructure, subgrain size, pressure on subgrain boundaries and softening parameters is discussed in detail. The model is validated with experimental data of P92 steel reported in the literature.

  16. Hybrid incompatibility arises in a sequence-based bioenergetic model of transcription factor binding.

    Science.gov (United States)

    Tulchinsky, Alexander Y; Johnson, Norman A; Watt, Ward B; Porter, Adam H

    2014-11-01

    Postzygotic isolation between incipient species results from the accumulation of incompatibilities that arise as a consequence of genetic divergence. When phenotypes are determined by regulatory interactions, hybrid incompatibility can evolve even as a consequence of parallel adaptation in parental populations because interacting genes can produce the same phenotype through incompatible allelic combinations. We explore the evolutionary conditions that promote and constrain hybrid incompatibility in regulatory networks using a bioenergetic model (combining thermodynamics and kinetics) of transcriptional regulation, considering the bioenergetic basis of molecular interactions between transcription factors (TFs) and their binding sites. The bioenergetic parameters consider the free energy of formation of the bond between the TF and its binding site and the availability of TFs in the intracellular environment. Together these determine fractional occupancy of the TF on the promoter site, the degree of subsequent gene expression and in diploids, and the degree of dominance among allelic interactions. This results in a sigmoid genotype-phenotype map and fitness landscape, with the details of the shape determining the degree of bioenergetic evolutionary constraint on hybrid incompatibility. Using individual-based simulations, we subjected two allopatric populations to parallel directional or stabilizing selection. Misregulation of hybrid gene expression occurred under either type of selection, although it evolved faster under directional selection. Under directional selection, the extent of hybrid incompatibility increased with the slope of the genotype-phenotype map near the derived parental expression level. Under stabilizing selection, hybrid incompatibility arose from compensatory mutations and was greater when the bioenergetic properties of the interaction caused the space of nearly neutral genotypes around the stable expression level to be wide. F2's showed higher

  17. Small World Effects in a Harmonious Unifying Hybrid Preferential Model Networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Small world effects in the harmonious unifying hybrid preferential model (HUHPM) networks are studied both numerically and analytically. The idea and method of the HUHPM is applied to three typical examples of unweighted BA model, weighted BBV model, and the TDE model, so-called HUHPM-BA, HUHPM-BBV and HUHPM-TDE networks. Comparing the HUHPM with current typical models above, it is found that the HUHPM networks has the smallest average path length and the biggest average clustering coefficient. The results demonstrate that the HUHPM is more suitable not only for the un-weighted models but also for the weighted models.

  18. A hybrid photoreceptor expressing both rod and cone genes in a mouse model of enhanced S-cone syndrome.

    Directory of Open Access Journals (Sweden)

    Joseph C Corbo

    2005-08-01

    Full Text Available Rod and cone photoreceptors subserve vision under dim and bright light conditions, respectively. The differences in their function are thought to stem from their different gene expression patterns, morphologies, and synaptic connectivities. In this study, we have examined the photoreceptor cells of the retinal degeneration 7(rd7 mutant mouse, a model for the human enhanced S-cone syndrome (ESCS. This mutant carries a spontaneous deletion in the mouse ortholog of NR2E3, an orphan nuclear receptor transcription factor mutated in ESCS. Employing microarray and in situ hybridization analysis we have found that the rd7 retina contains a modestly increased number of S-opsin-expressing cells that ultrastructurally appear to be normal cones. Strikingly, the majority of the photoreceptors in the rd7 retina represent a morphologically hybrid cell type that expresses both rod- and cone-specific genes. In addition, in situ hybridization screening of genes shown to be up-regulated in the rd7 mutant retina by microarray identified ten new cone-specific or cone-enriched genes with a wide range of biochemical functions, including two genes specifically involved in glucose/glycogen metabolism. We suggest that the abnormal electroretinograms, slow retinal degeneration, and retinal dysmorphology seen in humans with ESCS may, in part, be attributable to the aberrant function of a hybrid photoreceptor cell type similar to that identified in this study. The functional diversity of the novel cone-specific genes identified here indicates molecular differences between rods and cones extending far beyond those previously discovered.

  19. Battery Sizing for Plug-in Hybrid Electric Vehicles in Beijing: A TCO Model Based Analysis

    OpenAIRE

    Cong Hou; Hewu Wang; Minggao Ouyang

    2014-01-01

    This paper proposes a total cost of ownership (TCO) model for battery sizing of plug-in hybrid electric vehicles (PHEVs). The proposed systematic TCO model innovatively integrates the Beijing driving database and optimal PHEV energy management strategies developed earlier. The TCO, including battery, fuel, electricity, and salvage costs, is calculated in yearly cash flows. The salvage cost, based on battery degradation model, is proposed for the first time. The results show that the optimal b...

  20. Mathematical Model and Its Hybrid Dynamic Mechanism in Intelligent Control of Ironmaking

    Institute of Scientific and Technical Information of China (English)

    LIU Xiang-guan; ZENG Jiu-sun; ZHAO Min

    2007-01-01

    A hybrid dynamic model was proposed, which considered both the hydrokinetic and the chaotic properties of the blast furnace ironmaking process; and great emphasis was put on its mechanism. The new model took the high complexity of the blast furnace as well as the effects of main parameters of the model into account, and the predicted results were in very good agreement with actual data.

  1. Influence of Li-ion Battery Models in the Sizing of Hybrid Storage Systems with Supercapacitors

    OpenAIRE

    Pinto, Claudio; Barreras, Jorge Varela; Castro, Ricardo; Schaltz, Erik; Andreasen, Søren Juhl; Araujo, Rui Esteves

    2014-01-01

    This paper presents a comparative study of the influence of different aggregated electrical circuit battery models in the sizing process of a hybrid energy storage system (ESS), composed by Li-ion batteries and supercapacitors (SCs). The aim is to find the number of cells required to propel a certain vehicle over a predefined driving cycle. During this process, three battery models will be considered. The first consists in a linear static zeroeth order battery model over a restricted operatin...

  2. Hybrid supply chain model for material requirement planning under financial constraints: A case study

    Science.gov (United States)

    Curci, Vita; Dassisti, Michele; Josefa, Mula Bru; Manuel, Díaz Madroñero

    2014-10-01

    Supply chain model (SCM) are potentially capable to integrate different aspects in supporting decision making for enterprise management tasks. The aim of the paper is to propose an hybrid mathematical programming model for optimization of production requirements resources planning. The preliminary model was conceived bottom-up from a real industrial case analysed oriented to maximize cash flow. Despite the intense computational effort required to converge to a solution, optimisation done brought good result in solving the objective function.

  3. Solving Problems in Various Domains by Hybrid Models of High Performance Computations

    Directory of Open Access Journals (Sweden)

    Yurii Rogozhin

    2014-03-01

    Full Text Available This work presents a hybrid model of high performance computations. The model is based on membrane system (P~system where some membranes may contain quantum device that is triggered by the data entering the membrane. This model is supposed to take advantages of both biomolecular and quantum paradigms and to overcome some of their inherent limitations. The proposed approach is demonstrated through two selected problems: SAT, and image retrieving.

  4. Battery Sizing for Plug-in Hybrid Electric Vehicles in Beijing: A TCO Model Based Analysis

    OpenAIRE

    Cong Hou; Hewu Wang; Minggao Ouyang

    2014-01-01

    This paper proposes a total cost of ownership (TCO) model for battery sizing of plug-in hybrid electric vehicles (PHEVs). The proposed systematic TCO model innovatively integrates the Beijing driving database and optimal PHEV energy management strategies developed earlier. The TCO, including battery, fuel, electricity, and salvage costs, is calculated in yearly cash flows. The salvage cost, based on battery degradation model, is proposed for the first time. The results show that the optimal b...

  5. Development of Fuzzy Logic and Neural Network Control and Advanced Emissions Modeling for Parallel Hybrid Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Rajagopalan, A.; Washington, G.; Rizzoni, G.; Guezennec, Y.

    2003-12-01

    This report describes the development of new control strategies and models for Hybrid Electric Vehicles (HEV) by the Ohio State University. The report indicates results from models created in NREL's ADvanced VehIcle SimulatOR (ADVISOR 3.2), and results of a scalable IC Engine model, called in Willan's Line technique, implemented in ADVISOR 3.2.

  6. Performance and robustness of hybrid model predictive control for controllable dampers in building models

    Science.gov (United States)

    Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

    2016-04-01

    A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

  7. Development of hybrid 3-D hydrological modeling for the NCAR Community Earth System Model (CESM)

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, Xubin [Univ. of Arizona, Tucson, AZ (United States); Troch, Peter [Univ. of Arizona, Tucson, AZ (United States); Pelletier, Jon [Univ. of Arizona, Tucson, AZ (United States); Niu, Guo-Yue [Univ. of Arizona, Tucson, AZ (United States); Gochis, David [NCAR Research Applications (RAL), Boulder, CO (United States)

    2015-11-15

    This is the Final Report of our four-year (3-year plus one-year no cost extension) collaborative project between the University of Arizona (UA) and the National Center for Atmospheric Research (NCAR). The overall objective of our project is to develop and evaluate the first hybrid 3-D hydrological model with a horizontal grid spacing of 1 km for the NCAR Community Earth System Model (CESM). We have made substantial progress in model development and evaluation, computational efficiencies and software engineering, and data development and evaluation, as discussed in Sections 2-4. Section 5 presents our success in data dissemination, while Section 6 discusses the scientific impacts of our work. Section 7 discusses education and mentoring success of our project, while Section 8 lists our relevant DOE services. All peer-reviewed papers that acknowledged this project are listed in Section 9. Highlights of our achievements include: • We have finished 20 papers (most published already) on model development and evaluation, computational efficiencies and software engineering, and data development and evaluation • The global datasets developed under this project have been permanently archived and publicly available • Some of our research results have already been implemented in WRF and CLM • Patrick Broxton and Michael Brunke have received their Ph.D. • PI Zeng has served on DOE proposal review panels and DOE lab scientific focus area (SFA) review panels

  8. Modeling and control of a hybrid-electric vehicle for drivability and fuel economy improvements

    Science.gov (United States)

    Koprubasi, Kerem

    The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems. Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability. In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation. Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid mode) is occasionally interrupted by event-based rules to enable the use of the engine start-stop function. The changes in the driveline dynamics during this transition further contribute to the hybrid nature of the system. To address the unique characteristics of the HEV

  9. Photonic states mixing beyond the plasmon hybridization model

    Science.gov (United States)

    Suryadharma, Radius N. S.; Iskandar, Alexander A.; Tjia, May-On

    2016-07-01

    A study is performed on a photonic-state mixing-pattern in an insulator-metal-insulator cylindrical silver nanoshell and its rich variations induced by changes in the geometry and dielectric media of the system, representing the combined influences of plasmon coupling strength and cavity effects. This study is performed in terms of the photonic local density of states (LDOS) calculated using the Green tensor method, in order to elucidate those combined effects. The energy profiles of LDOS inside the dielectric core are shown to exhibit consistently growing number of redshifted photonic states due to an enhanced plasmon coupling induced state mixing arising from decreased shell thickness, increased cavity size effect, and larger symmetry breaking effect induced by increased permittivity difference between the core and the background media. Further, an increase in cavity size leads to increased additional peaks that spread out toward the lower energy regime. A systematic analysis of those variations for a silver nanoshell with a fixed inner radius in vacuum background reveals a certain pattern of those growing number of redshifted states with an analytic expression for the corresponding energy downshifts, signifying a photonic state mixing scheme beyond the commonly adopted plasmon hybridization scheme. Finally, a remarkable correlation is demonstrated between the LDOS energy profiles outside the shell and the corresponding scattering efficiencies.

  10. Reduced-size kernel models for nonlinear hybrid system identification.

    Science.gov (United States)

    Le, Van Luong; Bloch, Grard; Lauer, Fabien

    2011-12-01

    This brief paper focuses on the identification of nonlinear hybrid dynamical systems, i.e., systems switching between multiple nonlinear dynamical behaviors. Thus the aim is to learn an ensemble of submodels from a single set of input-output data in a regression setting with no prior knowledge on the grouping of the data points into similar behaviors. To be able to approximate arbitrary nonlinearities, kernel submodels are considered. However, in order to maintain efficiency when applying the method to large data sets, a preprocessing step is required in order to fix the submodel sizes and limit the number of optimization variables. This brief paper proposes four approaches, respectively inspired by the fixed-size least-squares support vector machines, the feature vector selection method, the kernel principal component regression and a modification of the latter, in order to deal with this issue and build sparse kernel submodels. These are compared in numerical experiments, which show that the proposed approach achieves the simultaneous classification of data points and approximation of the nonlinear behaviors in an efficient and accurate manner.

  11. Exploring key factors in online shopping with a hybrid model.

    Science.gov (United States)

    Chen, Hsiao-Ming; Wu, Chia-Huei; Tsai, Sang-Bing; Yu, Jian; Wang, Jiangtao; Zheng, Yuxiang

    2016-01-01

    Nowadays, the web increasingly influences retail sales. An in-depth analysis of consumer decision-making in the context of e-business has become an important issue for internet vendors. However, factors affecting e-business are complicated and intertwined. To stimulate online sales, understanding key influential factors and causal relationships among the factors is important. To gain more insights into this issue, this paper introduces a hybrid method, which combines the Decision Making Trial and Evaluation Laboratory (DEMATEL) with the analytic network process, called DANP method, to find out the driving factors that influence the online business mostly. By DEMATEL approach the causal graph showed that "online service" dimension has the highest degree of direct impact on other dimensions; thus, the internet vendor is suggested to made strong efforts on service quality throughout the online shopping process. In addition, the study adopted DANP to measure the importance of key factors, among which "transaction security" proves to be the most important criterion. Hence, transaction security should be treated with top priority to boost the online businesses. From our study with DANP approach, the comprehensive information can be visually detected so that the decision makers can spotlight on the root causes to develop effectual actions.

  12. Photonic states mixing beyond the plasmon hybridization model

    Energy Technology Data Exchange (ETDEWEB)

    Suryadharma, Radius N. S.; Iskandar, Alexander A., E-mail: iskandar@fi.itb.ac.id; Tjia, May-On [Physics of Magnetism and Photonics Research Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jl. Ganesha 10, Bandung 40132 (Indonesia)

    2016-07-28

    A study is performed on a photonic-state mixing-pattern in an insulator-metal-insulator cylindrical silver nanoshell and its rich variations induced by changes in the geometry and dielectric media of the system, representing the combined influences of plasmon coupling strength and cavity effects. This study is performed in terms of the photonic local density of states (LDOS) calculated using the Green tensor method, in order to elucidate those combined effects. The energy profiles of LDOS inside the dielectric core are shown to exhibit consistently growing number of redshifted photonic states due to an enhanced plasmon coupling induced state mixing arising from decreased shell thickness, increased cavity size effect, and larger symmetry breaking effect induced by increased permittivity difference between the core and the background media. Further, an increase in cavity size leads to increased additional peaks that spread out toward the lower energy regime. A systematic analysis of those variations for a silver nanoshell with a fixed inner radius in vacuum background reveals a certain pattern of those growing number of redshifted states with an analytic expression for the corresponding energy downshifts, signifying a photonic state mixing scheme beyond the commonly adopted plasmon hybridization scheme. Finally, a remarkable correlation is demonstrated between the LDOS energy profiles outside the shell and the corresponding scattering efficiencies.

  13. Predicting Grade Point Average from the Hybrid Model of Learning in Personality: Consistent Findings from Ugandan and Australian Students

    Science.gov (United States)

    Jackson, Chris; Baguma, Peter; Furnham, Adrian

    2009-01-01

    Jackson developed a hybrid model of learning in personality, known as the Learning Styles Profiler (LSP), which seeks to explain personality in terms of biological, socio-cognitive and experiential processes. The hybrid model argues that functional learning outcomes can be understood in terms of how cognitions and experiences re-express sensation…

  14. Strategy and gaps for modeling, simulation, and control of hybrid systems

    Energy Technology Data Exchange (ETDEWEB)

    Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Garcia, Humberto E. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Hovsapian, Rob [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kinoshita, Robert [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mesina, George L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bragg-Sitton, Shannon M. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Boardman, Richard D. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-04-01

    The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers, and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled

  15. Modelling the World Wool Market: A Hybrid Approach

    OpenAIRE

    2007-01-01

    We present a model of the world wool market that merges two modelling traditions: the partialequilibrium commodity-specific approach and the computable general-equilibrium approach. The model captures the multistage nature of the wool production system, and the heterogeneous nature of raw wool, processed wool and wool garments. It also captures the important wool producing and consuming regions of the world. We illustrate the utility of the model by estimating the effects of tariff barriers o...

  16. Empirical Estimation of Hybrid Model: A Controlled Case Study

    OpenAIRE

    Sadaf Un Nisa; M. Rizwan Jameel Qureshi

    2012-01-01

    Scrum and Extreme Programming (XP) are frequently used models among all agile models whereas Rational Unified Process (RUP) is one of the widely used conventional plan driven software development models. The agile and plan driven approaches both have their own strengths and weaknesses. Although RUP model has certain drawbacks, such as tendency to be over budgeted, slow in adaptation to rapidly changing requirements and reputation of being impractical for small and fast paced projects. XP mode...

  17. Comparative study of hybrid RANS-LES models for separated flows

    Science.gov (United States)

    Kumar, G.; Lakshmanan, S. K.; Gopalan, H.; De, A.

    2016-06-01

    Hybrid RANS-LES models are proven to be capable of predicting massively separated flows with reasonable computation cost. In this paper, Spalart-Allmaras (S-A) based detached eddy simulation (DES) model and three SST based hybrid models with different RANS to LES switching criteriaare investigated. The flow over periodic hill at Re = 10,595 is chosen as the benchmark for comparing the performance of the different models due to the complex flow physics and reasonablecomputational cost. The model performances are evaluated based on their prediction capabilities of velocity and stress profiles, and separation and reattachment point. The simulated results are validatedagainst experimental and numerical results available in literature. The S-A DES model predicted separation bubble accurately at the top of the hill, as reported earlier in experiments and other numerical results. This model also correctly predicted velocity and stress profiles in recirculation region. However, the performance of this model was poor in the post reattachment region. On the other hand, the k-ω SST based hybrid models performed poorly in recirculation region, but it fairly predicted stress profiles in post reattachment region.

  18. Fuzzy logic-based analogue forecasting and hybrid modelling of horizontal visibility

    Science.gov (United States)

    Tuba, Zoltán; Bottyán, Zsolt

    2017-02-01

    Forecasting visibility is one of the greatest challenges in aviation meteorology. At the same time, high accuracy visibility forecasts can significantly reduce or make avoidable weather-related risk in aviation as well. To improve forecasting visibility, this research links fuzzy logic-based analogue forecasting and post-processed numerical weather prediction model outputs in hybrid forecast. Performance of analogue forecasting model was improved by the application of Analytic Hierarchy Process. Then, linear combination of the mentioned outputs was applied to create ultra-short term hybrid visibility prediction which gradually shifts the focus from statistical to numerical products taking their advantages during the forecast period. It gives the opportunity to bring closer the numerical visibility forecast to the observations even it is wrong initially. Complete verification of categorical forecasts was carried out; results are available for persistence and terminal aerodrome forecasts (TAF) as well in order to compare. The average value of Heidke Skill Score (HSS) of examined airports of analogue and hybrid forecasts shows very similar results even at the end of forecast period where the rate of analogue prediction in the final hybrid output is 0.1-0.2 only. However, in case of poor visibility (1000-2500 m), hybrid (0.65) and analogue forecasts (0.64) have similar average of HSS in the first 6 h of forecast period, and have better performance than persistence (0.60) or TAF (0.56). Important achievement that hybrid model takes into consideration physics and dynamics of the atmosphere due to the increasing part of the numerical weather prediction. In spite of this, its performance is similar to the most effective visibility forecasting methods and does not follow the poor verification results of clearly numerical outputs.

  19. Hybrid Model of Inhomogeneous Solar Wind Plasma Heating by Alfven Wave Spectrum: Parametric Studies

    Science.gov (United States)

    Ofman, L.

    2010-01-01

    Observations of the solar wind plasma at 0.3 AU and beyond show that a turbulent spectrum of magnetic fluctuations is present. Remote sensing observations of the corona indicate that heavy ions are hotter than protons and their temperature is anisotropic (T(sub perpindicular / T(sub parallel) >> 1). We study the heating and the acceleration of multi-ion plasma in the solar wind by a turbulent spectrum of Alfvenic fluctuations using a 2-D hybrid numerical model. In the hybrid model the protons and heavy ions are treated kinetically as particles, while the electrons are included as neutralizing background fluid. This is the first two-dimensional hybrid parametric study of the solar wind plasma that includes an input turbulent wave spectrum guided by observation with inhomogeneous background density. We also investigate the effects of He++ ion beams in the inhomogeneous background plasma density on the heating of the solar wind plasma. The 2-D hybrid model treats parallel and oblique waves, together with cross-field inhomogeneity, self-consistently. We investigate the parametric dependence of the perpendicular heating, and the temperature anisotropy in the H+-He++ solar wind plasma. It was found that the scaling of the magnetic fluctuations power spectrum steepens in the higher-density regions, and the heating is channeled to these regions from the surrounding lower-density plasma due to wave refraction. The model parameters are applicable to the expected solar wind conditions at about 10 solar radii.

  20. Mixed model approaches for the identification of QTLs within a maize hybrid breeding program.

    NARCIS (Netherlands)

    Eeuwijk, van F.A.; Boer, M.; Totir, L.; Bink, M.C.A.M.; Wright, D.; Winkler, C.; Podlich, D.; Boldman, K.; Baumgarten, R.; Smalley, M.; Arbelbide, M.; Braak, ter C.J.F.; Cooper, M.

    2010-01-01

    Two outlines for mixed model based approaches to quantitative trait locus (QTL) mapping in existing maize hybrid selection programs are presented: a restricted maximum likelihood (REML) and a Bayesian Markov Chain Monte Carlo (MCMC) approach. The methods use the in-silico-mapping procedure developed

  1. Technical model for optimising PV/diesel/battery hybrid power systems

    CSIR Research Space (South Africa)

    Tazvinga, Henerica

    2010-08-31

    Full Text Available is required for optimising the sizing and operational strategy of the PV-diesel-battery hybrid system than is required for single-source systems. Various models are available on the market and in research groups but the challenge is to customise these to suit...

  2. Investigation of a Hybrid Winding Concept for Toroidal Inductors using 3D Finite Element Modeling

    DEFF Research Database (Denmark)

    Schneider, Henrik; Andersen, Thomas; Mønster, Jakob Døllner;

    2013-01-01

    This paper investigates a hybrid winding concept for a toroidal inductor by simulating the winding resistance as a function of frequency. The problem of predicting the resistance of a non-uniform and complex winding shape is solved using 3D Finite Element Modeling. A prototype is built and tested...

  3. Hybrid and Model-Based Iterative Reconstruction Techniques for Pediatric CT

    NARCIS (Netherlands)

    den Harder, Annemarie M.; Willemink, Martin J.; Budde, Ricardo P. J.; Schilham, Arnold M. R.; Leiner, Tim; de Jong, Pim A.

    2015-01-01

    OBJECTIVE. Radiation exposure from CT examinations should be reduced to a minimum in children. Iterative reconstruction (IR) is a method to reduce image noise that can be used to improve CT image quality, thereby allowing radiation dose reduction. This article reviews the use of hybrid and model-bas

  4. Ocean U.S. GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM)

    Science.gov (United States)

    2008-10-01

    Ocean U.S. GODAE: Global Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM) By Eric P. Chassignet1 and Harley E. Hurlburt2 1 COAPS ...UAcademia:U Florida State University/Center for Ocean-Atmospheric Prediction Studies ( COAPS ); University of Miami/Rosenstiel School of Marine and

  5. Putting "Organizations" into an Organization Theory Course: A Hybrid CAO Model for Teaching Organization Theory

    Science.gov (United States)

    Hannah, David R.; Venkatachary, Ranga

    2010-01-01

    In this article, the authors present a retrospective analysis of an instructor's multiyear redesign of a course on organization theory into what is called a hybrid Classroom-as-Organization model. It is suggested that this new course design served to apprentice students to function in quasi-real organizational structures. The authors further argue…

  6. Hybrid local FEM/global LISA modeling of damped guided wave propagation in complex composite structures

    Science.gov (United States)

    Shen, Yanfeng; Cesnik, Carlos E. S.

    2016-09-01

    This paper presents a new hybrid modeling technique for the efficient simulation of guided wave generation, propagation, and interaction with damage in complex composite structures. A local finite element model is deployed to capture the piezoelectric effects and actuation dynamics of the transmitter, while the global domain wave propagation and interaction with structural complexity (structure features and damage) are solved utilizing a local interaction simulation approach (LISA). This hybrid approach allows the accurate modeling of the local dynamics of the transducers and keeping the LISA formulation in an explicit format, which facilitates its readiness for parallel computing. The global LISA framework was extended through the 3D Kelvin-Voigt viscoelasticity theory to include anisotropic damping effects for composite structures, as an improvement over the existing LISA formulation. The global LISA framework was implemented using the compute unified device architecture running on graphic processing units. A commercial preprocessor is integrated seamlessly with the computational framework for grid generation and material property allocation to handle complex structures. The excitability and damping effects are successfully captured by this hybrid model, with experimental validation using the scanning laser doppler vibrometry. To demonstrate the capability of our hybrid approach for complex structures, guided wave propagation and interaction with a delamination in a composite panel with stiffeners is presented.

  7. Separable Transition Density in the Hybrid Model for Tumor-Immune System Competition

    Directory of Open Access Journals (Sweden)

    Carlo Cattani

    2012-01-01

    Full Text Available A hybrid model, on the competition tumor cells immune system, is studied under suitable hypotheses. The explicit form for the equations is obtained in the case where the density function of transition is expressed as the product of separable functions. A concrete application is given starting from a modified Lotka-Volterra system of equations.

  8. Innovation in Doctoral Degrees Designed for Adult Learners: A Hybrid Model in Personal Financial Planning

    Science.gov (United States)

    Grable, John E.

    2011-01-01

    Innovation in doctoral degree program development and delivery provides an effective counterpoint to the expert-apprentice model established in the Middle Ages. The author outlines the importance of innovation in reaching adult learners and describes an innovative hybrid PhD program designed to allow aspiring doctoral adult-age students to pursue…

  9. Hybrid Model of Inhomogeneous Solar Wind Plasma Heating by Alfven Wave Spectrum: Parametric Studies

    Science.gov (United States)

    Ofman, L.

    2010-01-01

    Observations of the solar wind plasma at 0.3 AU and beyond show that a turbulent spectrum of magnetic fluctuations is present. Remote sensing observations of the corona indicate that heavy ions are hotter than protons and their temperature is anisotropic (T(sub perpindicular / T(sub parallel) >> 1). We study the heating and the acceleration of multi-ion plasma in the solar wind by a turbulent spectrum of Alfvenic fluctuations using a 2-D hybrid numerical model. In the hybrid model the protons and heavy ions are treated kinetically as particles, while the electrons are included as neutralizing background fluid. This is the first two-dimensional hybrid parametric study of the solar wind plasma that includes an input turbulent wave spectrum guided by observation with inhomogeneous background density. We also investigate the effects of He++ ion beams in the inhomogeneous background plasma density on the heating of the solar wind plasma. The 2-D hybrid model treats parallel and oblique waves, together with cross-field inhomogeneity, self-consistently. We investigate the parametric dependence of the perpendicular heating, and the temperature anisotropy in the H+-He++ solar wind plasma. It was found that the scaling of the magnetic fluctuations power spectrum steepens in the higher-density regions, and the heating is channeled to these regions from the surrounding lower-density plasma due to wave refraction. The model parameters are applicable to the expected solar wind conditions at about 10 solar radii.

  10. A Hybrid Approach to Combine Physically Based and Data-Driven Models in Simulating Sediment Transportation

    NARCIS (Netherlands)

    Sewagudde, S.

    2008-01-01

    The objective of this study is to develop a methodology for hybrid modelling of sedimentation in a coastal basin or large shallow lake where physically based and data driven approaches are combined. This research was broken down into three blocks. The first block explores the possibility of approxim

  11. Innovation in Doctoral Degrees Designed for Adult Learners: A Hybrid Model in Personal Financial Planning

    Science.gov (United States)

    Grable, John E.

    2011-01-01

    Innovation in doctoral degree program development and delivery provides an effective counterpoint to the expert-apprentice model established in the Middle Ages. The author outlines the importance of innovation in reaching adult learners and describes an innovative hybrid PhD program designed to allow aspiring doctoral adult-age students to pursue…

  12. HYBRID SNCR-SCR TECHNOLOGIES FOR NOX CONTROL: MODELING AND EXPERIMENT

    Science.gov (United States)

    The hybrid process of homogeneous gas-phase selective non-catalytic reduction (SNCR) followed by selective catalytic reduction (SCR) of nitric oxide (NO) was investigated through experimentation and modeling. Measurements, using NO-doped flue gas from a gas-fired 29 kW test combu...

  13. Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model

    Science.gov (United States)

    Allen, Douglas R.; Hoppel, Karl W.; Kuhl, David D.

    2016-07-01

    Wind extraction from stratospheric ozone (O3) assimilation is examined using a hybrid ensemble 4-D variational assimilation (4DVar) shallow water model (SWM) system coupled to the tracer advection equation. Stratospheric radiance observations are simulated using global observations of the SWM fluid height (Z), while O3 observations represent sampling by a typical polar-orbiting satellite. Four ensemble sizes were examined (25, 50, 100, and 1518 members), with the largest ensemble equal to the number of dynamical state variables. The optimal length scale for ensemble localization was found by tuning an ensemble Kalman filter (EnKF). This scale was then used for localizing the ensemble covariances that were blended with conventional covariances in the hybrid 4DVar experiments. Both optimal length scale and optimal blending coefficient increase with ensemble size, with optimal blending coefficients varying from 0.2-0.5 for small ensembles to 0.5-1.0 for large ensembles. The hybrid system outperforms conventional 4DVar for all ensemble sizes, while for large ensembles the hybrid produces similar results to the offline EnKF. Assimilating O3 in addition to Z benefits the winds in the hybrid system, with the fractional improvement in global vector wind increasing from ˜ 35 % with 25 and 50 members to ˜ 50 % with 1518 members. For the smallest ensembles (25 and 50 members), the hybrid 4DVar assimilation improves the zonal wind analysis over conventional 4DVar in the Northern Hemisphere (winter-like) region and also at the Equator, where Z observations alone have difficulty constraining winds due to lack of geostrophy. For larger ensembles (100 and 1518 members), the hybrid system results in both zonal and meridional wind error reductions, relative to 4DVar, across the globe.

  14. Noise propagation in hybrid models of nonlinear systems: The Ginzburg–Landau equation

    Energy Technology Data Exchange (ETDEWEB)

    Taverniers, Søren [Department of Mechanical and Aerospace Engineering, University of California, San Diego, 9500 Gilman Dr., La Jolla, CA 92093 (United States); Alexander, Francis J. [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Tartakovsky, Daniel M. [Department of Mechanical and Aerospace Engineering, University of California, San Diego, 9500 Gilman Dr., La Jolla, CA 92093 (United States)

    2014-04-01

    Every physical phenomenon can be described by multiple models with varying degrees of fidelity. The computational cost of higher fidelity models (e.g., molecular dynamics simulations) is invariably higher than that of their lower fidelity counterparts (e.g., a continuum model based on differential equations). While the former might not be suitable for large-scale simulations, the latter are not universally valid. Hybrid algorithms provide a compromise between the computational efficiency of a coarse-scale model and the representational accuracy of a fine-scale description. This is achieved by conducting a fine-scale computation in subdomains where it is absolutely required (e.g., due to a local breakdown of a continuum model) and coupling it with a coarse-scale computation in the rest of a computational domain. We analyze the effects of random fluctuations generated by the fine-scale component of a nonlinear hybrid on the hybrid's overall accuracy and stability. Two variants of the time-dependent Ginzburg–Landau equation (GLE) and their discrete representations provided by a nearest-neighbor Ising model serve as a computational testbed. Our analysis shows that coupling these descriptions in a one-dimensional simulation leads to erroneous results. Adding a random source term to the GLE provides accurate prediction of the mean behavior of the quantity of interest (magnetization). It also allows the two GLE variants to correctly capture the strength of the microscale fluctuations. Our work demonstrates the importance of fine-scale noise in hybrid simulations, and suggests the need for replacing an otherwise deterministic coarse-scale component of the hybrid with its stochastic counterpart.

  15. Modeling and Simulation of Metallurgical Process Based on Hybrid Petri Net

    Science.gov (United States)

    Ren, Yujuan; Bao, Hong

    2016-11-01

    In order to achieve the goals of energy saving and emission reduction of iron and steel enterprises, an increasing number of modeling and simulation technologies are used to research and analyse metallurgical production process. In this paper, the basic principle of Hybrid Petri net is used to model and analyse the Metallurgical Process. Firstly, the definition of Hybrid Petri Net System of Metallurgical Process (MPHPNS) and its modeling theory are proposed. Secondly, the model of MPHPNS based on material flow is constructed. The dynamic flow of materials and the real-time change of each technological state in metallurgical process are simulated vividly by using this model. The simulation process can implement interaction between the continuous event dynamic system and the discrete event dynamic system at the same level, and play a positive role in the production decision.

  16. Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems

    Energy Technology Data Exchange (ETDEWEB)

    Elsheikh, Ahmed H., E-mail: aelsheikh@ices.utexas.edu [Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh EH14 4AS (United Kingdom); Wheeler, Mary F. [Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Hoteit, Ibrahim [Department of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia)

    2014-02-01

    A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithm that can be used for Bayesian calibration and estimating the Bayesian evidence for prior model selection. Nested sampling has the advantage of computational feasibility. Within the nested sampling algorithm, a constrained sampling step is performed. For this step, we utilize HMC to reduce the correlation between successive sampled states. HMC relies on the gradient of the logarithm of the posterior distribution, which we estimate using a stochastic ensemble method based on an ensemble of directional derivatives. SEM only requires forward model runs and the simulator is then used as a black box and no adjoint code is needed. The developed HNS algorithm is successfully applied for Bayesian calibration and prior model selection of several nonlinear subsurface flow problems.

  17. One hybrid model combining singular spectrum analysis and LS + ARMA for polar motion prediction

    Science.gov (United States)

    Shen, Yi; Guo, Jinyun; Liu, Xin; Wei, Xiaobei; Li, Wudong

    2017-01-01

    Accurate real-time polar motion parameters play an important role in satellite navigation and positioning and spacecraft tracking. To meet the needs for real-time and high-accuracy polar motion prediction, a hybrid model that integrated singular spectrum analysis (SSA), least-squares (LS) extrapolation and an autoregressive moving average (ARMA) model was proposed. SSA was applied to separate the trend, the annual and the Chandler components from a given polar motion time series. LS extrapolation models were constructed for the separated trend, annual and Chandler components. An ARMA model was established for a synthetic sequence that contained the remaining SSA component and the residual series of LS fitting. In applying this hybrid model, multiple sets of polar motion predictions with lead times of 360 days were made based on an IERS 08 C04 series. The results showed that the proposed method could effectively predict the polar motion parameters.

  18. Mechanisms underlying REBT in mood disordered patients: predicting depression from the hybrid model of learning.

    Science.gov (United States)

    Jackson, Chris J; Izadikah, Zahra; Oei, Tian P S

    2012-06-01

    Jackson's (2005, 2008a) hybrid model of learning identifies a number of learning mechanisms that lead to the emergence and maintenance of the balance between rationality and irrationality. We test a general hypothesis that Jackson's model will predict depressive symptoms, such that poor learning is related to depression. We draw comparisons between Jackson's model and Ellis' (2004) Rational Emotive Behavior Therapy and Theory (REBT) and thereby provide a set of testable learning mechanisms potentially underlying REBT. Results from 80 patients diagnosed with depression completed the learning styles profiler (LSP; Jackson, 2005) and two measures of depression. Results provide support for the proposed model of learning and further evidence that low rationality is a key predictor of depression. We conclude that the hybrid model of learning has the potential to explain some of the learning and cognitive processes related to the development and maintenance of irrational beliefs and depression. Copyright © 2011. Published by Elsevier B.V.

  19. Hybrid Modeling and Simulation of Automotive Supply Chain Network

    Directory of Open Access Journals (Sweden)

    Wen Wang

    2013-07-01

    Full Text Available According to the operation of automotive supply chain and the features of various simulation methods, we create and simulate a automotive supply chain network model with the core enterprise of two vehicle manufacturers, consisting of several parts suppliers, vehicle distributors and logistics service providers. On this basis of a conceptual model including the establishment of enterprise layer, business layer and operation layer, we establish a detailed model of the network system according to the network structure of automotive supply chain, the operation process and the internal business process of core enterprises; then we use System Dynamics (SD, Discrete Event Simulation (DES and Agent Based Modeling (ABM to describe the operating state of each node in the network model. We execute and analyze the simulation model of the whole network system described by Anylogic, using the results of the distributors’ inventory, inventory cost and customer’s satisfaction to prove the effectiveness of the model.

  20. Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

    Science.gov (United States)

    Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

    2017-09-01

    This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

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

    Science.gov (United States)

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

    2016-11-01

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

  2. E324 Simulation of Turbulent Channel Flow Using a RANS/LES Hybrid Model

    OpenAIRE

    半場, 藤弘; Fujihiro, Hamba; 東大生研; Institute of Industrial Science, University of Tokyo

    2004-01-01

    A RANS/LES hybrid simulation of a channel flow at Reτ=5000 was carried out using the Smagorinsky model. It is known that some hybrid simulations including the detached eddy simulation have a common defect: the mean velocity profile has a mismatch between the RANS and LES regions due to a steep gradient near the interface. New filtering for the velocity was introduced to improve the mean velocity profile. It was shown that this method increases the intensity of the normal velocity component in...

  3. Angular Structure of Jet Quenching Within a Hybrid Strong/Weak Coupling Model

    CERN Document Server

    Casalderrey-Solana, Jorge; Milhano, Guilherme; Pablos, Daniel; Rajagopal, Krishna

    2017-01-01

    Within the context of a hybrid strong/weak coupling model of jet quenching, we study the modification of the angular distribution of the energy within jets in heavy ion collisions, as partons within jet showers lose energy and get kicked as they traverse the strongly coupled plasma produced in the collision. To describe the dynamics transverse to the jet axis, we add the effects of transverse momentum broadening into our hybrid construction, introducing a parameter $K\\equiv \\hat q/T^3$ that governs its magnitude. We show that, because of the quenching of the energy of partons within a jet, even when $K\

  4. Three thermal analysis models for laser, GMAW-P and Iaser+GMAW-P hybrid welding

    Institute of Scientific and Technical Information of China (English)

    XU Guoxiang; WU Chuansong; QIN Guoliang; WANG Xuyou; LIN Shangyang

    2009-01-01

    The temperature fields and the weld pool geometries for laser + GMA W-P hybrid welding, laser welding and pulsed gas metal arc welding (GMAW-P) are numerically simulated in quasi-steady state by using the developed heat source models, respectively. The calculated weld cross-sections of the three types of welding processes agree well with their respective measured results. Through comparison, it is found that the temperature distribution of laser+ GMAW-P hybrid welding possesses the advantages of those in both laser and GMA W-P welding processes so that the improvement of welding productivity and weld quality are ensured.

  5. Modeling and control of a small solar fuel cell hybrid energy system

    Institute of Scientific and Technical Information of China (English)

    LI Wei; ZHU Xin-jian; CAO Guang-yi

    2007-01-01

    This paper describes a solar photovoltaic fuel cell (PVEC) hybrid generation system consisting of a photovoltaic (PV) generator, a proton exchange membrane fuel cell (PEMFC), an electrolyser, a supercapacitor, a storage gas tank and power conditioning unit (PCU). The load is supplied from the PV generator with a fuel cell working in parallel. Excess PV energy when available is converted to hydrogen using an electrolyser for later use in the fuel cell. The individual mathematical model for each component is presented. Control strategy for the system is described. MATLAB/Simulink is used for the simulation of this highly nonlinear hybrid energy system. The simulation results are shown in the paper.

  6. Angular Structure of Jet Quenching Within a Hybrid Strong/Weak Coupling Model

    CERN Document Server

    Casalderrey-Solana, Jorge; Milhano, Guilherme; Pablos, Daniel; Rajagopal, Krishna

    2016-01-01

    Within the context of a hybrid strong/weak coupling model of jet quenching, we study the modification of the angular distribution of the energy within jets in heavy ion collisions, as partons within jet showers lose energy and get kicked as they traverse the strongly coupled plasma produced in the collision. To describe the dynamics transverse to the jet axis, we add the effects of transverse momentum broadening into our hybrid construction, introducing a parameter $K\\equiv \\hat q/T^3$ that governs its magnitude. We show that, because of the quenching of the energy of partons within a jet, even when $K\

  7. Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA-ANN model

    Energy Technology Data Exchange (ETDEWEB)

    Cadenas, Erasmo [Facultad de Ingenieria Mecanica, Universidad Michoacana de San Nicolas de Hidalgo, Santiago Tapia No. 403, Centro (Mexico); Rivera, Wilfrido [Centro de Ivestigacion en Energia, Universidad Nacional Autonoma de Mexico, Apartado Postal 34, Temixco 62580, Morelos (Mexico)

    2010-12-15

    In this paper the wind speed forecasting in the Isla de Cedros in Baja California, in the Cerro de la Virgen in Zacatecas and in Holbox in Quintana Roo is presented. The time series utilized are average hourly wind speed data obtained directly from the measurements realized in the different sites during about one month. In order to do wind speed forecasting Hybrid models consisting of Autoregressive Integrated Moving Average (ARIMA) models and Artificial Neural Network (ANN) models were developed. The ARIMA models were first used to do the wind speed forecasting of the time series and then with the obtained errors ANN were built taking into account the nonlinear tendencies that the ARIMA technique could not identify, reducing with this the final errors. Once the Hybrid models were developed 48 data out of sample for each one of the sites were used to do the wind speed forecasting and the results were compared with the ARIMA and the ANN models working separately. Statistical error measures such as the mean error (ME), the mean square error (MSE) and the mean absolute error (MAE) were calculated to compare the three methods. The results showed that the Hybrid models predict the wind velocities with a higher accuracy than the ARIMA and ANN models in the three examined sites. (author)

  8. A general model of distant hybridization reveals the conditions for extinction in Atlantic salmon and brown trout.

    Directory of Open Access Journals (Sweden)

    Claudio S Quilodrán

    Full Text Available Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.

  9. Modelling grain-scattered ultrasound in austenitic stainless-steel welds: A hybrid model

    Science.gov (United States)

    Nowers, O.; Duxbury, D. J.; Velichko, A.; Drinkwater, B. W.

    2015-03-01

    The ultrasonic inspection of austenitic stainless steel welds can be challenging due to their coarse grain structure, charaterised by preferentially oriented, elongated grains. The anisotropy of the weld is manifested as both a `steering' of the beam and the back-scatter of energy due to the macroscopic granular structure of the weld. However, the influence of weld properties, such as mean grain size and orientation distribution, on the magnitude of scattered ultrasound is not well understood. A hybrid model has been developed to allow the study of grain-scatter effects in austenitic welds. An efficient 2D Finite Element (FE) method is used to calculate the complete scattering response from a single elliptical austenitic grain of arbitrary length and width as a function of the specific inspection frequency. A grain allocation model of the weld is presented to approximate the characteristic structures observed in austenitic welds and the complete scattering behaviour of each grain calculated. This model is incorporated into a semi-analytical framework for a single-element inspection of a typical weld in immersion. Experimental validation evidence is demonstrated indicating excellent qualitative agreement of SNR as a function of frequency and a minimum SNR difference of 2 dB at a centre frequency of 2.25 MHz. Additionally, an example Monte-Carlo study is presented detailing the variation of SNR as a function of the anisotropy distribution of the weld, and the application of confidence analysis to inform inspection development.

  10. A comprehensive mathematical model for hybrid flexible flowshop lot streaming problem

    Directory of Open Access Journals (Sweden)

    Fantahun M. Defersha

    2011-04-01

    Full Text Available Lot streaming is a technique of splitting production lots into smaller sublots in a multi-stage manufacturing systems so that operations of a given lot can be overlapped. This technique can reduce manufacturing makespan and is an effective tool for time-based manufacturing strategy. Several research articles appeared in literature to solve this problem and most of these studies are limited to pure flowshop environments where there is only a single machine in each stage. On the other hand, because of the applicability of hybrid flowshops in different manufacturing settings, the scheduling of these types of shops is also extensively studied by several authors. However, the issue of lot streaming in hybrid flowshop environment is not well studied. In this paper, we aim to initiate research in bridging the gap between the research efforts in flowshop lot streaming and hybrid flowshop scheduling. We present a comprehensive mathematical model for scheduling flexible hybrid flowshop with lot streaming. Numerical example demonstrated that lot streaming can result in larger makespan reduction in hybrid flowshop where there is a limited research than in pure flowshop where research is abundant.

  11. Modelling and Simulation of System Dynamics of Hybrid-Driven Precision Press

    Institute of Scientific and Technical Information of China (English)

    LI Yonggang; ZHANG Ce; MENG Caifang; SONG Yimin

    2005-01-01

    Different from conventional mechanical systems with single degree of freedom (DOF), the main idea of the system of hybrid-driven precision press is to combine the motion of a constant speed motor with a servomotor via a two-DOF mechanism to provide flexible output. In order to make the feasibility clear, this paper studies theoretically the dynamic characteristics of this hybrid-driven mechanical system.Firstly,the dynamics model of the whole electromechanical system is set up by combining dynamic equations of DC motors with those of two-DOF nine-bar mechanism deduced by the Lagrange′s formula. Secondly through the numerical solution with the fourth Runge-Kutta, computer simulation about the dynamics is done, which shows that the designed and optimized hybrid-driven precision press is feasible in theory. These provide theoretical basis for later experimental research.

  12. Model predictive control for power fluctuation supression in hybrid wind/PV/battery systems

    DEFF Research Database (Denmark)

    You, Shi; Liu, Zongyu; Zong, Yi

    2015-01-01

    predictive control (MPC)-based algorithm for battery management in a hybrid wind/PV/battery system to suppress the short-term power fluctuation on the ‘minute’ scale. A case study with data collected from a practical hybrid system setup is used to demonstrate the effectiveness of the proposed algorithm......A hybrid energy system, the combination of wind turbines, PV panels and battery storage with effective control mechanism, represents a promising solution to the power fluctuation problem when integrating renewable energy resources (RES) into conventional power systems. This paper proposes a model...... together with a Monte Carlo simulation-based sensitivity analysis. In addition to illustrating the complementarity between the fluctuations of wind power and PV power, the results prove the proposed MPC algorithm is effective in fluctuation suppression but sensitive to factors such as forecast accuracy...

  13. Promoting Student Autonomy and Competence Using a Hybrid Model for Teaching Physical Activity

    Directory of Open Access Journals (Sweden)

    Christine Bachman

    2015-01-01

    Full Text Available For approximately twenty-years, Web-enhanced learning environments have been popular in higher education. Much research has examined how best practices can integrate technology, pedagogical theories, and resources to enhance learning. Numerous studies of hybrid teaching have revealed mostly positive effects. Yet, very little research has examined how to teach a successful physical activity course using a hybrid format. Review of the literature: We reviewed the research regarding the design and implementation of a Web-enhanced physical activity course in a college population using pedagogical principles of learning and the10 self-determination theory. Method: Data were collected from students at the beginning and end of the course. The hybrid course consisted of completing weekly online activities, and selecting and participating in a face-to-face physical activity based on student’s choice. Conclusion: The authors propose this template as a model to assist faculty in designing and implementing a blended physical activity course.

  14. Hybrid and hierarchical nanoreinforced polymer composites: Computational modelling of structure–properties relationships

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon; Dai, Gaoming

    2014-01-01

    Hybrid and hierarchical polymer composites represent a promising group of materials for engineering applications. In this paper, computational studies of the strength and damage resistance of hybrid and hierarchical composites are reviewed. The reserves of the composite improvement are explored...... by using computational micromechanical models. It is shown that while glass/carbon fibers hybrid composites clearly demonstrate higher stiffness and lower weight with increasing the carbon content, they can have lower strength as compared with usual glass fiber polymer composites. Secondary...... nanoreinforcement can drastically increase the fatigue lifetime of composites. Especially, composites with the nanoplatelets localized in the fiber/matrix interface layer (fiber sizing) ensure much higher fatigue lifetime than those with the nanoplatelets in the matrix....

  15. Accelerating a hybrid continuum-atomistic fluidic model with on-the-fly machine learning

    CERN Document Server

    Stephenson, David; Lockerby, Duncan A

    2016-01-01

    We present a hybrid continuum-atomistic scheme which combines molecular dynamics (MD) simulations with on-the-fly machine learning techniques for the accurate and efficient prediction of multiscale fluidic systems. By using a Gaussian process as a surrogate model for the computationally expensive MD simulations, we use Bayesian inference to predict the system behaviour at the atomistic scale, purely by consideration of the macroscopic inputs and outputs. Whenever the uncertainty of this prediction is greater than a predetermined acceptable threshold, a new MD simulation is performed to continually augment the database, which is never required to be complete. This provides a substantial enhancement to the current generation of hybrid methods, which often require many similar atomistic simulations to be performed, discarding information after it is used once. We apply our hybrid scheme to nano-confined unsteady flow through a high-aspect-ratio converging-diverging channel, and make comparisons between the new s...

  16. Shallow landslide susceptibility model for the Oria river basin, Gipuzkoa province (North of Spain). Application of the logistic regression and comparison with previous studies.

    Science.gov (United States)

    Bornaetxea, Txomin; Antigüedad, Iñaki; Ormaetxea, Orbange

    2016-04-01

    In the Oria river basin (885 km2) shallow landslides are very frequent and they produce several roadblocks and damage in the infrastructure and properties, causing big economic loss every year. Considering that the zonification of the territory in different landslide susceptibility levels provides a useful tool for the territorial planning and natural risk management, this study has the objective of identifying the most prone landslide places applying an objective and reproducible methodology. To do so, a quantitative multivariate methodology, the logistic regression, has been used. Fieldwork landslide points and randomly selected stable points have been used along with Lithology, Land Use, Distance to the transport infrastructure, Altitude, Senoidal Slope and Normalized Difference Vegetation Index (NDVI) independent variables to carry out a landslide susceptibility map. The model has been validated by the prediction and success rate curves and their corresponding area under the curve (AUC). In addition, the result has been compared to those from two landslide susceptibility models, covering the study area previously applied in different scales, such as ELSUS1000 version 1 (2013) and Landslide Susceptibility Map of Gipuzkoa (2007). Validation results show an excellent prediction capacity of the proposed model (AUC 0,962), and comparisons highlight big differences with previous studies.

  17. A hybrid deep neural network and physically based distributed model for river stage prediction

    Science.gov (United States)

    hitokoto, Masayuki; sakuraba, Masaaki

    2016-04-01

    We developed the real-time river stage prediction model, using the hybrid deep neural network and physically based distributed model. As the basic model, 4 layer feed-forward artificial neural network (ANN) was used. As a network training method, the deep learning technique was applied. To optimize the network weight, the stochastic gradient descent method based on the back propagation method was used. As a pre-training method, the denoising autoencoder was used. Input of the ANN model is hourly change of water level and hourly rainfall, output data is water level of downstream station. In general, the desirable input of the ANN has strong correlation with the output. In conceptual hydrological model such as tank model and storage-function model, river discharge is governed by the catchment storage. Therefore, the change of the catchment storage, downstream discharge subtracted from rainfall, can be the potent input candidate of the ANN model instead of rainfall. From this point of view, the hybrid deep neural network and physically based distributed model was developed. The prediction procedure of the hybrid model is as follows; first, downstream discharge was calculated by the distributed model, and then estimates the hourly change of catchment storage form rainfall and calculated discharge as the input of the ANN model, and finally the ANN model was calculated. In the training phase, hourly change of catchment storage can be calculated by the observed rainfall and discharge data. The developed model was applied to the one catchment of the OOYODO River, one of the first-grade river in Japan. The modeled catchment is 695 square km. For the training data, 5 water level gauging station and 14 rain-gauge station in the catchment was used. The training floods, superior 24 events, were selected during the period of 2005-2014. Prediction was made up to 6 hours, and 6 models were developed for each prediction time. To set the proper learning parameters and network

  18. A hybrid model for the computationally-efficient simulation of the cerebellar granular layer

    Directory of Open Access Journals (Sweden)

    Anna eCattani

    2016-04-01

    Full Text Available The aim of the present paper is to efficiently describe the membrane potential dynamics of neural populations formed by species having a high density difference in specific brain areas. We propose a hybrid model whose main ingredients are a conductance-based model (ODE system and its continuous counterpart (PDE system obtained through a limit process in which the number of neurons confined in a bounded region of the brain tissue is sent to infinity. Specifically, in the discrete model, each cell is described by a set of time-dependent variables, whereas in the continuum model, cells are grouped into populations that are described by a set of continuous variables.Communications between populations, which translate into interactions among the discrete and the continuous models, are the essence of the hybrid model we present here. The cerebellum and cerebellum-like structures show in their granular layer a large difference in the relative density of neuronal species making them a natural testing ground for our hybrid model. By reconstructing the ensemble activity of the cerebellar granular layer network and by comparing our results to a more realistic computational network, we demonstrate that our description of the network activity, even though it is not biophysically detailed, is still capable of reproducing salient features of neural network dynamics. Our modeling approach yields a significant computational cost reduction by increasing the simulation speed at least $270$ times. The hybrid model reproduces interesting dynamics such as local microcircuit synchronization, traveling waves, center-surround and time-windowing.

  19. Modeling Hybridization Kinetics of Gene Probes in a DNA Biochip Using FEMLAB

    Directory of Open Access Journals (Sweden)

    Ahsan Munir

    2017-05-01

    Full Text Available Microfluidic DNA biochips capable of detecting specific DNA sequences are useful in medical diagnostics, drug discovery, food safety monitoring and agriculture. They are used as miniaturized platforms for analysis of nucleic acids-based biomarkers. Binding kinetics between immobilized single stranded DNA on the surface and its complementary strand present in the sample are of interest. To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the thermodynamic characteristics of the probe is crucial. In this study, a computer aided numerical model for the design and optimization of a flow-through biochip was developed using a finite element technique packaged software tool (FEMLAB; package included in COMSOL Multiphysics to simulate the transport of DNA through a microfluidic chamber to the reaction surface. The model accounts for fluid flow, convection and diffusion in the channel and on the reaction surface. Concentration, association rate constant, dissociation rate constant, recirculation flow rate, and temperature were key parameters affecting the rate of hybridization. The model predicted the kinetic profile and signal intensities of eighteen 20-mer probes targeting vancomycin resistance genes (VRGs. Predicted signal intensities and hybridization kinetics strongly correlated with experimental data in the biochip (R2 = 0.8131.

  20. Two-dimensional magnetic modeling of ferromagnetic materials by using a neural networks based hybrid approach

    Energy Technology Data Exchange (ETDEWEB)

    Cardelli, E.; Faba, A. [Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia (Italy); Laudani, A.; Lozito, G.M.; Riganti Fulginei, F.; Salvini, A. [Department of Engineering, Roma Tre University, Via V. Volterra 62, 00146 Rome (Italy)

    2016-04-01

    This paper presents a hybrid neural network approach to model magnetic hysteresis at macro-magnetic scale. That approach aims to be coupled together with numerical treatments of magnetic hysteresis such as FEM numerical solvers of the Maxwell's equations in time domain, as in case of the non-linear dynamic analysis of electrical machines, and other similar devices, allowing a complete computer simulation with acceptable run times. The proposed Hybrid Neural System consists of four inputs representing the magnetic induction and magnetic field components at each time step and it is trained by 2D and scalar measurements performed on the magnetic material to be modeled. The magnetic induction B is assumed as entry point and the output of the Hybrid Neural System returns the predicted value of the field H at the same time step. Within the Hybrid Neural System, a suitably trained neural network is used for predicting the hysteretic behavior of the material to be modeled. Validations with experimental tests and simulations for symmetric, non-symmetric and minor loops are presented.

  1. Time-dependent Mott transition in the periodic Anderson model with nonlocal hybridization

    Science.gov (United States)

    Hofmann, Felix; Potthoff, Michael

    2016-08-01

    The time-dependent Mott transition in a periodic Anderson model with off-site, nearest-neighbor hybridization is studied within the framework of nonequilibrium self-energy functional theory. Using the two-site dynamical-impurity approximation, we compute the real-time dynamics of the optimal variational parameter and of different observables initiated by sudden quenches of the Hubbard-U and identify the critical interaction. The time-dependent transition is orbital selective, i.e., in the final state, reached in the long-time limit after the quench to the critical interaction, the Mott gap opens in the spectral function of the localized orbitals only. We discuss the dependence of the critical interaction and of the final-state effective temperature on the hybridization strength and point out the various similarities between the nonequilibrium and the equilibrium Mott transition. It is shown that these can also be smoothly connected to each other by increasing the duration of a U-ramp from a sudden quench to a quasi-static process. The physics found for the model with off-site hybridization is compared with the dynamical Mott transition in the single-orbital Hubbard model and with the dynamical crossover found for the real-time dynamics of the conventional Anderson lattice with on-site hybridization.

  2. A hybrid classical-quantum approach for ultra-scaled confined nanostructures : modeling and simulation*

    Directory of Open Access Journals (Sweden)

    Pietra Paola

    2012-04-01

    Full Text Available We propose a hybrid classical-quantum model to study the motion of electrons in ultra-scaled confined nanostructures. The transport of charged particles, considered as one dimensional, is described by a quantum effective mass model in the active zone coupled directly to a drift-diffusion problem in the rest of the device. We explain how this hybrid model takes into account the peculiarities due to the strong confinement and we present numerical simulations for a simplified carbon nanotube. Nous proposons un modèle hybride classique-quantique pour décrire le mouvement des électrons dans des nanostructures très fortement confinées. Le transport des particules, consideré unidimensionel, est décrit par un modèle quantique avec masse effective dans la zone active couplé à un problème de dérive-diffusion dans le reste du domaine. Nous expliquons comment ce modèle hybride prend en compte les spécificités de ce très fort confinement et nous présentons des résultats numériques pour un nanotube de carbone simplifié.

  3. Child human model development: a hybrid validation approach

    NARCIS (Netherlands)

    Forbes, P.A.; Rooij, L. van; Rodarius, C.; Crandall, J.

    2008-01-01

    The current study presents a development and validation approach of a child human body model that will help understand child impact injuries and improve the biofidelity of child anthropometric test devices. Due to the lack of fundamental child biomechanical data needed to fully develop such models a

  4. Hybrid Compensatory-Noncompensatory Choice Sets in Semicompensatory Models

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Bekhor, Shlomo; Shiftan, Yoram

    2013-01-01

    by a mathematical model that combines multinomial-response and ordered-response thresholds with a utility-based choice. The proposed model is applied to a stated preference experiment of off-campus rental apartment choices by students. Results demonstrate the applicability and feasibility of incorporating...

  5. Child human model development: a hybrid validation approach

    NARCIS (Netherlands)

    Forbes, P.A.; Rooij, L. van; Rodarius, C.; Crandall, J.

    2008-01-01

    The current study presents a development and validation approach of a child human body model that will help understand child impact injuries and improve the biofidelity of child anthropometric test devices. Due to the lack of fundamental child biomechanical data needed to fully develop such models a

  6. Adjoint method for hybrid guidance loop state-space models

    NARCIS (Netherlands)

    Weiss, M.; Bucco, D.

    2015-01-01

    A framework is introduced to develop the theory of the adjoint method for models including both continuous and discrete dynamics. The basis of this framework consists of the class of impulsive linear dynamic systems. It allows extension of the adjoint method to more general models that include multi

  7. Hybrid modeling and empirical analysis of automobile supply chain network

    Science.gov (United States)

    Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying

    2017-05-01

    Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.

  8. Hybrid model for wireless mobility management using IPv6

    Science.gov (United States)

    Howie, Douglas P.; Sun, Junzhao; Koivisto, Antti T.

    2001-07-01

    Within the coming decade, there will be a dramatic increase in the availability of inexpensive, computationally powerful mobile devices running applications which use the Internet Protocol (IP) to access multimedia services over broad-band wireless connections. To this end, there has been extensive research and standardization in the areas of Mobile IP and IPv6. The purpose of this paper is to apply this work to the issues involved in designing a mobility model able to adapt to different wireless mobile IP scenarios. We describe the usefulness of this model in the 4th generation mobile multimedia systems to come. This new model has been synthesized through a comparative analysis of current mobile IP models where particular attention has been given to the problems of mobile IP handoff and mobility management and their impact on QoS. By applying a unique perspective to these problems, our model is used to set a roadmap for future mobile IPv6 testbed construction.

  9. Hybrid Modelling of a Traveling Wave Piezoelectric Motor

    DEFF Research Database (Denmark)

    El, Ghouti N.

    torque at low speed, quiet operation (ultrasonic), simple structure, compactness in size and no electromagnetic interferences. However, the mathematical model of the PEM is complex and difficult to derive due to its driving principle based on high-frequency mechanical vibrations and frictional force...... the performance characteristics of the PEM under various working conditions. The main objective of this PhD project is to derive a suitable model for investigating some nonlinear control strategies in a simulated environment. Most of the existing modeling approaches are inappropriate for the control community due......) and finally the basic laws of dynamics. In order to overcome some of the drawbacks of the existing methods, and thereby meet the needs of the control community, three main approaches are considered in this modeling task. First, the equivalent circuit method is investigated in order to derive a lumped model...

  10. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    Science.gov (United States)

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.

  11. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    Science.gov (United States)

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model. PMID:28120889

  12. A hybrid model for mapping simplified seismic response via a GIS-metamodel approach

    Directory of Open Access Journals (Sweden)

    G. Grelle

    2014-02-01

    Full Text Available An hybrid model, consisting of GIS and metamodel (model of model procedures, was introduced with the aim of estimating the 1-D spatial seismic site response. Inputs and outputs are provided and processed by means of an appropriate GIS model, named GIS Cubic Model (GCM. This discretizes the seismic underground half-space in a pseudo-tridimensional way. GCM consists of a layered parametric structure aimed at resolving a predicted metamodel by means of pixel to pixel vertical computing. The metamodel leading to the determination of a bilinear-polynomial function is able to design the classic shape of the spectral acceleration response in relation to the main physical parameters that characterize the spectrum itself. The main physical parameters consist of (i the average shear wave velocity of the shallow layer, (ii the fundamental period and, (iii the period where the spatial spectral response is required. The metamodel is calibrated on theoretical spectral accelerations regarding the local likely Vs-profiles, which are obtained using the Monte Carlo simulation technique on the basis of the GCM information. Therefore, via the GCM structure and the metamodel, the hybrid model provides maps of normalized acceleration response spectra. The hybrid model was applied and tested on the built-up area of the San Giorgio del Sannio village, located in a high-risk seismic zone of Southern Italy.

  13. Accurate modeling of switched reluctance machine based on hybrid trained WNN

    Science.gov (United States)

    Song, Shoujun; Ge, Lefei; Ma, Shaojie; Zhang, Man

    2014-04-01

    According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.

  14. Two-field axion-monodromy hybrid inflation model: Dante's Waterfall

    Science.gov (United States)

    Carone, Christopher D.; Erlich, Joshua; Sensharma, Anuraag; Wang, Zhen

    2015-02-01

    We describe a hybrid axion-monodromy inflation model motivated by the Dante's Inferno scenario. In Dante's Inferno, a two-field potential features a stable trench along which a linear combination of the two fields slowly rolls, rendering the dynamics essentially identical to that of single-field chaotic inflation. A shift symmetry allows for the Lyth bound to be effectively evaded as in other axion-monodromy models. In our proposal, the potential is concave downward near the origin and the inflaton trajectory is a gradual downward spiral, ending at a point where the trench becomes unstable. There, the fields begin falling rapidly towards the minimum of the potential and inflation terminates as in a hybrid model. We find parameter choices that reproduce observed features of the cosmic microwave background, and discuss our model in light of recent results from the BICEP2 and Planck experiments.

  15. PERFORMANCE EVALUATION METHOD FOR BUSINESS PROCESS OF MACHINERY MANUFACTURER BASED ON DEA/AHP HYBRID MODEL

    Institute of Scientific and Technical Information of China (English)

    WANG Ting; YI Shuping; YANG Yuanzhao

    2007-01-01

    A set of indices for performance evaluation for business processes with multiple inputs and multiple outputs is proposed, which are found in machinery manufacturers. Based on the traditional methods of data envelopment analysis (DEA) and analytical hierarchical process (AHP), a hybrid model called DEA/AHP model is proposed to deal with the evaluation of business process performance. With the proposed method, the DEA is firstly used to develop a pairwise comparison matrix, and then the AHP is applied to evaluate the performance of business process using the pairwise comparison matrix. The significant advantage of this hybrid model is the use of objective data instead of subjective human judgment for performance evaluation. In the case study, a project of business process reengineering (BPR) with a hydraulic machinery manufacturer is used to demonstrate the effectiveness of the DEA/AHP model.

  16. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

    DEFF Research Database (Denmark)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L

    2016-01-01

    and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...... on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network...... model for a ∼1 mm(2) patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its...

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

    Science.gov (United States)

    Chiadamrong, N.; Piyathanavong, V.

    2017-04-01

    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.

  18. A harmonious unifying hybrid preferential model and its universal properties for complex dynamical networks

    Institute of Scientific and Technical Information of China (English)

    FANG JinQing; BI Qiao; LI Yong; LU XinBiao; LIU Qiang

    2007-01-01

    To describe the real world which is a harmonious unification world with both determinism and randomness, we propose a harmonious unifying hybrid preferential model (HUHPM) of a certain class of complex dynamical networks. HUHPM is governed only by the total hybrid ratio dlr according to the practical need. As some typical examples, the concepts and methods of the HUHPM are applied to the un-weighted BA model proposed by Barabási et al., the weighted BBV model proposed by Barat et al. and the weighted TDE model proposed by Wang et al. to get the so-called HUHPM-BA network, HUHPM-BBV network and HUHPM-TDE network.These HUHPM networks are investigated both analytically and numerically. It is found that the HUHPM reveals several universal properties, which more approach to the real-world networks for both un-weighted and weighted networks and have potential for applications.

  19. A hybrid model of the CO2 geochemical cycle and its application to large impact events

    Science.gov (United States)

    Kasting, J. F.; Pollack, J. B.; Toon, O. B.; Richardson, S. M.

    1986-01-01

    The effects of a large asteriod or comet impact on modern and ancient marine biospheres are analyzed. A hybrid model of the carbonate-silicate geochemical cycle, which is capable of calculating the concentrations of carbon dioxide in the atmosphere, ocean, and sedimentary rocks, is described. The differences between the Keir and Berger (1983) model and the hybrid model are discussed. Equilibrium solutions are derived for the preindustrial atmosphere/ocean system and for a system similar to that of the late Cretaceous Period. The model data reveal that globl darkening caused by a stratospheric dust veil could destroy the existing phytoplankton within a period of several weeks or months, nd the dissolution of atmospheric NO(x) compounds would lower the pH of ocean surface waters and release CO2 into the atmosphere. It is noted that the surface temperatures could be increased by several degrees and surface oceans would be uninhabitable for calcaerous organisms for approximately 20 years.

  20. A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model

    Science.gov (United States)

    Mizzi, A. P.

    2011-12-01

    A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model Arthur P. Mizzi National Center for Atmospheric Research Boulder, CO 80307 303-497-8987 mizzi@ucar.edu Recently, there has been increased interest in hybrid variational data assimilation due to its ability to improve numerical weather forecast accuracy by incorporating ensemble error information into the data assimilation process (Buehner, 2010a, b; Wang 2010). In this paper, we introduce a GSI/ETKF regional hybrid (Mizzi, 2011). The GSI/ETKF regional hybrid uses a modified version of NOAA/EMC's GSI global hybrid (Wang, 2010) for the ensemble mean analysis and an ETKF (Bishop, et. al., 2001) to update the ensemble perturbations. We tested the GSI/ETKF regional hybrid by applying it to cycling experiments with WRF/ARW on a coarse-resolution domain covering the continental United States (CONUS) that: (i) compared different ETKF schemes, and (ii) reduced and held the number of ETKF observations constant. The results from those experiments showed that: (i) the ETKF scheme requiring the least amount of inflation provided the lowest 12-hr forecast RMSEs (ii) holding the number of ETKF observations constant removed the oscillation in the posterior ETKF ensemble spread noted by Bowler et al., (2008), and (iii) reducing the number of ETKF observations lowered the 12-hr forecast RMSEs. Presently, we are extending this work to a comparison of the GSI/ETKF regional hybrid with a GSI/LETKF regional hybrid based on the LETKF of Ott, et. al., (2004) and a GSI/EnKF regional hybrid based on the DART EnKF (Anderson et. al., 2009). Generally, the GSI/LETKF and GSI/EnKF schemes require less ensemble spread inflation compared to the GSI/ETKF scheme. Consequently, we expect the GSI/LETKF and GSI/EnKF schemes to provide lower 12-hr forecast RMSEs compared to the GSI/ETKF results. Our preliminary results are consistent with that supposition.

  1. Hybrid Weyl semimetal

    Science.gov (United States)

    Li, Fei-Ye; Luo, Xi; Dai, Xi; Yu, Yue; Zhang, Fan; Chen, Gang

    2016-09-01

    We construct a tight-binding model realizing one pair of Weyl nodes and three distinct Weyl semimetals. In the type-I (type-II) Weyl semimetal, both nodes belong to type-I (type-II) Weyl nodes. In addition, there exists a third type, previously undiscovered and dubbed "hybrid Weyl semimetal", in which one Weyl node is of type I while the other is of type II. For the hybrid Weyl semimetal, we further demonstrate the bulk Fermi surfaces and the topologically protected surface states, analyze the unique Landau-level structure and quantum oscillation, and discuss the conditions for possible material realization.

  2. Polarization of inclusively produced $\\Lambda_{c}$ in a QCD based hybrid model

    CERN Document Server

    Goldstein, G R

    1999-01-01

    A hybrid model is presented for hadron polarization that is based on perturbative QCD subprocesses and the recombination of polarized quarks to form polarized hadrons. The model, originally applied to polarized $\\Lambda$'s that were inclusively produced by proton beams, is extended to include pion beams and polarized $\\Lambda_c$'s. The resulting polarizations are calculated as functions of $x_F$ and $p_T$ for high energies and are found to be in fair agreement with recent experiments.

  3. Multiscale modeling for classification of SAR imagery using hybrid EM algorithm and genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    Xianbin Wen; Hua Zhang; Jianguang Zhang; Xu Jiao; Lei Wang

    2009-01-01

    A novel method that hybridizes genetic algorithm (GA) and expectation maximization (EM) algorithm for the classification of syn-thetic aperture radar (SAR) imagery is proposed by the finite Gaussian mixtures model (GMM) and multiscale autoregressive (MAR)model. This algorithm is capable of improving the global optimality and consistency of the classification performance. The experiments on the SAR images show that the proposed algorithm outperforms the standard EM method significantly in classification accuracy.

  4. A hybrid mathematical model for self-organizing cell migration in the zebrafish lateral line

    OpenAIRE

    Preziosi, Luigi

    2015-01-01

    In this paper we propose a discrete in continuous mathematical model for the morphogenesis of the posterior lateral line system in zebrafish. Our model follows closely the results obtained in recent biological experiments. We rely on a hybrid description: discrete for the cellular level and continuous for the molecular level. We prove the existence of steady solutions consistent with the formation of particular biological structure, the neuromasts. Dynamical numerical simulations are performe...

  5. Parameter estimation for stochastic hybrid model applied to urban traffic flow estimation

    OpenAIRE

    2015-01-01

    This study proposes a novel data-based approach for estimating the parameters of a stochastic hybrid model describing the traffic flow in an urban traffic network with signalized intersections. The model represents the evolution of the traffic flow rate, measuring the number of vehicles passing a given location per time unit. This traffic flow rate is described using a mode-dependent first-order autoregressive (AR) stochastic process. The parameters of the AR process take different values dep...

  6. Mapping Seasonal Evapotranspiration and Root Zone Soil Moisture using a Hybrid Modeling Approach over Vineyards

    Science.gov (United States)

    Geli, H. M. E.

    2015-12-01

    Estimates of actual crop evapotranspiration (ETa) at field scale over the growing season are required for improving agricultural water management, particularly in water limited and drought prone regions. Remote sensing data from multiple platforms such as airborne and Landsat-based sensors can be used to provide these estimates. Combining these data with surface energy balance models can provide ETa estimates at sub- field scale as well as information on vegetation stress and soil moisture conditions. However, the temporal resolution of airborne and Landsat data does not allow for a continuous ETa monitoring over the course of the growing season. This study presents the application of a hybrid ETa modeling approach developed for monitoring daily ETa and root zone available water at high spatial resolutions. The hybrid ETa modeling approach couples a thermal-based energy balance model with a water balance-based scheme using data assimilation. The two source energy balance (TSEB) model is used to estimate instantaneous ETa which can be extrapolated to daily ETa using a water balance model modified to use the reflectance-based basal crop coefficient for interpolating ETa in between airborne and/or Landsat overpass dates. Moreover, since it is a water balance model, the soil moisture profile is also estimated. The hybrid ETa approach is applied over vineyard fields in central California. High resolution airborne and Landsat imagery were used to drive the hybrid model. These images were collected during periods that represented different vine phonological stages in 2013 growing season. Estimates of daily ETa and surface energy balance fluxes will be compared with ground-based eddy covariance tower measurements. Estimates of soil moisture at multiple depths will be compared with measurements.

  7. Preliminary Hybrid Modeling of the Panama Canal: Operations and Salinity Diffusion

    Directory of Open Access Journals (Sweden)

    Luis Rabelo

    2012-01-01

    Full Text Available This paper deals with the initial modeling of water salinity and its diffusion into the lakes during lock operation on the Panama Canal. A hybrid operational model was implemented using the AnyLogic software simulation environment. This was accomplished by generating an operational discrete-event simulation model and a continuous simulation model based on differential equations, which modeled the salinity diffusion in the lakes. This paper presents that unique application and includes the effective integration of lock operations and its impact on the environment.

  8. Temperature analysis of induction motors using a hybrid thermal model with distributed heat sources

    Science.gov (United States)

    Mukhopadhyay, S. C.; Pal, S. K.

    1998-06-01

    The article presents a hybrid thermal model for the accurate estimation of temperature distribution of induction motors. The developed model is a combination of lumped and distributed thermal parameters which are obtained from motor dimensions and other constants such as material density, specific heats, thermal conductivity, etc. The model is especially suited for the derating of induction motors operating under distorted and unbalanced supply condition. The model have been applied to a small (2hp, 415 V, 3-phase) cage rotor induction motor. The performance of the model is confirmed by experimental temperature data from the body and the conductor inside the slots of the motor.

  9. Evaluation of models generated via hybrid evolutionary algorithms ...

    African Journals Online (AJOL)

    2016-04-02

    Apr 2, 2016 ... Cyanobacteria are responsible for many problems in drinking water treatment works ... events of high cyanobacterial cell concentrations in the source water is evident. ..... Improvement of the models was achieved by structure.

  10. Hybrid Computational Model for High-Altitude Aeroassist Vehicles Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed effort addresses a need for accurate computational models to support aeroassist and entry vehicle system design over a broad range of flight conditions...

  11. A hybrid plume model for local-scale dispersion

    Energy Technology Data Exchange (ETDEWEB)

    Nikmo, J.; Tuovinen, J.P.; Kukkonen, J.; Valkama, I.

    1997-12-31

    The report describes the contribution of the Finnish Meteorological Institute to the project `Dispersion from Strongly Buoyant Sources`, under the `Environment` programme of the European Union. The project addresses the atmospheric dispersion of gases and particles emitted from typical fires in warehouses and chemical stores. In the study only the `passive plume` regime, in which the influence of plume buoyancy is no longer important, is addressed. The mathematical model developed and its numerical testing is discussed. The model is based on atmospheric boundary-layer scaling theory. In the vicinity of the source, Gaussian equations are used in both the horizontal and vertical directions. After a specified transition distance, gradient transfer theory is applied in the vertical direction, while the horizontal dispersion is still assumed to be Gaussian. The dispersion parameters and eddy diffusivity are modelled in a form which facilitates the use of a meteorological pre-processor. Also a new model for the vertical eddy diffusivity (K{sub z}), which is a continuous function of height in the various atmospheric scaling regions is presented. The model includes a treatment of the dry deposition of gases and particulate matter, but wet deposition has been neglected. A numerical solver for the atmospheric diffusion equation (ADE) has been developed. The accuracy of the numerical model was analysed by comparing the model predictions with two analytical solutions of ADE. The numerical deviations of the model predictions from these analytic solutions were less than two per cent for the computational regime. The report gives numerical results for the vertical profiles of the eddy diffusivity and the dispersion parameters, and shows spatial concentration distributions in various atmospheric conditions 39 refs.

  12. Fractional snow cover mapping from MODIS data using wavelet-artificial intelligence hybrid models

    Science.gov (United States)

    Moosavi, Vahid; Malekinezhad, Hossein; Shirmohammadi, Bagher

    2014-04-01

    This study was carried out to evaluate the wavelet-artificial intelligence hybrid models to produce fractional snow cover maps. At first, cloud cover was removed from MODIS data and cloud free images were produced. SVM-based binary classified ETM+ imagery were then used as reference maps in order to obtain train and test data for sub-pixel classification models. ANN and ANFIS-based modeling were performed using raw data (without wavelet-based preprocessing). In the next step, several mother wavelets and levels were used in order to decompose the original data to obtain wavelet coefficients. Then, the decomposed data were used for further modeling processes. ANN, ANFIS, wavelet-ANN and wavelet-ANFIS models were compared to evaluate the effect of wavelet transformation on the ability of artificial intelligence models. It was demonstrated that wavelet transformation as a preprocessing approach can significantly enhance the performance of ANN and ANFIS models. This study indicated an overall accuracy of 92.45% for wavelet-ANFIS model, 86.13% for wavelet-ANN, 72.23% for ANFIS model and 66.78% for ANN model. In fact, hybrid wavelet-artificial intelligence models can extract the characteristics of the original signals (i.e. model inputs) accurately through decomposing the non-stationary and complex signals into several stationary and simpler signals. The positive effect of fuzzification as well as wavelet transformation in the wavelet-ANFIS model was also confirmed.

  13. Performance of hybrid programming models for multiscale cardiac simulations: preparing for petascale computation.

    Science.gov (United States)

    Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias

    2011-10-01

    Future multiscale and multiphysics models that support research into human disease, translational medical science, and treatment can utilize the power of high-performance computing (HPC) systems. We anticipate that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message-passing processes [e.g., the message-passing interface (MPI)] with multithreading (e.g., OpenMP, Pthreads). The objective of this study is to compare the performance of such hybrid programming models when applied to the simulation of a realistic physiological multiscale model of the heart. Our results show that the hybrid models perform favorably when compared to an implementation using only the MPI and, furthermore, that OpenMP in combination with the MPI provides a satisfactory compromise between performance and code complexity. Having the ability to use threads within MPI processes enables the sophisticated use of all processor cores for both computation and communication phases. Considering that HPC systems in 2012 will have two orders of magnitude more cores than what was used in this study, we believe that faster than real-time multiscale cardiac simulations can be achieved on these systems.

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

    Directory of Open Access Journals (Sweden)

    Kang-Wook Lee

    2017-05-01

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

  15. Financial Time Series Modelling with Hybrid Model Based on Customized RBF Neural Network Combined With Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2014-01-01

    Full Text Available In this paper, authors apply feed-forward artificial neural network (ANN of RBF type into the process of modelling and forecasting the future value of USD/CAD time series. Authors test the customized version of the RBF and add the evolutionary approach into it. They also combine the standard algorithm for adapting weights in neural network with an unsupervised clustering algorithm called K-means. Finally, authors suggest the new hybrid model as a combination of a standard ANN and a moving average for error modeling that is used to enhance the outputs of the network using the error part of the original RBF. Using high-frequency data, they examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, authors perform the comparative out-of-sample analysis of the suggested hybrid model with statistical models and the standard neural network.

  16. Introducing A Hybrid Data Mining Model to Evaluate Customer Loyalty

    Directory of Open Access Journals (Sweden)

    H. Alizadeh

    2016-12-01

    Full Text Available The main aim of this study was introducing a comprehensive model of bank customers᾽ loyalty evaluation based on the assessment and comparison of different clustering methods᾽ performance. This study also pursues the following specific objectives: a using different clustering methods and comparing them for customer classification, b finding the effective variables in determining the customer loyalty, and c using different collective classification methods to increase the modeling accuracy and comparing the results with the basic methods. Since loyal customers generate more profit, this study aims at introducing a two-step model for classification of customers and their loyalty. For this purpose, various methods of clustering such as K-medoids, X-means and K-means were used, the last of which outperformed the other two through comparing with Davis-Bouldin index. Customers were clustered by using K-means and members of these four clusters were analyzed and labeled. Then, a predictive model was run based on demographic variables of customers using various classification methods such as DT (Decision Tree, ANN (Artificial Neural Networks, NB (Naive Bayes, KNN (K-Nearest Neighbors and SVM (Support Vector Machine, as well as their bagging and boosting to predict the class of loyal customers. The results showed that the bagging-ANN was the most accurate method in predicting loyal customers. This two-stage model can be used in banks and financial institutions with similar data to identify the type of future customers.

  17. Hybrid Corporate Performance Prediction Model Considering Technical Capability

    Directory of Open Access Journals (Sweden)

    Joonhyuck Lee

    2016-07-01

    Full Text Available Many studies have tried to predict corporate performance and stock prices to enhance investment profitability using qualitative approaches such as the Delphi method. However, developments in data processing technology and machine-learning algorithms have resulted in efforts to develop quantitative prediction models in various managerial subject areas. We propose a quantitative corporate performance prediction model that applies the support vector regression (SVR algorithm to solve the problem of the overfitting of training data and can be applied to regression problems. The proposed model optimizes the SVR training parameters based on the training data, using the genetic algorithm to achieve sustainable predictability in changeable markets and managerial environments. Technology-intensive companies represent an increasing share of the total economy. The performance and stock prices of these companies are affected by their financial standing and their technological capabilities. Therefore, we apply both financial indicators and technical indicators to establish the proposed prediction model. Here, we use time series data, including financial, patent, and corporate performance information of 44 electronic and IT companies. Then, we predict the performance of these companies as an empirical verification of the prediction performance of the proposed model.

  18. Dynamic modeling of hybrid energy storage systems coupled to photovoltaic generation in residential applications

    Science.gov (United States)

    Maclay, James D.; Brouwer, Jacob; Samuelsen, G. Scott

    A model of a photovoltaic (PV) powered residence in stand-alone configuration was developed and evaluated. The model assesses the sizing, capital costs, control strategies, and efficiencies of reversible fuel cells (RFC), batteries, and ultra-capacitors (UC) both individually, and in combination, as hybrid energy storage devices. The choice of control strategy for a hybrid energy storage system is found to have a significant impact on system efficiency, hydrogen production and component utilization. A hybrid energy storage system comprised of batteries and RFC has the advantage of reduced cost (compared to using a RFC as the sole energy storage device), high system efficiency and hydrogen energy production capacity. A control strategy that preferentially used the RFC before the battery in meeting load demand allows both grid independent operation and better RFC utilization compared to a system that preferentially used the battery before the RFC. Ultra-capacitors coupled with a RFC in a hybrid energy storage system contain insufficient energy density to meet dynamic power demands typical of residential applications.

  19. Modelling and Optimising the Value of a Hybrid Solar-Wind System

    Science.gov (United States)

    Nair, Arjun; Murali, Kartik; Anbuudayasankar, S. P.; Arjunan, C. V.

    2017-05-01

    In this paper, a net present value (NPV) approach for a solar hybrid system has been presented. The system, in question aims at supporting an investor by assessing an investment in solar-wind hybrid system in a given area. The approach follow a combined process of modelling the system, with optimization of major investment-related variables to maximize the financial yield of the investment. The consideration of solar wind hybrid supply presents significant potential for cost reduction. The investment variables concern the location of solar wind plant, and its sizing. The system demand driven, meaning that its primary aim is to fully satisfy the energy demand of the customers. Therefore, the model is a practical tool in the hands of investor to assess and optimize in financial terms an investment aiming at covering real energy demand. Optimization is performed by taking various technical, logical constraints. The relation between the maximum power obtained between individual system and the hybrid system as a whole in par with the net present value of the system has been highlighted.

  20. A Hybrid Authorization Model For Project-Oriented Workflow

    Institute of Scientific and Technical Information of China (English)

    Zhang Xiaoguang(张晓光); Cao Jian; Zhang Shensheng

    2003-01-01

    In the context of workflow systems, security-relevant aspect is related to the assignment of activities to (human or automated) agents. This paper intends to cast light on the management of project-oriented workflow. A comprehensive authorization model is proposed from the perspective of project management. In this model, the concept of activity decomposition and team is introduced, which improves the security of conventional role-based access control. Furthermore, policy is provided to define the static and dynamic constraints such as Separation of Duty (SoD). Validity of constraints is proposed to provide a fine-grained assignment, which improves the performance of policy management. The model is applicable not only to project-oriented workflow applications but also to other teamwork environments such as virtual enterprise.