WorldWideScience

Sample records for hybrid model adaptation

  1. 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.

  2. 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.

  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. 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.

  5. 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.

  6. 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.

  7. Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models

    CERN Document Server

    Vesselinov, Velimir V

    2011-01-01

    A new adaptive hybrid optimization strategy, entitled squads, is proposed for complex inverse analysis of computationally intensive physical models. The new strategy is designed to be computationally efficient and robust in identification of the global optimum (e.g. maximum or minimum value of an objective function). It integrates a global Adaptive Particle Swarm Optimization (APSO) strategy with a local Levenberg-Marquardt (LM) optimization strategy using adaptive rules based on runtime performance. The global strategy optimizes the location of a set of solutions (particles) in the parameter space. The LM strategy is applied only to a subset of the particles at different stages of the optimization based on the adaptive rules. After the LM adjustment of the subset of particle positions, the updated particles are returned to the APSO strategy. The advantages of coupling APSO and LM in the manner implemented in squads is demonstrated by comparisons of squads performance against Levenberg-Marquardt (LM), Particl...

  8. Recurrent rearrangement during adaptive evolution in an interspecific yeast hybrid suggests a model for rapid introgression.

    Directory of Open Access Journals (Sweden)

    Barbara Dunn

    2013-03-01

    Full Text Available Genome rearrangements are associated with eukaryotic evolutionary processes ranging from tumorigenesis to speciation. Rearrangements are especially common following interspecific hybridization, and some of these could be expected to have strong selective value. To test this expectation we created de novo interspecific yeast hybrids between two diverged but largely syntenic Saccharomyces species, S. cerevisiae and S. uvarum, then experimentally evolved them under continuous ammonium limitation. We discovered that a characteristic interspecific genome rearrangement arose multiple times in independently evolved populations. We uncovered nine different breakpoints, all occurring in a narrow ~1-kb region of chromosome 14, and all producing an "interspecific fusion junction" within the MEP2 gene coding sequence, such that the 5' portion derives from S. cerevisiae and the 3' portion derives from S. uvarum. In most cases the rearrangements altered both chromosomes, resulting in what can be considered to be an introgression of a several-kb region of S. uvarum into an otherwise intact S. cerevisiae chromosome 14, while the homeologous S. uvarum chromosome 14 experienced an interspecific reciprocal translocation at the same breakpoint within MEP2, yielding a chimaeric chromosome; these events result in the presence in the cell of two MEP2 fusion genes having identical breakpoints. Given that MEP2 encodes for a high-affinity ammonium permease, that MEP2 fusion genes arise repeatedly under ammonium-limitation, and that three independent evolved isolates carrying MEP2 fusion genes are each more fit than their common ancestor, the novel MEP2 fusion genes are very likely adaptive under ammonium limitation. Our results suggest that, when homoploid hybrids form, the admixture of two genomes enables swift and otherwise unavailable evolutionary innovations. Furthermore, the architecture of the MEP2 rearrangement suggests a model for rapid introgression, a

  9. Simulation modeling of functional adaptive interference nulling for multibeam hybrid reflector antenna systems

    Science.gov (United States)

    Kartsan, I. N.; Tyapkin, V. N.; Dmitriev, D. D.; Goncharov, A. E.; Zelenkov, P. V.; Kovalev, I. V.

    2016-11-01

    This paper considers the simulation of adaptive nulling mechanism patterns in hybrid reflector antenna systems with a 19-element feed element, in which the radiation pattern is formed as a cluster. Incidents of broadband and narrowband interference are studied in the article.

  10. Full Gradient Solution to Adaptive Hybrid Control

    Science.gov (United States)

    Bean, Jacob; Schiller, Noah H.; Fuller, Chris

    2017-01-01

    This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

  11. An adaptive hybrid EnKF-OI scheme for efficient state-parameter estimation of reactive contaminant transport models

    KAUST Repository

    El Gharamti, Mohamad

    2014-09-01

    Reactive contaminant transport models are used by hydrologists to simulate and study the migration and fate of industrial waste in subsurface aquifers. Accurate transport modeling of such waste requires clear understanding of the system\\'s parameters, such as sorption and biodegradation. In this study, we present an efficient sequential data assimilation scheme that computes accurate estimates of aquifer contamination and spatially variable sorption coefficients. This assimilation scheme is based on a hybrid formulation of the ensemble Kalman filter (EnKF) and optimal interpolation (OI) in which solute concentration measurements are assimilated via a recursive dual estimation of sorption coefficients and contaminant state variables. This hybrid EnKF-OI scheme is used to mitigate background covariance limitations due to ensemble under-sampling and neglected model errors. Numerical experiments are conducted with a two-dimensional synthetic aquifer in which cobalt-60, a radioactive contaminant, is leached in a saturated heterogeneous clayey sandstone zone. Assimilation experiments are investigated under different settings and sources of model and observational errors. Simulation results demonstrate that the proposed hybrid EnKF-OI scheme successfully recovers both the contaminant and the sorption rate and reduces their uncertainties. Sensitivity analyses also suggest that the adaptive hybrid scheme remains effective with small ensembles, allowing to reduce the ensemble size by up to 80% with respect to the standard EnKF scheme. © 2014 Elsevier Ltd.

  12. Designframework for an Adaptive, Hybrid MOOC

    DEFF Research Database (Denmark)

    Gynther, Karsten

    2015-01-01

    The research project has developed a design framework for an adaptive hybrid MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of pedagogical design principles that can be used to design courses for teacher professional...

  13. Invited review: Adaptive numerical modelling and hybrid physically based ANM approaches in materials engineering - a survey

    OpenAIRE

    Reed, P.A.S; Starink, M.J.; Gunn, S.R.; Sinclair, I.

    2009-01-01

    Many adaptive numerical modelling (ANM) techniques such as artificial neural networks, (including multi-layer perceptrons) support vector machines and Gaussian processes have now been applied to a wide range of regression and classification problems in materials science. Materials science offers a wide range of industrial applications and hence problem complexity levels from well physically characterised systems (e.g. high value, low volume products) to high volume low cost applications with ...

  14. Adaptation and hybridization in computational intelligence

    CERN Document Server

    Jr, Iztok

    2015-01-01

      This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.  

  15. Hybrid Adaptive Observer for a Brushless DC Motor

    DEFF Research Database (Denmark)

    Niemczyk, Piotr; Porchez, Thomas; Bendtsen, Jan Dimon

    2008-01-01

    A novel hybrid adaptive observer for Brushless DC Motors (BLDCM) is presented. It uses two current measurements of BLDCM phases to estimate the angle and the speed of the rotor. The observer is designed on the basis of a hybrid model, which is also presented in this paper. The parameters...

  16. Hybrid Wind Speed Prediction Based on a Self-Adaptive ARIMAX Model with an Exogenous WRF Simulation

    Directory of Open Access Journals (Sweden)

    Erdong Zhao

    2015-12-01

    Full Text Available Wind speed forecasting is difficult not only because of the influence of atmospheric dynamics but also for the impossibility of providing an accurate prediction with traditional statistical forecasting models that work by discovering an inner relationship within historical records. This paper develops a self-adaptive (SA auto-regressive integrated moving average with exogenous variables (ARIMAX model that is optimized very-short-term by the chaotic particle swarm optimization (CPSO algorithm, known as the SA-ARIMA-CPSO approach, for wind speed prediction. The ARIMAX model chooses the wind speed result from the Weather Research and Forecasting (WRF simulation as an exogenous input variable. Further, an SA strategy is applied to the ARIMAX process. When new information is available, the model process can be updated adaptively with parameters optimized by the CPSO algorithm. The proposed SA-ARIMA-CPSO approach enables the forecasting process to update training information and model parameters intelligently and adaptively. As tested using the 15-min wind speed data collected from a wind farm in Northern China, the improved method has the best performance compared with several other models.

  17. Hybrid adaptive ascent flight control for a flexible launch vehicle

    Science.gov (United States)

    Lefevre, Brian D.

    For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the

  18. 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

  19. Probabilistic assessment of uncertain adaptive hybrid composites

    Science.gov (United States)

    Shiao, Michael C.; Singhal, Surendra N.; Chamis, Christos C.

    1994-01-01

    Adaptive composite structures using actuation materials, such as piezoelectric fibers, were assessed probabilistically utilizing intraply hybrid composite mechanics in conjunction with probabilistic composite structural analysis. Uncertainties associated with the actuation material as well as the uncertainties in the regular (traditional) composite material properties were quantified and considered in the assessment. Static and buckling analyses were performed for rectangular panels with various boundary conditions and different control arrangements. The probability density functions of the structural behavior, such as maximum displacement and critical buckling load, were computationally simulated. The results of the assessment indicate that improved design and reliability can be achieved with actuation material.

  20. 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.

  1. 基于AMMI模型对蓖麻杂交种适应性的分析%Adaptability Analysis of Hybrid Castor Based on AMMI Model

    Institute of Scientific and Technical Information of China (English)

    张宝贤; 王光明; 谭德云; 刘红光; 孙丽娟

    2011-01-01

    [目的]分析4个蓖麻杂交种的生产适应性和稳定性,探讨AMMI模型在品种评价中的应用方法。[方法]应用AMMI模型及双标图对4个蓖麻杂交组合2008-2009年多点试验的产量性状进行稳定性分析,进而评价各参试组合的稳定性和适应性。[结果]AMMI模型分析表明,交互作用主成分轴奇异值IPCA1、IPCA2两项共解释了92.24%的互作变异,AMMI模型不仅最大程度地反应互作变异,而且能准确地分析品种的适应能力和稳产性。[结论]AMMI模型把方差分析和主成分分析结合在一起,相对于传统的方差分析方法提高了精确度。甚至能够对自身没有结果能力的雌性系,也可以通过鉴定其F1代的基因和环境的互作效应,间接评价雌性系的适应性。%[Objective] The paper analyzed production adaptability and stability of 4 hybrids of castor,so as to explore the application method of AMMI model in variety evaluation.[Method] AMMI model and biplot were used to carry out stability analysis on 4 castor combinations in multi-point test during 2008 and 2009,and further evaluate the stability and adaptability of various tested combinations.[Result] AMMI model analysis showed that the singular values IPCA1 and IPCA2 in principal component axis of interaction totally explained 92.24% of the interaction variance.AMMI model not only maximizes the reflection on variation of interaction,but also can accurately analyze the adaptability and yield stability of varieties.[Conclusion] AMMI model integrates variance analysis and principal component analysis together,which improves accuracy compared with the traditional method.Even the adaptability of female line without fertility could be indirectly evaluated through the identification on the genotype and environment interaction effects in F1 generation.

  2. A Hybrid Multi-Step Rolling Forecasting Model Based on SSA and Simulated Annealing—Adaptive Particle Swarm Optimization for Wind Speed

    Directory of Open Access Journals (Sweden)

    Pei Du

    2016-08-01

    Full Text Available With the limitations of conventional energy becoming increasing distinct, wind energy is emerging as a promising renewable energy source that plays a critical role in the modern electric and economic fields. However, how to select optimization algorithms to forecast wind speed series and improve prediction performance is still a highly challenging problem. Traditional single algorithms are widely utilized to select and optimize parameters of neural network algorithms, but these algorithms usually ignore the significance of parameter optimization, precise searching, and the application of accurate data, which results in poor forecasting performance. With the aim of overcoming the weaknesses of individual algorithms, a novel hybrid algorithm was created, which can not only easily obtain the real and effective wind speed series by using singular spectrum analysis, but also possesses stronger adaptive search and optimization capabilities than the other algorithms: it is faster, has fewer parameters, and is less expensive. For the purpose of estimating the forecasting ability of the proposed combined model, 10-min wind speed series from three wind farms in Shandong Province, eastern China, are employed as a case study. The experimental results were considerably more accurately predicted by the presented algorithm than the comparison algorithms.

  3. A Novel Thin Client Architecture with Hybrid Push-Pull Model, Adaptive Display Pre-Fetching and Graph Colouring

    Directory of Open Access Journals (Sweden)

    Sumalatha.M.R

    2016-06-01

    Full Text Available The advent of cloud computing has driven away the notion of having sophisticated hardware devices for performing computing intensive tasks. This feature is very essential for resource-constrained devices. In mobile cloud computing, it is sufficient that the device be a thin client i.e. which concentrates solely on providing a graphical user interface to the end-user and the processing is done in the cloud. We focus on adaptive display virtualization where the display updates are computed in advance using synchronization techniques and classifying the job as computationally intensive or not based on the complexity of the program and the interaction pattern. Based on application, the next possible key-press is identified and those particular frames are pre-fetched into the local buffer. Based on these two factors, a decision is then made whether to execute the job locally or in the cloud or whether we must take the next frame from the local buffer or pull it from server. Jobs requiring greater interaction are executed locally in the mobile to reduce interaction delay. If a job is to be executed in the cloud, then the results of the processing alone are sent via the network to the device. The parameters are varied in runtime based on network conditions and application parameters to minimise the interaction delay.

  4. Prediction of settled water turbidity and optimal coagulant dosage in drinking water treatment plant using a hybrid model of k-means clustering and adaptive neuro-fuzzy inference system

    Science.gov (United States)

    Kim, Chan Moon; Parnichkun, Manukid

    2017-02-01

    Coagulation is an important process in drinking water treatment to attain acceptable treated water quality. However, the determination of coagulant dosage is still a challenging task for operators, because coagulation is nonlinear and complicated process. Feedback control to achieve the desired treated water quality is difficult due to lengthy process time. In this research, a hybrid of k-means clustering and adaptive neuro-fuzzy inference system (k-means-ANFIS) is proposed for the settled water turbidity prediction and the optimal coagulant dosage determination using full-scale historical data. To build a well-adaptive model to different process states from influent water, raw water quality data are classified into four clusters according to its properties by a k-means clustering technique. The sub-models are developed individually on the basis of each clustered data set. Results reveal that the sub-models constructed by a hybrid k-means-ANFIS perform better than not only a single ANFIS model, but also seasonal models by artificial neural network (ANN). The finally completed model consisting of sub-models shows more accurate and consistent prediction ability than a single model of ANFIS and a single model of ANN based on all five evaluation indices. Therefore, the hybrid model of k-means-ANFIS can be employed as a robust tool for managing both treated water quality and production costs simultaneously.

  5. 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.

  6. Adaptive powertrain control for plugin hybrid electric vehicles

    Science.gov (United States)

    Kedar-Dongarkar, Gurunath; Weslati, Feisel

    2013-10-15

    A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

  7. Adaptive powertrain control for plugin hybrid electric vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Kedar-Dongarkar, Gurunath; Weslati, Feisel

    2013-10-15

    A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

  8. Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

    KAUST Repository

    Rakia, Tamer

    2015-07-23

    Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

  9. Hybrid fitness, adaptation and evolutionary diversification: lessons learned from Louisiana Irises.

    Science.gov (United States)

    Arnold, M L; Ballerini, E S; Brothers, A N

    2012-03-01

    Estimates of hybrid fitness have been used as either a platform for testing the potential role of natural hybridization in the evolution of species and species complexes or, alternatively, as a rationale for dismissing hybridization events as being of any evolutionary significance. From the time of Darwin's publication of The Origin, through the neo-Darwinian synthesis, to the present day, the observation of variability in hybrid fitness has remained a challenge for some models of speciation. Yet, Darwin and others have reported the elevated fitness of hybrid genotypes under certain environmental conditions. In modern scientific terminology, this observation reflects the fact that hybrid genotypes can demonstrate genotype × environment interactions. In the current review, we illustrate the development of one plant species complex, namely the Louisiana Irises, into a 'model system' for investigating hybrid fitness and the role of genetic exchange in adaptive evolution and diversification. In particular, we will argue that a multitude of approaches, involving both experimental and natural environments, and incorporating both manipulative analyses and surveys of natural populations, are necessary to adequately test for the evolutionary significance of introgressive hybridization. An appreciation of the variability of hybrid fitness leads to the conclusion that certain genetic signatures reflect adaptive evolution. Furthermore, tests of the frequency of allopatric versus sympatric/parapatric divergence (that is, divergence with ongoing gene flow) support hybrid genotypes as a mechanism of evolutionary diversification in numerous species complexes.

  10. A hybrid adaptive control strategy for a smart prosthetic hand.

    Science.gov (United States)

    Chen, Cheng-Hung; Naidu, D Subbaram; Perez-Gracia, Alba; Schoen, Marco P

    2009-01-01

    This paper presents a hybrid of a soft computing technique of adaptive neuro-fuzzy inference system (ANFIS) and a hard computing technique of adaptive control for a two-dimensional movement of a prosthetic hand with a thumb and index finger. In particular, ANFIS is used for inverse kinematics, and the adaptive control is used for linearized dynamics to minimize tracking error. The simulations of this hybrid controller, when compared with the proportional-integral-derivative (PID) controller showed enhanced performance. Work is in progress to extend this methodology to a five-fingered, three-dimensional prosthetic hand.

  11. Adaptive response modelling

    Science.gov (United States)

    Campa, Alessandro; Esposito, Giuseppe; Belli, Mauro

    Cellular response to radiation is often modified by a previous delivery of a small "priming" dose: a smaller amount of damage, defined by the end point being investigated, is observed, and for this reason the effect is called adaptive response. An improved understanding of this effect is essential (as much as for the case of the bystander effect) for a reliable radiation risk assessment when low dose irradiations are involved. Experiments on adaptive response have shown that there are a number of factors that strongly influence the occurrence (and the level) of the adaptation. In particular, priming doses and dose rates have to fall in defined ranges; the same is true for the time interval between the delivery of the small priming dose and the irradiation with the main, larger, dose (called in this case challenging dose). Different hypotheses can be formulated on the main mechanism(s) determining the adaptive response: an increased efficiency of DNA repair, an increased level of antioxidant enzymes, an alteration of cell cycle progression, a chromatin conformation change. An experimental clearcut evidence going definitely in the direction of one of these explanations is not yet available. Modelling can be done at different levels. Simple models, relating the amount of damage, through elementary differential equations, to the dose and dose rate experienced by the cell, are relatively easy to handle, and they can be modified to account for the priming irradiation. However, this can hardly be of decisive help in the explanation of the mechanisms, since each parameter of these models often incorporates in an effective way several cellular processes related to the response to radiation. In this presentation we show our attempts to describe adaptive response with models that explicitly contain, as a dynamical variable, the inducible adaptive agent. At a price of a more difficult treatment, this approach is probably more prone to give support to the experimental studies

  12. Adaptive Current Control Method for Hybrid Active Power Filter

    Science.gov (United States)

    Chau, Minh Thuyen

    2016-09-01

    This paper proposes an adaptive current control method for Hybrid Active Power Filter (HAPF). It consists of a fuzzy-neural controller, identification and prediction model and cost function. The fuzzy-neural controller parameters are adjusted according to the cost function minimum criteria. For this reason, the proposed control method has a capability on-line control clings to variation of the load harmonic currents. Compared to the single fuzzy logic control method, the proposed control method shows the advantages of better dynamic response, compensation error in steady-state is smaller, able to online control is better and harmonics cancelling is more effective. Simulation and experimental results have demonstrated the effectiveness of the proposed control method.

  13. Adapted Active Appearance Models

    Directory of Open Access Journals (Sweden)

    Renaud Séguier

    2009-01-01

    Full Text Available Active Appearance Models (AAMs are able to align efficiently known faces under duress, when face pose and illumination are controlled. We propose Adapted Active Appearance Models to align unknown faces in unknown poses and illuminations. Our proposal is based on the one hand on a specific transformation of the active model texture in an oriented map, which changes the AAM normalization process; on the other hand on the research made in a set of different precomputed models related to the most adapted AAM for an unknown face. Tests on public and private databases show the interest of our approach. It becomes possible to align unknown faces in real-time situations, in which light and pose are not controlled.

  14. Novel hybrid adaptive controller for manipulation in complex perturbation environments.

    Directory of Open Access Journals (Sweden)

    Alex M C Smith

    Full Text Available In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.

  15. Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments

    Science.gov (United States)

    Smith, Alex M. C.; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne

    2015-01-01

    In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing. PMID:26029916

  16. 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.

  17. 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...

  18. Ancient hybridization fuels rapid cichlid fish adaptive radiations

    Science.gov (United States)

    Meier, Joana I.; Marques, David A.; Mwaiko, Salome; Wagner, Catherine E.; Excoffier, Laurent; Seehausen, Ole

    2017-01-01

    Understanding why some evolutionary lineages generate exceptionally high species diversity is an important goal in evolutionary biology. Haplochromine cichlid fishes of Africa's Lake Victoria region encompass >700 diverse species that all evolved in the last 150,000 years. How this ‘Lake Victoria Region Superflock' could evolve on such rapid timescales is an enduring question. Here, we demonstrate that hybridization between two divergent lineages facilitated this process by providing genetic variation that subsequently became recombined and sorted into many new species. Notably, the hybridization event generated exceptional allelic variation at an opsin gene known to be involved in adaptation and speciation. More generally, differentiation between new species is accentuated around variants that were fixed differences between the parental lineages, and that now appear in many new combinations in the radiation species. We conclude that hybridization between divergent lineages, when coincident with ecological opportunity, may facilitate rapid and extensive adaptive radiation. PMID:28186104

  19. 一种适应GPU的混合OLAP查询处理模型%GPU Adaptive Hybrid OLAP Query Processing Model

    Institute of Scientific and Technical Information of China (English)

    张宇; 张延松; 陈红; 王珊

    2016-01-01

    The general purpose graphic computing units (GPGPUs) have become the new platform for high performance computing due to their massive parallel computing power, and in recent years more and more high performance database research has placed focus on GPU database development. However, today's GPU database researches commonly inherit ROLAP (relational OLAP) model, and mainly address how to realize relational operators in GPU platform and performance tuning, especially on GPU oriented parallel hash join algorithm. GPUs have higher parallel computing power than CPUs but less logical control and management capacity for complex data structure, therefore they are not adaptive for directly migrating the in-memory database query processing algorithms based on complex data structure and memory management. This paper proposes a GPU vectorized processing oriented hybrid OLAP model, semi-MOLAP, which combines direct array access and array computing of MOLAP with storage efficiency of ROLAP. The pure array oriented GPU semi-MOLAP model simplifies GPU data management, reduces complexity of GPU semi-MOLAP algorithms and improves their code efficiency. Meanwhile, the semi-MOLAP operators are divided into co-computing operators on CPU and GPU platforms to improve utilization of both CPUs and GPUs for higher query processing performance.%通用GPU因其强大的并行计算能力成为新兴的高性能计算平台,并逐渐成为近年来学术界在高性能数据库实现技术领域的研究热点.但当前GPU数据库领域的研究沿袭的是ROLAP(relational OLAP)多维分析模型,研究主要集中在关系操作符在GPU平台上的算法实现和性能优化技术,以哈希连接的GPU并行算法研究为中心.GPU拥有数千个并行计算单元,但其逻辑控制单元较少,相对于CPU具有更强的并行计算能力,但逻辑控制和复杂内存管理能力较弱,因此并不适合需要复杂数据结构和复杂内存管理机制的内存数据库查询处理算

  20. 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...

  1. On-line identification of hybrid systems using an adaptive growing and pruning RBF neural network

    DEFF Research Database (Denmark)

    Alizadeh, Tohid

    2008-01-01

    This paper introduces an adaptive growing and pruning radial basis function (GAP-RBF) neural network for on-line identification of hybrid systems. The main idea is to identify a global nonlinear model that can predict the continuous outputs of hybrid systems. In the proposed approach, GAP......-RBF neural network uses a modified unscented kalman filter (UKF) with forgetting factor scheme as the required on-line learning algorithm. The effectiveness of the resulting identification approach is tested and evaluated on a simulated benchmark hybrid system....

  2. A hybrid RNS adaptive filter for channel equalization

    DEFF Research Database (Denmark)

    Bernocchi, Gian Luca; Cardarilli, Gian Carlo; Re, Andrea Del

    2006-01-01

    In this work a hybrid Residue Number System (RNS) implementation of an adaptive FIR filter is presented. The used adaptation algorithm is the Least Mean Squares (LMS). The filter has been designed to meet the constraints of specific class of applications. In fact, it is suitable for applications...... requiring a large number of taps where a serial updating of the filter coefficients is feasible (channel equalization or echo cancellation). In the literature, it has been shown that the RNS implementation of FIR filters grants earnings in area ad power consumption due to the introduced arithmetic...... simplifications. Vice versa, the RNS implementation of the adaptation algorithm needs scaling circuits that are complex and expensive in RNS arithmetic. For this reason, a serial binary implementation of the adaptation algorithm is chosen. The advantages in terms of area and speed of the RNS adaptive filter...

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

    Science.gov (United States)

    Kalwij, Ineke M.; Peralta, Richard C.

    2008-09-01

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

  4. 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...

  5. Forecasting Daily Precipitation Using Hybrid Model of Wavelet-Artificial Neural Network and Comparison with Adaptive Neurofuzzy Inference System (Case Study: Verayneh Station, Nahavand

    Directory of Open Access Journals (Sweden)

    Abazar Solgi

    2014-01-01

    Full Text Available Doubtlessly the first step in a river management is the precipitation modeling over the related watershed. However, considering high-stochastic property of the process, many models are still being developed in order to define such a complex phenomenon in the field of hydrologic engineering. Recently artificial neural network (ANN as a nonlinear interextrapolator is extensively used by hydrologists for precipitation modeling as well as other fields of hydrology. In the present study, wavelet analysis combined with artificial neural network and finally was compared with adaptive neurofuzzy system to predict the precipitation in Verayneh station, Nahavand, Hamedan, Iran. For this purpose, the original time series using wavelet theory decomposed to multiple subtime series. Then, these subseries were applied as input data for artificial neural network, to predict daily precipitation, and compared with results of adaptive neurofuzzy system. The results showed that the combination of wavelet models and neural networks has a better performance than adaptive neurofuzzy system, and can be applied to predict both short- and long-term precipitations.

  6. 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.

  7. 一种去除乘性噪声的自适应混合阶偏微分方法%Adaptive Hybrid-order PDEs Based Multiplicative Noise Removal Model

    Institute of Scientific and Technical Information of China (English)

    张宏群; 陈小晴; 陶兴龙

    2013-01-01

    针对偏微分方程在图像处理中的斑点噪声滤除问题,在自适应全变分去噪模型和四阶LLT去噪模型的基础上,提出一种针对乘性噪声的自适应混合阶变分去噪方法.该方法引入混合阶偏微分方程和尺度自适应边缘检测函数作为正则项,并利用乘性噪声分布构建保真项.用标准测试数据对所提自适应混合阶变分降噪模型进行验证,试验结果表明,该模型在有效滤除图像乘性噪声的同时,能很好地保护图像的边缘和纹理细节信息.处理后的图像在峰值信噪比PSNR、均方误差MSE、运行效率方面均优于自适应全变分和LLT模型.%An adaptive hybrid-order PDE method based on the adaptive total variation and a fourth-order PDE is proposed to reduce the multiplicative noise in images. A fidelity term constructed by noise distribution is used to enhance the edge of the image, when the adaptive hybrid-order partial differential equation is added as regular item. Denoising experiments on testing images show that the proposed method has higher capability of noise reduction and image edge details preserving. The results show that the new method has better performance than the adaptive total variation model and the LLT model in respects of PSNR: peak signal to noise ratio, MSE: mean square error and operating efficiency.

  8. A fully adaptive hybrid optimization of aircraft engine blades

    Science.gov (United States)

    Dumas, L.; Druez, B.; Lecerf, N.

    2009-10-01

    A new fully adaptive hybrid optimization method (AHM) has been developed and applied to an industrial problem in the field of the aircraft engine industry. The adaptivity of the coupling between a global search by a population-based method (Genetic Algorithms or Evolution Strategies) and the local search by a descent method has been particularly emphasized. On various analytical test cases, the AHM method overperforms the original global search method in terms of computational time and accuracy. The results obtained on the industrial case have also confirmed the interest of AHM for the design of new and original solutions in an affordable time.

  9. Adaptive Optoelectronic Eyes: Hybrid Sensor/Processor Architectures

    Science.gov (United States)

    2006-11-13

    J.  Lange , C. von der Malsburg, R. P. Würtz, and W. Konen, “Distortion Invariant Object Recognition Adaptive Optoelectronic Eyes: Hybrid Sensor...Meeting, Dallas, Texas, (November, 1998). 17.  G. Sáry, G. Kovács, K. Köteles, G.  Benedek , J. Fiser, and I. Biederman, “Selectivity Variations in Monkey

  10. 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...

  11. 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.

  12. 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

  13. 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.

  14. Finite Element Analysis of Adaptive-Stiffening and Shape-Control SMA Hybrid Composites

    Science.gov (United States)

    Gao, Xiujie; Burton, Deborah; Turner, Travis L.; Brinson, Catherine

    2005-01-01

    Shape memory alloy hybrid composites with adaptive-stiffening or morphing functions are simulated using finite element analysis. The composite structure is a laminated fiber-polymer composite beam with embedded SMA ribbons at various positions with respect to the neutral axis of the beam. Adaptive stiffening or morphing is activated via selective resistance heating of the SMA ribbons or uniform thermal loads on the beam. The thermomechanical behavior of these composites was simulated in ABAQUS using user-defined SMA elements. The examples demonstrate the usefulness of the methods for the design and simulation of SMA hybrid composites. Keywords: shape memory alloys, Nitinol, ABAQUS, finite element analysis, post-buckling control, shape control, deflection control, adaptive stiffening, morphing, constitutive modeling, user element

  15. What Drives Business Model Adaptation?

    DEFF Research Database (Denmark)

    Saebi, Tina; Lien, Lasse B.; Foss, Nicolai Juul

    2016-01-01

    -rigidity as well as prospect theory to examine business model adaptation in response to external threats and opportunities. Additionally, drawing on the behavioural theory of the firm, we argue that the past strategic orientation of a firm creates path dependencies that influence the propensity of the firm...... to adapt its business model. We test our hypotheses on a sample of 1196 Norwegian companies, and find that firms are more likely to adapt their business model under conditions of perceived threats than opportunities, and that strategic orientation geared towards market development is more conducive......Business models change as managers not only innovate business models, but also engage in more mundane adaptation in response to external changes, such as changes in the level or composition of demand. However, little is known about what causes such business model adaptation. We employ threat...

  16. 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.

  17. An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment

    KAUST Repository

    Bonny, Talal

    2012-07-28

    Sequence alignment algorithms such as the Smith-Waterman algorithm are among the most important applications in the development of bioinformatics. Sequence alignment algorithms must process large amounts of data which may take a long time. Here, we introduce our Adaptive Hybrid Multiprocessor technique to accelerate the implementation of the Smith-Waterman algorithm. Our technique utilizes both the graphics processing unit (GPU) and the central processing unit (CPU). It adapts to the implementation according to the number of CPUs given as input by efficiently distributing the workload between the processing units. Using existing resources (GPU and CPU) in an efficient way is a novel approach. The peak performance achieved for the platforms GPU + CPU, GPU + 2CPUs, and GPU + 3CPUs is 10.4 GCUPS, 13.7 GCUPS, and 18.6 GCUPS, respectively (with the query length of 511 amino acid). © 2010 IEEE.

  18. 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.

  19. Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

    KAUST Repository

    Rakia, Tamer

    2016-02-26

    Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non- coherent hybrid FSO/RF systems, employing an adaptive combining scheme. Specifically, we activate the RF link along with the FSO link when FSO link quality is unacceptable, and adaptively set RF transmission power to ensure constant combined signal-to-noise ratio at receiver terminal. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are derived. Numerical examples show that, the hybrid FSO/RF systems with power adaptation achieve considerable outage performance improvement over conventional hybrid FSO/RF systems without power adaptation. © 2015 IEEE.

  20. Adaptive Hybrid Mobile Agent Protocol for Wireless Multihop Internet Access

    Directory of Open Access Journals (Sweden)

    A. Velmurugan

    2006-01-01

    Full Text Available Internet-based Mobile Ad Hoc Networking (MANET is an emerging technology that supports self-organizing mobile networking infrastructures. This is expected to be of great use in commercial applications for the next generation Internet users. A number of technical challenges are faced today due to the heterogeneous, dynamic nature of this hybrid MANET. A new hybrid routing scheme AODV_ALMA is proposed, which act simultaneously combining mobile agents to find path to the gateway to establish connection with Internet host and on-demand distance vector approach to find path in local MANET is one of the unique solution. An adaptive gateway discovery mechanism based on mobile agents making use of pheromone value, pheromone decay time and balance index is used to estimate the path and next hop to the gateway. The mobile nodes automatically configure the address using mobile agents first selecting the gateway and then using the gateway prefix address. The mobile agents are also used to track changes in topology enabling high network connectivity with reduced delay in packet transmission to Internet. The performance tradeoffs and limitations with existing solutions for various mobility conditions are evaluated using simulation."

  1. Passivity-based adaptive hybrid synchronization of a new hyperchaotic system with uncertain parameters.

    Science.gov (United States)

    Zhou, Xiaobing; Fan, Zhangbiao; Zhou, Dongming; Cai, Xiaomei

    2012-01-01

    We investigate the adaptive hybrid synchronization problem for a new hyperchaotic system with uncertain parameters. Based on the passivity theory and the adaptive control theory, corresponding controllers and parameter estimation update laws are proposed to achieve hybrid synchronization between two identical uncertain hyperchaotic systems with different initial values, respectively. Numerical simulation indicates that the presented methods work effectively.

  2. Passivity-Based Adaptive Hybrid Synchronization of a New Hyperchaotic System with Uncertain Parameters

    OpenAIRE

    Xiaobing Zhou; Zhangbiao Fan; Dongming Zhou; Xiaomei Cai

    2012-01-01

    We investigate the adaptive hybrid synchronization problem for a new hyperchaotic system with uncertain parameters. Based on the passivity theory and the adaptive control theory, corresponding controllers and parameter estimation update laws are proposed to achieve hybrid synchronization between two identical uncertain hyperchaotic systems with different initial values, respectively. Numerical simulation indicates that the presented methods work effectively.

  3. Adaptive, Active and Multifunctional Composite and Hybrid Materials Program: Composite and Hybrid Materials ERA

    Science.gov (United States)

    2014-04-01

    16 4.2.4.3 Fabrication and Modeling of Rubber Muscle Actuators ..........17 4.2.4.4 Modeling of Power Response of SMP/SMA...Processing of BMI/Preceramic Polymer Blends .................................28 4.9 Task 9.0 Hybrid Material Processing and Fabrication...electrical stimulus, similar in action to the natural response of the conformation of a bird wing during flight vs. takeoff or landing, a muscle pair

  4. Adaptive visual attention model

    OpenAIRE

    Hügli, Heinz; Bur, Alexandre

    2009-01-01

    Visual attention, defined as the ability of a biological or artificial vision system to rapidly detect potentially relevant parts of a visual scene, provides a general purpose solution for low level feature detection in a vision architecture. Well considered for its universal detection behaviour, the general model of visual attention is suited for any environment but inferior to dedicated feature detectors in more specific environments. The goal of the development presented in this paper is t...

  5. 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...

  6. Specialized hybrid learners resolve Rogers' paradox about the adaptive value of social learning.

    Science.gov (United States)

    Kharratzadeh, Milad; Montrey, Marcel; Metz, Alex; Shultz, Thomas R

    2017-02-07

    Culture is considered an evolutionary adaptation that enhances reproductive fitness. A common explanation is that social learning, the learning mechanism underlying cultural transmission, enhances mean fitness by avoiding the costs of individual learning. This explanation was famously contradicted by Rogers (1988), who used a simple mathematical model to show that cheap social learning can invade a population without raising its mean fitness. He concluded that some crucial factor remained unaccounted for, which would reverse this surprising result. Here we extend this model to include a more complex environment and limited resources, where individuals cannot reliably learn everything about the environment on their own. Under such conditions, cheap social learning evolves and enhances mean fitness, via hybrid learners capable of specializing their individual learning. We then show that while spatial or social constraints hinder the evolution of hybrid learners, a novel social learning strategy, complementary copying, can mitigate these effects.

  7. 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.

  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 ap...

  9. 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.

  10. Hybrid Adaptive Filter development for the minimisation of transient fluctuations superimposed on electrotelluric field recordings mainly by magnetic storms

    Directory of Open Access Journals (Sweden)

    A. Konstantaras

    2006-01-01

    Full Text Available The method of Hybrid Adaptive Filtering (HAF aims to recover the recorded electric field signals from anomalies of magnetotelluric origin induced mainly by magnetic storms. An adaptive filter incorporating neuro-fuzzy technology has been developed to remove any significant distortions from the equivalent magnetic field signal, as retrieved from the original electric field signal by reversing the magnetotelluric method. Testing with further unseen data verifies the reliability of the model and demonstrates the effectiveness of the HAF method.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Ícaro Lins Leitão da Cunha

    2016-04-01

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

  13. Hybrid Multilevel Sparse Reconstruction for a Whole Domain Bioluminescence Tomography Using Adaptive Finite Element

    Directory of Open Access Journals (Sweden)

    Jingjing Yu

    2013-01-01

    Full Text Available Quantitative reconstruction of bioluminescent sources from boundary measurements is a challenging ill-posed inverse problem owing to the high degree of absorption and scattering of light through tissue. We present a hybrid multilevel reconstruction scheme by combining the ability of sparse regularization with the advantage of adaptive finite element method. In view of the characteristics of different discretization levels, two different inversion algorithms are employed on the initial coarse mesh and the succeeding ones to strike a balance between stability and efficiency. Numerical experiment results with a digital mouse model demonstrate that the proposed scheme can accurately localize and quantify source distribution while maintaining reconstruction stability and computational economy. The effectiveness of this hybrid reconstruction scheme is further confirmed with in vivo experiments.

  14. 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…

  15. 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:

  16. 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....

  17. A Muscle Synergy-inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis

    Directory of Open Access Journals (Sweden)

    Naji A Alibeji

    2015-12-01

    Full Text Available Abstract--- Abstract--- A hybrid neuroprosthesis that uses an electric motor-based wearable exoskeleton and functional electrical stimulation (FES has a promising potential to restore walking in persons with paraplegia. A hybrid actuation structure introduces effector redundancy, making its automatic control a challenging task because multiple muscles and additional electric motor need to be coordinated. Inspired by the muscle synergy principle, we designed a low dimensional controller to control multiple effectors: FES of multiple muscles and electric motors. The resulting control system may be less complex and easier to control. To obtain the muscle synergy-inspired low dimensional control, a subject-specific gait model was optimized to compute optimal control signals for the multiple effectors. The optimal control signals were then dimensionally reduced by using principal component analysis to extract synergies. Then, an adaptive feedforward controller with an update law for the synergy activation was designed. In addition, feedback control was used to provide stability and robustness to the control design. The adaptive-feedforward and feedback control structure makes the low dimensional controller more robust to disturbances and variations in the model parameters and may help to compensate for other time-varying phenomena (e.g., muscle fatigue. This is proven by using a Lyapunov stability analysis, which yielded semi-global uniformly ultimately bounded tracking. Computer simulations were performed to test the new controller on a 4 degree of freedom gait model.

  18. 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.

  19. 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.

  20. A Hybrid Adaptive Routing Algorithm for Event-Driven Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Antonio A. F. Loureiro

    2009-09-01

    Full Text Available Routing is a basic function in wireless sensor networks (WSNs. For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption.

  1. A hybrid adaptive routing algorithm for event-driven wireless sensor networks.

    Science.gov (United States)

    Figueiredo, Carlos M S; Nakamura, Eduardo F; Loureiro, Antonio A F

    2009-01-01

    Routing is a basic function in wireless sensor networks (WSNs). For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load) may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption.

  2. NEURAL NETWORKS CONTROL OF THE HYBRID POWER UNIT BASED ON THE METHOD OF ADAPTIVE CRITICS

    Directory of Open Access Journals (Sweden)

    S. Serikov

    2012-01-01

    Full Text Available The formal statement of the optimization problem of hybrid vehicle power unit control is given. Its solving by neural networks method application on the basis of adaptive critic is considered.

  3. 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)...

  4. Adaptive Passivity-Based Control of PEM Fuel Cell/Battery Hybrid Power Source for Stand-Alone Applications

    Directory of Open Access Journals (Sweden)

    KALANTAR, A.

    2010-11-01

    Full Text Available In this paper, a DC hybrid power source composed of PEM fuel cell as main source, Li-ion battery storage as transient power source and their power electronic interfacing is modelled based on Euler-Lagrange framework. Subsequently, adaptive passivity-based controllers are synthesized using the energy shaping and damping injection technique. Local asymptotic stability is insured as well. In addition, the power management system is designed in order to manage power flow between components. Evaluation of the proposed system and simulation of the hybrid system are accomplished using MATLAB/Simulink. Afterwards, linear PI controllers are provided for the purpose of comparison with proposed controllers responses. The results show that the outputs of hybrid system based on adaptive passivity-based controllers have a good tracking response, low overshoot, short settling time and zero steady-state error. The comparison of results demonstrates the robustness of the proposed controllers for reference DC voltage and resistive load changes.

  5. 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

  6. 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....

  7. Hybrid intelligent system for Sale Forecasting using Delphi and adaptive Fuzzy Back-Propagation Neural Networks

    Directory of Open Access Journals (Sweden)

    Attariuas Hicham

    2012-12-01

    Full Text Available ales forecasting is one of the most crucial issues addressed in business. Control and evaluation of future sales still seem concerned both researchers and policy makers and managers of companies. this research propose an intelligent hybrid sales forecasting system Delphi-FCBPN sales forecast based on Delphi Method, fuzzy clustering and Back-propagation (BP Neural Networks with adaptive learning rate. The proposed model is constructed to integrate expert judgments, using Delphi method, in enhancing the model of FCBPN. Winter’s Exponential Smoothing method will be utilized to take the trend effect into consideration. The data for this search come from an industrial company that manufactures packaging. Analyze of results show that the proposed model outperforms other three different forecasting models in MAPE and RMSE measures.

  8. Hybrid Adaptive Ray-Moment Method (HARM2): A highly parallel method for radiation hydrodynamics on adaptive grids

    Science.gov (United States)

    Rosen, A. L.; Krumholz, M. R.; Oishi, J. S.; Lee, A. T.; Klein, R. I.

    2017-02-01

    We present a highly-parallel multi-frequency hybrid radiation hydrodynamics algorithm that combines a spatially-adaptive long characteristics method for the radiation field from point sources with a moment method that handles the diffuse radiation field produced by a volume-filling fluid. Our Hybrid Adaptive Ray-Moment Method (HARM2) operates on patch-based adaptive grids, is compatible with asynchronous time stepping, and works with any moment method. In comparison to previous long characteristics methods, we have greatly improved the parallel performance of the adaptive long-characteristics method by developing a new completely asynchronous and non-blocking communication algorithm. As a result of this improvement, our implementation achieves near-perfect scaling up to O (103) processors on distributed memory machines. We present a series of tests to demonstrate the accuracy and performance of the method.

  9. Hybrid Adaptive Ray-Moment Method (HARM$^2$): A Highly Parallel Method for Radiation Hydrodynamics on Adaptive Grids

    CERN Document Server

    Rosen, Anna L; Oishi, Jeffrey S; Lee, Aaron T; Klein, Richard I

    2016-01-01

    We present a highly-parallel multi-frequency hybrid radiation hydrodynamics algorithm that combines a spatially-adaptive long characteristics method for the radiation field from point sources with a moment method that handles the diffuse radiation field produced by a volume-filling fluid. Our Hybrid Adaptive Ray-Moment Method (HARM$^2$) operates on patch-based adaptive grids, is compatible with asynchronous time stepping, and works with any moment method. In comparison to previous long characteristics methods, we have greatly improved the parallel performance of the adaptive long-characteristics method by developing a new completely asynchronous and non-blocking communication algorithm. As a result of this improvement, our implementation achieves near-perfect scaling up to $\\mathcal{O}(10^3)$ processors on distributed memory machines. We present a series of tests to demonstrate the accuracy and performance of the method.

  10. 基于改进混合卡尔曼滤波器的航空发动机机载自适应模型%Aeroengine on-board adaptive model based on improved hybrid Kalman filter

    Institute of Scientific and Technical Information of China (English)

    陆军; 郭迎清; 张书刚

    2011-01-01

    提出了基于改进混合卡尔曼滤波器的航空发动机机载自适应模型方法,即以机载非线性模型的输出作为分段线性卡尔曼滤波器的稳态基准值,将性能蜕化因子作为该滤波器的增广状态量进行在线估计,并反馈给机载非线性模型使其完成在线更新.同时,根据工作模式切换机制使该模型获得有效输出.通过将该方法应用于某型涡扇发动机进行一系列仿真表明,在全飞行包线内、不同工作状态以及性能蜕化严重的情况下,该模型能够始终与实际发动机相匹配,满足实际应用需求.%A method of establishing aeroengine on-board adaptive model was proposed based on improved hybrid Kalman filter(IHKF).The output of nonlinear on-board engine model(NOBEM) was regarded as the steady-state basic model of piecewise linear Kalman filter(PWKF),while its performance deterioration factor was regarded as the augmented state vector of PWKF for on-line estimation,and fed back to NOBEM for on-line updating.In addition,the switching logic of work mode was established,which could make the IHKF work better.By applying this method to a turbofan engine,a series of simulation results show that the model can always match the actual engine in the whole flight envelope,under different engine states and severe performance deterioration,thus meeting the needs of practical applications.

  11. 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...

  12. Hybrid Sterility over Tens of Meters Between Ecotypes Adapted to Serpentine and Non-Serpentine Soils

    Science.gov (United States)

    Leonie Moyle; Levine Mia; Stanton Maureen; Jessica Wright

    2012-01-01

    The development of hybrid sterility is an important step in the process of speciation, however the role of adaptive evolution in triggering these postzygotic barriers is poorly understood. We show that, in the California endemic plant Collinsia sparsiflora ecotypic adaptation to two distinct soil types is associated with the expression of...

  13. Flexible Microgrid Power Quality Enhancement Using Adaptive Hybrid Voltage and Current Controller

    DEFF Research Database (Denmark)

    He, Jinwei; Li, Yun Wei; Blaabjerg, Frede

    2014-01-01

    To accomplish superior harmonic compensation performance using distributed generation (DG) unit power electronics interfaces, an adaptive hybrid voltage and current controlled method (HCM) is proposed in this paper. It shows that the proposed adaptive HCM can reduce the numbers of low-pass/bandpa...

  14. 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.

  15. 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.

  16. Joint Adaptive Modulation and Combining for Hybrid FSO/RF Systems

    KAUST Repository

    Rakia, Tamer

    2015-11-12

    In this paper, we present and analyze a new transmission scheme for hybrid FSO/RF communication system based on joint adaptive modulation and adaptive combining. Specifically, the data rate on the FSO link is adjusted in discrete manner according to the FSO link\\'s instantaneous received signal-to-noise-ratio (SNR). If the FSO link\\'s quality is too poor to maintain the target bit-error-rate, the system activates the RF link along with the FSO link. When the RF link is activated, simultaneous transmission of the same modulated data takes place on both links, where the received signals from both links are combined using maximal ratio combining scheme. In this case, the data rate of the system is adjusted according to the instantaneous combined SNRs. Novel analytical expression for the cumulative distribution function (CDF) of the received SNR for the proposed adaptive hybrid system is obtained. This CDF expression is used to study the spectral and outage performances of the proposed adaptive hybrid FSO/RF system. Numerical examples are presented to compare the performance of the proposed adaptive hybrid FSO/RF system with that of switch-over hybrid FSO/RF and FSO-only systems employing the same adaptive modulation schemes. © 2015 IEEE.

  17. 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.

  18. 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...

  19. 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.

  20. A hybrid method for optimization of the adaptive Goldstein filter

    Science.gov (United States)

    Jiang, Mi; Ding, Xiaoli; Tian, Xin; Malhotra, Rakesh; Kong, Weixue

    2014-12-01

    The Goldstein filter is a well-known filter for interferometric filtering in the frequency domain. The main parameter of this filter, alpha, is set as a power of the filtering function. Depending on it, considered areas are strongly or weakly filtered. Several variants have been developed to adaptively determine alpha using different indicators such as the coherence, and phase standard deviation. The common objective of these methods is to prevent areas with low noise from being over filtered while simultaneously allowing stronger filtering over areas with high noise. However, the estimators of these indicators are biased in the real world and the optimal model to accurately determine the functional relationship between the indicators and alpha is also not clear. As a result, the filter always under- or over-filters and is rarely correct. The study presented in this paper aims to achieve accurate alpha estimation by correcting the biased estimator using homogeneous pixel selection and bootstrapping algorithms, and by developing an optimal nonlinear model to determine alpha. In addition, an iteration is also merged into the filtering procedure to suppress the high noise over incoherent areas. The experimental results from synthetic and real data show that the new filter works well under a variety of conditions and offers better and more reliable performance when compared to existing approaches.

  1. Adapted nested force-gradient integrators for the Schwinger model

    CERN Document Server

    Shcherbakov, Dmitry; Günther, Michael; Finkenrath, Jacob; Knechtli, Francesco; Peardon, Michael

    2016-01-01

    We study a novel class of numerical integrators, the adapted nested force-gradient schemes, used within the molecular dynamics step of the Hybrid Monte Carlo (HMC) algorithm. We test these methods in the Schwinger model on the lattice, a well known benchmark problem. We derive the analytical basis of nested force-gradient type methods and demonstrate the advantage of the proposed approach, namely reduced computational costs compared with other numerical integration schemes in HMC.

  2. 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

  3. 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.

  4. 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.

  5. 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.)

  6. 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.

  7. 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...

  8. Adaptive and Reliable Control Algorithm for Hybrid System Architecture

    Directory of Open Access Journals (Sweden)

    Osama Abdel Hakeem Abdel Sattar

    2012-01-01

    Full Text Available A stand-alone system is defined as an autonomous system that supplies electricity without being connected to the electric grid. Hybrid systems combined renewable energy source, that are never depleted (such solar (photovoltaic (PV, wind, hydroelectric, etc. , With other sources of energy, like Diesel. If these hybrid systems are optimally designed, they can be more cost effective and reliable than single systems. However, the design of hybrid systems is complex because of the uncertain renewable energy supplies, load demands and the non-linear characteristics of some components, so the design problem cannot be solved easily by classical optimisation methods. The use of heuristic techniques, such as the genetic algorithms, can give better results than classical methods. This paper presents to a hybrid system control algorithm and also dispatches strategy design in which wind is the primary energy resource with photovoltaic cells. The dimension of the design (max. load is 2000 kW and the sources is implemented as flow 1500 kw from wind, 500 kw from solar and diesel 2000 kw. The main task of the preposed algorithm is to take full advantage of the wind energy and solar energy when it is available and to minimize diesel fuel consumption.

  9. 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.

  10. Constrained Optimization Based on Hybrid Evolutionary Algorithm and Adaptive Constraint-Handling Technique

    DEFF Research Database (Denmark)

    Wang, Yong; Cai, Zixing; Zhou, Yuren

    2009-01-01

    A novel approach to deal with numerical and engineering constrained optimization problems, which incorporates a hybrid evolutionary algorithm and an adaptive constraint-handling technique, is presented in this paper. The hybrid evolutionary algorithm simultaneously uses simplex crossover and two...... mutation operators to generate the offspring population. Additionally, the adaptive constraint-handling technique consists of three main situations. In detail, at each situation, one constraint-handling mechanism is designed based on current population state. Experiments on 13 benchmark test functions...... and four well-known constrained design problems verify the effectiveness and efficiency of the proposed method. The experimental results show that integrating the hybrid evolutionary algorithm with the adaptive constraint-handling technique is beneficial, and the proposed method achieves competitive...

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Learning and Adaptive Hybrid Systems for Nonlinear Control

    Science.gov (United States)

    1991-05-01

    6 2.1.1 Single Layer Networks 8 Perceptrons 8 Samuel’s Checker Player 10 ADALINE and MADALINE 12 2.1.2 Multilayer Networks 13 Hebbian Learning 13...was Widrow’s ADALINE and MADALINE [Wid89]. He developed a type of adaptive filter which is still in widespread use today in such items as high speed...time step, and used it for pattern recognition. This "Adaptive Linear Neuron" ( ADALINE ) [Wid89] was then built in actual hardware, where weights were

  16. 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)

  17. 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,

  18. Heterosis in locally adapted sorghum genotypes and potential of hybrids for increased productivity in contrasting environments in Ethiopia

    Institute of Scientific and Technical Information of China (English)

    Taye T. Mindaye; Emma S. Mace; Ian D. Godwin; David R. Jordan

    2016-01-01

    Increased productivity in sorghum has been achieved in the developed world using hybrids. Despite their yield advantage, introduced hybrids have not been adopted in Ethiopia due to the lack of adaptive traits, their short plant stature and small grain size. This study was conducted to investigate hybrid performance and the magnitude of heterosis of locally adapted genotypes in addition to introduced hybrids in three contrasting environments in Ethiopia. In total, 139 hybrids, derived from introduced seed parents crossed with locally adapted genotypes and introduced R lines, were evaluated. Overall, the hybrids matured earlier than the adapted parents, but had higher grain yield, plant height, grain number and grain weight in all environments. The lowland adapted hybrids displayed a mean better parent heterosis (BPH) of 19%, equating to 1160 kg ha−1 and a 29%mean increase in grain yield, in addition to increased plant height and grain weight, in comparison to the hybrids derived from the introduced R lines. The mean BPH for grain yield for the highland adapted hybrids was 16%in the highland and 52%in the intermediate environment equating to 698 kg ha−1 and 2031 kg ha−1, respectively, in addition to increased grain weight. The magnitude of heterosis observed for each hybrid group was related to the genetic distance between the parental lines. The majority of hybrids also showed superiority over the standard check varieties. In general, hybrids from locally adapted genotypes were superior in grain yield, plant height and grain weight compared to the high parents and introduced hybrids indicating the potential for hybrids to increase productivity while addressing farmers' required traits.

  19. 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.

  20. 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

  1. Quadratic adaptive algorithm for solving cardiac action potential models.

    Science.gov (United States)

    Chen, Min-Hung; Chen, Po-Yuan; Luo, Ching-Hsing

    2016-10-01

    An adaptive integration method is proposed for computing cardiac action potential models accurately and efficiently. Time steps are adaptively chosen by solving a quadratic formula involving the first and second derivatives of the membrane action potential. To improve the numerical accuracy, we devise an extremum-locator (el) function to predict the local extremum when approaching the peak amplitude of the action potential. In addition, the time step restriction (tsr) technique is designed to limit the increase in time steps, and thus prevent the membrane potential from changing abruptly. The performance of the proposed method is tested using the Luo-Rudy phase 1 (LR1), dynamic (LR2), and human O'Hara-Rudy dynamic (ORd) ventricular action potential models, and the Courtemanche atrial model incorporating a Markov sodium channel model. Numerical experiments demonstrate that the action potential generated using the proposed method is more accurate than that using the traditional Hybrid method, especially near the peak region. The traditional Hybrid method may choose large time steps near to the peak region, and sometimes causes the action potential to become distorted. In contrast, the proposed new method chooses very fine time steps in the peak region, but large time steps in the smooth region, and the profiles are smoother and closer to the reference solution. In the test on the stiff Markov ionic channel model, the Hybrid blows up if the allowable time step is set to be greater than 0.1ms. In contrast, our method can adjust the time step size automatically, and is stable. Overall, the proposed method is more accurate than and as efficient as the traditional Hybrid method, especially for the human ORd model. The proposed method shows improvement for action potentials with a non-smooth morphology, and it needs further investigation to determine whether the method is helpful during propagation of the action potential. Copyright © 2016 Elsevier Ltd. All rights

  2. 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.

  3. 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.

  4. Context-Aware Adaptive Hybrid Semantic Relatedness in Biomedical Science

    Science.gov (United States)

    Emadzadeh, Ehsan

    Text mining of biomedical literature and clinical notes is a very active field of research in biomedical science. Semantic analysis is one of the core modules for different Natural Language Processing (NLP) solutions. Methods for calculating semantic relatedness of two concepts can be very useful in solutions solving different problems such as relationship extraction, ontology creation and question / answering [1--6]. Several techniques exist in calculating semantic relatedness of two concepts. These techniques utilize different knowledge sources and corpora. So far, researchers attempted to find the best hybrid method for each domain by combining semantic relatedness techniques and data sources manually. In this work, attempts were made to eliminate the needs for manually combining semantic relatedness methods targeting any new contexts or resources through proposing an automated method, which attempted to find the best combination of semantic relatedness techniques and resources to achieve the best semantic relatedness score in every context. This may help the research community find the best hybrid method for each context considering the available algorithms and resources.

  5. 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

  6. A hybrid adaptive large neighborhood search algorithm applied to a lot-sizing problem

    DEFF Research Database (Denmark)

    Muller, Laurent Flindt; Spoorendonk, Simon

    This paper presents a hybrid of a general heuristic framework that has been successfully applied to vehicle routing problems and a general purpose MIP solver. The framework uses local search and an adaptive procedure which choses between a set of large neighborhoods to be searched. A mixed integer...

  7. GA and Lyapunov theory-based hybrid adaptive fuzzy controller for non-linear systems

    Science.gov (United States)

    Roy, Ananya; Das Sharma, Kaushik

    2015-02-01

    In this present article, a new hybrid methodology for designing stable adaptive fuzzy logic controllers (AFLCs) for a class of non-linear system is proposed. The proposed design strategy exploits the features of genetic algorithm (GA)-based stochastic evolutionary global search technique and Lyapunov theory-based local adaptation scheme. The objective is to develop a methodology for designing AFLCs with optimised free parameters and guaranteed closed-loop stability. Simultaneously, the proposed method introduces automation in the design process. The stand-alone Lyapunov theory-based design, GA-based design and proposed hybrid GA-Lyapunov design methodologies are implemented for two benchmark non-linear plants in simulation case studies with different reference signals and one experimental case study. The results demonstrate that the hybrid design methodology outperforms the other control strategies on the whole.

  8. OMEGA: The operational multiscale environment model with grid adaptivity

    Energy Technology Data Exchange (ETDEWEB)

    Bacon, D.P.

    1995-07-01

    This review talk describes the OMEGA code, used for weather simulation and the modeling of aerosol transport through the atmosphere. Omega employs a 3D mesh of wedge shaped elements (triangles when viewed from above) that adapt with time. Because wedges are laid out in layers of triangular elements, the scheme can utilize structured storage and differencing techniques along the elevation coordinate, and is thus a hybrid of structured and unstructured methods. The utility of adaptive gridding in this moded, near geographic features such as coastlines, where material properties change discontinuously, is illustrated. Temporal adaptivity was used additionally to track moving internal fronts, such as clouds of aerosol contaminants. The author also discusses limitations specific to this problem, including manipulation of huge data bases and fixed turn-around times. In practice, the latter requires a carefully tuned optimization between accuracy and computation speed.

  9. Adaptive Swarm Formation Control for Hybrid Ground and Aerial Assets

    OpenAIRE

    Barnes, Laura; Garcia, Richard; Fields, Mary Anne; Valavanis, Kimon

    2010-01-01

    In this work, a methodology for control and coordination of UAVs and UGVs has been presented. UAVs and UGVs were integrated into a single team and were able to adapt their formation accordingly. Potential field functions together with limiting functions can be successfully utilized to control UGV and UAV swarm formation, obstacle avoidance and the overall swarm movement. A single UAV was also successfully used to pull the UGV swarm into formation. These formations can move as a un...

  10. A diversified portfolio model of adaptability.

    Science.gov (United States)

    Chandra, Siddharth; Leong, Frederick T L

    2016-12-01

    A new model of adaptability, the diversified portfolio model (DPM) of adaptability, is introduced. In the 1950s, Markowitz developed the financial portfolio model by demonstrating that investors could optimize the ratio of risk and return on their portfolios through risk diversification. The DPM integrates attractive features of a variety of models of adaptability, including Linville's self-complexity model, the risk and resilience model, and Bandura's social cognitive theory. The DPM draws on the concept of portfolio diversification, positing that diversified investment in multiple life experiences, life roles, and relationships promotes positive adaptation to life's challenges. The DPM provides a new integrative model of adaptability across the biopsychosocial levels of functioning. More importantly, the DPM addresses a gap in the literature by illuminating the antecedents of adaptive processes studied in a broad array of psychological models. The DPM is described in relation to the biopsychosocial model and propositions are offered regarding its utility in increasing adaptiveness. Recommendations for future research are also offered. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  11. Unobtrusive user modeling for adaptive hypermedia

    NARCIS (Netherlands)

    Holz, H.J.; Hofmann, K.; Reed, C.; Uchyigit, G.; Ma, M.Y.

    2008-01-01

    We propose a technique for user modeling in Adaptive Hypermedia (AH) that is unobtrusive at both the level of observable behavior and that of cognition. Unobtrusive user modeling is complementary to transparent user modeling. Unobtrusive user modeling induces user models appropriate for Educational

  12. [The model of adaptive primary image processing].

    Science.gov (United States)

    Dudkin, K N; Mironov, S V; Dudkin, A K; Chikhman, V N

    1998-07-01

    A computer model of adaptive segmentation of the 2D visual objects was developed. Primary image descriptions are realised via spatial frequency filters and feature detectors performing as self-organised mechanisms. Simulation of the control processes related to attention, lateral, frequency-selective and cross-orientation inhibition, determines the adaptive image processing.

  13. Multiple models adaptive feedforward decoupling controller

    Institute of Scientific and Technical Information of China (English)

    Wang Xin; Li Shaoyuan; Wang Zhongjie

    2005-01-01

    When the parameters of the system change abruptly, a new multivariable adaptive feedforward decoupling controller using multiple models is presented to improve the transient response. The system models are composed of multiple fixed models, one free-running adaptive model and one re-initialized adaptive model. The fixed models are used to provide initial control to the process. The re-initialized adaptive model can be reinitialized as the selected model to improve the adaptation speed. The free-running adaptive controller is added to guarantee the overall system stability. At each instant, the best system model is selected according to the switching index and the corresponding controller is designed. During the controller design, the interaction is viewed as the measurable disturbance and eliminated by the choice of the weighting polynomial matrix. It not only eliminates the steady-state error but also decouples the system dynamically. The global convergence is obtained and several simulation examples are presented to illustrate the effectiveness of the proposed controller.

  14. An adaptive metamaterial beam with hybrid shunting circuits for extremely broadband control of flexural waves

    Science.gov (United States)

    Chen, Y. Y.; Hu, G. K.; Huang, G. L.

    2016-10-01

    A great deal of research has been devoted to controlling the dynamic behaviors of phononic crystals and metamaterials by directly tuning the frequency regions and/or widths of their inherent band gaps. Here, we report a new class of adaptive metamaterial beams with hybrid shunting circuits to realize super broadband Lamb-wave band gaps at an extreme subwavelength scale. The proposed metamaterial is made of a homogeneous host beam on which tunable local resonators consisting of hybrid shunted piezoelectric stacks with proof masses are attached. The hybrid shunting circuits are composed of negative-capacitance and negative-inductance elements connected in series or in parallel in order to tune the desired frequency-dependent stiffness. It is shown theoretically and numerically that by properly modifying the shunting impedance, the adaptive mechanical mechanism within the tunable resonator can produce high-pass and low-pass wave filtering capabilities for the zeroth-order anti-symmetric Lamb-wave modes. These unique behaviors are due to the hybrid effects from the negative-capacitance and negative-inductance circuit elements. Such a system opens up important perspectives for the development of adaptive vibration or wave-attenuation devices for broadband frequency applications.

  15. 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.

  16. Vegetative and adaptive traits predict different outcomes for restoration using hybrids

    Directory of Open Access Journals (Sweden)

    Philip Crystal

    2016-11-01

    Full Text Available Abstract – Hybridization has been implicated as a driver of speciation, extinction, and invasiveness, but can also provide resistant breeding stock following epidemics. However, evaluating the appropriateness of hybrids for use in restoration programs is difficult. Past the F1 generation, the proportion of a progenitor’s genome can vary widely, as can the combinations of parental genomes. Detailed genetic analysis can reveal this information, but cannot expose phenotypic alterations due to heterosis, transgressive traits, or changes in metabolism or development. In addition, because evolution is often driven by extreme individuals, decisions based on phenotypic averages of hybrid classes may have unintended results. We demonstrate a strategy to evaluate hybrids for use in restoration by visualizing hybrid phenotypes across selected groups of traits relative to both progenitor species. Specifically, we used discriminant analysis to differentiate among butternut (Juglans cinerea L., black walnut (J. nigra L., and Japanese walnut (J. ailantifolia Carr. var. cordiformis using vegetative characters and then with functional adaptive traits associated with seedling performance. When projected onto the progenitor trait space, naturally occurring hybrids (J. ×bixbyi Rehd. between butternut and Japanese walnut showed introgression towards Japanese walnut at vegetative characters but exhibited a hybrid swarm at functional traits. Both results indicate that hybrids have morphological and ecological phenotypes that distinguish them from butternut, demonstrating a lack of ecological equivalency that should not be carried into restoration breeding efforts. Despite these discrepancies, some hybrids were projected into the space occupied by butternut seedlings’ 95% confidence ellipse, signifying that some hybrids were similar at the measured traits. Determining how to consistently identify these individuals is imperative for future breeding and species

  17. Yield stability and adaptability of maize hybrids based on GGE biplot analysis characteristics

    Directory of Open Access Journals (Sweden)

    Marcio Balestre

    2009-01-01

    Full Text Available The objective of this study was to evaluate stability and adaptability of the grain yield of commercial intervarietalmaize hybrids by the GGE (Genotype and Genotype by Environment Interaction biplot and AMMI (Additive Main Effects andMultiplicative Interaction analyses. Two intervarietal hybrids (BIO 2 and BIO4 were evaluated together with single, doubleand three-way cross hybrids. The performance of the intervarietal hybrid BIO 4 was superior to all double and three-waycross hybrids and outmatched the single-cross hybrids by 43%. In terms of stability, BIO 2 was more stable than BIO4, whichis desirable, but biological stability, which is not necessarily desirable, was also observed, since the yield was below theenvironmental mean. The graphical GGE biplot analysis was superior to the AMMI1 since a greater portion of the sum ofsquares of GE and G+GE was captured and the predictive accuracy was higher. On the other hand, the AMMI2 graphoutperformed the GGE biplot in predictive accuracy and explanation of G + GE and GE, although the difference in accuracywas smaller than between GGE2 and AMMI1.

  18. 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.

  19. Assessing the adaptive capacity of maize hybrids to climate change in an irrigated district of Southern Italy

    Science.gov (United States)

    Monaco, Eugenia; Bonfante, Antonello; De Mascellis, Roberto; Alfieri, Silvia Maria; Menenti, Massimo; De Lorenzi, Francesca

    2013-04-01

    Climate change will cause significant changes in water distribution and availability; as a consequence the water resources in some areas (like Mediterranean regions) will be limiting factors to the cultivation of some species, included cereals. So the perspective of climate change requires an analysis of the adaptation possibilities of food and fiber species currently cultivated. A powerful tool for adaptation is the relevant intra-specific biodiversity of crops. The knowledge, for different crop cultivars, of the responses to different environmental conditions (e.g. yield response functions to water regime) can be a tool to identify adaptation options to future climate. Moreover, simulation models of water flow in the soil-plant-atmosphere system can be coupled with future climate scenarios to predict the soil water regime also accounting for different irrigation scheduling options. In this work the adaptive capacity of maize hybrids (Zea mays L.) was evaluated in an irrigated district of Southern Italy (the "Destra Sele" plain, an area of about 18.000 ha), where maize is extensively grown for water buffalo feeding. Horticultural crops (tomato, fennel, artichoke) are grown, as well. The methodology applied is based on two complementary elements: - a database on climatic requirements of 30 maize hybrids: the yield response functions to water availability were determined from experimental data derived both from scientific literature and from field trials carried out by ISAFOM-CNR. These functions were applied to describe the behaviour of the hybrids with respect to the relative evapotranspiration deficit; - the simulation performed by the agro-hydrological model SWAP (soil-water-plant and atmosphere), to determine the future soil water regime at landscape scale. Two climate scenarios were studied: "past" (1961-1990) and "future" (2021-2050). Future climate scenarios were generated within the Italian National Project AGROSCENARI. Climate scenarios at low spatial

  20. Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation

    Directory of Open Access Journals (Sweden)

    Yechen Qin

    2015-01-01

    Full Text Available A new road estimation based suspension hybrid control strategy is proposed. Its aim is to adaptively change control gains to improve both ride comfort and road handling with the constraint of rattle space. To achieve this, analytical expressions for ride comfort, road handling, and rattle space with respect to road input are derived based on the hybrid control, and the problem is transformed into a MOOP (Multiobjective Optimization Problem and has been solved by NSGA-II (Nondominated Sorting Genetic Algorithm-II. A new road estimation and classification method, which is based on ANFIS (Adaptive Neurofuzzy Inference System and wavelet transforms, is then presented as a means of detecting the road profile level, and a Kalman filter is designed for observing unknown states. The results of simulations conducted with random road excitation show that the efficiency of the proposed control strategy compares favourably to that of a passive system.

  1. 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.

  2. A new multi-tier adaptive military MANET security protocol using hybrid cryptography and signcryption

    OpenAIRE

    YAVUZ, Attila A.; ALAGÖZ, Fatih; Anarim, Emin

    2014-01-01

    Mobile Ad-hoc NETworks (MANETs) are expected to play an important role in tactical military networks by providing infrastructureless communication. However, maintaining secure and instant information sharing is a difficult task especially for highly dynamic military MANETs. To address this requirement, we propose a new multi-tier adaptive military MANET security protocol using hybrid cryptography and signcryption. In our protocol, we bring novelties to secure military MANET communic...

  3. Adaptive kanban control mechanism for a single-stage hybrid system

    Science.gov (United States)

    Korugan, Aybek; Gupta, Surendra M.

    2002-02-01

    In this paper, we consider a hybrid manufacturing system with two discrete production lines. Here the output of either production line can satisfy the demand for the same type of product without any penalties. The interarrival times for demand occurrences and service completions are exponentially distributed i.i.d. variables. In order to control this type of manufacturing system we suggest a single stage pull type control mechanism with adaptive kanbans and state independent routing of the production information.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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...

  10. 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.

  11. A new approach to adaptive data models

    Directory of Open Access Journals (Sweden)

    Ion LUNGU

    2016-12-01

    Full Text Available Over the last decade, there has been a substantial increase in the volume and complexity of data we collect, store and process. We are now aware of the increasing demand for real time data processing in every continuous business process that evolves within the organization. We witness a shift from a traditional static data approach to a more adaptive model approach. This article aims to extend understanding in the field of data models used in information systems by examining how an adaptive data model approach for managing business processes can help organizations accommodate on the fly and build dynamic capabilities to react in a dynamic environment.

  12. 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)

  13. Graphical Models and Computerized Adaptive Testing.

    Science.gov (United States)

    Mislevy, Robert J.; Almond, Russell G.

    This paper synthesizes ideas from the fields of graphical modeling and education testing, particularly item response theory (IRT) applied to computerized adaptive testing (CAT). Graphical modeling can offer IRT a language for describing multifaceted skills and knowledge, and disentangling evidence from complex performances. IRT-CAT can offer…

  14. G/SPLINES: A hybrid of Friedman's Multivariate Adaptive Regression Splines (MARS) algorithm with Holland's genetic algorithm

    Science.gov (United States)

    Rogers, David

    1991-01-01

    G/SPLINES are a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least squares computations, and allows significantly larger problems to be considered.

  15. 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)

  16. 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.

  17. 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.

  18. Hybrid Self-Adaptive Algorithm for Community Detection in Complex Networks

    Directory of Open Access Journals (Sweden)

    Bin Xu

    2015-01-01

    Full Text Available The study of community detection algorithms in complex networks has been very active in the past several years. In this paper, a Hybrid Self-adaptive Community Detection Algorithm (HSCDA based on modularity is put forward first. In HSCDA, three different crossover and two different mutation operators for community detection are designed and then combined to form a strategy pool, in which the strategies will be selected probabilistically based on statistical self-adaptive learning framework. Then, by adopting the best evolving strategy in HSCDA, a Multiobjective Community Detection Algorithm (MCDA based on kernel k-means (KKM and ratio cut (RC objective functions is proposed which efficiently make use of recommendation of strategy by statistical self-adaptive learning framework, thus assisting the process of community detection. Experimental results on artificial and real networks show that the proposed algorithms achieve a better performance compared with similar state-of-the-art approaches.

  19. Is Hybridization a Source of Adaptive Venom Variation in Rattlesnakes? A Test, Using a Crotalus scutulatus × viridis Hybrid Zone in Southwestern New Mexico.

    Science.gov (United States)

    Zancolli, Giulia; Baker, Timothy G; Barlow, Axel; Bradley, Rebecca K; Calvete, Juan J; Carter, Kimberley C; de Jager, Kaylah; Owens, John Benjamin; Price, Jenny Forrester; Sanz, Libia; Scholes-Higham, Amy; Shier, Liam; Wood, Liam; Wüster, Catharine E; Wüster, Wolfgang

    2016-06-16

    Venomous snakes often display extensive variation in venom composition both between and within species. However, the mechanisms underlying the distribution of different toxins and venom types among populations and taxa remain insufficiently known. Rattlesnakes (Crotalus, Sistrurus) display extreme inter- and intraspecific variation in venom composition, centered particularly on the presence or absence of presynaptically neurotoxic phospholipases A₂ such as Mojave toxin (MTX). Interspecific hybridization has been invoked as a mechanism to explain the distribution of these toxins across rattlesnakes, with the implicit assumption that they are adaptively advantageous. Here, we test the potential of adaptive hybridization as a mechanism for venom evolution by assessing the distribution of genes encoding the acidic and basic subunits of Mojave toxin across a hybrid zone between MTX-positive Crotalus scutulatus and MTX-negative C. viridis in southwestern New Mexico, USA. Analyses of morphology, mitochondrial and single copy-nuclear genes document extensive admixture within a narrow hybrid zone. The genes encoding the two MTX subunits are strictly linked, and found in most hybrids and backcrossed individuals, but not in C. viridis away from the hybrid zone. Presence of the genes is invariably associated with presence of the corresponding toxin in the venom. We conclude that introgression of highly lethal neurotoxins through hybridization is not necessarily favored by natural selection in rattlesnakes, and that even extensive hybridization may not lead to introgression of these genes into another species.

  20. Is Hybridization a Source of Adaptive Venom Variation in Rattlesnakes? A Test, Using a Crotalus scutulatus × viridis Hybrid Zone in Southwestern New Mexico

    Directory of Open Access Journals (Sweden)

    Giulia Zancolli

    2016-06-01

    Full Text Available Venomous snakes often display extensive variation in venom composition both between and within species. However, the mechanisms underlying the distribution of different toxins and venom types among populations and taxa remain insufficiently known. Rattlesnakes (Crotalus, Sistrurus display extreme inter- and intraspecific variation in venom composition, centered particularly on the presence or absence of presynaptically neurotoxic phospholipases A2 such as Mojave toxin (MTX. Interspecific hybridization has been invoked as a mechanism to explain the distribution of these toxins across rattlesnakes, with the implicit assumption that they are adaptively advantageous. Here, we test the potential of adaptive hybridization as a mechanism for venom evolution by assessing the distribution of genes encoding the acidic and basic subunits of Mojave toxin across a hybrid zone between MTX-positive Crotalus scutulatus and MTX-negative C. viridis in southwestern New Mexico, USA. Analyses of morphology, mitochondrial and single copy-nuclear genes document extensive admixture within a narrow hybrid zone. The genes encoding the two MTX subunits are strictly linked, and found in most hybrids and backcrossed individuals, but not in C. viridis away from the hybrid zone. Presence of the genes is invariably associated with presence of the corresponding toxin in the venom. We conclude that introgression of highly lethal neurotoxins through hybridization is not necessarily favored by natural selection in rattlesnakes, and that even extensive hybridization may not lead to introgression of these genes into another species.

  1. Hybrid Adaptive Intrusion Prevention%自适应混合入侵防御

    Institute of Scientific and Technical Information of China (English)

    乔佩利; 韩伟

    2011-01-01

    This paper proposed a model of Intrusion Prevent System, which has the adaptive ability and apply a hybrid approach to host security that prevents binary code injection attacks. It incorporates three major components: an anomaly-based classifier, a signature-based filtering scheme, and a supervision framework that employs Instruction Set Randomization ( ISR ). ISR can precisely identify the injected code, the classifier and the filter via a learning mechanism based on this feedback can be tuned. Capturing the injected code allows FLIPS to construct signatures for zero-day exploits. Experimental results show that the model can discard input that is anomalous matches or malicious input, protecting the application from attack effectively.%提出一个应用混合的方法来阻止破坏主机安全的二进制代码注入式攻击并具有自适应能力的入侵防御系统模型(Feedback Leaming IPS,FLIPS).它包括三个主要组成部分:基于异常的分类器,基于签名的过滤系统,和采用指令集随机化(Instruction Set Randomization,ISR)的监管框架.ISR可以准确识别注入的代码,以这种反馈为基础对分类器和过滤器进行调整,并允许FLIPS对捕捉到的注入代码构建零日攻击签名.经试验表明,该模型能够丢弃那些匹配异常或已知的恶意输入,从而有效地保护应用程序免受攻击.

  2. Intelligent CAD Methodology Research of Adaptive Modeling

    Institute of Scientific and Technical Information of China (English)

    ZHANG Weibo; LI Jun; YAN Jianrong

    2006-01-01

    The key to carry out ICAD technology is to establish the knowledge-based and wide rang of domains-covered product model. This paper put out a knowledge-based methodology of adaptive modeling. It is under the Ontology mind, using the Object-Oriented technology and being a knowledge-based model framework. It involves the diverse domains in product design and realizes the multi-domain modeling, embedding the relative information including standards, regulars and expert experience. To test the feasibility of the methodology, the research bonds of the automotive diaphragm spring clutch design and an adaptive clutch design model is established, using the knowledge-based modeling language-AML.

  3. Hybridization of Adaptive Differential Evolution with an Expensive Local Search Method

    Directory of Open Access Journals (Sweden)

    Rashida Adeeb Khanum

    2016-01-01

    Full Text Available Differential evolution (DE is an effective and efficient heuristic for global optimization problems. However, it faces difficulty in exploiting the local region around the approximate solution. To handle this issue, local search (LS techniques could be hybridized with DE to improve its local search capability. In this work, we hybridize an updated version of DE, adaptive differential evolution with optional external archive (JADE with an expensive LS method, Broydon-Fletcher-Goldfarb-Shano (BFGS for solving continuous unconstrained global optimization problems. The new hybrid algorithm is denoted by DEELS. To validate the performance of DEELS, we carried out extensive experiments on well known test problems suits, CEC2005 and CEC2010. The experimental results, in terms of function error values, success rate, and some other statistics, are compared with some of the state-of-the-art algorithms, self-adaptive control parameters in differential evolution (jDE, sequential DE enhanced by neighborhood search for large-scale global optimization (SDENS, and differential ant-stigmergy algorithm (DASA. These comparisons reveal that DEELS outperforms jDE and SDENS except DASA on the majority of test instances.

  4. Convergent adaptation to a marginal habitat by homoploid hybrids and polyploid ecads in the seaweed genus Fucus

    Science.gov (United States)

    Coyer, James A; Hoarau, Galice; Pearson, Gareth A; Serrão, Ester A; Stam, Wytze T; Olsen, Jeanine L

    2006-01-01

    Hybridization and polyploidy are two major sources of genetic variability that can lead to adaptation in new habitats. Most species of the brown algal genus Fucus are found along wave-swept rocky shores of the Northern Hemisphere, but some species have adapted to brackish and salt marsh habitats. Using five microsatellite loci and mtDNA RFLP, we characterize two populations of morphologically similar, muscoides-like Fucus inhabiting salt marshes in Iceland and Ireland. The Icelandic genotypes were consistent with Fucus vesiculosus×Fucus spiralis F1 hybrids with asymmetrical hybridization, whereas the Irish ones consisted primarily of polyploid F. vesiculosus. PMID:17148415

  5. 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....

  6. Outage Analysis of Practical FSO/RF Hybrid System With Adaptive Combining

    KAUST Repository

    Rakia, Tamer

    2015-08-01

    Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless transmission. We present and analyze a transmission scheme for the hybrid FSO/RF communication system based on adaptive combining. Specifically, only FSO link is active as long as the instantaneous signal-to-noise ratio (SNR) at the FSO receiver is above a certain threshold level. When it falls below this threshold level, the RF link is activated along with the FSO link and the signals from the two links are combined at the receiver using a dual-branch maximal ratio combiner. Novel analytical expression for the cumulative distribution function (CDF) of the received SNR for the proposed hybrid system is obtained. This CDF expression is used to study the system outage performance. Numerical examples are presented to compare the outage performance of the proposed hybrid FSO/RF system with that of the FSO-only and RF-only systems. © 1997-2012 IEEE.

  7. Adaptive regression for modeling nonlinear relationships

    CERN Document Server

    Knafl, George J

    2016-01-01

    This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of outcome variables. Such nonlinear dependence is often not considered in applied research, yet nonlinear relationships are common and so need to be addressed. A standard linear analysis can produce misleading conclusions, while a nonlinear analysis can provide novel insights into data, not otherwise possible. A variety of examples of the benefits of modeling nonlinear relationships are presented throughout the book. Methods are covered using what are called fractional polynomials based on real-valued power transformations of primary predictor variables combined with model selection based on likelihood cross-validation. The book covers how to formulate and conduct such adaptive fractional polynomial modeling in the s...

  8. 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.

  9. Parameter estimation for chaotic systems using a hybrid adaptive cuckoo search with simulated annealing algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Sheng, Zheng, E-mail: 19994035@sina.com [College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101 (China); Wang, Jun; Zhou, Bihua [National Defense Key Laboratory on Lightning Protection and Electromagnetic Camouflage, PLA University of Science and Technology, Nanjing 210007 (China); Zhou, Shudao [College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101 (China); Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044 (China)

    2014-03-15

    This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.

  10. Parameter estimation for chaotic systems using a hybrid adaptive cuckoo search with simulated annealing algorithm

    Science.gov (United States)

    Sheng, Zheng; Wang, Jun; Zhou, Shudao; Zhou, Bihua

    2014-03-01

    This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.

  11. A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Li Hsin-Te

    2008-01-01

    Full Text Available Abstract A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.

  12. A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition

    Directory of Open Access Journals (Sweden)

    He-Yuan Lin

    2008-03-01

    Full Text Available A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion, edges, textures, and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover, predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences.

  13. Signatures of selection for environmental adaptation and zebu × taurine hybrid fitness in East African shorthorn zebu

    Science.gov (United States)

    The East African Shorthorn Zebu (EASZ) cattle are ancient hybrid between Asian zebu × African taurine cattle preferred by local farmers due to their adaptability to the African environment. The genetic controls of these adaptabilities are not clearly understood yet. Here, we genotyped 92 EASZ sample...

  14. Convergent adaptation to a marginal habitat by homoploid hybrids and polyploid ecads in the seaweed genus Fucus

    NARCIS (Netherlands)

    Coyer, James A.; Hoarau, Galice; Pearson, Gareth A.; Serrao, Ester A.; Stam, Wytze T.; Olsen, Jeanine L.

    2006-01-01

    Hybridization and polyploidy are two major sources of genetic variability that can lead to adaptation in new habitats. Most species of the brown algal genus Fucus are found along wave-swept rocky shores of the Northern Hemisphere, but some species have adapted to brackish and salt marsh habitats. Us

  15. Convergent adaptation to a marginal habitat by homoploid hybrids and polyploid ecads in the seaweed genus Fucus

    NARCIS (Netherlands)

    Coyer, James A.; Hoarau, Galice; Pearson, Gareth A.; Serrao, Ester A.; Stam, Wytze T.; Olsen, Jeanine L.

    2006-01-01

    Hybridization and polyploidy are two major sources of genetic variability that can lead to adaptation in new habitats. Most species of the brown algal genus Fucus are found along wave-swept rocky shores of the Northern Hemisphere, but some species have adapted to brackish and salt marsh habitats.

  16. 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...

  17. An explanatory model of underwater adaptation

    Directory of Open Access Journals (Sweden)

    Joaquín Colodro

    Full Text Available The underwater environment is an extreme environment that requires a process of human adaptation with specific psychophysiological demands to ensure survival and productive activity. From the standpoint of existing models of intelligence, personality and performance, in this explanatory study we have analyzed the contribution of individual differences in explaining the adaptation of military personnel in a stressful environment. Structural equation analysis was employed to verify a model representing the direct effects of psychological variables on individual adaptation to an adverse environment, and we have been able to confirm, during basic military diving courses, the structural relationships among these variables and their ability to predict a third of the variance of a criterion that has been studied very little to date. In this way, we have confirmed in a sample of professionals (N = 575 the direct relationship of emotional adjustment, conscientiousness and general mental ability with underwater adaptation, as well as the inverse relationship of emotional reactivity. These constructs are the psychological basis for working under water, contributing to an improved adaptation to this environment and promoting risk prevention and safety in diving activities.

  18. A general hybrid radiation transport scheme for star formation simulations on an adaptive grid

    CERN Document Server

    Klassen, Mikhail; Pudritz, Ralph E; Peters, Thomas; Banerjee, Robi; Buntemeyer, Lars

    2014-01-01

    Radiation feedback plays a crucial role in the process of star formation. In order to simulate the thermodynamic evolution of disks, filaments, and the molecular gas surrounding clusters of young stars, we require an efficient and accurate method for solving the radiation transfer problem. We describe the implementation of a hybrid radiation transport scheme in the adaptive grid-based FLASH general magnetohydrodynamics code. The hybrid scheme splits the radiative transport problem into a raytracing step and a diffusion step. The raytracer captures the first absorption event, as stars irradiate their environments, while the evolution of the diffuse component of the radiation field is handled by a flux-limited diffusion (FLD) solver. We demonstrate the accuracy of our method through a variety of benchmark tests including the irradiation of a static disk, subcritical and supercritical radiative shocks, and thermal energy equilibration. We also demonstrate the capability of our method for casting shadows and calc...

  19. Semantic models for adaptive interactive systems

    CERN Document Server

    Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

    2013-01-01

    Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

  20. Error estimation and adaptive chemical transport modeling

    Directory of Open Access Journals (Sweden)

    Malte Braack

    2014-09-01

    Full Text Available We present a numerical method to use several chemical transport models of increasing accuracy and complexity in an adaptive way. In largest parts of the domain, a simplified chemical model may be used, whereas in certain regions a more complex model is needed for accuracy reasons. A mathematically derived error estimator measures the modeling error and provides information where to use more accurate models. The error is measured in terms of output functionals. Therefore, one has to consider adjoint problems which carry sensitivity information. This concept is demonstrated by means of ozone formation and pollution emission.

  1. Local vascular adaptations after hybrid training in spinal cord-injured subjects.

    NARCIS (Netherlands)

    Thijssen, D.H.J.; Heesterbeek, P.; Kuppevelt, D. van; Duysens, J.E.J.; Hopman, M.T.E.

    2005-01-01

    PURPOSE: Studies investigating vascular adaptations in non-exercised areas during whole body exercise training show conflicting results. Individuals with spinal cord injury (SCI) provide a unique model to examine vascular adaptations in active tissue vs adjacent inactive areas. The purpose of this s

  2. Modeling and (adaptive) control of greenhouse climates

    NARCIS (Netherlands)

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.

    System concepts

    In Chapters 1 and 2 an overview of the problem formulation

  3. Modelling and (adaptive) control of greenhouse climates

    NARCIS (Netherlands)

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.System conceptsIn Chapters 1 and 2 an overview of the problem formulation is presented. It is suggested that there

  4. 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

  5. Adaptive Modeling for Security Infrastructure Fault Response

    Institute of Scientific and Technical Information of China (English)

    CUI Zhong-jie; YAO Shu-ping; HU Chang-zhen

    2008-01-01

    Based on the analysis of inherent limitations in existing security response decision-making systems, a dynamic adaptive model of fault response is presented. Several security fault levels were founded, which comprise the basic level, equipment level and mechanism level. Fault damage cost is calculated using the analytic hierarchy process. Meanwhile, the model evaluates the impact of different responses upon fault repair and normal operation. Response operation cost and response negative cost are introduced through quantitative calculation. This model adopts a comprehensive response decision of security fault in three principles-the maximum and minimum principle, timeliness principle, acquiescence principle, which assure optimal response countermeasure is selected for different situations. Experimental results show that the proposed model has good self-adaptation ability, timeliness and cost-sensitiveness.

  6. Adaptive Covariance Estimation with model selection

    CERN Document Server

    Biscay, Rolando; Loubes, Jean-Michel

    2012-01-01

    We provide in this paper a fully adaptive penalized procedure to select a covariance among a collection of models observing i.i.d replications of the process at fixed observation points. For this we generalize previous results of Bigot and al. and propose to use a data driven penalty to obtain an oracle inequality for the estimator. We prove that this method is an extension to the matricial regression model of the work by Baraud.

  7. [Mitochondrial DNA polymorphisms shared between modern humans and neanderthals: adaptive convergence or evidence for interspecific hybridization?].

    Science.gov (United States)

    Maliarchuk, B A

    2013-09-01

    An analysis of the variability of the nucleotide sequences in the mitochondrial genome of modern humans, neanderthals, Denisovans, and other primates has shown that there are shared polymorphisms at positions 2758 and 7146 between modern Homo sapiens (in phylogenetic cluster L2'3'4'5'6) and Homo neanderthalensis (in the group of European neanderthals younger than 48000 years). It is suggested that the convergence may be due to adaptive changes in the mitochondrial genomes of modern humans and neanderthals or interspecific hybridization associated with mtDNA recombination.

  8. A hybrid adaptive large neighborhood search heuristic for lot-sizing with setup times

    DEFF Research Database (Denmark)

    Muller, Laurent Flindt; Spoorendonk, Simon; Pisinger, David

    2012-01-01

    This paper presents a hybrid of a general heuristic framework and a general purpose mixed-integer programming (MIP) solver. The framework is based on local search and an adaptive procedure which chooses between a set of large neighborhoods to be searched. A mixed integer programming solver and its......, and the upper bounds found by the commercial MIP solver ILOG CPLEX using state-of-the-art MIP formulations. Furthermore, we improve the best known solutions on 60 out of 100 and improve the lower bound on all 100 instances from the literature...

  9. Adaptive hybrid subband image coding with DWT, DCT, and modified DPCM

    Science.gov (United States)

    Kim, Tae W.; Choe, Howard C.; Griswold, Norman C.

    1997-04-01

    Image coding based on subband decomposition with DPCM and PCM has received much attention in the areas of image compression research and industry. In this paper we present a new adaptive image subband coding with discrete wavelet transform, discrete cosine transform, and a modified DPCM. The main contribution of this work is the development of a simple, yet effective image compression and transmission algorithm. An important feature of this algorithm is the hybrid modified DPCM coding scheme which produces both simple, but significant, image compression and transmission coding.

  10. 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.

  11. 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,

  12. Research on the adaptive hybrid search tree anti-collision algorithm in RFID system

    Institute of Scientific and Technical Information of China (English)

    靳晓芳

    2016-01-01

    Due to more tag-collisions result in failed transmissions, tag anti-collision is a very vital issue in the radio frequency identification ( RFID) system.However, so far decreases in communication time and increases in throughput are very limited.In order to solve these problems, this paper presents a novel tag anti-collision scheme, namely adaptive hybrid search tree ( AHST) , by combining two al-gorithms of the adaptive binary-tree disassembly ( ABD) and the combination query tree ( CQT) , in which ABD has superior tag identification velocity and CQT has optimum performance in system throughput and search timeslots.From the theoretical analysis and numerical simulations, the pro-posed algorithm can colligate the advantages of above algorithms, improve the system throughput and reduce the searching timeslots dramatically.

  13. 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 ...

  14. Adapting virtual camera behaviour through player modelling

    DEFF Research Database (Denmark)

    Burelli, Paolo; Yannakakis, Georgios N.

    2015-01-01

    Research in virtual camera control has focused primarily on finding methods to allow designers to place cameras effectively and efficiently in dynamic and unpredictable environments, and to generate complex and dynamic plans for cinematography in virtual environments. In this article, we propose...... a novel approach to virtual camera control, which builds upon camera control and player modelling to provide the user with an adaptive point-of-view. To achieve this goal, we propose a methodology to model the player’s preferences on virtual camera movements and we employ the resulting models to tailor...... the viewpoint movements to the player type and her game-play style. Ultimately, the methodology is applied to a 3D platform game and is evaluated through a controlled experiment; the results suggest that the resulting adaptive cinematographic experience is favoured by some player types and it can generate...

  15. 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...

  16. 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.

  17. Directional hearing aid using hybrid adaptive beamformer (HAB) and binaural ITE array

    Science.gov (United States)

    Shaw, Scott T.; Larow, Andy J.; Gibian, Gary L.; Sherlock, Laguinn P.; Schulein, Robert

    2002-05-01

    A directional hearing aid algorithm called the Hybrid Adaptive Beamformer (HAB), developed for NIH/NIA, can be applied to many different microphone array configurations. In this project the HAB algorithm was applied to a new array employing in-the-ear microphones at each ear (HAB-ITE), to see if previous HAB performance could be achieved with a more cosmetically acceptable package. With diotic output, the average benefit in threshold SNR was 10.9 dB for three HoH and 11.7 dB for five normal-hearing subjects. These results are slightly better than previous results of equivalent tests with a 3-in. array. With an innovative binaural fitting, a small benefit beyond that provided by diotic adaptive beamforming was observed: 12.5 dB for HoH and 13.3 dB for normal-hearing subjects, a 1.6 dB improvement over the diotic presentation. Subjectively, the binaural fitting preserved binaural hearing abilities, giving the user a sense of space, and providing left-right localization. Thus the goal of creating an adaptive beamformer that simultaneously provides excellent noise reduction and binaural hearing was achieved. Further work remains before the HAB-ITE can be incorporated into a real product, optimizing binaural adaptive beamforming, and integrating the concept with other technologies to produce a viable product prototype. [Work supported by NIH/NIDCD.

  18. Adaptive evolution on a continuous lattice model

    Science.gov (United States)

    Claudino, Elder S.; Lyra, M. L.; Gleria, Iram; Campos, Paulo R. A.

    2013-03-01

    In the current work, we investigate the evolutionary dynamics of a spatially structured population model defined on a continuous lattice. In the model, individuals disperse at a constant rate v and competition is local and delimited by the competition radius R. Due to dispersal, the neighborhood size (number of individuals competing for reproduction) fluctuates over time. Here we address how these new variables affect the adaptive process. While the fixation probabilities of beneficial mutations are roughly the same as in a panmitic population for small fitness effects s, a dependence on v and R becomes more evident for large s. These quantities also strongly influence fixation times, but their dependencies on s are well approximated by s-1/2, which means that the speed of the genetic wave front is proportional to s. Most important is the observation that the model exhibits a dual behavior displaying a power-law growth for the fixation rate and speed of adaptation with the beneficial mutation rate, as observed in other spatially structured population models, while simultaneously showing a nonsaturating behavior for the speed of adaptation with the population size N, as in homogeneous populations.

  19. Adaptive Numerical Algorithms in Space Weather Modeling

    Science.gov (United States)

    Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.; Stout, Quentin F.; Glocer, Alex; Ma, Ying-Juan; Opher, Merav

    2010-01-01

    Space weather describes the various processes in the Sun-Earth system that present danger to human health and technology. The goal of space weather forecasting is to provide an opportunity to mitigate these negative effects. Physics-based space weather modeling is characterized by disparate temporal and spatial scales as well as by different physics in different domains. A multi-physics system can be modeled by a software framework comprising of several components. Each component corresponds to a physics domain, and each component is represented by one or more numerical models. The publicly available Space Weather Modeling Framework (SWMF) can execute and couple together several components distributed over a parallel machine in a flexible and efficient manner. The framework also allows resolving disparate spatial and temporal scales with independent spatial and temporal discretizations in the various models. Several of the computationally most expensive domains of the framework are modeled by the Block-Adaptive Tree Solar wind Roe Upwind Scheme (BATS-R-US) code that can solve various forms of the magnetohydrodynamics (MHD) equations, including Hall, semi-relativistic, multi-species and multi-fluid MHD, anisotropic pressure, radiative transport and heat conduction. Modeling disparate scales within BATS-R-US is achieved by a block-adaptive mesh both in Cartesian and generalized coordinates. Most recently we have created a new core for BATS-R-US: the Block-Adaptive Tree Library (BATL) that provides a general toolkit for creating, load balancing and message passing in a 1, 2 or 3 dimensional block-adaptive grid. We describe the algorithms of BATL and demonstrate its efficiency and scaling properties for various problems. BATS-R-US uses several time-integration schemes to address multiple time-scales: explicit time stepping with fixed or local time steps, partially steady-state evolution, point-implicit, semi-implicit, explicit/implicit, and fully implicit numerical

  20. An Adaptive Hybrid Multi-level Intelligent Intrusion Detection System for Network Security

    Directory of Open Access Journals (Sweden)

    P. Ananthi

    2014-04-01

    Full Text Available Intrusion Detection System (IDS plays a vital factor in providing security to the networks through detecting malicious activities. Due to the extensive advancements in the computer networking, IDS has become an active area of research to determine various types of attacks in the networks. A large number of intrusion detection approaches are available in the literature using several traditional statistical and data mining approaches. Data mining techniques in IDS observed to provide significant results. Data mining approaches for misuse and anomaly-based intrusion detection generally include supervised, unsupervised and outlier approaches. It is important that the efficiency and potential of IDS be updated based on the criteria of new attacks. This study proposes a novel Adaptive Hybrid Multi-level Intelligent IDS (AHMIIDS system which is the combined version of anomaly and misuse detection techniques. The anomaly detection is based on Bayesian Networks and then the misuse detection is performed using Adaptive Neuro Fuzzy Inference System (ANFIS. The outputs of both anomaly detection and misuse detection modules are applied to Decision Table Majority (DTM to perform the final decision making. A rule-base approach is used in this system. It is observed from the results that the proposed AHMIIDS performs better than other conventional hybrid IDS.

  1. Adaptive Second Order Sliding Mode Control of a Fuel Cell Hybrid System for Electric Vehicle Applications

    Directory of Open Access Journals (Sweden)

    Jianxing Liu

    2015-01-01

    Full Text Available We present an adaptive-gain second order sliding mode (SOSM control applied to a hybrid power system for electric vehicle applications. The main advantage of the adaptive SOSM is that it does not require the upper bound of the uncertainty. The proposed hybrid system consists of a polymer electrolyte membrane fuel cell (PEMFC with a unidirectional DC/DC converter and a Li-ion battery stack with a bidirectional DC/DC converter, where the PEMFC is employed as the primary energy source and the battery is employed as the second energy source. One of the main limitations of the FC is its slow dynamics mainly due to the air-feed system and fuel-delivery system. Fuel starvation phenomenon will occur during fast load demand. Therefore, the second energy source is required to assist the main source to improve system perofrmance. The proposed energy management system contains two cascade control structures, which are used to regulate the fuel cell and battery currents to track the given reference currents and stabilize the DC bus voltage while satisfying the physical limitations. The proposed control strategy is evaluated for two real driving cycles, that is, Urban Dynamometer Driving Schedule (UDDS and Highway Fuel Economy Driving Schedule (HWFET.

  2. Adaptation of Hybrid FSO/RF Communication System Using Puncturing Technique

    Directory of Open Access Journals (Sweden)

    M. N. Khan

    2016-12-01

    Full Text Available Spectrum of radio frequency (RF communications is limited and expensive to install new applications. Free space optical (FSO communication is a viable technology which offers enormous bandwidth, license free installation, inexpensive deployment and error prone links. The FSO links degrade significantly due to the varying atmospheric and weather conditions (fog, cloud, snow, haze and combination of these. We propose a hybrid FSO/RF communication system which adapts the varying nature of atmosphere and weather. For the adaption of varying atmosphere and weather scenarios, we develop a novel optimization algorithm. The proposed algorithm is based on the well-known puncturing technique. We provide an extrinsic information transfer (EXIT chart for the binary and quaternary mapping scheme for the proposed communication system. We simulate the proposed algorithm for the hybrid communication system and analyze the system performance. The proposed algorithm is computationally less expensive and provide better performance gains over varying atmosphere and weather conditions. The algorithm is suitable for fast speed applications.

  3. A hybrid strategy of offline adaptive planning and online image guidance for prostate cancer radiotherapy

    Science.gov (United States)

    Lei, Yu; Wu, Qiuwen

    2010-04-01

    Offline adaptive radiotherapy (ART) has been used to effectively correct and compensate for prostate motion and reduce the required margin. The efficacy depends on the characteristics of the patient setup error and interfraction motion through the whole treatment; specifically, systematic errors are corrected and random errors are compensated for through the margins. In online image-guided radiation therapy (IGRT) of prostate cancer, the translational setup error and inter-fractional prostate motion are corrected through pre-treatment imaging and couch correction at each fraction. However, the rotation and deformation of the target are not corrected and only accounted for with margins in treatment planning. The purpose of this study was to investigate whether the offline ART strategy is necessary for an online IGRT protocol and to evaluate the benefit of the hybrid strategy. First, to investigate the rationale of the hybrid strategy, 592 cone-beam-computed tomography (CBCT) images taken before and after each fraction for an online IGRT protocol from 16 patients were analyzed. Specifically, the characteristics of prostate rotation were analyzed. It was found that there exist systematic inter-fractional prostate rotations, and they are patient specific. These rotations, if not corrected, are persistent through the treatment fraction, and rotations detected in early fractions are representative of those in later fractions. These findings suggest that the offline adaptive replanning strategy is beneficial to the online IGRT protocol with further margin reductions. Second, to quantitatively evaluate the benefit of the hybrid strategy, 412 repeated helical CT scans from 25 patients during the course of treatment were included in the replanning study. Both low-risk patients (LRP, clinical target volume, CTV = prostate) and intermediate-risk patients (IRP, CTV = prostate + seminal vesicles) were included in the simulation. The contours of prostate and seminal vesicles were

  4. A hybrid strategy of offline adaptive planning and online image guidance for prostate cancer radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Lei Yu [Department of Radiation Oncology, Wayne State University, 4100 John R, Detroit, MI 48201 (United States); Wu Qiuwen [Department of Radiation Oncology, William Beaumont Hospital, 3601 West 13 Mile Rd, Royal Oak, MI 48073 (United States)], E-mail: Qiuwen.Wu@Duke.edu

    2010-04-21

    Offline adaptive radiotherapy (ART) has been used to effectively correct and compensate for prostate motion and reduce the required margin. The efficacy depends on the characteristics of the patient setup error and interfraction motion through the whole treatment; specifically, systematic errors are corrected and random errors are compensated for through the margins. In online image-guided radiation therapy (IGRT) of prostate cancer, the translational setup error and inter-fractional prostate motion are corrected through pre-treatment imaging and couch correction at each fraction. However, the rotation and deformation of the target are not corrected and only accounted for with margins in treatment planning. The purpose of this study was to investigate whether the offline ART strategy is necessary for an online IGRT protocol and to evaluate the benefit of the hybrid strategy. First, to investigate the rationale of the hybrid strategy, 592 cone-beam-computed tomography (CBCT) images taken before and after each fraction for an online IGRT protocol from 16 patients were analyzed. Specifically, the characteristics of prostate rotation were analyzed. It was found that there exist systematic inter-fractional prostate rotations, and they are patient specific. These rotations, if not corrected, are persistent through the treatment fraction, and rotations detected in early fractions are representative of those in later fractions. These findings suggest that the offline adaptive replanning strategy is beneficial to the online IGRT protocol with further margin reductions. Second, to quantitatively evaluate the benefit of the hybrid strategy, 412 repeated helical CT scans from 25 patients during the course of treatment were included in the replanning study. Both low-risk patients (LRP, clinical target volume, CTV = prostate) and intermediate-risk patients (IRP, CTV = prostate + seminal vesicles) were included in the simulation. The contours of prostate and seminal vesicles were

  5. 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.

  6. 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.

  7. Model-Free Adaptive Heating Process Control

    OpenAIRE

    Ivana LUKÁČOVÁ; Piteľ, Ján

    2009-01-01

    The aim of this paper is to analyze the dynamic behaviour of a Model-Free Adaptive (MFA) heating process control. The MFA controller is designed as three layer neural network with proportional element. The method of backward propagation of errors was used for neural network training. Visualization and training of the artificial neural network was executed by Netlab in Matlab environment. Simulation of the MFA heating process control with outdoor temperature compensation has proved better resu...

  8. Fully Adaptive Radar Modeling and Simulation Development

    Science.gov (United States)

    2017-04-01

    Organization (NATO) Sensors Electronics Technology (SET)-227 Panel on Cognitive Radar. The FAR M&S architecture developed in Phase I allows for...Air Force’s previously developed radar M&S tools. This report is organized as follows. In Chapter 3, we provide an overview of the FAR framework...AFRL-RY-WP-TR-2017-0074 FULLY ADAPTIVE RADAR MODELING AND SIMULATION DEVELOPMENT Kristine L. Bell and Anthony Kellems Metron, Inc

  9. Adaptive cyber-attack modeling system

    Science.gov (United States)

    Gonsalves, Paul G.; Dougherty, Edward T.

    2006-05-01

    The pervasiveness of software and networked information systems is evident across a broad spectrum of business and government sectors. Such reliance provides an ample opportunity not only for the nefarious exploits of lone wolf computer hackers, but for more systematic software attacks from organized entities. Much effort and focus has been placed on preventing and ameliorating network and OS attacks, a concomitant emphasis is required to address protection of mission critical software. Typical software protection technique and methodology evaluation and verification and validation (V&V) involves the use of a team of subject matter experts (SMEs) to mimic potential attackers or hackers. This manpower intensive, time-consuming, and potentially cost-prohibitive approach is not amenable to performing the necessary multiple non-subjective analyses required to support quantifying software protection levels. To facilitate the evaluation and V&V of software protection solutions, we have designed and developed a prototype adaptive cyber attack modeling system. Our approach integrates an off-line mechanism for rapid construction of Bayesian belief network (BN) attack models with an on-line model instantiation, adaptation and knowledge acquisition scheme. Off-line model construction is supported via a knowledge elicitation approach for identifying key domain requirements and a process for translating these requirements into a library of BN-based cyber-attack models. On-line attack modeling and knowledge acquisition is supported via BN evidence propagation and model parameter learning.

  10. 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.

  11. 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.

  12. Optimal reactive power and voltage control in distribution networks with distributed generators by fuzzy adaptive hybrid particle swarm optimisation method

    DEFF Research Database (Denmark)

    Chen, Shuheng; Hu, Weihao; Su, Chi

    2015-01-01

    A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid PSO (FAHPSO) is proposed. The objective is to minimize comprehensive cost, consisting of power loss and operation cost of transformers...... and capacitors, and subject to constraints such as minimum and maximum reactive power limits of distributed generators, maximum deviation of bus voltages, maximum allowable daily switching operation number (MADSON). Particle swarm optimization (PSO) is used to solve the corresponding mixed integer non......-linear programming problem (MINLP) and the hybrid PSO method (HPSO), consisting of three PSO variants, is presented. In order to mitigate the local convergence problem, fuzzy adaptive inference is used to improve the searching process and the final fuzzy adaptive inference based hybrid PSO is proposed. The proposed...

  13. Adaptive Control and Synchronization of the Shallow Water Model

    Directory of Open Access Journals (Sweden)

    P. Sangapate

    2012-01-01

    Full Text Available The shallow water model is one of the important models in dynamical systems. This paper investigates the adaptive chaos control and synchronization of the shallow water model. First, adaptive control laws are designed to stabilize the shallow water model. Then adaptive control laws are derived to chaos synchronization of the shallow water model. The sufficient conditions for the adaptive control and synchronization have been analyzed theoretically, and the results are proved using a Barbalat's Lemma.

  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 Model for Climate Change Adaptation

    Science.gov (United States)

    Pasqualini, D.; Keating, G. N.

    2009-12-01

    Climate models predict serious impacts on the western U.S. in the next few decades, including increased temperatures and reduced precipitation. In combination, these changes are linked to profound impacts on fundamental systems, such as water and energy supplies, agriculture, population stability, and the economy. Global and national imperatives for climate change mitigation and adaptation are made actionable at the state level, for instance through greenhouse gas (GHG) emission regulations and incentives for renewable energy sources. However, adaptation occurs at the local level, where energy and water usage can be understood relative to local patterns of agriculture, industry, and culture. In response to the greenhouse gas emission reductions required by California’s Assembly Bill 32 (2006), Sonoma County has committed to sharp emissions reductions across several sectors, including water, energy, and transportation. To assist Sonoma County develop a renewable energy (RE) portfolio to achieve this goal we have developed an integrated assessment model, CLEAR (CLimate-Energy Assessment for Resiliency) model. Building on Sonoma County’s existing baseline studies of energy use, carbon emissions and potential RE sources, the CLEAR model simulates the complex interactions among technology deployment, economics and social behavior. This model enables assessment of these and other components with specific analysis of their coupling and feedbacks because, due to the complex nature of the problem, the interrelated sectors cannot be studied independently. The goal is an approach to climate change mitigation and adaptation that is replicable for use by other interested communities. The model user interfaces helps stakeholders and policymakers understand options for technology implementation.

  16. 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.

  17. Income distribution: An adaptive heterogeneous model

    Science.gov (United States)

    da Silva, L. C.; de Figueirêdo, P. H.

    2014-02-01

    In this communication an adaptive process is introduced into a many-agent model for closed economic system in order to establish general features of income distribution. In this new version agents are able to modify their exchange parameter ωi of resources through an adaptive process. The conclusions indicate that assuming an instantaneous learning behavior of all agents a Γ-distribution for income is reproduced while a frozen behavior establishes a Pareto’s distribution for income with an exponent ν=0.94±0.02. A third case occurs when a heterogeneous “inertia” behavior is introduced leading us to a Γ-distribution at the low income regime and a power-law decay for the large income values with an exponent ν=2.05±0.05. This method enables investigation of the resources flux in the economic environment and produces also bounding values for the Gini index comparable with data evidences.

  18. Hybrid Vibration Control under Broadband Excitation and Variable Temperature Using Viscoelastic Neutralizer and Adaptive Feedforward Approach

    Directory of Open Access Journals (Sweden)

    João C. O. Marra

    2016-01-01

    Full Text Available Vibratory phenomena have always surrounded human life. The need for more knowledge and domain of such phenomena increases more and more, especially in the modern society where the human-machine integration becomes closer day after day. In that context, this work deals with the development and practical implementation of a hybrid (passive-active/adaptive vibration control system over a metallic beam excited by a broadband signal and under variable temperature, between 5 and 35°C. Since temperature variations affect directly and considerably the performance of the passive control system, composed of a viscoelastic dynamic vibration neutralizer (also called a viscoelastic dynamic vibration absorber, the associative strategy of using an active-adaptive vibration control system (based on a feedforward approach with the use of the FXLMS algorithm working together with the passive one has shown to be a good option to compensate the neutralizer loss of performance and generally maintain the extended overall level of vibration control. As an additional gain, the association of both vibration control systems (passive and active-adaptive has improved the attenuation of vibration levels. Some key steps matured over years of research on this experimental setup are presented in this paper.

  19. 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.

  20. 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.

  1. 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.

  2. 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...

  3. Bridging the gap: adapting advanced display technologies for use in hybrid control rooms

    Energy Technology Data Exchange (ETDEWEB)

    Jokstad, Håkon [Inst. for Energy Technology, Halden (Norway); Boring, Ronald [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-02-01

    The Institute for Energy Technology (IFE), runs the OECD Halden Reactor Project (HRP), featuring a state-of-the-art research simulator facility in Halden, Norway, called HAMMLAB. HAMMLAB serves two main purposes: the study of human behaviour in interaction with complex process systems; and the development, test and evaluation of prototype control centres and their individual systems. By studying operator performance in HAMMLAB and integrating the knowledge gained into new designs, the HRP contributes to improving operational safety, reliability, efficiency and productivity. The U.S. Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program has contracted IFE to assist DOE national laboratory staff at Idaho National Laboratory (INL) in adapting HAMMLAB design concepts for the purpose of control room modernization at nuclear power plants in the U.S. In support of this effort, the DOE has built a simulator research facility at INL called the Human Systems Simulation Laboratory (HSSL). The HSSL is centered on control room modernization, in which industry provided plant instrumentation and controls are modified for upgrade opportunities. The HSSL houses the LWRS simulator, which is a reconfigurable full-scale and full-scope control room simulator. Consisting of 45 large touchscreens on 15 panels, the LWRS simulator is currently using this glass top technology to digitally represent and replicate the functionality of the analog I&C systems in existing control rooms. The LWRS simulator is reconfigurable in that different plant training simulator models obtained from the utilities can be run on the panels, and the panels can be physically moved and arranged to mimic the layout of those control rooms. The glass top technology and reconfigurability capabilities allow the LWRS simulator to be the research platform that is necessary to design, prototype, and validate human-system interface (HSI) technologies that can replace existing analog I&C. IFE has

  4. 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.

  5. An adaptive contextual quantum language model

    Science.gov (United States)

    Li, Jingfei; Zhang, Peng; Song, Dawei; Hou, Yuexian

    2016-08-01

    User interactions in search system represent a rich source of implicit knowledge about the user's cognitive state and information need that continuously evolves over time. Despite massive efforts that have been made to exploiting and incorporating this implicit knowledge in information retrieval, it is still a challenge to effectively capture the term dependencies and the user's dynamic information need (reflected by query modifications) in the context of user interaction. To tackle these issues, motivated by the recent Quantum Language Model (QLM), we develop a QLM based retrieval model for session search, which naturally incorporates the complex term dependencies occurring in user's historical queries and clicked documents with density matrices. In order to capture the dynamic information within users' search session, we propose a density matrix transformation framework and further develop an adaptive QLM ranking model. Extensive comparative experiments show the effectiveness of our session quantum language models.

  6. Adaptive Lattice Boltzmann Model for Compressible Flows

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    A new lattice Boltzmann model for compressible flows is presented. The main difference from the standard lattice Boltzmann model is that the particle velocities are no longer constant, but vary with the mean velocity and internal energy. The adaptive nature of the particle velocities permits the mean flow to have a high Mach number. The introduction of a particle potential energy makes the model suitable for a perfect gas with arbitrary specific heat ratio. The Navier-Stokes (N-S) equations are derived by the Chapman-Enskog method from the BGK Boltzmann equation. Two kinds of simulations have been carried out on the hexagonal lattice to test the proposed model. One is the Sod shock-tube simulation. The other is a strong shock of Mach number 5.09 diffracting around a corner.

  7. On adaptive refinements in discrete probabilistic fracture models

    Directory of Open Access Journals (Sweden)

    J. Eliáš

    2017-01-01

    Full Text Available The possibility to adaptively change discretization density is a well acknowledged and used feature of many continuum models. It is employed to save computational time and increase solution accuracy. Recently, adaptivity has been introduced also for discrete particle models. This contribution applies adaptive technique in probabilistic discrete modelling where material properties are varying in space according to a random field. The random field discretization is adaptively refined hand in hand with the model geometry.

  8. Hybrid routing and spectrum assignment algorithms based on distance-adaptation combined coevolution and heuristics in elastic optical networks

    Science.gov (United States)

    Ding, Zhe; Xu, Zhanqi; Zeng, Xiaodong; Ma, Tao; Yang, Fan

    2014-04-01

    By adopting the orthogonal frequency division multiplexing technology, spectrum-sliced elastic optical path networks can offer flexible bandwidth to each connection request and utilize the spectrum resources efficiently. The routing and spectrum assignment (RSA) problems in SLICE networks are solved by using heuristic algorithms in most prior studies and addressed by intelligent algorithms in few investigations. The performance of RSA algorithms can be further improved if we could combine such two types of algorithms. Therefore, we propose three hybrid RSA algorithms: DACE-GMSF, DACE-GLPF, and DACE-GEMkPSF, which are the combination of the heuristic algorithm and coevolution based on distance-adaptive policy. In the proposed algorithms, we first groom the connection requests, then sort the connection requests by using the heuristic algorithm (most subcarriers first, longest path first, and extended most k paths' slots first), and finally search the approximately optimal solution with the coevolutionary policy. We present a model of the RSA problem by using integral linear programming, and key elements in the proposed algorithms are addressed in detail. Simulations under three topologies show that the proposed hybrid RSA algorithms can save spectrum resources efficiently.

  9. Synaptic dynamics: linear model and adaptation algorithm.

    Science.gov (United States)

    Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W

    2014-08-01

    In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and

  10. Model Driven Mutation Applied to Adaptative Systems Testing

    CERN Document Server

    Bartel, Alexandre; Munoz, Freddy; Klein, Jacques; Mouelhi, Tejeddine; Traon, Yves Le

    2012-01-01

    Dynamically Adaptive Systems modify their behav- ior and structure in response to changes in their surrounding environment and according to an adaptation logic. Critical sys- tems increasingly incorporate dynamic adaptation capabilities; examples include disaster relief and space exploration systems. In this paper, we focus on mutation testing of the adaptation logic. We propose a fault model for adaptation logics that classifies faults into environmental completeness and adaptation correct- ness. Since there are several adaptation logic languages relying on the same underlying concepts, the fault model is expressed independently from specific adaptation languages. Taking benefit from model-driven engineering technology, we express these common concepts in a metamodel and define the operational semantics of mutation operators at this level. Mutation is applied on model elements and model transformations are used to propagate these changes to a given adaptation policy in the chosen formalism. Preliminary resul...

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

    Science.gov (United States)

    Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

    2017-01-01

    In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used.

  19. [An adaptive scaling hybrid algorithm for reduction of CT artifacts caused by metal objects].

    Science.gov (United States)

    Chen, Yu; Luo, Hai; Zhou, He-qin

    2009-03-01

    A new adaptively hybrid filtering algorithm is proposed to reduce the artifacts caused by metal in CT image. Firstly, the method is used to preprocess the projection data of metal region and is reconstruct by filtered back projection (FBP) method. Then the expectation maximization algorithm (EM) is performed on the iterative original metal project data. Finally, a compensating procedure is applied to the reconstructed metal region. The simulation result has demonstrated that the proposed algorithm can remove the metal artifacts and keep the structure information of metal object effectively. It ensures that the tissues around the metal will not be distorted. The method is also computational efficient and effective for the CT images which contains several metal objects.

  20. 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.

  1. 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.

  2. Adaptive Genetic Algorithm Model for Intrusion Detection

    Directory of Open Access Journals (Sweden)

    K. S. Anil Kumar

    2012-09-01

    Full Text Available Intrusion detection systems are intelligent systems designed to identify and prevent the misuse of computer networks and systems. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Thus the emerging network security systems need be part of the life system and this ispossible only by embedding knowledge into the network. The Adaptive Genetic Algorithm Model - IDS comprising of K-Means clustering Algorithm, Genetic Algorithm and Neural Network techniques. Thetechnique is tested using multitude of background knowledge sets in DARPA network traffic datasets.

  3. A Model for Dynamic Adaptive Coscheduling

    Institute of Scientific and Technical Information of China (English)

    LU Sanglu; ZHOU Xiaobo; XIE Li

    1999-01-01

    This paper proposes a dynamic adaptive coscheduling modelDASIC to take advantage of excess available resources in anetwork of workstations (NOW). Besides coscheduling related subtasksdynamically, DASIC can scale up or down the process space dependingupon the number of available processors on an NOW. Based on thedynamic idle processor group (IPG), DASIC employs three modules: thecoscheduling module, the scalable scheduling module and the loadbalancing module, and uses six algorithms to achieve scalability. Asimplified DASIC was also implemented, and experimental results arepresented in this paper, which show that it can maximize systemutilization, and achieve task parallelism as much as possible.

  4. 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.

  5. A general hybrid radiation transport scheme for star formation simulations on an adaptive grid

    Energy Technology Data Exchange (ETDEWEB)

    Klassen, Mikhail; Pudritz, Ralph E. [Department of Physics and Astronomy, McMaster University 1280 Main Street W, Hamilton, ON L8S 4M1 (Canada); Kuiper, Rolf [Max Planck Institute for Astronomy Königstuhl 17, D-69117 Heidelberg (Germany); Peters, Thomas [Institut für Computergestützte Wissenschaften, Universität Zürich Winterthurerstrasse 190, CH-8057 Zürich (Switzerland); Banerjee, Robi; Buntemeyer, Lars, E-mail: klassm@mcmaster.ca [Hamburger Sternwarte, Universität Hamburg Gojenbergsweg 112, D-21029 Hamburg (Germany)

    2014-12-10

    Radiation feedback plays a crucial role in the process of star formation. In order to simulate the thermodynamic evolution of disks, filaments, and the molecular gas surrounding clusters of young stars, we require an efficient and accurate method for solving the radiation transfer problem. We describe the implementation of a hybrid radiation transport scheme in the adaptive grid-based FLASH general magnetohydrodyanmics code. The hybrid scheme splits the radiative transport problem into a raytracing step and a diffusion step. The raytracer captures the first absorption event, as stars irradiate their environments, while the evolution of the diffuse component of the radiation field is handled by a flux-limited diffusion solver. We demonstrate the accuracy of our method through a variety of benchmark tests including the irradiation of a static disk, subcritical and supercritical radiative shocks, and thermal energy equilibration. We also demonstrate the capability of our method for casting shadows and calculating gas and dust temperatures in the presence of multiple stellar sources. Our method enables radiation-hydrodynamic studies of young stellar objects, protostellar disks, and clustered star formation in magnetized, filamentary environments.

  6. A General Hybrid Radiation Transport Scheme for Star Formation Simulations on an Adaptive Grid

    Science.gov (United States)

    Klassen, Mikhail; Kuiper, Rolf; Pudritz, Ralph E.; Peters, Thomas; Banerjee, Robi; Buntemeyer, Lars

    2014-12-01

    Radiation feedback plays a crucial role in the process of star formation. In order to simulate the thermodynamic evolution of disks, filaments, and the molecular gas surrounding clusters of young stars, we require an efficient and accurate method for solving the radiation transfer problem. We describe the implementation of a hybrid radiation transport scheme in the adaptive grid-based FLASH general magnetohydrodyanmics code. The hybrid scheme splits the radiative transport problem into a raytracing step and a diffusion step. The raytracer captures the first absorption event, as stars irradiate their environments, while the evolution of the diffuse component of the radiation field is handled by a flux-limited diffusion solver. We demonstrate the accuracy of our method through a variety of benchmark tests including the irradiation of a static disk, subcritical and supercritical radiative shocks, and thermal energy equilibration. We also demonstrate the capability of our method for casting shadows and calculating gas and dust temperatures in the presence of multiple stellar sources. Our method enables radiation-hydrodynamic studies of young stellar objects, protostellar disks, and clustered star formation in magnetized, filamentary environments.

  7. Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding

    Science.gov (United States)

    Lai, Hong; Zhang, Jun; Luo, Ming-Xing; Pan, Lei; Pieprzyk, Josef; Xiao, Fuyuan; Orgun, Mehmet A.

    2016-08-01

    With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m-bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m-bonacci sequences to detect eavesdropping. Meanwhile, we encode m-bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications.

  8. Plant adaptive behaviour in hydrological models (Invited)

    Science.gov (United States)

    van der Ploeg, M. J.; Teuling, R.

    2013-12-01

    Models that will be able to cope with future precipitation and evaporation regimes need a solid base that describes the essence of the processes involved [1]. Micro-behaviour in the soil-vegetation-atmosphere system may have a large impact on patterns emerging at larger scales. A complicating factor in the micro-behaviour is the constant interaction between vegetation and geology in which water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. As a result of environmental changes vegetation may wither and die, but such environmental changes may also trigger gene adaptation. Constant exposure to environmental stresses, biotic or abiotic, influences plant physiology, gene adaptations, and flexibility in gene adaptation [2-6]. Gene expression as a result of different environmental conditions may profoundly impact drought responses across the same plant species. Differences in response to an environmental stress, has consequences for the way species are currently being treated in models (single plant to global scale). In particular, model parameters that control root water uptake and plant transpiration are generally assumed to be a property of the plant functional type. Assigning plant functional types does not allow for local plant adaptation to be reflected in the model parameters, nor does it allow for correlations that might exist between root parameters and soil type. Models potentially provide a means to link root water uptake and transport to large scale processes (e.g. Rosnay and Polcher 1998, Feddes et al. 2001, Jung 2010), especially when powered with an integrated hydrological, ecological and physiological base. We explore the experimental evidence from natural vegetation to formulate possible alternative modeling concepts. [1] Seibert, J. 2000. Multi-criteria calibration of a conceptual runoff model using a genetic algorithm. Hydrology and Earth System Sciences 4(2): 215

  9. 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.

  10. A three-degree-of-freedom hybrid vibration isolation system using adaptive proportional control supported by passive weight support mechanism

    Science.gov (United States)

    Liu, Yun-Hui; Wu, Wei-Hao; Chu, Chih-Liang

    2013-10-01

    This paper presents a three-degree-of-freedom hybrid vibration isolation system integrated with an active sky-hook damper and a passive weight support mechanism for highly sensitive measurement equipment, e.g. atomic force microscopes, suffering from building vibration. Active sky-hook damper applies proportional controller incorporated with an adaptive filter to reduce the resonance of the passive weight support mechanism at nature frequency. The absolute vibration velocity signal acquired from an accelerator and being processed through an integrator is input to the controller as a feedback signal, and the controller output signal drives the voice coil actuator to produce a sky-hook damper force. The adaptive filter is used to compensate the phase error between the measuring input signal and the absolute vibration velocity. An analysis of this active vibration isolation system is presented, and model predictions are compared to experimental results. The results show that the system could effectively reduce transmissibility at resonance without the penalty of increased transmissibility at higher frequencies both in vertical and horizontal directions.

  11. 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.

  12. Adaptive control paradigm for photovoltaic and solid oxide fuel cell in a grid-integrated hybrid renewable energy system.

    Science.gov (United States)

    Mumtaz, Sidra; Khan, Laiq

    2017-01-01

    The hybrid power system (HPS) is an emerging power generation scheme due to the plentiful availability of renewable energy sources. Renewable energy sources are characterized as highly intermittent in nature due to meteorological conditions, while the domestic load also behaves in a quite uncertain manner. In this scenario, to maintain the balance between generation and load, the development of an intelligent and adaptive control algorithm has preoccupied power engineers and researchers. This paper proposes a Hermite wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control of photovoltaic (PV) systems to extract maximum power and a Hermite wavelet incorporated NeuroFuzzy indirect adaptive control of Solid Oxide Fuel Cells (SOFC) to obtain a swift response in a grid-connected hybrid power system. A comprehensive simulation testbed for a grid-connected hybrid power system (wind turbine, PV cells, SOFC, electrolyzer, battery storage system, supercapacitor (SC), micro-turbine (MT) and domestic load) is developed in Matlab/Simulink. The robustness and superiority of the proposed indirect adaptive control paradigm are evaluated through simulation results in a grid-connected hybrid power system testbed by comparison with a conventional PI (proportional and integral) control system. The simulation results verify the effectiveness of the proposed control paradigm.

  13. Adaptive control paradigm for photovoltaic and solid oxide fuel cell in a grid-integrated hybrid renewable energy system

    Science.gov (United States)

    Khan, Laiq

    2017-01-01

    The hybrid power system (HPS) is an emerging power generation scheme due to the plentiful availability of renewable energy sources. Renewable energy sources are characterized as highly intermittent in nature due to meteorological conditions, while the domestic load also behaves in a quite uncertain manner. In this scenario, to maintain the balance between generation and load, the development of an intelligent and adaptive control algorithm has preoccupied power engineers and researchers. This paper proposes a Hermite wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control of photovoltaic (PV) systems to extract maximum power and a Hermite wavelet incorporated NeuroFuzzy indirect adaptive control of Solid Oxide Fuel Cells (SOFC) to obtain a swift response in a grid-connected hybrid power system. A comprehensive simulation testbed for a grid-connected hybrid power system (wind turbine, PV cells, SOFC, electrolyzer, battery storage system, supercapacitor (SC), micro-turbine (MT) and domestic load) is developed in Matlab/Simulink. The robustness and superiority of the proposed indirect adaptive control paradigm are evaluated through simulation results in a grid-connected hybrid power system testbed by comparison with a conventional PI (proportional and integral) control system. The simulation results verify the effectiveness of the proposed control paradigm. PMID:28329015

  14. Adaptive Hybrid Visual Servo Regulation of Mobile Robots Based on Fast Homography Decomposition

    Directory of Open Access Journals (Sweden)

    Chunfu Wu

    2015-01-01

    Full Text Available For the monocular camera-based mobile robot system, an adaptive hybrid visual servo regulation algorithm which is based on a fast homography decomposition method is proposed to drive the mobile robot to its desired position and orientation, even when object’s imaging depth and camera’s position extrinsic parameters are unknown. Firstly, the homography’s particular properties caused by mobile robot’s 2-DOF motion are taken into account to induce a fast homography decomposition method. Secondly, the homography matrix and the extracted orientation error, incorporated with the desired view’s single feature point, are utilized to form an error vector and its open-loop error function. Finally, Lyapunov-based techniques are exploited to construct an adaptive regulation control law, followed by the experimental verification. The experimental results show that the proposed fast homography decomposition method is not only simple and efficient, but also highly precise. Meanwhile, the designed control law can well enable mobile robot position and orientation regulation despite the lack of depth information and camera’s position extrinsic parameters.

  15. Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Linhui Li

    2014-01-01

    Full Text Available Energy management control strategy of hybrid electric vehicle has a great influence on the vehicle fuel consumption with electric motors adding to the traditional vehicle power system. As vehicle real driving cycles seem to be uncertain, the dynamic driving cycles will have an impact on control strategy’s energy-saving effect. In order to better adapt the dynamic driving cycles, control strategy should have the ability to recognize the real-time driving cycle and adaptively adjust to the corresponding off-line optimal control parameters. In this paper, four types of representative driving cycles are constructed based on the actual vehicle operating data, and a fuzzy driving cycle recognition algorithm is proposed for online recognizing the type of actual driving cycle. Then, based on the equivalent fuel consumption minimization strategy, an ant colony optimization algorithm is utilized to search the optimal control parameters “charge and discharge equivalent factors” for each type of representative driving cycle. At last, the simulation experiments are conducted to verify the accuracy of the proposed fuzzy recognition algorithm and the validity of the designed control strategy optimization method.

  16. An Adaptive 6-DOF Tracking Method by Hybrid Sensing for Ultrasonic Endoscopes

    Directory of Open Access Journals (Sweden)

    Chengyang Du

    2014-06-01

    Full Text Available In this paper, a novel hybrid sensing method for tracking an ultrasonic endoscope within the gastrointestinal (GI track is presented, and the prototype of the tracking system is also developed. We implement 6-DOF localization by sensing integration and information fusion. On the hardware level, a tri-axis gyroscope and accelerometer, and a magnetic angular rate and gravity (MARG sensor array are attached at the end of endoscopes, and three symmetric cylindrical coils are placed around patients’ abdomens. On the algorithm level, an adaptive fast quaternion convergence (AFQC algorithm is introduced to determine the orientation by fusing inertial/magnetic measurements, in which the effects of magnetic disturbance and acceleration are estimated to gain an adaptive convergence output. A simplified electro-magnetic tracking (SEMT algorithm for dimensional position is also implemented, which can easily integrate the AFQC’s results and magnetic measurements. Subsequently, the average position error is under 0.3 cm by reasonable setting, and the average orientation error is 1° without noise. If magnetic disturbance or acceleration exists, the average orientation error can be controlled to less than 3.5°.

  17. An adaptive 6-DOF tracking method by hybrid sensing for ultrasonic endoscopes.

    Science.gov (United States)

    Du, Chengyang; Chen, Xiaodong; Wang, Yi; Li, Junwei; Yu, Daoyin

    2014-06-06

    In this paper, a novel hybrid sensing method for tracking an ultrasonic endoscope within the gastrointestinal (GI) track is presented, and the prototype of the tracking system is also developed. We implement 6-DOF localization by sensing integration and information fusion. On the hardware level, a tri-axis gyroscope and accelerometer, and a magnetic angular rate and gravity (MARG) sensor array are attached at the end of endoscopes, and three symmetric cylindrical coils are placed around patients' abdomens. On the algorithm level, an adaptive fast quaternion convergence (AFQC) algorithm is introduced to determine the orientation by fusing inertial/magnetic measurements, in which the effects of magnetic disturbance and acceleration are estimated to gain an adaptive convergence output. A simplified electro-magnetic tracking (SEMT) algorithm for dimensional position is also implemented, which can easily integrate the AFQC's results and magnetic measurements. Subsequently, the average position error is under 0.3 cm by reasonable setting, and the average orientation error is 1° without noise. If magnetic disturbance or acceleration exists, the average orientation error can be controlled to less than 3.5°.

  18. Adaptation dynamics of the quasispecies model

    Indian Academy of Sciences (India)

    Kavita Jain

    2008-08-01

    We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen’s model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a quasispecies which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.

  19. Adaptation dynamics of the quasispecies model

    Science.gov (United States)

    Jain, Kavita

    2009-02-01

    We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.

  20. 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

  1. 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.

  2. Calibration of the Hall Measurement System for a 6-DOF Precision Stage Using Self-Adaptive Hybrid TLBO.

    Science.gov (United States)

    Chen, Zhenyu; Liu, Yang; Fu, Zhenxian; Song, Shenmin; Tan, Jiubin

    2016-06-14

    To determine the planar motion of a 6-DOF precision stage, a measurement system based on three Hall sensors is adopted to obtain the X, Y, Rz motions of the stage. The machining and assembly errors in the actual mechanical system, which are difficult to measure directly, cause the parameters in the model of the Hall measurement system to deviate from their designed values. Additionally, the vertical movement of the stage will render the measurement model nonlinear. To guarantee the accuracy of the measurement, the parameters in the measurement model should be estimated and the nonlinearity compensated. In this paper, a novel approach based on self-adaptive hybrid TLBO (teaching-learning-based-optimization) is proposed to estimate the parameters in the Hall measurement model. The influences of zero deviations and vertical movements on the measurement accuracy are analyzed and compensated. The effectiveness of the proposed method is validated by experimental results obtained on a 6-DOF precision stage. Thanks to parameter estimation and calibration, the measurement error of the Hall sensor array is reduced to 6 micrometers.

  3. Calibration of the Hall Measurement System for a 6-DOF Precision Stage Using Self-Adaptive Hybrid TLBO

    Directory of Open Access Journals (Sweden)

    Zhenyu Chen

    2016-06-01

    Full Text Available To determine the planar motion of a 6-DOF precision stage, a measurement system based on three Hall sensors is adopted to obtain the X, Y, Rz motions of the stage. The machining and assembly errors in the actual mechanical system, which are difficult to measure directly, cause the parameters in the model of the Hall measurement system to deviate from their designed values. Additionally, the vertical movement of the stage will render the measurement model nonlinear. To guarantee the accuracy of the measurement, the parameters in the measurement model should be estimated and the nonlinearity compensated. In this paper, a novel approach based on self-adaptive hybrid TLBO (teaching-learning-based-optimization is proposed to estimate the parameters in the Hall measurement model. The influences of zero deviations and vertical movements on the measurement accuracy are analyzed and compensated. The effectiveness of the proposed method is validated by experimental results obtained on a 6-DOF precision stage. Thanks to parameter estimation and calibration, the measurement error of the Hall sensor array is reduced to 6 micrometers.

  4. 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

  5. European upper mantle tomography: adaptively parameterized models

    Science.gov (United States)

    Schäfer, J.; Boschi, L.

    2009-04-01

    We have devised a new algorithm for upper-mantle surface-wave tomography based on adaptive parameterization: i.e. the size of each parameterization pixel depends on the local density of seismic data coverage. The advantage in using this kind of parameterization is that a high resolution can be achieved in regions with dense data coverage while a lower (and cheaper) resolution is kept in regions with low coverage. This way, parameterization is everywhere optimal, both in terms of its computational cost, and of model resolution. This is especially important for data sets with inhomogenous data coverage, as it is usually the case for global seismic databases. The data set we use has an especially good coverage around Switzerland and over central Europe. We focus on periods from 35s to 150s. The final goal of the project is to determine a new model of seismic velocities for the upper mantle underlying Europe and the Mediterranean Basin, of resolution higher than what is currently found in the literature. Our inversions involve regularization via norm and roughness minimization, and this in turn requires that discrete norm and roughness operators associated with our adaptive grid be precisely defined. The discretization of the roughness damping operator in the case of adaptive parameterizations is not as trivial as it is for the uniform ones; important complications arise from the significant lateral variations in the size of pixels. We chose to first define the roughness operator in a spherical harmonic framework, and subsequently translate it to discrete pixels via a linear transformation. Since the smallest pixels we allow in our parameterization have a size of 0.625 °, the spherical-harmonic roughness operator has to be defined up to harmonic degree 899, corresponding to 810.000 harmonic coefficients. This results in considerable computational costs: we conduct the harmonic-pixel transformations on a small Beowulf cluster. We validate our implementation of adaptive

  6. 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.

  7. An Approach of Bio-inspired Hybrid Model for Financial Markets

    Science.gov (United States)

    Simić, Dragan; Gajić, Vladeta; Simić, Svetlana

    Biological systems are inspiration for the design of optimisation and classification models. Applying various forms of bio-inspired algorithms may be a very high-complex system. Modelling of financial markets is challenging for several reasons, because many plausible factors impact on it. An automated trading on financial market is not a new phenomenon. The model of bio-inspired hybrid adaptive trading system based on technical indicators usage by grammatical evolution and moving window is presented in this paper. The proposed system is just one of possible bio-inspired system which can be used in financial forecast, corporate failure prediction or bond rating company.

  8. 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.

  9. Marginal and internal adaptation of Class II ormocer and hybrid resin composite restorations before and after load cycling.

    Science.gov (United States)

    Kournetas, N; Chakmakchi, M; Kakaboura, A; Rahiotis, C; Geis-Gerstorfer, J

    2004-09-01

    To overcome the shortcomings of the conventional composite restorative materials, ormocer materials have been introduced over the past few years. The purpose of this study was to evaluate the marginal and internal adaptation of two ormocer restorative systems (Admira, Voco and Definite, Degussa) compared to a hybrid composite one (TPH Spectrum, Dentsply/ DeTrey), before and after load cycling in Class II restorations. Standardized Class II restorations with cervical margins on enamel were divided into three groups ( n=16). Teeth of each group were filled with one of the restoratives tested and its respective bonding agent. Each group was divided into two equal subgroups. The marginal and internal adaptation of the first subgroup was evaluated after 7-day water storage at room temperature and of the second after cyclic loading in a mastication simulator (1.2x10(6) cycles, 49 N, 1.6 Hz). The occlusal and cervical marginal evaluation was conducted by videomicroscope and ranked as "excellent" and "not excellent". One thin section (150 microm), in mesial-distal direction, of each restoration, was examined under metallographic microscope to determine the quality of internal adaptation. The occlusal and cervical adaptation of both ormocer restorative systems was similar and clearly worse compared with the hybrid composite restorative one before as well as after load cycling. Concerning internal adaptation, no gap-free ormocer restorations were detected, whereas all Spectrum restorations presented perfect adaptation. The bonding agents of the ormocers formed layers with unacceptable features (pores, fractures) whereas that of the hybrid composite achieved perfect bonding layer even after loading. The rheological characteristics of the bonding agents of the ormocer restorative systems are proposed to be responsible for their inferior marginal and internal quality in Class II restorations compared with the hybrid composite one.

  10. 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.

  11. Adaptable Multivariate Calibration Models for Spectral Applications

    Energy Technology Data Exchange (ETDEWEB)

    THOMAS,EDWARD V.

    1999-12-20

    Multivariate calibration techniques have been used in a wide variety of spectroscopic situations. In many of these situations spectral variation can be partitioned into meaningful classes. For example, suppose that multiple spectra are obtained from each of a number of different objects wherein the level of the analyte of interest varies within each object over time. In such situations the total spectral variation observed across all measurements has two distinct general sources of variation: intra-object and inter-object. One might want to develop a global multivariate calibration model that predicts the analyte of interest accurately both within and across objects, including new objects not involved in developing the calibration model. However, this goal might be hard to realize if the inter-object spectral variation is complex and difficult to model. If the intra-object spectral variation is consistent across objects, an effective alternative approach might be to develop a generic intra-object model that can be adapted to each object separately. This paper contains recommendations for experimental protocols and data analysis in such situations. The approach is illustrated with an example involving the noninvasive measurement of glucose using near-infrared reflectance spectroscopy. Extensions to calibration maintenance and calibration transfer are discussed.

  12. 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.

  13. 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).

  14. An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

    Science.gov (United States)

    Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

    2008-01-01

    This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

  15. 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.

  16. 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.

  17. Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler

    Directory of Open Access Journals (Sweden)

    Zhenhao Tang

    2017-01-01

    Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.

  18. Resource allocation among sexual, clonal reproduction and vegetative growth of two Potamogeton species and their hybrid:Adaptability of the hybrid in relation to its parents

    Institute of Scientific and Technical Information of China (English)

    Fan LIU; Xiao-Lin ZHANG; Qing-Feng WANG; Hui LIU; Guang-Xi WANG; Wei LI

    2013-01-01

    Resource allocation,as well as the tradeoffs among different reproductive components,plays an important role in the adaptability of plants to different environments.The hybrid may exhibit a higher adaptability in life history in heterogeneous environments because of the genetic variation derived from its parents.In this study,we exploited three levels of water depths and two types of sediments to investigate the resource allocation pattern of the first generation of the natural hybrid Potamogeton × intortifolius compared to its parents P.wrightii and P.perfoliatus.We also measured the ramet survivorship and the seed set of the hybrid P.× intortifolius.Our results showed that P.×intortifolius had higher ramet survival than its parents at 1.5-m water depth on clay sediment.The possible tradeoffs showed that in P.×intortifolius the tradeoff pattern between sexual and clonal reproduction was more pronounced in limiting environments.The individuals allocated more resources to sexual reproduction when the environment was limiting,which might confer a higher ability to utilize resources,to produce offspring and to found new populations.Although the seed set of P.×intortifolius was lower than its parents,it had a higher ability to increase its seed set when the environment was limiting (sandy sediment) than its parents,which might benefit its future survival.These results indicated that the F1 hybrid P.×intortifolius was more able to adapt to limiting environments than one or both of its two parental taxa.

  19. Adaptive filtering for deformation parameter estimation in consideration of geometrical measurements and geophysical models

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    There are two kinds of methods in researching the crust deformation: geophysical method and geometrical (or observational) method. Considerable differences usually exist between the two kinds of results, because of the datum differences, geophysical model errors, observational model errors, and so on. Thus, it is reasonable to combine the two kinds of information to collect the crust deformation information. To use the reliable geometrical and geophysical information, we have to control the observational and geophysical model error influences on the estimated deformation parameters, and to balance their contributions to the evaluated parameters. A hybrid estimation strategy is proposed here for evaluating the deformation parameters employing an adaptively robust filtering. The effects of measurement outliers on the estimated parameters are controlled by robust equivalent weights. Adaptive factors are introduced to balance the contribution of the geophysical model information and the geometrical measurements to the model parameters. The datum for the local deformation analysis is mainly determined by the highly accurate IGS station velocities. The hybrid estimation strategy is applied in an actual GPS monitoring network. It is shown that the hybrid technique employs locally repeated geometrical displacements to reduce the displacement errors caused by the mis-modeling of geophysical technique, and thus improves the precision of the estimated crust deformation parameters.

  20. 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.

  1. Adaptation of indeterminate tomato hybrids [Solanum lycopersicum L. (Mill.] under greenhouse conditions

    Directory of Open Access Journals (Sweden)

    Gabriel Julio

    2016-08-01

    Full Text Available Were evaluated 11 hybrids of indeterminate tomato company by ENZA ZADEN and a witness of the company SEMINIS, under greenhouse and laboratory with the objectives of: i evaluate and participatory select 11 new hybrids of indeterminate tomato company ENZA ZADEN by adaptation, agronomic and health in the crop cycle, in harvest and post-harvest and ii implement farmers with entrepreneurial char-acteristics, business participatory hybrids selected indeterminate tomatoes. The results showed that varie-ties with higher number of fruits and yield were Shannon and Afamia between type beef (round and Granadero between pears. The round varieties had a higher average yield of pears. Pears are a number of varieties had higher than average round fruits. There was a high positive correlation between the number of fruits and yield both pears and round. The varieties with higher fruit weight were Bruni (between the round and Centenario, Granadero and (from pears. Fruit weight in time is reduced linearly for all varie-ties except Corleone. The round variety with greater firmness fruit was Shannon. There was no difference in firmness between the pears. The firmness of fruit reduced linearly time for Bruni, Elpida, Hechicero, Rally, Centenario, Corleone and varieties and reduces linearly but increases quadratically for Maradona and Shannon varieties. The varieties that reduced fruit firmness were slower Corleone, Centenario and Afamia. The varieties with lower pH were Afamia (between the rounds and Centenario and Granadero (from pears. The pH increases over time in linear form in all varieties. The varieties with higher content of Brix were Hechicero, Afamia, Granadero, Elpida, Rally, Maradona and Sebatina (between the rounds and Corleone (from pears. Brix content increases linearly over time in all varieties. There were high and positive significant correlations between Brix and pH; weight and firmness of fruit. Participatory selection of varieties Elpida, Rally

  2. Hybrid internal model control and proportional control of chaotic dynamical systems

    Institute of Scientific and Technical Information of China (English)

    齐冬莲; 姚良宾

    2004-01-01

    A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.

  3. Hybrid internal model control and proportional control of chaotic dynamical systems.

    Science.gov (United States)

    Qi, Dong-lian; Yao, Liang-bin

    2004-01-01

    A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.

  4. 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

  5. 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.

  6. 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.

  7. Hybrid Data Hiding Scheme Using Right-Most Digit Replacement and Adaptive Least Significant Bit for Digital Images

    Directory of Open Access Journals (Sweden)

    Mehdi Hussain

    2016-05-01

    Full Text Available The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR with an adaptive least significant bit (ALSB is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns and higher texture (asymmetry patterns areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images are conducted with recent least significant bit (LSB-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR.

  8. 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.

  9. 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

  10. Use of adaptive hybrid filtering process in Crohn's disease lesion detection from real capsule endoscopy videos.

    Science.gov (United States)

    Charisis, Vasileios S; Hadjileontiadis, Leontios J

    2016-03-01

    The aim of this Letter is to present a new capsule endoscopy (CE) image analysis scheme for the detection of small bowel ulcers that relate to Crohn's disease. More specifically, this scheme is based on: (i) a hybrid adaptive filtering (HAF) process, that utilises genetic algorithms to the curvelet-based representation of images for efficient extraction of the lesion-related morphological characteristics, (ii) differential lacunarity (DL) analysis for texture feature extraction from the HAF-filtered images and (iii) support vector machines for robust classification performance. For the training of the proposed scheme, namely HAF-DL, an 800-image database was used and the evaluation was based on ten 30-second long endoscopic videos. Experimental results, along with comparison with other related efforts, have shown that the HAF-DL approach evidently outperforms the latter in the field of CE image analysis for automated lesion detection, providing higher classification results. The promising performance of HAF-DL paves the way for a complete computer-aided diagnosis system that could support the physicians' clinical practice.

  11. Potential of hybrid adaptive filtering in inflammatory lesion detection from capsule endoscopy images.

    Science.gov (United States)

    Charisis, Vasileios S; Hadjileontiadis, Leontios J

    2016-10-21

    A new feature extraction technique for the detection of lesions created from mucosal inflammations in Crohn's disease, based on wireless capsule endoscopy (WCE) images processing is presented here. More specifically, a novel filtering process, namely Hybrid Adaptive Filtering (HAF), was developed for efficient extraction of lesion-related structural/textural characteristics from WCE images, by employing Genetic Algorithms to the Curvelet-based representation of images. Additionally, Differential Lacunarity (DLac) analysis was applied for feature extraction from the HAF-filtered images. The resulted scheme, namely HAF-DLac, incorporates support vector machines for robust lesion recognition performance. For the training and testing of HAF-DLac, an 800-image database was used, acquired from 13 patients who undertook WCE examinations, where the abnormal cases were grouped into mild and severe, according to the severity of the depicted lesion, for a more extensive evaluation of the performance. Experimental results, along with comparison with other related efforts, have shown that the HAF-DLac approach evidently outperforms them in the field of WCE image analysis for automated lesion detection, providing higher classification results, up to 93.8% (accuracy), 95.2% (sensitivity), 92.4% (specificity) and 92.6% (precision). The promising performance of HAF-DLac paves the way for a complete computer-aided diagnosis system that could support physicians' clinical practice.

  12. Targeted nucleotide editing using hybrid prokaryotic and vertebrate adaptive immune systems.

    Science.gov (United States)

    Nishida, Keiji; Arazoe, Takayuki; Yachie, Nozomu; Banno, Satomi; Kakimoto, Mika; Tabata, Mayura; Mochizuki, Masao; Miyabe, Aya; Araki, Michihiro; Hara, Kiyotaka Y; Shimatani, Zenpei; Kondo, Akihiko

    2016-09-16

    The generation of genetic variation (somatic hypermutation) is an essential process for the adaptive immune system in vertebrates. We demonstrate the targeted single-nucleotide substitution of DNA using hybrid vertebrate and bacterial immune systems components. Nuclease-deficient type II CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated) and the activation-induced cytidine deaminase (AID) ortholog PmCDA1 were engineered to form a synthetic complex (Target-AID) that performs highly efficient target-specific mutagenesis. Specific point mutation was induced primarily at cytidines within the target range of five bases. The toxicity associated with the nuclease-based CRISPR/Cas9 system was greatly reduced. Although combination of nickase Cas9(D10A) and the deaminase was highly effective in yeasts, it also induced insertion and deletion (indel) in mammalian cells. Use of uracil DNA glycosylase inhibitor suppressed the indel formation and improved the efficiency. Copyright © 2016, American Association for the Advancement of Science.

  13. First carrot, then stick: how the adaptive hybridization of incentives promotes cooperation

    Science.gov (United States)

    Chen, Xiaojie; Sasaki, Tatsuya; Brännström, Åke; Dieckmann, Ulf

    2015-01-01

    Social institutions often use rewards and penalties to promote cooperation. Providing incentives tends to be costly, so it is important to find effective and efficient policies for the combined use of rewards and penalties. Most studies of cooperation, however, have addressed rewarding and punishing in isolation and have focused on peer-to-peer sanctioning as opposed to institutional sanctioning. Here, we demonstrate that an institutional sanctioning policy we call ‘first carrot, then stick’ is unexpectedly successful in promoting cooperation. The policy switches the incentive from rewarding to punishing when the frequency of cooperators exceeds a threshold. We find that this policy establishes and recovers full cooperation at lower cost and under a wider range of conditions than either rewards or penalties alone, in both well-mixed and spatial populations. In particular, the spatial dynamics of cooperation make it evident how punishment acts as a ‘booster stage’ that capitalizes on and amplifies the pro-social effects of rewarding. Together, our results show that the adaptive hybridization of incentives offers the ‘best of both worlds’ by combining the effectiveness of rewarding in establishing cooperation with the effectiveness of punishing in recovering it, thereby providing a surprisingly inexpensive and widely applicable method of promoting cooperation. PMID:25551138

  14. AN INDUCTIVE, INTERACTIVE AND ADAPTIVE HYBRID PROBLEM-BASED LEARNING METHODOLOGY: APPLICATION TO STATISTICS

    Directory of Open Access Journals (Sweden)

    ADA ZHENG

    2011-10-01

    Full Text Available We have developed an innovative hybrid problem-based learning (PBL methodology. The methodology has the following distinctive features: i Each complex question was decomposed into a set of coherent finer subquestions by following the carefully designed criteria to maintain a delicate balance between guiding the students and inspiring them to think independently. This learning methodology enabled the students to solve the complex questions progressively in an inductive context. ii Facilitated by the utilization of our web-based learning systems, the teacher was able to interact with the students intensively and could allocate more teaching time to provide tailor-made feedback for individual student. The students were actively engaged in the learning activities, stimulated by the intensive interaction. iii The answers submitted by the students could be automatically consolidated in the report of the Moodle system in real-time. The teacher could adjust the teaching schedule and focus of the class to adapt to the learning progress of the students by analysing the automatically generated report and log files of the web-based learning system. As a result, the attendance rate of the students increased from about 50% to more than 90%, and the students’ learning motivation have been significantly enhanced.

  15. Adaptation of hybrid human-computer interaction systems using EEG error-related potentials.

    Science.gov (United States)

    Chavarriaga, Ricardo; Biasiucci, Andrea; Forster, Killian; Roggen, Daniel; Troster, Gerhard; Millan, Jose Del R

    2010-01-01

    Performance improvement in both humans and artificial systems strongly relies in the ability of recognizing erroneous behavior or decisions. This paper, that builds upon previous studies on EEG error-related signals, presents a hybrid approach for human computer interaction that uses human gestures to send commands to a computer and exploits brain activity to provide implicit feedback about the recognition of such commands. Using a simple computer game as a case study, we show that EEG activity evoked by erroneous gesture recognition can be classified in single trials above random levels. Automatic artifact rejection techniques are used, taking into account that subjects are allowed to move during the experiment. Moreover, we present a simple adaptation mechanism that uses the EEG signal to label newly acquired samples and can be used to re-calibrate the gesture recognition system in a supervised manner. Offline analysis show that, although the achieved EEG decoding accuracy is far from being perfect, these signals convey sufficient information to significantly improve the overall system performance.

  16. Cost analysis of hybrid adaptive routing protocol for heterogeneous wireless sensor network

    Indian Academy of Sciences (India)

    NONITA SHARMA; AJAY K SHARMA

    2016-03-01

    This study aims to explore the impact of heterogeneity on a hybrid algorithm called Multi Adaptive Filter Algorithm by constructing series of experiments. Here, the simulations were made between ‘Total Energy Spent’ and ‘Number of Sources’ considering temporal correlation. The results were drawn from the trace information generated using ‘Monte Carlo’ simulation methods. After keen analysis, the results show that different levels of heterogeneity are best suited for correlated event detections. Moreover, based on the conclusions drawn,it can be safely inferred that n-level heterogeneity reduces the total energy spent close to 60%. Further, cost analysis recommends that adding progressive nodes preserves the cost factor in the bracket of 230–280$/Joule. Thenovel approach can immensely help the future solution providers to overcome the battery limitations of wireless sensor networks. This study provides insights into designing heterogeneous wireless sensor networks and aims atproviding the cost-benefit analysis that can be used in selecting the critical parameters of the network.

  17. Hybrid collaborative optimization based on selection strategy of initial point and adaptive relaxation

    Energy Technology Data Exchange (ETDEWEB)

    Ji, Aimin; Yin, Xu; Yuan, Minghai [Hohai University, Changzhou (China)

    2015-09-15

    There are two problems in Collaborative optimization (CO): (1) the local optima arising from the selection of an inappropriate initial point; (2) the low efficiency and accuracy root in inappropriate relaxation factors. To solve these problems, we first develop the Latin hypercube design (LHD) to determine an initial point of optimization, and then use the non-linear programming by quadratic Lagrangian (NLPQL) to search for the global solution. The effectiveness of the initial point selection strategy is verified by three benchmark functions with some dimensions and different complexities. Then we propose the Adaptive relaxation collaborative optimization (ARCO) algorithm to solve the inconsistency between the system level and the disciplines level, and in this method, the relaxation factors are determined according to the three separated stages of CO respectively. The performance of the ARCO algorithm is compared with the standard collaborative algorithm and the constant relaxation collaborative algorithm with a typical numerical example, which indicates that the ARCO algorithm is more efficient and accurate. Finally, we propose a Hybrid collaborative optimization (HCO) approach, which integrates the selection strategy of initial point with the ARCO algorithm. The results show that HCO can achieve the global optimal solution without the initial value and it also has advantages in convergence, accuracy and robustness. Therefore, the proposed HCO approach can solve the CO problems with applications in the spindle and the speed reducer.

  18. The ADAPT design model: towards instructional control of transfer

    NARCIS (Netherlands)

    Jelsma, Otto; Merrienboer, van Jeroen J.G.; Bijlstra, Jim P.

    1990-01-01

    This paper presents a detailed description of the ADAPT (Apply Delayed Automatization for Positive Transfer) design model. ADAPT is based upon production system models of learning and provides guidelines for developing instructional systems that offer transfer of leamed skills. The model suggests th

  19. A theoretical adaptive model of thermal comfort - Adaptive Predicted Mean Vote (aPMV)

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Runming [School of Construction Management and Engineering, The University of Reading (United Kingdom); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Li, Baizhan [Key Laboratory of the Three Gorges Reservoir Region' s Eco-Environment (Ministry of Education), Chongqing University (China); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Liu, Jing [School of Construction Management and Engineering, The University of Reading (United Kingdom)

    2009-10-15

    This paper presents in detail a theoretical adaptive model of thermal comfort based on the ''Black Box'' theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient ({lambda}) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results. (author)

  20. 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.

  1. 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.

  2. 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.

  3. Application of Cu-polyimide flex circuit and Al-on-glass pitch adapter for the ATLAS SCT barrel hybrid

    CERN Document Server

    Unno, Y; Ikegami, Y; Iwata, Y; Kohriki, T; Kondo, T; Nakano, I; Ohsugi, T; Takashima, R; Tanaka, R; Terada, S; Ujiie, N

    2005-01-01

    We applied the surface build-up Cu-polyimide flex-circuit technology with laser vias to the ATLAS SCT barrel hybrid to be made in one piece from the connector to the electronics sections including cables. The hybrids, reinforced with carbon-carbon substrates, provide mechanical strength, thermal conductivity, low-radiation length, and stability in application-specific integrated circuit (ASIC) operation. By following the design rules, we experienced little trouble in breaking the traces. The pitch adapter between the sensor and the ASICs was made of aluminum traces on glass substrate. We identified that the generation of whiskers around the wire-bonding feet was correlated with the hardness of metallized aluminum. The appropriate hardness has been achieved by keeping the temperature of the glasses as low as room temperature during the metallization. The argon plasma cleaning procedure cleaned the contamination on the gold pads of the hybrids for successful wire bonding, although it was unsuccessful in the alu...

  4. 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.

  5. 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.

  6. Assessment of fusion facility dose rate map using mesh adaptivity enhancements of hybrid Monte Carlo/deterministic techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ibrahim, Ahmad M., E-mail: ibrahimam@ornl.gov [Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831 (United States); Wilson, Paul P. [University of Wisconsin-Madison, 1500 Engineering Dr., Madison, WI 53706 (United States); Sawan, Mohamed E., E-mail: sawan@engr.wisc.edu [University of Wisconsin-Madison, 1500 Engineering Dr., Madison, WI 53706 (United States); Mosher, Scott W.; Peplow, Douglas E.; Grove, Robert E. [Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831 (United States)

    2014-10-15

    Highlights: •Calculate the prompt dose rate everywhere throughout the entire fusion energy facility. •Utilize FW-CADIS to accurately perform difficult neutronics calculations for fusion energy systems. •Develop three mesh adaptivity algorithms to enhance FW-CADIS efficiency in fusion-neutronics calculations. -- Abstract: Three mesh adaptivity algorithms were developed to facilitate and expedite the use of the CADIS and FW-CADIS hybrid Monte Carlo/deterministic techniques in accurate full-scale neutronics simulations of fusion energy systems with immense sizes and complicated geometries. First, a macromaterial approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as much geometric detail as possible without exceeding a specified maximum number of mesh elements. Finally, a weight window coarsening algorithm decouples the weight window mesh and energy bins from the mesh and energy group structure of the deterministic calculations in order to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to enhance an FW-CADIS calculation of the prompt dose rate throughout the ITER experimental facility and resulted in a 23.3% increase in the number of mesh tally elements in which the dose rates were calculated in a 10-day Monte Carlo calculation. Additionally, because of the significant increase in the efficiency of FW-CADIS simulations, the three algorithms enabled this difficult calculation to be accurately solved on a regular computer cluster, eliminating the need for a world-class super computer.

  7. 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...

  8. 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.

  9. (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.

  10. 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.…

  11. 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…

  12. 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.

  13. Modeling level change in Lake Urmia using hybrid artificial intelligence approaches

    Science.gov (United States)

    Esbati, M.; Ahmadieh Khanesar, M.; Shahzadi, Ali

    2017-06-01

    The investigation of water level fluctuations in lakes for protecting them regarding the importance of these water complexes in national and regional scales has found a special place among countries in recent years. The importance of the prediction of water level balance in Lake Urmia is necessary due to several-meter fluctuations in the last decade which help the prevention from possible future losses. For this purpose, in this paper, the performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the lake water level balance has been studied. In addition, for the training of the adaptive neuro-fuzzy inference system, particle swarm optimization (PSO) and hybrid backpropagation-recursive least square method algorithm have been used. Moreover, a hybrid method based on particle swarm optimization and recursive least square (PSO-RLS) training algorithm for the training of ANFIS structure is introduced. In order to have a more fare comparison, hybrid particle swarm optimization and gradient descent are also applied. The models have been trained, tested, and validated based on lake level data between 1991 and 2014. For performance evaluation, a comparison is made between these methods. Numerical results obtained show that the proposed methods with a reasonable error have a good performance in water level balance prediction. It is also clear that with continuing the current trend, Lake Urmia will experience more drop in the water level balance in the upcoming years.

  14. Modeling of processes of an adaptive business management

    OpenAIRE

    Karev Dmitry Vladimirovich; Karev Vladimir Petrovich

    2011-01-01

    On the basis of the analysis of systems of adaptive management board business proposed the original version of the real system of adaptive management, the basis of which used dynamic recursive model cash flow forecast and real data. Proposed definitions and the simulation of scales and intervals of model time in the control system, as well as the thresholds observations and conditions of changing (correction) of the administrative decisions. The process of adaptive management is illustrated o...

  15. 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.

  16. 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.

  17. Aerosol model selection and uncertainty modelling by adaptive MCMC technique

    Directory of Open Access Journals (Sweden)

    M. Laine

    2008-12-01

    Full Text Available We present a new technique for model selection problem in atmospheric remote sensing. The technique is based on Monte Carlo sampling and it allows model selection, calculation of model posterior probabilities and model averaging in Bayesian way.

    The algorithm developed here is called Adaptive Automatic Reversible Jump Markov chain Monte Carlo method (AARJ. It uses Markov chain Monte Carlo (MCMC technique and its extension called Reversible Jump MCMC. Both of these techniques have been used extensively in statistical parameter estimation problems in wide area of applications since late 1990's. The novel feature in our algorithm is the fact that it is fully automatic and easy to use.

    We show how the AARJ algorithm can be implemented and used for model selection and averaging, and to directly incorporate the model uncertainty. We demonstrate the technique by applying it to the statistical inversion problem of gas profile retrieval of GOMOS instrument on board the ENVISAT satellite. Four simple models are used simultaneously to describe the dependence of the aerosol cross-sections on wavelength. During the AARJ estimation all the models are used and we obtain a probability distribution characterizing how probable each model is. By using model averaging, the uncertainty related to selecting the aerosol model can be taken into account in assessing the uncertainty of the estimates.

  18. 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...

  19. 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 ...

  20. Adaptive multi-rate interface: development and experimental verification for real-time hybrid simulation

    DEFF Research Database (Denmark)

    Maghareh, Amin; Waldbjørn, Jacob Paamand; Dyke, Shirley J.;

    2016-01-01

    Real-time hybrid simulation (RTHS) is a powerful cyber-physical technique that is a relatively cost-effective method to perform global/local system evaluation of structural systems. A major factor that determines the ability of an RTHS to represent true system-level behavior is the fidelity...... it employs different time steps in the numerical and the physical substructures while including rate-transitioning to link the components appropriately. Typically, a higher-order numerical substructure model is solved at larger time intervals, and is coupled with a physical substructure that is driven...... frequency between the numerical and physical substructures and for input signals with high-frequency content. Further, it does not induce signal chattering at the coupling frequency. The effectiveness of AMRI is also verified experimentally....

  1. Hybrid Parallel Programming Models for AMR Neutron Monte-Carlo Transport

    Science.gov (United States)

    Dureau, David; Poëtte, Gaël

    2014-06-01

    This paper deals with High Performance Computing (HPC) applied to neutron transport theory on complex geometries, thanks to both an Adaptive Mesh Refinement (AMR) algorithm and a Monte-Carlo (MC) solver. Several Parallelism models are presented and analyzed in this context, among them shared memory and distributed memory ones such as Domain Replication and Domain Decomposition, together with Hybrid strategies. The study is illustrated by weak and strong scalability tests on complex benchmarks on several thousands of cores thanks to the petaflopic supercomputer Tera100.

  2. 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.

  3. 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}).

  4. Fuzzy Adaptive Model Following Speed Control for Vector Controlled Permanent Magnet Synchronous Motor

    Directory of Open Access Journals (Sweden)

    Baghdad BELABES

    2008-12-01

    Full Text Available In this paper a hybrid controller combining a linear model following controller (LMFC and fuzzy logic control (FLC for speed vector controlled permanent magnet synchronous motor (PMSM is described on this study. The FLC is introduced at the adaptive mechanism level. First, an LMFC system is designed to allow the plant states to be controlled to follow the states produced by a reference model. In the nominal conditions, the model following is perfect and the adaptive mechanism based on the fuzzy logic is idle. Secondly, when parameter variations or external disturbances occur, an augmented signal will be generated by FLC mechanism to preserve the desired model following control performance. The effectiveness and robustness of the proposed controller is demonstrated by some simulation results.

  5. Prediction of Rolling Force Using AN Adaptive Neural Network Model during Cold Rolling of Thin Strip

    Science.gov (United States)

    Xie, H. B.; Jiang, Z. Y.; Tieu, A. K.; Liu, X. H.; Wang, G. D.

    Customers for cold rolled strip products expect the good flatness and surface finish, consistent metallurgical properties and accurate strip thickness. These requirements demand accurate prediction model for rolling parameters. This paper presents a set-up optimization system developed to predict the rolling force during cold strip rolling. As the rolling force has the very nonlinear and time-varying characteristics, conventional methods with simple mathematical models and a coarse learning scheme are not sufficient to achieve a good prediction for rolling force. In this work, all the factors that influence the rolling force are analyzed. A hybrid mathematical roll force model and an adaptive neural network have been improved by adjusting the adaptive learning algorithm. A good agreement between the calculated results and measured values verifies that the approach is applicable in the prediction of rolling force during cold rolling of thin strips, and the developed model is efficient and stable.

  6. Adaptable Authentication Model: Exploring Security with Weaker Attacker Models

    DEFF Research Database (Denmark)

    Ahmed, Naveed; Jensen, Christian D.

    2011-01-01

    suffer because of the identified vulnerabilities. Therefore, we may need to analyze a protocol for weaker notions of security. In this paper, we present a security model that supports such weaker notions. In this model, the overall goals of an authentication protocol are broken into a finer granularity......; for each fine level authentication goal, we determine the “least strongest-attacker” for which the authentication goal can be satisfied. We demonstrate that this model can be used to reason about the security of supposedly insecure protocols. Such adaptability is particularly useful in those applications......Most methods for protocol analysis classify protocols as “broken” if they are vulnerable to attacks from a strong attacker, e.g., assuming the Dolev-Yao attacker model. In many cases, however, exploitation of existing vulnerabilities may not be practical and, moreover, not all applications may...

  7. LIMIT THEOREMS AND OPTIMAL DESIGN WITH ADAPTIVE URN MODELS

    Institute of Scientific and Technical Information of China (English)

    CHEN Guijing; ZHU Chunhua; WANG Yao-hung

    2005-01-01

    In this paper we study urn model, using some available estimates of successes probabilities, and adding particle parameter, we establish adaptive models. We obtain some strong convergence theorems, rates of convergence, asymptotic normality of components in the urn, and estimates. With these asymptotical results, we show that the adaptive designs given in this paper are asymptotically optimal designs.

  8. 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 $T$.

  9. 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.

  10. Using field theory to construct hybrid particle-continuum simulation schemes with adaptive resolution for soft matter systems

    OpenAIRE

    Qi, Shuanhu; Behringer, Hans; Schmid, Friederike

    2013-01-01

    We develop a multiscale hybrid scheme for simulations of soft condensed matter systems, which allows one to treat the system at the particle level in selected regions of space, and at the continuum level elsewhere. It is derived systematically from an underlying particle-based model by field theoretic methods. Particles in different representation regions can switch representations on the fly, controlled by a spatially varying tuning function. As a test case, the hybrid scheme is applied to s...

  11. 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...

  12. 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.

  13. Hybrid feedback feedforward: An efficient design of adaptive neural network control.

    Science.gov (United States)

    Pan, Yongping; Liu, Yiqi; Xu, Bin; Yu, Haoyong

    2016-04-01

    This paper presents an efficient hybrid feedback feedforward (HFF) adaptive approximation-based control (AAC) strategy for a class of uncertain Euler-Lagrange systems. The control structure includes a proportional-derivative (PD) control term in the feedback loop and a radial-basis-function (RBF) neural network (NN) in the feedforward loop, which mimics the human motor learning control mechanism. At the presence of discontinuous friction, a sigmoid-jump-function NN is incorporated to improve control performance. The major difference of the proposed HFF-AAC design from the traditional feedback AAC (FB-AAC) design is that only desired outputs, rather than both tracking errors and desired outputs, are applied as RBF-NN inputs. Yet, such a slight modification leads to several attractive properties of HFF-AAC, including the convenient choice of an approximation domain, the decrease of the number of RBF-NN inputs, and semiglobal practical asymptotic stability dominated by control gains. Compared with previous HFF-AAC approaches, the proposed approach possesses the following two distinctive features: (i) all above attractive properties are achieved by a much simpler control scheme; (ii) the bounds of plant uncertainties are not required to be known. Consequently, the proposed approach guarantees a minimum configuration of the control structure and a minimum requirement of plant knowledge for the AAC design, which leads to a sharp decrease of implementation cost in terms of hardware selection, algorithm realization and system debugging. Simulation results have demonstrated that the proposed HFF-AAC can perform as good as or even better than the traditional FB-AAC under much simpler control synthesis and much lower computational cost.

  14. Optimal setting of FACTS devices for voltage stability improvement using PSO adaptive GSA hybrid algorithm

    Directory of Open Access Journals (Sweden)

    Sai Ram Inkollu

    2016-09-01

    Full Text Available This paper presents a novel technique for optimizing the FACTS devices, so as to maintain the voltage stability in the power transmission systems. Here, the particle swarm optimization algorithm (PSO and the adaptive gravitational search algorithm (GSA technique are proposed for improving the voltage stability of the power transmission systems. In the proposed approach, the PSO algorithm is used for optimizing the gravitational constant and to improve the searching performance of the GSA. Using the proposed technique, the optimal settings of the FACTS devices are determined. The proposed algorithm is an effective method for finding out the optimal location and the sizing of the FACTS controllers. The optimal locations and the power ratings of the FACTS devices are determined based on the voltage collapse rating as well as the power loss of the system. Here, two FACTS devices are used to evaluate the performance of the proposed algorithm, namely, the unified power flow controller (UPFC and the interline power flow controller (IPFC. The Newton–Raphson load flow study is used for analyzing the power flow in the transmission system. From the power flow analysis, bus voltages, active power, reactive power, and power loss of the transmission systems are determined. Then, the voltage stability is enhanced while satisfying a given set of operating and physical constraints. The proposed technique is implemented in the MATLAB platform and consequently, its performance is evaluated and compared with the existing GA based GSA hybrid technique. The performance of the proposed technique is tested with the benchmark system of IEEE 30 bus using two FACTS devices such as, the UPFC and the IPFC.

  15. Three-dimensional hierarchical cultivation of human skin cells on bio-adaptive hybrid fibers.

    Science.gov (United States)

    Planz, Viktoria; Seif, Salem; Atchison, Jennifer S; Vukosavljevic, Branko; Sparenberg, Lisa; Kroner, Elmar; Windbergs, Maike

    2016-07-11

    The human skin comprises a complex multi-scale layered structure with hierarchical organization of different cells within the extracellular matrix (ECM). This supportive fiber-reinforced structure provides a dynamically changing microenvironment with specific topographical, mechanical and biochemical cell recognition sites to facilitate cell attachment and proliferation. Current advances in developing artificial matrices for cultivation of human cells concentrate on surface functionalizing of biocompatible materials with different biomolecules like growth factors to enhance cell attachment. However, an often neglected aspect for efficient modulation of cell-matrix interactions is posed by the mechanical characteristics of such artificial matrices. To address this issue, we fabricated biocompatible hybrid fibers simulating the complex biomechanical characteristics of native ECM in human skin. Subsequently, we analyzed interactions of such fibers with human skin cells focusing on the identification of key fiber characteristics for optimized cell-matrix interactions. We successfully identified the mediating effect of bio-adaptive elasto-plastic stiffness paired with hydrophilic surface properties as key factors for cell attachment and proliferation, thus elucidating the synergistic role of these parameters to induce cellular responses. Co-cultivation of fibroblasts and keratinocytes on such fiber mats representing the specific cells in dermis and epidermis resulted in a hierarchical organization of dermal and epidermal tissue layers. In addition, terminal differentiation of keratinocytes at the air interface was observed. These findings provide valuable new insights into cell behaviour in three-dimensional structures and cell-material interactions which can be used for rational development of bio-inspired functional materials for advanced biomedical applications.

  16. 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.

  17. ADAPTIVE MODEL REFINEMENT FOR THE IONOSPHERE AND THERMOSPHERE

    Data.gov (United States)

    National Aeronautics and Space Administration — ADAPTIVE MODEL REFINEMENT FOR THE IONOSPHERE AND THERMOSPHERE ANTHONY M. D’AMATO∗, AARON J. RIDLEY∗∗, AND DENNIS S. BERNSTEIN∗∗∗ Abstract. Mathematical models of...

  18. Gradient-based adaptation of continuous dynamic model structures

    Science.gov (United States)

    La Cava, William G.; Danai, Kourosh

    2016-01-01

    A gradient-based method of symbolic adaptation is introduced for a class of continuous dynamic models. The proposed model structure adaptation method starts with the first-principles model of the system and adapts its structure after adjusting its individual components in symbolic form. A key contribution of this work is its introduction of the model's parameter sensitivity as the measure of symbolic changes to the model. This measure, which is essential to defining the structural sensitivity of the model, not only accommodates algebraic evaluation of candidate models in lieu of more computationally expensive simulation-based evaluation, but also makes possible the implementation of gradient-based optimisation in symbolic adaptation. The proposed method is applied to models of several virtual and real-world systems that demonstrate its potential utility.

  19. 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.

  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. Hierarchical Fault Diagnosis for a Hybrid System Based on a Multidomain Model

    Directory of Open Access Journals (Sweden)

    Jiming Ma

    2015-01-01

    Full Text Available The diagnosis procedure is performed by integrating three steps: multidomain modeling, event identification, and failure event classification. Multidomain model can describe the normal and fault behaviors of hybrid systems efficiently and can meet the diagnosis requirements of hybrid systems. Then the multidomain model is used to simulate and obtain responses under different failure events; the responses are further utilized as a priori information when training the event identification library. Finally, a brushless DC motor is selected as the study case. The experimental result indicates that the proposed method could identify the known and unknown failure events of the studied system. In particular, for a system with less response information under a failure event, the accuracy of diagnosis seems to be higher. The presented method integrates the advantages of current quantitative and qualitative diagnostic procedures and can distinguish between failures caused by parametric and abrupt structure faults. Another advantage of our method is that it can remember unknown failure types and automatically extend the adaptive resonance theory neural network library, which is extremely useful for complex hybrid systems.

  2. 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.

  3. 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.

  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. 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...

  10. 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.

  11. 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

  12. Histogram Equalization to Model Adaptation for Robust Speech Recognition

    Directory of Open Access Journals (Sweden)

    Hoirin Kim

    2010-01-01

    Full Text Available We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization algorithm on a single utterance basis. For more robust speech recognition in the heavily noisy conditions, trained acoustic covariance models are efficiently adapted by the signal-to-noise ratio-dependent linear interpolation between trained covariance models and utterance-level sample covariance models. Speech recognition experiments on both the digit-based Aurora2 task and the large vocabulary-based task showed that the proposed model adaptation approach provides significant performance improvements compared to the baseline speech recognizer trained on the clean speech data.

  13. Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations

    KAUST Repository

    Rached, Nadhir B.

    2013-12-01

    The Monte Carlo forward Euler method with uniform time stepping is the standard technique to compute an approximation of the expected payoff of a solution of an Itô SDE. For a given accuracy requirement TOL, the complexity of this technique for well behaved problems, that is the amount of computational work to solve the problem, is O(TOL-3). A new hybrid adaptive Monte Carlo forward Euler algorithm for SDEs with non-smooth coefficients and low regular observables is developed in this thesis. This adaptive method is based on the derivation of a new error expansion with computable leading-order terms. The basic idea of the new expansion is the use of a mixture of prior information to determine the weight functions and posterior information to compute the local error. In a number of numerical examples the superior efficiency of the hybrid adaptive algorithm over the standard uniform time stepping technique is verified. When a non-smooth binary payoff with either GBM or drift singularity type of SDEs is considered, the new adaptive method achieves the same complexity as the uniform discretization with smooth problems. Moreover, the new developed algorithm is extended to the MLMC forward Euler setting which reduces the complexity from O(TOL-3) to O(TOL-2(log(TOL))2). For the binary option case with the same type of Itô SDEs, the hybrid adaptive MLMC forward Euler recovers the standard multilevel computational cost O(TOL-2(log(TOL))2). When considering a higher order Milstein scheme, a similar complexity result was obtained by Giles using the uniform time stepping for one dimensional SDEs. The difficulty to extend Giles\\' Milstein MLMC method to the multidimensional case is an argument for the flexibility of our new constructed adaptive MLMC forward Euler method which can be easily adapted to this setting. Similarly, the expected complexity O(TOL-2(log(TOL))2) is reached for the multidimensional case and verified numerically.

  14. Overshooting dynamics in a model adaptive radiation

    NARCIS (Netherlands)

    Meyer, J.R.; Schoustra, S.E.; LaChapelle, J.; Kassen, R.K.

    2011-01-01

    The history of life is punctuated by repeated periods of unusually rapid evolutionary diversification called adaptive radiation. The dynamics of diversity during a radiation reflect an overshooting pattern with an initial phase of exponential-like increase followed by a slower decline. Much

  15. 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.

  16. 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.)

  17. 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.

  18. ADAPTIVE LEARNING OF HIDDEN MARKOV MODELS FOR EMOTIONAL SPEECH

    Directory of Open Access Journals (Sweden)

    A. V. Tkachenia

    2014-01-01

    Full Text Available An on-line unsupervised algorithm for estimating the hidden Markov models (HMM parame-ters is presented. The problem of hidden Markov models adaptation to emotional speech is solved. To increase the reliability of estimated HMM parameters, a mechanism of forgetting and updating is proposed. A functional block diagram of the hidden Markov models adaptation algorithm is also provided with obtained results, which improve the efficiency of emotional speech recognition.

  19. Hybrid transfinite element modeling/analysis of nonlinear heat conduction problems involving phase change

    Science.gov (United States)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

    The present paper describes the applicability of hybrid transfinite element modeling/analysis formulations for nonlinear heat conduction problems involving phase change. The methodology is based on application of transform approaches and classical Galerkin schemes with finite element formulations to maintain the modeling versatility and numerical features for computational analysis. In addition, in conjunction with the above, the effects due to latent heat are modeled using enthalpy formulations to enable a physically realistic approximation to be dealt computationally for materials exhibiting phase change within a narrow band of temperatures. Pertinent details of the approach and computational scheme adapted are described in technical detail. Numerical test cases of comparative nature are presented to demonstrate the applicability of the proposed formulations for numerical modeling/analysis of nonlinear heat conduction problems involving phase change.

  20. Hybrid models for the simulation of microstructural evolution influenced by coupled, multiple physical processes

    Energy Technology Data Exchange (ETDEWEB)

    Tikare, Veena [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hernandez-Rivera, Efrain [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Madison, Jonathan D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Holm, Elizabeth Ann [Carnegie Mellon Univ., Pittsburgh, PA (United States); Patterson, Burton R. [Univ. of Florida, Gainesville, FL (United States). Dept. of Materials Science and Engineering; Homer, Eric R. [Brigham Young Univ., Provo, UT (United States). Dept. of Mechanical Engineering

    2013-09-01

    Most materials microstructural evolution processes progress with multiple processes occurring simultaneously. In this work, we have concentrated on the processes that are active in nuclear materials, in particular, nuclear fuels. These processes are coarsening, nucleation, differential diffusion, phase transformation, radiation-induced defect formation and swelling, often with temperature gradients present. All these couple and contribute to evolution that is unique to nuclear fuels and materials. Hybrid model that combines elements from the Potts Monte Carlo, phase-field models and others have been developed to address these multiple physical processes. These models are described and applied to several processes in this report. An important feature of the models developed are that they are coded as applications within SPPARKS, a Sandiadeveloped framework for simulation at the mesoscale of microstructural evolution processes by kinetic Monte Carlo methods. This makes these codes readily accessible and adaptable for future applications.

  1. 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.

  2. MIP models and hybrid algorithms for simultaneous job splitting and scheduling on unrelated parallel machines.

    Science.gov (United States)

    Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk

    2014-01-01

    We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.

  3. Multiple-Model Adaptive Switching Control for Uncertain Multivariable Systems

    NARCIS (Netherlands)

    Baldi, Simone; Battistelli, Giorgio; Mari, Daniele; Mosca, Edoardo; Tesi, Pietro

    2011-01-01

    This paper addresses the problem of controlling an uncertain multi-input multi-output (MIMO) system by means of adaptive switching control schemes. In particular, the paper aims at extending the approach of multiple-model unfalsified adaptive switched control, so far restricted to single-input singl

  4. 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.

  5. 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...

  6. 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.

  7. 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...

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

    Science.gov (United States)

    Malin, Jane T.; Basham, Bryan D.

    1989-01-01

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

  9. 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.

  10. 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.

  11. Integration of variable-rate OWC with OFDM-PON for hybrid optical access based on adaptive envelope modulation

    Science.gov (United States)

    Chen, Chen; Zhong, Wen-De; Wu, Dehao

    2016-12-01

    In this paper, we investigate an integrated optical wireless communication (OWC) and orthogonal frequency division multiplexing based passive optical network (OFDM-PON) system for hybrid wired and wireless optical access, based on an adaptive envelope modulation technique. Both the outdoor and indoor wireless communications are considered in the integrated system. The data for wired access is carried by a conventional OFDM signal, while the data for wireless access is carried by an M-ary pulse amplitude modulation (M-PAM) signal which is modulated onto the envelope of a phase-modulated OFDM signal. By adaptively modulating the wireless M-PAM signal onto the envelope of the wired phase-modulated constant envelope OFDM (CE-OFDM) signal, hybrid wired and wireless optical access can be seamlessly integrated and variable-rate optical wireless transmission can also be achieved. Analytical bit-error-rate (BER) expressions are derived for both the CE-OFDM signal with M-PAM overlay and the overlaid unipolar M-PAM signal, which are verified by Monte Carlo simulations. The BER performances of wired access, indoor OWC wireless access and outdoor OWC wireless access are evaluated. Moreover, variable-rate indoor and outdoor optical wireless access based on the adaptive envelope modulation technique is also discussed.

  12. 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.

  13. Risk and efficacy of human-enabled interspecific hybridization for climate-change adaptation: Response to Hamilton and Miller (2016)

    Science.gov (United States)

    Kovach, Ryan P.; Luikart, Gordon; Lowe, Winsor H.; Boyer, Matthew C.; Muhlfeld, Clint C.

    2016-01-01

    Hamilton and Miller (2016) provide an interesting and provocative discussion of how hybridization and introgression can promote evolutionary potential in the face of climate change. They argue that hybridization—mating between individuals from genetically distinct populations—can alleviate inbreeding depression and promote adaptive introgression and evolutionary rescue. We agree that deliberate intraspecific hybridization (mating between individuals of the same species) is an underused management tool for increasing fitness in inbred populations (i.e., genetic rescue; Frankham 2015; Whiteley et al. 2015). The potential risks and benefits of assisted gene flow have been discussed in the literature, and an emerging consensus suggests that mating between populations isolated for approximately 50–100 generations can benefit fitness, often with a minor risk of outbreeding depression (Frankham et al. 2011; Aitken & Whitlock 2013; Allendorf et al. 2013).

  14. Hybrid Adaptive Multilevel Monte Carlo Algorithm for Non-Smooth Observables of Itô Stochastic Differential Equations

    KAUST Repository

    Rached, Nadhir B.

    2014-01-06

    A new hybrid adaptive MC forward Euler algorithm for SDEs with singular coefficients and non-smooth observables is developed. This adaptive method is based on the derivation of a new error expansion with computable leading order terms. When a non-smooth binary payoff is considered, the new adaptive method achieves the same complexity as the uniform discretization with smooth problems. Moreover, the new developed algorithm is extended to the multilevel Monte Carlo (MLMC) forward Euler setting which reduces the complexity from O(TOL-3) to O(TOL-2(log(TOL))2). For the binary option case, it recovers the standard multilevel computational cost O(TOL-2(log(TOL))2). When considering a higher order Milstein scheme, a similar complexity result was obtained by Giles using the uniform time stepping for one dimensional SDEs, see [2]. The difficulty to extend Giles’ Milstein MLMC method to the multidimensional case is an argument for the flexibility of our new constructed adaptive MLMC forward Euler method which can be easily adapted to this setting. Similarly, the expected complexity O(TOL-2(log(TOL))2) is reached for the multidimensional case and verified numerically.

  15. 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.

  16. 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.

  17. Modeling adaptation of carbon use efficiency in microbial communities

    Directory of Open Access Journals (Sweden)

    Steven D Allison

    2014-10-01

    Full Text Available In new microbial-biogeochemical models, microbial carbon use efficiency (CUE is often assumed to decline with increasing temperature. Under this assumption, soil carbon losses under warming are small because microbial biomass declines. Yet there is also empirical evidence that CUE may adapt (i.e. become less sensitive to warming, thereby mitigating negative effects on microbial biomass. To analyze potential mechanisms of CUE adaptation, I used two theoretical models to implement a tradeoff between microbial uptake rate and CUE. This rate-yield tradeoff is based on thermodynamic principles and suggests that microbes with greater investment in resource acquisition should have lower CUE. Microbial communities or individuals could adapt to warming by reducing investment in enzymes and uptake machinery. Consistent with this idea, a simple analytical model predicted that adaptation can offset 50% of the warming-induced decline in CUE. To assess the ecosystem implications of the rate-yield tradeoff, I quantified CUE adaptation in a spatially-structured simulation model with 100 microbial taxa and 12 soil carbon substrates. This model predicted much lower CUE adaptation, likely due to additional physiological and ecological constraints on microbes. In particular, specific resource acquisition traits are needed to maintain stoichiometric balance, and taxa with high CUE and low enzyme investment rely on low-yield, high-enzyme neighbors to catalyze substrate degradation. In contrast to published microbial models, simulations with greater CUE adaptation also showed greater carbon storage under warming. This pattern occurred because microbial communities with stronger CUE adaptation produced fewer degradative enzymes, despite increases in biomass. Thus the rate-yield tradeoff prevents CUE adaptation from driving ecosystem carbon loss under climate warming.

  18. Traffic flow characteristics in a mixed traffic system consisting of ACC vehicles and manual vehicles: A hybrid modelling approach

    Science.gov (United States)

    Yuan, Yao-Ming; Jiang, Rui; Hu, Mao-Bin; Wu, Qing-Song; Wang, Ruili

    2009-06-01

    In this paper, we have investigated traffic flow characteristics in a traffic system consisting of a mixture of adaptive cruise control (ACC) vehicles and manual-controlled (manual) vehicles, by using a hybrid modelling approach. In the hybrid approach, (i) the manual vehicles are described by a cellular automaton (CA) model, which can reproduce different traffic states (i.e., free flow, synchronised flow, and jam) as well as probabilistic traffic breakdown phenomena; (ii) the ACC vehicles are simulated by using a car-following model, which removes artificial velocity fluctuations due to intrinsic randomisation in the CA model. We have studied the traffic breakdown probability from free flow to congested flow, the phase transition probability from synchronised flow to jam in the mixed traffic system. The results are compared with that, where both ACC vehicles and manual vehicles are simulated by CA models. The qualitative and quantitative differences are indicated.

  19. 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.

  20. 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.

  1. Computational quantum chemistry and adaptive ligand modeling in mechanistic QSAR.

    Science.gov (United States)

    De Benedetti, Pier G; Fanelli, Francesca

    2010-10-01

    Drugs are adaptive molecules. They realize this peculiarity by generating different ensembles of prototropic forms and conformers that depend on the environment. Among the impressive amount of available computational drug discovery technologies, quantitative structure-activity relationship approaches that rely on computational quantum chemistry descriptors are the most appropriate to model adaptive drugs. Indeed, computational quantum chemistry descriptors are able to account for the variation of the intramolecular interactions of the training compounds, which reflect their adaptive intermolecular interaction propensities. This enables the development of causative, interpretive and reasonably predictive quantitative structure-activity relationship models, and, hence, sound chemical information finalized to drug design and discovery.

  2. 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...

  3. An adaptation model for trabecular bone at different mechanical levels

    Directory of Open Access Journals (Sweden)

    Lv Linwei

    2010-07-01

    Full Text Available Abstract Background Bone has the ability to adapt to mechanical usage or other biophysical stimuli in terms of its mass and architecture, indicating that a certain mechanism exists for monitoring mechanical usage and controlling the bone's adaptation behaviors. There are four zones describing different bone adaptation behaviors: the disuse, adaptation, overload, and pathologic overload zones. In different zones, the changes of bone mass, as calculated by the difference between the amount of bone formed and what is resorbed, should be different. Methods An adaptation model for the trabecular bone at different mechanical levels was presented in this study based on a number of experimental observations and numerical algorithms in the literature. In the proposed model, the amount of bone formation and the probability of bone remodeling activation were proposed in accordance with the mechanical levels. Seven numerical simulation cases under different mechanical conditions were analyzed as examples by incorporating the adaptation model presented in this paper with the finite element method. Results The proposed bone adaptation model describes the well-known bone adaptation behaviors in different zones. The bone mass and architecture of the bone tissue within the adaptation zone almost remained unchanged. Although the probability of osteoclastic activation is enhanced in the overload zone, the potential of osteoblasts to form bones compensate for the osteoclastic resorption, eventually strengthening the bones. In the disuse zone, the disuse-mode remodeling removes bone tissue in disuse zone. Conclusions The study seeks to provide better understanding of the relationships between bone morphology and the mechanical, as well as biological environments. Furthermore, this paper provides a computational model and methodology for the numerical simulation of changes of bone structural morphology that are caused by changes of mechanical and biological

  4. 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.

  5. 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

  6. 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

  7. 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

  8. 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

  9. Dosimetric and geometric evaluation of a hybrid strategy of offline adaptive planning and online image guidance for prostate cancer radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Liu Han; Wu Qiuwen, E-mail: Qiuwen.Wu@Duke.edu [Department of Radiation Oncology, Duke University Medical Center, Durham, NC 27710 (United States)

    2011-08-07

    For prostate cancer patients, online image-guided (IG) radiotherapy has been widely used in clinic to correct the translational inter-fractional motion at each treatment fraction. For uncertainties that cannot be corrected online, such as rotation and deformation of the target volume, margins are still required to be added to the clinical target volume (CTV) for the treatment planning. Offline adaptive radiotherapy has been implemented to optimize the treatment for each individual patient based on the measurements at early stages of treatment process. It has been shown that offline adaptive radiotherapy can effectively reduce the required margin. Recently a hybrid strategy of offline adaptive replanning and online IG was proposed and the geometric evaluation was performed. It was found that the planning margins can further be reduced by 1-2 mm compared to online IG only strategy. The purpose of this study was to investigate the dosimetric benefits of such a hybrid strategy on the target and organs at risk. A total of 420 repeated helical computed tomography scans from 28 patients were included in the study. Both low-risk patients (LRP, CTV = prostate) and intermediate-risk patients (IRP, CTV = prostate + seminal vesicles, SV) were included in the simulation. Two registration methods, based on center-of-mass shift of prostate only and prostate plus SV, were performed for IRP. The intensity-modulated radiotherapy was used in the simulation. Criteria on both cumulative and fractional doses were evaluated. Furthermore, the geometric evaluation was extended to investigate the optimal number of fractions necessary to construct the internal target volume (ITV) for the hybrid strategy. The dosimetric margin improvement was smaller than its geometric counterpart and was in the range of 0-1 mm. The optimal number of fractions necessary for the ITV construction is 2 for LRPs and 3-4 for IRPs in a hypofractionation protocol. A new cumulative index of target volume was proposed

  10. Dosimetric and geometric evaluation of a hybrid strategy of offline adaptive planning and online image guidance for prostate cancer radiotherapy

    Science.gov (United States)

    Liu, Han; Wu, Qiuwen

    2011-08-01

    For prostate cancer patients, online image-guided (IG) radiotherapy has been widely used in clinic to correct the translational inter-fractional motion at each treatment fraction. For uncertainties that cannot be corrected online, such as rotation and deformation of the target volume, margins are still required to be added to the clinical target volume (CTV) for the treatment planning. Offline adaptive radiotherapy has been implemented to optimize the treatment for each individual patient based on the measurements at early stages of treatment process. It has been shown that offline adaptive radiotherapy can effectively reduce the required margin. Recently a hybrid strategy of offline adaptive replanning and online IG was proposed and the geometric evaluation was performed. It was found that the planning margins can further be reduced by 1-2 mm compared to online IG only strategy. The purpose of this study was to investigate the dosimetric benefits of such a hybrid strategy on the target and organs at risk. A total of 420 repeated helical computed tomography scans from 28 patients were included in the study. Both low-risk patients (LRP, CTV = prostate) and intermediate-risk patients (IRP, CTV = prostate + seminal vesicles, SV) were included in the simulation. Two registration methods, based on center-of-mass shift of prostate only and prostate plus SV, were performed for IRP. The intensity-modulated radiotherapy was used in the simulation. Criteria on both cumulative and fractional doses were evaluated. Furthermore, the geometric evaluation was extended to investigate the optimal number of fractions necessary to construct the internal target volume (ITV) for the hybrid strategy. The dosimetric margin improvement was smaller than its geometric counterpart and was in the range of 0-1 mm. The optimal number of fractions necessary for the ITV construction is 2 for LRPs and 3-4 for IRPs in a hypofractionation protocol. A new cumulative index of target volume was proposed

  11. 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.

  12. 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...

  13. Adapting Dynamic Mathematical Models to a Pilot Anaerobic Digestion Reactor

    Directory of Open Access Journals (Sweden)

    F. Haugen, R. Bakke, and B. Lie

    2013-04-01

    Full Text Available A dynamic model has been adapted to a pilot anaerobic reactor fed diarymanure. Both steady-state data from online sensors and laboratory analysis anddynamic operational data from online sensors are used in the model adaptation.The model is based on material balances, and comprises four state variables,namely biodegradable volatile solids, volatile fatty acids, acid generatingmicrobes (acidogens, and methane generating microbes (methanogens. The modelcan predict the methane gas flow produced in the reactor. The model may beused for optimal reactor design and operation, state-estimation and control.Also, a dynamic model for the reactor temperature based on energy balance ofthe liquid in the reactor is adapted. This model may be used for optimizationand control when energy and economy are taken into account.

  14. 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.

  15. Modeling Students' Memory for Application in Adaptive Educational Systems

    Science.gov (United States)

    Pelánek, Radek

    2015-01-01

    Human memory has been thoroughly studied and modeled in psychology, but mainly in laboratory setting under simplified conditions. For application in practical adaptive educational systems we need simple and robust models which can cope with aspects like varied prior knowledge or multiple-choice questions. We discuss and evaluate several models of…

  16. The Adaptation Fund: a model for the future?

    Energy Technology Data Exchange (ETDEWEB)

    Chandani, Achala; Harmeling, Sven; Kaloga, Alpha Oumar

    2009-08-15

    With millions of the poor already facing the impacts of a changing climate, adaptation is a globally urgent – and costly – issue. The Adaptation Fund, created under the Kyoto Protocol, has unique features that could herald a new era of international cooperation on adaptation. Its governance structure, for instance, offers a fresh approach to fund management under the UN climate convention. The Fund's Board has also developed a constructive working atmosphere, and further progress is expected before the 2009 climate summit in Copenhagen. But developing countries' demand for adaptation funding is huge: conservative estimates put it at US$50 billion a year. The Fund's current structure and funding base are clearly only a first step towards filling that gap. And despite its significant progress over the last 18 months, many countries, particularly in the developed world, remain sceptical about this approach. Looking in detail at the Fund's evolution offers insight into its future potential as a model for adaptation finance.

  17. Adaptive Networks Theory, Models and Applications

    CERN Document Server

    Gross, Thilo

    2009-01-01

    With adaptive, complex networks, the evolution of the network topology and the dynamical processes on the network are equally important and often fundamentally entangled. Recent research has shown that such networks can exhibit a plethora of new phenomena which are ultimately required to describe many real-world networks. Some of those phenomena include robust self-organization towards dynamical criticality, formation of complex global topologies based on simple, local rules, and the spontaneous division of "labor" in which an initially homogenous population of network nodes self-organizes into functionally distinct classes. These are just a few. This book is a state-of-the-art survey of those unique networks. In it, leading researchers set out to define the future scope and direction of some of the most advanced developments in the vast field of complex network science and its applications.

  18. 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.

  19. Research on the Adaptive Object-Model Architecture Style

    Institute of Scientific and Technical Information of China (English)

    YAO Hai-qiong; NI Gui-qiang

    2004-01-01

    The rapidly changing requirements and business rules stimulate software developers to make their applications more dynamic, configurable, and adaptable. An effective way to meet such requirements is to apply an adaptive object-model (AOM). The AOM architecture style is composed of metamodel, model engine and tools. Firstly, two small patterns for building up metamodel are analyzed in detail. Then model engine for interpreting metamodel and tools for end-uses to define and configure object models are discussed. Finally, a novel platform-applicationware-is proposed.

  20. Accelerated parabolic Radon domain 2D adaptive multiple subtraction with fast iterative shrinkage thresholding algorithm and its application in parabolic Radon domain hybrid demultiple method

    Science.gov (United States)

    Li, Zhong-xiao; Li, Zhen-chun

    2017-08-01

    Adaptive multiple subtraction is an important step for successfully conducting surface-related multiple elimination in marine seismic exploration. 2D adaptive multiple subtraction conducted in the parabolic Radon domain has been proposed to better separate primaries and multiples than 2D adaptive multiple subtraction conducted in the time-offset domain. Additionally, the parabolic Radon domain hybrid demultiple method combining parabolic Radon filtering and parabolic Radon domain 2D adaptive multiple subtraction can better remove multiples than the cascaded demultiple method using time-offset domain 2D adaptive multiple subtraction and the parabolic Radon transform method sequentially. To solve the matching filter in the optimization problem with L1 norm minimization constraint of primaries, traditional parabolic Radon domain 2D adaptive multiple subtraction uses the iterative reweighted least squares (IRLS) algorithm, which is computationally expensive for solving a weighted LS inversion in each iteration. In this paper we introduce the fast iterative shrinkage thresholding algorithm (FISTA) as a faster alternative to the IRLS algorithm for parabolic Radon domain 2D adaptive multiple subtraction. FISTA uses the shrinkage-thresholding operator to promote the sparsity of estimated primaries and solves the 2D matching filter with iterative steps. FISTA based parabolic Radon domain 2D adaptive multiple subtraction reduces the computation time effectively while achieving similar accuracy compared with IRLS based parabolic Radon domain 2D adaptive multiple subtraction. Additionally, the provided examples show that FISTA based parabolic Radon domain 2D adaptive multiple subtraction can better separate primaries and multiples than FISTA based time-offset domain 2D adaptive multiple subtraction. Furthermore, we introduce FISTA based parabolic Radon domain 2D adaptive multiple subtraction into the parabolic Radon domain hybrid demultiple method to improve its computation

  1. 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.

  2. 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}...

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. The Distance Field Model and Distance Constrained MAP Adaptation Algorithm

    Institute of Scientific and Technical Information of China (English)

    YUPeng; WANGZuoying

    2003-01-01

    Spatial structure information, i.e., the rel-ative position information of phonetic states in the feature space, is long to be carefully researched yet. In this pa-per, a new model named “Distance Field” is proposed to describe the spatial structure information. Based on this model, a modified MAP adaptation algorithm named dis-tance constrained maximum a poateriori (DCMAP) is in-troduced. The distance field model gives large penalty when the spatial structure is destroyed. As a result the DCMAP reserves the spatial structure information in adaptation process. Experiments show the Distance Field Model improves the performance of MAP adapta-tion. Further results show DCMAP has strong cross-state estimation ability, which is used to train a well-performed speaker-dependent model by data from only part of pho-

  8. Comprehensive Evaluation Cloud Model for Ship Navigation Adaptability

    OpenAIRE

    Man Zhu; Y.Q. Wen; Zhou, C. H.; C.S. Xiao

    2014-01-01

    In this paper, using cloud model and Delphi, we build a comprehensive evaluation cloud model to solve the problems of qualitative description and quantitative transformation in ship navigation adaptability comprehensive evaluation. In the model, the normal cloud generator is used to find optimal cloud models of reviews and evaluation factors. The weight of each evaluation factor is determined by cloud model and Delphi. The floating cloud algorithm is applied to aggregate the bottom level’s ev...

  9. 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.

  10. 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.

  11. 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.)

  12. An adaptive metamaterial beam with hybrid shunting circuits for extremely broadband control of flexural wave (Conference Presentation)

    Science.gov (United States)

    Chen, Yangyang; Huang, Guoliang

    2017-04-01

    A great deal of research has been devoted to controlling the dynamic behaviors of phononic crystals and metamaterials by directly tuning the frequency regions and/or widths of their inherent band gaps. Here, we present a novel approach to achieve extremely broadband flexural wave/vibration attenuation based on tunable local resonators made of piezoelectric stacks shunted by hybrid negative capacitance and negative inductance circuits with proof masses attached on a host beam. First, wave dispersion relations of the adaptive metamaterial beam are calculated analytically by using the transfer matrix method. The unique modulus tuning properties induced by the hybrid shunting circuits are then characterized conceptually, from which the frequency dependent modulus tuning curves of the piezoelectric stack located within wave attenuation frequency regions are quantitatively identified. As an example, a flexural wave high-pass band filter with a wave attenuation region from 0 to 23.0 kHz is demonstrated analytically and numerically by using the hybrid shunting circuit, in which the two electric components are connected in series. By changing the connection pattern to be parallel, another super wide wave attenuation region from 13.5 to 73.0 kHz is demonstrated to function as a low-pass filter at a subwavelength scale. The proposed adaptive metamaterial possesses a super wide band gap created both naturally and artificially. Therefore, it can be used for the transient wave mitigation at extremely broadband frequencies such as blast or impact loadings. We envision that the proposed design and approach can open many possibilities in broadband vibration and wave control.

  13. Model-based design of adaptive embedded systems

    CERN Document Server

    Hamberg, Roelof; Reckers, Frans; Verriet, Jacques

    2013-01-01

    Today’s embedded systems have to operate in a wide variety of dynamically changing environmental circumstances. Adaptivity, the ability of a system to autonomously adapt itself, is a means to optimise a system’s behaviour to accommodate changes in its environment. It involves making in-product trade-offs between system qualities at system level. The main challenge in the development of adaptive systems is keeping control of the intrinsic complexity of such systems while working with multi-disciplinary teams to create different parts of the system. Model-Based Development of Adaptive Embedded Systems focuses on the development of adaptive embedded systems both from an architectural and methodological point of view. It describes architectural solution patterns for adaptive systems and state-of-the-art model-based methods and techniques to support adaptive system development. In particular, the book describes the outcome of the Octopus project, a cooperation of a multi-disciplinary team of academic and indus...

  14. 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.

  15. 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.

  16. Basic Research on Adaptive Model Algorithmic Control

    Science.gov (United States)

    1985-12-01

    Control Conference. Richalet, J., A. Rault, J.L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial...pp.977-982. Richalet, J., A. Rault, J. L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial processes

  17. Adaptive hybrid control of a flexible master-slave arm system%柔性主从手臂系统自适应混合控制的研究

    Institute of Scientific and Technical Information of China (English)

    贾百龙; 刘颖; 小林幸德

    2011-01-01

    以柔性主从手臂系统为研究对象,提出一种新的自适应混合控制方法.建立了系统的动力学模型,在系数敏感性实验的基础上,分析了控制器权重系数对系统性能的影响,提出根据系统实时跟踪误差调整控制器中的权重系数,进而设计了自适应双向控制器和基于LQR的自适应伺服控制器.并以此为基础,通过选取合理的阈值,将两种自适应控制器有效结合,设计了自适应混合控制器.实验结果表明,自适应混合控制有效提高系统运动的稳定性,并显著减少了柔性执行手臂的振动衰减时间.%To study the motion and vibration of a flexible master-slave arm system, a new adaptive hybrid controller was designed here. In order to improve the performance of the system, a dynamic model was established, parameters sensitivity was analyzed based on experimental results, and then the adaptive bilateral controller and the adaptive servo controller based on LQR were designed. In both controllers, the parameters could be changed according to the real-time tracing error. Finally, the adaptive hybrid controller was built, it combined the adaptive bilateral controller and adaptive servo one based on LQR with the gauge of real-time tracing error. Experimental results indicated that the adaptive hybrid controller improves the motion stability and vibration suppression performance of the arm system significantly.

  18. Development and evaluation of novel forecasting adaptive ensemble model

    Directory of Open Access Journals (Sweden)

    C.M. Anish

    2016-09-01

    Full Text Available This paper proposes a new ensemble based adaptive forecasting structure for efficient different interval days' ahead prediction of five different asset values (NAV. In this approach three individual adaptive structures such as adaptive moving average (AMA, adaptive auto regressive moving average (AARMA and feedback radial basis function network (FRBF are employed to first train with conventional LMS, conventional forward-backward LMS and corresponding learning algorithm of FRBF respectively. After successful validation of each model the output obtained by each individual model is optimally weighted using Genetic algorithm (GA as well as particle swarm optimization (PSO based techniques to produce the best possible different days ahead prediction accuracy. Finally the results of prediction obtained of the NAV values are compared with the results obtained by individual predictors as well as by other four existing ensemble schemes. It is in general demonstrated that in all cases the proposed forecasting scheme outperforms other competitive methods.

  19. Improved Gaussian Mixture Models for Adaptive Foreground Segmentation

    DEFF Research Database (Denmark)

    Katsarakis, Nikolaos; Pnevmatikakis, Aristodemos; Tan, Zheng-Hua

    2016-01-01

    Adaptive foreground segmentation is traditionally performed using Stauffer & Grimson’s algorithm that models every pixel of the frame by a mixture of Gaussian distributions with continuously adapted parameters. In this paper we provide an enhancement of the algorithm by adding two important dynamic...... elements to the baseline algorithm: The learning rate can change across space and time, while the Gaussian distributions can be merged together if they become similar due to their adaptation process. We quantify the importance of our enhancements and the effect of parameter tuning using an annotated...

  20. 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.

  1. 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

  2. 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.

  3. 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...

  4. Modeling Power Systems as Complex Adaptive Systems

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  5. Adaptive mixed-hybrid and penalty discontinuous Galerkin method for two-phase flow in heterogeneous media

    KAUST Repository

    Hou, Jiangyong

    2016-02-05

    In this paper, we present a hybrid method, which consists of a mixed-hybrid finite element method and a penalty discontinuous Galerkin method, for the approximation of a fractional flow formulation of a two-phase flow problem in heterogeneous media with discontinuous capillary pressure. The fractional flow formulation is comprised of a wetting phase pressure equation and a wetting phase saturation equation which are coupled through a total velocity and the saturation affected coefficients. For the wetting phase pressure equation, the continuous mixed-hybrid finite element method space can be utilized due to a fundamental property that the wetting phase pressure is continuous. While it can reduce the computational cost by using less degrees of freedom and avoiding the post-processing of velocity reconstruction, this method can also keep several good properties of the discontinuous Galerkin method, which are important to the fractional flow formulation, such as the local mass balance, continuous normal flux and capability of handling the discontinuous capillary pressure. For the wetting phase saturation equation, the penalty discontinuous Galerkin method is utilized due to its capability of handling the discontinuous jump of the wetting phase saturation. Furthermore, an adaptive algorithm for the hybrid method together with the centroidal Voronoi Delaunay triangulation technique is proposed. Five numerical examples are presented to illustrate the features of proposed numerical method, such as the optimal convergence order, the accurate and efficient velocity approximation, and the applicability to the simulation of water flooding in oil field and the oil-trapping or barrier effect phenomena.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. Hybrid wavelet-support vector machine approach for modelling rainfall-runoff process.

    Science.gov (United States)

    Komasi, Mehdi; Sharghi, Soroush

    2016-01-01

    Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfall-runoff modeling and the other fields of hydrology. Similar to the other artificial intelligence models, such as artificial neural network (ANN) and adaptive neural fuzzy inference system, the SVM model is based on the autoregressive properties. In this paper, the wavelet analysis was linked to the SVM model concept for modeling the rainfall-runoff process of Aghchai and Eel River watersheds. In this way, the main time series of two variables, rainfall and runoff, were decomposed to multiple frequent time series by wavelet theory; then, these time series were imposed as input data on the SVM model in order to predict the runoff discharge one day ahead. The obtained results show that the wavelet SVM model can predict both short- and long-term runoff discharges by considering the seasonality effects. Also, the proposed hybrid model is relatively more appropriate than classical autoregressive ones such as ANN and SVM because it uses the multi-scale time series of rainfall and runoff data in the modeling process.

  11. Adaptive Modeling and Real-Time Simulation

    Science.gov (United States)

    1984-01-01

    34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in

  12. 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.

  13. 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.

  14. Adaptive network models of collective decision making in swarming systems

    Science.gov (United States)

    Chen, Li; Huepe, Cristián; Gross, Thilo

    2016-08-01

    We consider a class of adaptive network models where links can only be created or deleted between nodes in different states. These models provide an approximate description of a set of systems where nodes represent agents moving in physical or abstract space, the state of each node represents the agent's heading direction, and links indicate mutual awareness. We show analytically that the adaptive network description captures a phase transition to collective motion in some swarming systems, such as the Vicsek model, and that the properties of this transition are determined by the number of states (discrete heading directions) that can be accessed by each agent.

  15. Roy's Adaptation Model-Based Patient Education for Promoting the Adaptation of Hemodialysis Patients.

    Science.gov (United States)

    Afrasiabifar, Ardashir; Karimi, Zohreh; Hassani, Parkhideh

    2013-07-01

    In addition to physical adaptation and psychosocial adjustment to chronic renal disease, hemodialysis (HD) patients must also adapt to dialysis therapy plan. The aim of the present study was to examine the effect of Roy's adaptation model-based patient education on adaptation of HD patients. This study is a semi-experimental research that was conducted with the participation of all patients with end-stage renal disease referred to the dialysis unit of Shahid Beheshti Hospital of Yasuj city, 2010. A total of 59 HD patients were randomly allocated to two groups of test and control. Data were collected by a questionnaire based on the Roy's Adaptation Model (RAM). Validity and reliability of the questionnaire were approved. Patient education was determined by eight one-hour sessions over eight weeks. At the end of the education plan, the patients were given an educational booklet containing the main points of self-care for HD patients. The effectiveness of education plan was assessed two months after plan completion and data were compared with the pre-education scores. All analyses were conducted using the SPSS software (version 16) through descriptive and inferential statistics including correlation, t-test, ANOVA and ANCOVA tests. The results showed significant differences in the mean scores of physiological and self-concept models between the test and control groups (P = 0.01 and P = 0.03 respectively). Also a statistical difference (P = 0.04) was observed in the mean scores of the role function mode of both groups. There was no significant difference in the mean scores of interdependence modes between the two groups. RAM based patient education could improve the patients' adaptation in physiologic and self-concept modes. In addition to suggesting further research in this area, nurses are recommended to pay more attention in applying RAM in dialysis centers.

  16. Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    M. Sudha

    2015-12-01

    Full Text Available Uncertain atmosphere is a prevalent factor affecting the existing prediction approaches. Rough set and fuzzy set theories as proposed by Pawlak and Zadeh have become an effective tool for handling vagueness and fuzziness in the real world scenarios. This research work describes the impact of Hybrid Intelligent System (HIS for strategic decision support in meteorology. In this research a novel exhaustive search based Rough set reduct Selection using Genetic Algorithm (RSGA is introduced to identify the significant input feature subset. The proposed model could identify the most effective weather parameters efficiently than other existing input techniques. In the model evaluation phase two adaptive techniques were constructed and investigated. The proposed Artificial Neural Network based on Back Propagation learning (ANN-BP and Adaptive Neuro Fuzzy Inference System (ANFIS was compared with existing Fuzzy Unordered Rule Induction Algorithm (FURIA, Structural Learning Algorithm on Vague Environment (SLAVE and Particle Swarm OPtimization (PSO. The proposed rainfall prediction models outperformed when trained with the input generated using RSGA. A meticulous comparison of the performance indicates ANN-BP model as a suitable HIS for effective rainfall prediction. The ANN-BP achieved 97.46% accuracy with a nominal misclassification rate of 0.0254 %.

  17. 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...

  18. 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.

  19. 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.

  20. Acoustic Model Adaptation for Indonesian Language Utterance Training System

    Directory of Open Access Journals (Sweden)

    Linda Indrayanti

    2010-01-01

    Full Text Available Problem statement: In order to build an utterance training system for Indonesian language, a speech recognition system designed for Indonesian is necessary. However, the system hardly works well due to the pronunciation variants of non-native utterances may lead to substitution/deletion error. This research investigated the pronunciation variant and proposes acoustic model adaptation to improve performance of the system. Approach: The proposed acoustic model adaptation worked in three steps: to analyze pronunciation variant with knowledge-based and data-derived methods; to align knowledge-based and data-derived results in order to list frequently mispronounced phones with their variants; to perform a state-clustering procedure with the list obtained from the second step. Further, three Speaker Adaptation (SA techniques were used in combination with the acoustic model adaptation and they are compared each other. In order to evaluate and tune the adaptation techniques, perceptual-based evaluation by three human raters is performed to obtain the "true"recognition results. Results: The proposed method achieved an average gain in Hit + Rejection (the percentage of correctly accepted and correctly rejected utterances by the system as the human raters do of 2.9 points and 2 points for native and non-native subjects, respectively, when compared with the system without adaptation. Average gains of 12.7 and 6.2 points for native and non-native students in Hit + Rejection were obtained by combining SA to the acoustic model adaptation. Conclusion/Recommendations: Performance evaluation of the adapted system demonstrated that the proposed acoustic model adaptation can improve Hit even though there is a slight increase of False Alarm (FA, the percentage of incorrectly accepted utterances by the system of which the human raters reject. The performance of the proposed acoustic model adaptation depends strongly on the effectiveness of state-clustering procedure

  1. The behavior of adaptive bone-remodeling simulation models

    NARCIS (Netherlands)

    H.H. Weinans (Harrie); R. Huiskes (Rik); H.J. Grootenboer

    1992-01-01

    textabstractThe process of adaptive bone remodeling can be described mathematically and simulated in a computer model, integrated with the finite element method. In the model discussed here, cortical and trabecular bone are described as continuous materials with variable density. The remodeling rule

  2. The Nominal Response Model in Computerized Adaptive Testing.

    Science.gov (United States)

    De Ayala, R. J.

    One important and promising application of item response theory (IRT) is computerized adaptive testing (CAT). The implementation of a nominal response model-based CAT (NRCAT) was studied. Item pool characteristics for the NRCAT as well as the comparative performance of the NRCAT and a CAT based on the three-parameter logistic (3PL) model were…

  3. Adapting the Kirkpatrick Model to Technical Communication Products and Services.

    Science.gov (United States)

    Carliner, Saul

    1997-01-01

    Proposes a four-level model for adapting the Kirkpatrick model of training evaluation to suit technical manuals and services assessing: (1) user satisfaction; (2) user performance; (3) client performance; and (4) client satisfaction. Discusses assessing of the value of work, limitations in evaluating technical communication products, and the…

  4. Model reference, sliding mode adaptive control for flexible structures

    Science.gov (United States)

    Yurkovich, S.; Ozguner, U.; Al-Abbass, F.

    1988-01-01

    A decentralized model reference adaptive approach using a variable-structure sliding model control has been developed for the vibration suppression of large flexible structures. Local models are derived based upon the desired damping and response time in a model-following scheme, and variable structure controllers are then designed which employ colocated angular rate and position feedback. Numerical simulations have been performed using NASA's flexible grid experimental apparatus.

  5. Adaptive Simulated Annealing Based Protein Loop Modeling of Neurotoxins

    Institute of Scientific and Technical Information of China (English)

    陈杰; 黄丽娜; 彭志红

    2003-01-01

    A loop modeling method, adaptive simulated annealing, for ab initio prediction of protein loop structures, as an optimization problem of searching the global minimum of a given energy function, is proposed. An interface-friendly toolbox-LoopModeller in Windows and Linux systems, VC++ and OpenGL environments is developed for analysis and visualization. Simulation results of three short-chain neurotoxins modeled by LoopModeller show that the method proposed is fast and efficient.

  6. Adversary Model: Adaptive Chosen Ciphertext Attack with Timing Attack

    OpenAIRE

    2014-01-01

    We have introduced a novel adversary model in Chosen-Ciphertext Attack with Timing Attack (CCA2-TA) and it was a practical model because the model incorporates the timing attack. This paper is an extended paper for 'A Secure TFTP Protocol with Security Proofs'. Keywords - Timing Attack, Random Oracle Model, Indistinguishabilit, Chosen Plaintext Attack, CPA, Chosen Ciphertext Attack, IND-CCA1, Adaptive Chosen Ciphertext Attack, IND-CCA2, Trivial File Transfer Protocol, TFTP, Security, Trust, P...

  7. Efficiently adapting graphical models for selectivity estimation

    DEFF Research Database (Denmark)

    Tzoumas, Kostas; Deshpande, Amol; Jensen, Christian S.

    2013-01-01

    of the selectivities of the constituent predicates. However, this independence assumption is more often than not wrong, and is considered to be the most common cause of sub-optimal query execution plans chosen by modern query optimizers. We take a step towards a principled and practical approach to performing...... cardinality estimation without making the independence assumption. By carefully using concepts from the field of graphical models, we are able to factor the joint probability distribution over all the attributes in the database into small, usually two-dimensional distributions, without a significant loss......Query optimizers rely on statistical models that succinctly describe the underlying data. Models are used to derive cardinality estimates for intermediate relations, which in turn guide the optimizer to choose the best query execution plan. The quality of the resulting plan is highly dependent...

  8. Research and Application of a New Hybrid Forecasting Model Based on Genetic Algorithm Optimization: A Case Study of Shandong Wind Farm in China

    Directory of Open Access Journals (Sweden)

    Ping Jiang

    2015-01-01

    Full Text Available With the increasing depletion of fossil fuel and serious destruction of environment, wind power, as a kind of clean and renewable resource, is more and more connected to the power system and plays a crucial role in power dispatch of hybrid system. Thus, it is necessary to forecast wind speed accurately for the operation of wind farm in hybrid system. In this paper, we propose a hybrid model called EEMD-GA-FAC/SAC to forecast wind speed. First, the Ensemble empirical mode decomposition (EEMD can be applied to eliminate the noise of the original data. After data preprocessing, first-order adaptive coefficient forecasting method (FAC or second-order adaptive coefficient forecasting method (SAC can be employed to do forecast. It is significant to select optimal parameters for an effective model. Thus, genetic algorithm (GA is used to determine parameter of the hybrid model. In order to verify the validity of the proposed model, every ten-minute wind speed data from three observation sites in Shandong Peninsula of China and several error evaluation criteria can be collected. Through comparing with traditional BP, ARIMA, FAC, and SAC model, the experimental results show that the proposed hybrid model EEMD-GA-FAC/SAC has the best forecasting performance.

  9. Adapting AIC to conditional model selection

    NARCIS (Netherlands)

    M. van Ommen (Matthijs)

    2012-01-01

    textabstractIn statistical settings such as regression and time series, we can condition on observed information when predicting the data of interest. For example, a regression model explains the dependent variables $y_1, \\ldots, y_n$ in terms of the independent variables $x_1, \\ldots, x_n$.

  10. An Adaptive Trust Model of Web Services

    Institute of Scientific and Technical Information of China (English)

    SU Jin-dian; GUO He-qing; GAO Yin

    2005-01-01

    This paper proposes a dynamic Web service trust(WS Trust ) model, and some corresponding trust metric evaluation algorithms. The main goal is to evaluate the trustworthiness and predict the future behaviors of entities in order to help users find trustworthy Web service providers and prevent users from providing unfair ratings against service providers.

  11. 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.

  12. 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.

  13. 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

  14. The Importance of Formalizing Computational Models of Face Adaptation Aftereffects

    Science.gov (United States)

    Ross, David A.; Palmeri, Thomas J.

    2016-01-01

    Face adaptation is widely used as a means to probe the neural representations that support face recognition. While the theories that relate face adaptation to behavioral aftereffects may seem conceptually simple, our work has shown that testing computational instantiations of these theories can lead to unexpected results. Instantiating a model of face adaptation not only requires specifying how faces are represented and how adaptation shapes those representations but also specifying how decisions are made, translating hidden representational states into observed responses. Considering the high-dimensionality of face representations, the parallel activation of multiple representations, and the non-linearity of activation functions and decision mechanisms, intuitions alone are unlikely to succeed. If the goal is to understand mechanism, not simply to examine the boundaries of a behavioral phenomenon or correlate behavior with brain activity, then formal computational modeling must be a component of theory testing. To illustrate, we highlight our recent computational modeling of face adaptation aftereffects and discuss how models can be used to understand the mechanisms by which faces are recognized. PMID:27378960

  15. Adaptive Identification of Logging Lithology Based on VPSO-ENN Hybrid Algorithm

    Institute of Scientific and Technical Information of China (English)

    GUO Jian; WANG Yuan-han; LI Yin-ping

    2008-01-01

    Particle swarm optimization (PSO) was modified by variation method of particle velocity, and a variation PSO (VPSO) algorithm was proposed to overcome the shortcomings of PSO, such as premature convergence and local optimization. The VPSO algorithm is combined with Elman neural network (ENN) to form a VPSO-ENN hybrid algorithm. Compared with the hybrid algorithm of genetic algorithm (GA) and BP neural network (GA-BP), VPSO-ENN has less adjustable parameters, faster convergence speed and higher identification precision in the numerical experiment. A system for identifying logging parameters was established based on VPSO-ENN. The results of an engineering case indicate that the intelligent identification system is effective in the lithology identification.

  16. Motion Planning Using an Impact-Based Hybrid Control for Trajectory Generation in Adaptive Walking

    Directory of Open Access Journals (Sweden)

    Umar Asif

    2011-09-01

    Full Text Available This paper aims to solve a major drawback of walking robots i.e. their inability to react to environmental disturbances while navigating in natural rough terrains. This problem is reduced here by suggesting the use of a hybrid force‐position control based trajectory generation with the impact dynamics into consideration that compensates for the stability variations, thus helping the robot react stably in the face of environmental disturbances. As a consequence, the proposed impact‐based hybrid control helps the robot achieve better and stable motion planning than conventional position‐based control algorithms. Dynamic simulations and real world outdoor experiments performed on a six legged hexapod robot show a relevant improvement in the robot locomotion.

  17. ADAPTING HYBRID MACHINE TRANSLATION TECHNIQUES FOR CROSS-LANGUAGE TEXT RETRIEVAL SYSTEM

    Directory of Open Access Journals (Sweden)

    P. ISWARYA

    2017-03-01

    Full Text Available This research work aims in developing Tamil to English Cross - language text retrieval system using hybrid machine translation approach. The hybrid machine translation system is a combination of rule based and statistical based approaches. In an existing word by word translation system there are lot of issues and some of them are ambiguity, Out-of-Vocabulary words, word inflections, and improper sentence structure. To handle these issues, proposed architecture is designed in such a way that, it contains Improved Part-of-Speech tagger, machine learning based morphological analyser, collocation based word sense disambiguation procedure, semantic dictionary, and tense markers with gerund ending rules, and two pass transliteration algorithm. From the experimental results it is clear that the proposed Tamil Query based translation system achieves significantly better translation quality over existing system, and reaches 95.88% of monolingual performance.

  18. Adaptability of grades and hybrids of tangerine in a subtropical zone of Russia

    OpenAIRE

    Julia Abilphazova; Oksana Belous

    2015-01-01

    Results of researches of various cultivars and hybrids of tangerine growing in the conditions of the humid subtropics of Russia and possessing valuable physiological and biochemical markers are presented in article. The stress factors limiting cultivation of tangerine culture in Krasnodar region are defined. The assessment of the water saving and enzymes activity in tangerine leaves is given. Changes of physiological parameters at influence of a stressful factor are shown. The analysis of wat...

  19. 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

  20. 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).

  1. 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.

  2. 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.

  3. 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.

  4. Adaptive plasticity model for bucket foundations

    DEFF Research Database (Denmark)

    Ibsen, Lars Bo; Barari, Amin; Larsen, Kim A.

    2014-01-01

    Based on experimental investigations, the literature proposes different methods for modeling the behavior and capacity of foundations subjected to combined loading. Generally, two methods are used to predict the behavior of foundations: traditional approaches and hardening plasticity solutions....... The first method is only capable of determining the capacity of the foundations and not the prepeak behavior. Thus, a new strain-hardening criterion is developed by calibrating failure criteria by employing data from small-scale tests on bucket foundations subjected to static loads. The shape of the yield...

  5. A new thermal comfort approach comparing adaptive and PMV models

    Energy Technology Data Exchange (ETDEWEB)

    Orosa, Jose A. [Universidade da Coruna, Departamento de Energia y P. M. Paseo de Ronda, n :51, 15011. A Coruna (Spain); Oliveira, Armando C. [Universidade do Porto, Faculdade de Engenharia, New Energy Tec. Unit. Rua Dr Roberto Frias, 4200-465 Porto (Portugal)

    2011-03-15

    In buildings with heating, ventilation, and air-conditioning (HVAC), the Predicted Mean Vote index (PMV) was successful at predicting comfort conditions, whereas in naturally ventilated buildings, only adaptive models provide accurate predictions. On the other hand, permeable coverings can be considered as a passive control method of indoor conditions and, consequently, have implications in the perception of indoor air quality, local thermal comfort, and energy savings. These energy savings were measured in terms of the set point temperature established in accordance with adaptive methods. Problems appear when the adaptive model suggests the same neutral temperature for ambiences with the same indoor temperature but different relative humidities. In this paper, a new design of the PMV model is described to compare the neutral temperature to real indoor conditions. Results showed that this new PMV model tends to overestimate thermal neutralities but with a lower value than Fanger's PMV index. On the other hand, this new PMV model considers indoor relative humidity, showing a clear differentiation of indoor ambiences in terms of it, unlike adaptive models. Finally, spaces with permeable coverings present indoor conditions closer to thermal neutrality, with corresponding energy savings. (author)

  6. Recent models for adaptive personality differences: a review

    Science.gov (United States)

    Dingemanse, Niels J.; Wolf, Max

    2010-01-01

    In this paper we review recent models that provide adaptive explanations for animal personalities: individual differences in behaviour (or suites of correlated behaviours) that are consistent over time or contexts. We start by briefly discussing patterns of variation in behaviour that have been documented in natural populations. In the main part of the paper we discuss models for personality differences that (i) explain animal personalities as adaptive behavioural responses to differences in state, (ii) investigate how feedbacks between state and behaviour can stabilize initial differences among individuals and (iii) provide adaptive explanations for animal personalities that are not based on state differences. Throughout, we focus on two basic questions. First, what is the basic conceptual idea underlying the model? Second, what are the key assumptions and predictions of the model? We conclude by discussing empirical features of personalities that have not yet been addressed by formal modelling. While this paper is primarily intended to guide empiricists through current adaptive theory, thereby stimulating empirical tests of these models, we hope it also inspires theoreticians to address aspects of personalities that have received little attention up to now. PMID:21078647

  7. Adaptive Estimation of Heteroscedastic Money Demand Model of Pakistan

    Directory of Open Access Journals (Sweden)

    Muhammad Aslam

    2007-07-01

    Full Text Available For the problem of estimation of Money demand model of Pakistan, money supply (M1 shows heteroscedasticity of the unknown form. For estimation of such model we compare two adaptive estimators with ordinary least squares estimator and show the attractive performance of the adaptive estimators, namely, nonparametric kernel estimator and nearest neighbour regression estimator. These comparisons are made on the basis standard errors of the estimated coefficients, standard error of regression, Akaike Information Criteria (AIC value, and the Durban-Watson statistic for autocorrelation. We further show that nearest neighbour regression estimator performs better when comparing with the other nonparametric kernel estimator.

  8. Adaptive network models of collective decision making in swarming systems

    CERN Document Server

    Chen, Li; Gross, Thilo

    2015-01-01

    We consider a class of adaptive network models where links can only be created or deleted between nodes in different states. These models provide an approximate description of a set of systems where nodes represent agents moving in physical or abstract space, the state of each node represents the agent's heading direction, and links indicate mutual awareness. We show analytically that the adaptive network description captures the phase transition to collective motion in swarming systems and that the properties of this transition are determined by the number of states (discrete heading directions) that can be accessed by each agent.

  9. The Adaptive LASSO Spline Estimation of Single-Index Model

    Institute of Scientific and Technical Information of China (English)

    LU Yiqiang; ZHANG Riquan; HU Bin

    2016-01-01

    In this paper,based on spline approximation,the authors propose a unified variable selection approach for single-index model via adaptive L1 penalty.The calculation methods of the proposed estimators are given on the basis of the known lars algorithm.Under some regular conditions,the authors demonstrate the asymptotic properties of the proposed estimators and the oracle properties of adaptive LASSO (aLASSO) variable selection.Simulations are used to investigate the performances of the proposed estimator and illustrate that it is effective for simultaneous variable selection as well as estimation of the single-index models.

  10. 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.

  11. 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

  12. 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

  13. The Nonlinear Sigma Model With Distributed Adaptive Mesh Refinement

    CERN Document Server

    Liebling, S L

    2004-01-01

    An adaptive mesh refinement (AMR) scheme is implemented in a distributed environment using Message Passing Interface (MPI) to find solutions to the nonlinear sigma model. Previous work studied behavior similar to black hole critical phenomena at the threshold for singularity formation in this flat space model. This work is a follow-up describing extensions to distribute the grid hierarchy and presenting tests showing the correctness of the model.

  14. 混合隔振系统自适应模糊滑模控制%Adaptive Fuzzy Sliding-mode Controller for Hybrid Vibration Isolation Systems

    Institute of Scientific and Technical Information of China (English)

    杨理华; 朱石坚; 楼京俊; 李棒

    2014-01-01

    针对机械设备被动隔振在低频段隔振效果较差的问题,建立磁致伸缩作动器的电—磁—机转化数学模型,提出一种基于自适应模糊滑模控制算法,并用李雅普诺夫方法证明控制器的稳定性,将该控制策略与磁致伸缩作动器应用于混合隔振系统中。仿真结果表明:在单频、多频及随即激励条件下,自适应模糊滑模控制器具有良好的动态特性和鲁棒性,能够提高系统隔振效率并拓宽隔振频段,有效减小传至基础的力。%Aiming at the problem of poor vibration isolation effect of passive vibration isolators of mechanical equip-ment in low frequency range, an electric-magnetic-mechanical conversion model for magnetostrictive actuators is estab-lished, and an adaptive fuzzy sliding-mode control algorithm is proposed. The stability of the controller is proved by Lyapu-nov method. Then, the control strategy and the magnetostrictive actuator are used in a hybrid vibration isolation system. The simulation results show that in whatever conditions of single frequency excitation, multi-frequency excitation or random ex-citation, the adaptive fuzzy sliding-mode controller has good dynamic characteristics and robustness. This property can also be used to improve the isolation efficiency and broaden the vibration isolation frequency band of the hybrid system, and ef-fectively reduce the force transmitted to the foundation of the mechanical equipment.

  15. 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

  16. 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

  17. 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

  18. Adaptive Shape Functions and Internal Mesh Adaptation for Modelling Progressive Failure in Adhesively Bonded Joints

    Science.gov (United States)

    Stapleton, Scott; Gries, Thomas; Waas, Anthony M.; Pineda, Evan J.

    2014-01-01

    Enhanced finite elements are elements with an embedded analytical solution that can capture detailed local fields, enabling more efficient, mesh independent finite element analysis. The shape functions are determined based on the analytical model rather than prescribed. This method was applied to adhesively bonded joints to model joint behavior with one element through the thickness. This study demonstrates two methods of maintaining the fidelity of such elements during adhesive non-linearity and cracking without increasing the mesh needed for an accurate solution. The first method uses adaptive shape functions, where the shape functions are recalculated at each load step based on the softening of the adhesive. The second method is internal mesh adaption, where cracking of the adhesive within an element is captured by further discretizing the element internally to represent the partially cracked geometry. By keeping mesh adaptations within an element, a finer mesh can be used during the analysis without affecting the global finite element model mesh. Examples are shown which highlight when each method is most effective in reducing the number of elements needed to capture adhesive nonlinearity and cracking. These methods are validated against analogous finite element models utilizing cohesive zone elements.

  19. Adaptation of the microdosimetric kinetic model to hypoxia

    Science.gov (United States)

    Bopp, C.; Hirayama, R.; Inaniwa, T.; Kitagawa, A.; Matsufuji, N.; Noda, K.

    2016-11-01

    Ion beams present a potential advantage in terms of treatment of lesions with hypoxic regions. In order to use this potential, it is important to accurately model the cell survival of oxic as well as hypoxic cells. In this work, an adaptation of the microdosimetric kinetic (MK) model making it possible to account for cell hypoxia is presented. The adaptation relies on the modification of damage quantity (double strand breaks and more complex lesions) due to the radiation. Model parameters such as domain size and nucleus size are then adapted through a fitting procedure. We applied this approach to two cell lines, HSG and V79 for helium, carbon and neon ions. A similar behaviour of the parameters was found for the two cell lines, namely a reduction of the domain size and an increase in the sensitive nuclear volume of hypoxic cells compared to those of oxic cells. In terms of oxygen enhancement ratio (OER), the experimental data behaviour can be reproduced, including dependence on particle type at the same linear energy transfer (LET). Errors on the cell survival prediction are of the same order of magnitude than for the original MK model. Our adaptation makes it possible to account for hypoxia without modelling the OER as a function of the LET of the particles, but directly accounting for hypoxic cell survival data.

  20. 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

  1. Modeling and Adaptive Control of a Planar Parallel Mechanism

    Institute of Scientific and Technical Information of China (English)

    敖银辉; 陈新

    2004-01-01

    Dynamic model and control strategy of parallel mechanism have always been a problem in robotics research. In this paper,different dynamics formulation methods are discussed first, A model of redundant driven parallel mechanism with a planar parallel manipulator is then constructed as an example. A nonlinear adaptive control method is introduced. Matrix pseudo-inversion is used to get a desired actuator torque from a desired end-effector coordinate while the feedback torque is directly calculated in the actuator space. This treatment avoids forward kinematics computation that is very difficult in a parallel mechanism. Experiments with PID together with the descibed adaptive control strategy were carried out for a planar parallel mechanism. The results show that the proposed adaptive controller outperforms conventional PID methods in tracking desired input at a high speed,

  2. Stock market modeling and forecasting a system adaptation approach

    CERN Document Server

    Zheng, Xiaolian

    2013-01-01

    Stock Market Modeling translates experience in system adaptation gained in an engineering context to the modeling of financial markets with a view to improving the capture and understanding of market dynamics. The modeling process is considered as identifying a dynamic system in which a real stock market is treated as an unknown plant and the identification model proposed is tuned by feedback of the matching error. Like a physical system, a stock market exhibits fast and slow dynamics corresponding to internal (such as company value and profitability) and external forces (such as investor sentiment and commodity prices) respectively. The framework presented here, consisting of an internal model and an adaptive filter, is successful at considering both fast and slow market dynamics. A double selection method is efficacious in identifying input factors influential in market movements, revealing them to be both frequency- and market-dependent.   The authors present work on both developed and developing markets ...

  3. Adaptation of a Multi-Block Structured Solver for Effective Use in a Hybrid CPU/GPU Massively Parallel Environment

    Science.gov (United States)

    Gutzwiller, David; Gontier, Mathieu; Demeulenaere, Alain

    2014-11-01

    Multi-Block structured solvers hold many advantages over their unstructured counterparts, such as a smaller memory footprint and efficient serial performance. Historically, multi-block structured solvers have not been easily adapted for use in a High Performance Computing (HPC) environment, and the recent trend towards hybrid GPU/CPU architectures has further complicated the situation. This paper will elaborate on developments and innovations applied to the NUMECA FINE/Turbo solver that have allowed near-linear scalability with real-world problems on over 250 hybrid GPU/GPU cluster nodes. Discussion will focus on the implementation of virtual partitioning and load balancing algorithms using a novel meta-block concept. This implementation is transparent to the user, allowing all pre- and post-processing steps to be performed using a simple, unpartitioned grid topology. Additional discussion will elaborate on developments that have improved parallel performance, including fully parallel I/O with the ADIOS API and the GPU porting of the computationally heavy CPUBooster convergence acceleration module. Head of HPC and Release Management, Numeca International.

  4. 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.

  5. 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.

  6. Student Modelling in Adaptive E-Learning Systems

    Directory of Open Access Journals (Sweden)

    Clemens Bechter

    2011-09-01

    Full Text Available Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.

  7. 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.

  8. Adjoint Methods for Guiding Adaptive Mesh Refinement in Tsunami Modeling

    Science.gov (United States)

    Davis, B. N.; LeVeque, R. J.

    2016-12-01

    One difficulty in developing numerical methods for tsunami modeling is the fact that solutions contain time-varying regions where much higher resolution is required than elsewhere in the domain, particularly when tracking a tsunami propagating across the ocean. The open source GeoClaw software deals with this issue by using block-structured adaptive mesh refinement to selectively refine around propagating waves. For problems where only a target area of the total solution is of interest (e.g., one coastal community), a method that allows identifying and refining the grid only in regions that influence this target area would significantly reduce the computational cost of finding a solution. In this work, we show that solving the time-dependent adjoint equation and using a suitable inner product with the forward solution allows more precise refinement of the relevant waves. We present the adjoint methodology first in one space dimension for illustration and in a broad context since it could also be used in other adaptive software, and potentially for other tsunami applications beyond adaptive refinement. We then show how this adjoint method has been integrated into the adaptive mesh refinement strategy of the open source GeoClaw software and present tsunami modeling results showing that the accuracy of the solution is maintained and the computational time required is significantly reduced through the integration of the adjoint method into adaptive mesh refinement.

  9. 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.

  10. 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

  11. Adaptation of Predictive Models to PDA Hand-Held Devices

    Directory of Open Access Journals (Sweden)

    Lin, Edward J

    2008-01-01

    Full Text Available Prediction models using multiple logistic regression are appearing with increasing frequency in the medical literature. Problems associated with these models include the complexity of computations when applied in their pure form, and lack of availability at the bedside. Personal digital assistant (PDA hand-held devices equipped with spreadsheet software offer the clinician a readily available and easily applied means of applying predictive models at the bedside. The purposes of this article are to briefly review regression as a means of creating predictive models and to describe a method of choosing and adapting logistic regression models to emergency department (ED clinical practice.

  12. A Model of Internal Communication in Adaptive Communication Systems.

    Science.gov (United States)

    Williams, M. Lee

    A study identified and categorized different types of internal communication systems and developed an applied model of internal communication in adaptive organizational systems. Twenty-one large organizations were selected for their varied missions and diverse approaches to managing internal communication. Individual face-to-face or telephone…

  13. Adapting the Transtheoretical Model of Change to the Bereavement Process

    Science.gov (United States)

    Calderwood, Kimberly A.

    2011-01-01

    Theorists currently believe that bereaved people undergo some transformation of self rather than returning to their original state. To advance our understanding of this process, this article presents an adaptation of Prochaska and DiClemente's transtheoretical model of change as it could be applied to the journey that bereaved individuals…

  14. Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies

    Science.gov (United States)

    Yu, Chao; Tan, Guozhen; Lv, Hongtao; Wang, Zhen; Meng, Jun; Hao, Jianye; Ren, Fenghui

    2016-06-01

    Learning is an important capability of humans and plays a vital role in human society for forming beliefs and opinions. In this paper, we investigate how learning affects the dynamics of opinion formation in social networks. A novel learning model is proposed, in which agents can dynamically adapt their learning behaviours in order to facilitate the formation of consensus among them, and thus establish a consistent social norm in the whole population more efficiently. In the model, agents adapt their opinions through trail-and-error interactions with others. By exploiting historical interaction experience, a guiding opinion, which is considered to be the most successful opinion in the neighbourhood, can be generated based on the principle of evolutionary game theory. Then, depending on the consistency between its own opinion and the guiding opinion, a focal agent can realize whether its opinion complies with the social norm (i.e., the majority opinion that has been adopted) in the population, and adapt its behaviours accordingly. The highlight of the model lies in that it captures the essential features of people’s adaptive learning behaviours during the evolution and formation of opinions. Experimental results show that the proposed model can facilitate the formation of consensus among agents, and some critical factors such as size of opinion space and network topology can have significant influences on opinion dynamics.

  15. A Context-Adaptive Model for Program Evaluation.

    Science.gov (United States)

    Lynch, Brian K.

    1990-01-01

    Presents an adaptable, context-sensitive model for ESL/EFL program evaluation, consisting of seven steps that guide an evaluator through consideration of relevant issues, information, and design elements. Examples from an evaluation of the Reading for Science and Technology Project at the University of Guadalajara, Mexico are given. (31…

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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).