Attitude determination using an adaptive multiple model filtering Scheme
Lam, Quang; Ray, Surendra N.
1995-05-01
Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown
Scheme of adaptive polarization filtering based on Kalman model
Song Lizhong; Qi Haiming; Qiao Xiaolin; Meng Xiande
2006-01-01
A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.
Unbiased Adaptive Expectation Schemes
Antonio Palestrini; Mauro Gallegati
2015-01-01
There are situations in which the old-fashioned adaptive expectation process seems to provide a good description of agents' behavior (Chow, 2011). Unfortunately, this expectation scheme may not satisfy the necessary rationality condition (unconditional mean-zero error). This paper shows how to simply fix the problem introducing a bias correction term.
Robust DTC-SVM Method for Matrix Converter Drives with Model Reference Adaptive Control Scheme
Lee, Kyo Beum; Huh, Sunghoi; Sim, Kyung-Hun;
2007-01-01
This paper presents a new robust DTC-SVM control system for high performance induction motor drives fed by a matrix converter with variable structure - model reference adaptive control scheme (VS-MRAC). It is possible to combine the advantages of matrix converters with the advantages of the DTC...
Shi, Yu; Liang, Long; Ge, Hai-Wen; Reitz, Rolf D.
2010-03-01
Acceleration of the chemistry solver for engine combustion is of much interest due to the fact that in practical engine simulations extensive computational time is spent solving the fuel oxidation and emission formation chemistry. A dynamic adaptive chemistry (DAC) scheme based on a directed relation graph error propagation (DRGEP) method has been applied to study homogeneous charge compression ignition (HCCI) engine combustion with detailed chemistry (over 500 species) previously using an R-value-based breadth-first search (RBFS) algorithm, which significantly reduced computational times (by as much as 30-fold). The present paper extends the use of this on-the-fly kinetic mechanism reduction scheme to model combustion in direct-injection (DI) engines. It was found that the DAC scheme becomes less efficient when applied to DI engine simulations using a kinetic mechanism of relatively small size and the accuracy of the original DAC scheme decreases for conventional non-premixed combustion engine. The present study also focuses on determination of search-initiating species, involvement of the NOx chemistry, selection of a proper error tolerance, as well as treatment of the interaction of chemical heat release and the fuel spray. Both the DAC schemes were integrated into the ERC KIVA-3v2 code, and simulations were conducted to compare the two schemes. In general, the present DAC scheme has better efficiency and similar accuracy compared to the previous DAC scheme. The efficiency depends on the size of the chemical kinetics mechanism used and the engine operating conditions. For cases using a small n-heptane kinetic mechanism of 34 species, 30% of the computational time is saved, and 50% for a larger n-heptane kinetic mechanism of 61 species. The paper also demonstrates that by combining the present DAC scheme with an adaptive multi-grid chemistry (AMC) solver, it is feasible to simulate a direct-injection engine using a detailed n-heptane mechanism with 543 species
Jha, Pradeep Kumar
Capturing the effects of detailed-chemistry on turbulent combustion processes is a central challenge faced by the numerical combustion community. However, the inherent complexity and non-linear nature of both turbulence and chemistry require that combustion models rely heavily on engineering approximations to remain computationally tractable. This thesis proposes a computationally efficient algorithm for modelling detailed-chemistry effects in turbulent diffusion flames and numerically predicting the associated flame properties. The cornerstone of this combustion modelling tool is the use of parallel Adaptive Mesh Refinement (AMR) scheme with the recently proposed Flame Prolongation of Intrinsic low-dimensional manifold (FPI) tabulated-chemistry approach for modelling complex chemistry. The effect of turbulence on the mean chemistry is incorporated using a Presumed Conditional Moment (PCM) approach based on a beta-probability density function (PDF). The two-equation k-w turbulence model is used for modelling the effects of the unresolved turbulence on the mean flow field. The finite-rate of methane-air combustion is represented here by using the GRI-Mech 3.0 scheme. This detailed mechanism is used to build the FPI tables. A state of the art numerical scheme based on a parallel block-based solution-adaptive algorithm has been developed to solve the Favre-averaged Navier-Stokes (FANS) and other governing partial-differential equations using a second-order accurate, fully-coupled finite-volume formulation on body-fitted, multi-block, quadrilateral/hexahedral mesh for two-dimensional and three-dimensional flow geometries, respectively. A standard fourth-order Runge-Kutta time-marching scheme is used for time-accurate temporal discretizations. Numerical predictions of three different diffusion flames configurations are considered in the present work: a laminar counter-flow flame; a laminar co-flow diffusion flame; and a Sydney bluff-body turbulent reacting flow
Chen, Ying; Shen, Jie
2016-03-01
In this paper we develop a fully adaptive energy stable scheme for Cahn-Hilliard Navier-Stokes system, which is a phase-field model for two-phase incompressible flows, consisting a Cahn-Hilliard-type diffusion equation and a Navier-Stokes equation. This scheme, which is decoupled and unconditionally energy stable based on stabilization, involves adaptive mesh, adaptive time and a nonlinear multigrid finite difference method. Numerical experiments are carried out to validate the scheme for problems with matched density and non-matched density, and also demonstrate that CPU time can be significantly reduced with our adaptive approach.
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.
Novel Link Adaptation Schemes for OFDM System
LEI Ming; CAI Peng; XU Yue-shan; ZHANG Ping
2003-01-01
Orthogonal Frequency Division Multiplexing (OFDM) is the most promising technique supporting the high data rate transmission. The combination of the link adaptation and OFDM can further increase the spectral efficiency. In this paper, we put forward two link adaptation schemes for OFDM system which have the advantages of both flexibility and practicability. Both of the two novel link adaptation schemes are based on the iterative mechanism to allocate the bit and power to subcarriers according to their channel gains and noisy levels which are assumed to be already known at the transmitter. The candidate modulation modes are determined freely before the link adaptation schemes are performed. The distinction between the two novel link adaptation schemes is that in the novel scheme A, the modulation mode is upgraded to the neighboring higher-order mode, while in the novel scheme B the modulation is upgraded to the genuine optimal mode. Therefore, the novel scheme A has the advantage of lower complexity and the novel scheme B has the advantage of higher spectral efficiency.
Application of stable adaptive schemes to nuclear reactor systems, (1)
Parameter identification and adaptive control schemes are presented for a point reactor with internal feedbacks which lead to the nonlinearity of the overall system. Both are shown stable with new representation of the system, which corresponds to the nonminimal system representation, in the vein of the Model Reference Adaptive System (MRAS) via the Lyapunov's method. For the sake of the parameter identification, model parameters can be adjusted adaptively as soon as measurements start, while plant parameters can also adaptively be compensated through control input to reduce the output error between the model and the plant for the case of the adaptive control. In the case of the adaptive control, control schemes are presented for two cases, the case of the unknown decay constant of the delayed neutron and the case of the known constant. The adaptive control scheme for the latter case is shown extremely simpler than that for the former. Furthermore, when plant parameters vary slowly with time, computer simulations show that the proposed adaptive control scheme works satisfactorily enough to stabilize an unstable reactor and that it does even in the noise with small variance. (auth.)
Robust adaptive fuzzy control scheme for nonlinear system with uncertainty
Mingjun ZHANG; Huaguang ZHANG
2006-01-01
In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.
A new adaptive scheme for the adaptive linearizing control of bioprocesses
Ferreira, E. C.; Azevedo, S. Feyo de
1996-01-01
This work deals with the development of model-based adaptive control algorithms for bioprocess operation. Non-linear adaptive control laws are proposed for single input single output regulation. Parameters are continuously adapted following a new adaptive scheme which ensures second-order dynamics of the parameter error system. A computational study is presented of the application of this theory to baker’s yeast fermentation. Results put in evidence the efficient performance both of ...
Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media
Application of stable adaptive schemes to nuclear reactor systems, (3)
Stable parameter identification and adaptive control schemes are considered for a reactor model embodying two temperature feedbacks-slow and fast. This reactor model is liable to see its feedback coefficients change sign in the course of long periods of operation, resulting in nonlinear oscillations of neutron flux, which cannot be described by a linearized model. This nonlinear system is expressed in terms of memoryless nonlinear elements in the feedback loop of a linear system, with the aid of linear and nonlinear transformations, and the nonlinear elements are here treated without being linearized. A new system representation is introduced, using which, stable parameter identification and adaptive control schemes are developed in the pattern of the Model Reference Adaptive System (MRAS) with use made of the Lyapunov method. Both schemes are shown to be stable, and furthermore globally stable if the input has frequencies sufficiently varied to permit all the excited modes to be considered linearly independent. It is thus shown that the estimated parameters converge to the true values for the parameter identification, and that, for the adaptive control, the output error between the plant and the model tends toward zero. (author)
Application of stable adaptive schemes to nuclear reactor systems, (4)
In undertaking parameter identification and adaptive control of a thermo-hydraulic system representing the core channels of nuclear reactor plants, if the flow velocity in a channel can be assumed to be the input and the outlet temperature the output, the system considered can be classed as bilinear on account of the multiplication terms for the temperature and flow velocity contained in the equations representing the same system. A new representation for this bilinear system is proposed, and the adaptive schemes for both parameter identification and control are developed in the pattern of the Model Reference Adaptive System with use made of the Lyapunov method. Both schemes are shown to be stable, and to further be globally stable if the inputs possess frequencies sufficiently varied. Some successful parameter identification experiments based on the proposed method are covered, which were performed on a test section representing a simplified channel in which the input-flow rate is varied in binary pattern. (author)
A cross-layer adaptive transmission scheme over correlated fading channels
XIAO Junfeng; QIU Jing; CHENG Shiduan
2007-01-01
Conventional adaptive transmission schemes perform poorly in wireless correlated slow-fading channels.A cross-layer adaptive transmission scheme combined with selective repeat automatic repeat request(SR-ARQ)is proposed.We apply a multi-state Markov system model for analyzing the performance of systems and optimizing the selection of modulation levels and packet sizes in correlated fading channels,which is also described by a finite-state Markov chain.A general closed-form expression of the average throughput for our suggested scheme is presented.Numerical results show that our adaptive scheme combined with SR-ARQ can obtain good performance in correlated fading channels.
Owolabi, Kolade M; Patidar, Kailash C
2016-01-01
In this paper, we consider the numerical simulations of an extended nonlinear form of Kierstead-Slobodkin reaction-transport system in one and two dimensions. We employ the popular fourth-order exponential time differencing Runge-Kutta (ETDRK4) schemes proposed by Cox and Matthew (J Comput Phys 176:430-455, 2002), that was modified by Kassam and Trefethen (SIAM J Sci Comput 26:1214-1233, 2005), for the time integration of spatially discretized partial differential equations. We demonstrate the supremacy of ETDRK4 over the existing exponential time differencing integrators that are of standard approaches and provide timings and error comparison. Numerical results obtained in this paper have granted further insight to the question 'What is the minimal size of the spatial domain so that the population persists?' posed by Kierstead and Slobodkin (J Mar Res 12:141-147, 1953), with a conclusive remark that the population size increases with the size of the domain. In attempt to examine the biological wave phenomena of the solutions, we present the numerical results in both one- and two-dimensional space, which have interesting ecological implications. Initial data and parameter values were chosen to mimic some existing patterns. PMID:27064984
Synchronization of general complex networks via adaptive control schemes
Ping He; Chun-Guo Jing; Chang-Zhong Chen; Tao Fan; Hassan Saberi Nik
2014-03-01
In this paper, the synchronization problem of general complex networks is investigated by using adaptive control schemes. Time-delay coupling, derivative coupling, nonlinear coupling etc. exist universally in real-world complex networks. The adaptive synchronization scheme is designed for the complex network with multiple class of coupling terms. A criterion guaranteeing synchronization of such complex networks is established by employing the Lyapunov stability theorem and adaptive control schemes. Finally, an illustrative example with numerical simulation is given to show the feasibility and efficiency of theoretical results.
Adaptive SPC monitoring scheme for DOE-based APC
Ye Liang; Pan Ershun; Xi Lifeng
2008-01-01
Automatic process control (APC) based on design of experiment (DOE) is a cost-efficient approach for variation reduction. The process changes both in mean and variance owing to online parameter adjustment make it hard to apply traditional SPC charts in such DOE-based APC applied process. An adaptive SPC scheme is developed, which can better track the process transitions and achieve the possible SPC run cost reduction when the process is stable. The control law of SPC parameters is designed by fully utilizing the estimation properties of the process model instead of traditionally using the data collected from the production line. An example is provided to illustrate the proposed adaptive SPC design approach.
Adaptive Multi-Resolution Scheme for Efficient Image Compression
Babel, Marie; Déforges, Olivier; Ronsin, Joseph
2003-01-01
The LAR (Locally Adaptive Resolution) method is a multi-layers still image coding scheme, efficient from very low to high bit rates. The first stage is devoted to the representation and compression of the global information (low resolution image), and relies on an adaptive resolution in the image. This paper presents some improvements on the first layer through an original quad-tree like decomposition based on a predictive scheme, and the integration of a powerful interpolation post-processin...
Adaptive Image Transmission Scheme over Wavelet-Based OFDM System
GAOXinying; YUANDongfeng; ZHANGHaixia
2005-01-01
In this paper an adaptive image transmission scheme is proposed over Wavelet-based OFDM (WOFDM) system with Unequal error protection (UEP) by the design of non-uniform signal constellation in MLC. Two different data division schemes: byte-based and bitbased, are analyzed and compared. Different bits are protected unequally according to their different contribution to the image quality in bit-based data division scheme, which causes UEP combined with this scheme more powerful than that with byte-based scheme. Simulation results demonstrate that image transmission by UEP with bit-based data division scheme presents much higher PSNR values and surprisingly better image quality. Furthermore, by considering the tradeoff of complexity and BER performance, Haar wavelet with the shortest compactly supported filter length is the most suitable one among orthogonal Daubechies wavelet series in our proposed system.
Adaptable Iterative and Recursive Kalman Filter Schemes
Zanetti, Renato
2014-01-01
Nonlinear filters are often very computationally expensive and usually not suitable for real-time applications. Real-time navigation algorithms are typically based on linear estimators, such as the extended Kalman filter (EKF) and, to a much lesser extent, the unscented Kalman filter. The Iterated Kalman filter (IKF) and the Recursive Update Filter (RUF) are two algorithms that reduce the consequences of the linearization assumption of the EKF by performing N updates for each new measurement, where N is the number of recursions, a tuning parameter. This paper introduces an adaptable RUF algorithm to calculate N on the go, a similar technique can be used for the IKF as well.
An adaptive chaotic secure communication scheme with channel noises
In this Letter, an adaptive secure communication scheme with channel noises is proposed. Based on the idea of chaotic masking-modulation, the message is encrypted by a chaotic signal. By using adaptive feedback control techniques, the transmitter and the receiver are synchronized, so the masked signal can be perfectly recovered by the receiver in the presence of channel noises. In light of the Lyapunov stability theory for stochastic differential equations, several theoretical results are rigorously established. Finally, the famous Chua's circuits is used to illustrate the possible applications of the obtained theoretical results, and the computer simulations show that the proposed scheme is feasible and efficient
Adaptive transmission schemes for MISO spectrum sharing systems
Bouida, Zied
2013-06-01
We propose three adaptive transmission techniques aiming to maximize the capacity of a multiple-input-single-output (MISO) secondary system under the scenario of an underlay cognitive radio network. In the first scheme, namely the best antenna selection (BAS) scheme, the antenna maximizing the capacity of the secondary link is used for transmission. We then propose an orthogonal space time bloc code (OSTBC) transmission scheme using the Alamouti scheme with transmit antenna selection (TAS), namely the TAS/STBC scheme. The performance improvement offered by this scheme comes at the expense of an increased complexity and delay when compared to the BAS scheme. As a compromise between these schemes, we propose a hybrid scheme using BAS when only one antenna verifies the interference condition and TAS/STBC when two or more antennas are illegible for communication. We first derive closed-form expressions of the statistics of the received signal-to-interference-and-noise ratio (SINR) at the secondary receiver (SR). These results are then used to analyze the performance of the proposed techniques in terms of the average spectral efficiency, the average number of transmit antennas, and the average bit error rate (BER). This performance is then illustrated via selected numerical examples. © 2013 IEEE.
Semantic HyperMultimedia Adaptation Schemes and Applications
Bieliková, Mária; Mylonas, Phivos; Tsapatsoulis, Nicolas
2013-01-01
Nowadays, more and more users are witnessing the impact of Hypermedia/Multimedia as well as the penetration of social applications in their life. Parallel to the evolution of the Internet and Web, several Hypermedia/Multimedia schemes and technologies bring semantic-based intelligent, personalized and adaptive services to the end users. More and more techniques are applied in media systems in order to be user/group-centric, adapting to different content and context features of a single or a community user. In respect to all the above, researchers need to explore and study the plethora of challenges that emergent personalisation and adaptation technologies bring to the new era. This edited volume aims to increase the awareness of researchers in this area. All contributions provide an in-depth investigation on research and deployment issues, regarding already introduced schemes and applications in Semantic Hyper/Multimedia and Social Media Adaptation. Moreover, the authors provide survey-based articles, so as p...
Adaptive Mesh Redistibution Method Based on Godunov's Scheme
Azarenok, Boris N.; Ivanenko, Sergey A.; Tang, Tao
2003-01-01
In this work, a detailed description for an efficent adaptive mesh redistribution algorithm based on the Godunov's scheme is presented. After each mesh iteration a second-order finite-volume flow solver is used to update the flow parameters at the new time level directly without using interpolation. Numerical experiments are perfomed to demonstrate the efficency and robustness of the proposed adaptive mesh algorithm in one and two dimensions.
Low color distortion adaptive dimming scheme for power efficient LCDs
Nam, Hyoungsik; Song, Eun-Ji
2013-06-01
This paper demonstrates the color compensation algorithm to reduce the color distortion caused by mismatches between the reference gamma value of a dimming algorithm and the display gamma values of an LCD panel in a low power adaptive dimming scheme. In 2010, we presented the YrYgYb algorithm, which used the display gamma values extracted from the luminance data of red, green, and blue sub-pixels, Yr, Yg, and Yb, with the simulation results. It was based on the ideal panel model where the color coordinates were maintained at the fixed values over the gray levels. Whereas, this work introduces an XrYgZb color compensation algorithm which obtains the display gamma values of red, green, and blue from the different tri-stimulus data of Xr, Yg, and Zb, to obtain further reduction on the color distortion. Both simulation and measurement results ensure that a XrYgZb algorithm outperforms a previous YrYgYb algorithm. In simulation which has been conducted at the practical model derived from the measured data, the XrYgZb scheme achieves lower maximum and average color difference values of 3.7743 and 0.6230 over 24 test picture images, compared to 4.864 and 0.7156 in the YrYgYb one. In measurement of a 19-inch LCD panel, the XrYgZb method also accomplishes smaller color difference values of 1.444072 and 5.588195 over 49 combinations of red, green, and blue data, compared to 1.50578 and 6.00403 of the YrYgYb at the backlight dimming ratios of 0.85 and 0.4.
A Novel Adaptive Channel Allocation Scheme To Handle Handoffs(
Alagu S
2012-06-01
Full Text Available Wireless networking is becoming an increasingly important and popular way of providing global information access to users on the move. One of the main challenges for seamless mobility is the availability of simple and robust handoff algorithms, which allow a mobile node to roam among heterogeneous wireless networks. In this paper, the authors devise a scheme, A Novel Adaptive Channel Allocation Scheme (ACAS where the number of guard channel(s is adjusted automatically based on the average handoff blocking rate measured in the past certain period of time. The handoff blocking rate is controlled under the designated threshold and the new call blocking rate is minimized. The performance evaluation of the ACAS is done through simulation of nodes. The result shows that the ACAS scheme outperforms the Static Channel Allocation Scheme by controlling a hard constraint on the handoff rejection probability. The proposed scheme achieves the optimal performance by maximizing the resource utilization and adapts itself to changing traffic conditions automatically.
An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery.
Leng, Xiangguang; Ji, Kefeng; Zhou, Shilin; Xing, Xiangwei; Zou, Huanxin
2016-01-01
With the rapid development of spaceborne synthetic aperture radar (SAR) and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way. PMID:27563902
Bouida, Zied
2012-09-01
Under the scenario of an underlay cognitive radio network, we propose in this paper an adaptive scheme using transmit power adaptation, switched transmit diversity, and adaptive modulation in order to improve the performance of existing switching efficient schemes (SES) and bandwidth efficient schemes (BES). Taking advantage of the channel reciprocity principle, we assume that the channel state information (CSI) of the interference link is available to the secondary transmitter. This information is then used by the secondary transmitter to adapt its transmit power, modulation constellation size, and used transmit branch. The goal of this joint adaptation is to minimize the average number of switched branches and the average system delay given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver. We analyze the proposed scheme in terms of the average number of branch switching, average delay, and we provide a closed-form expression of the average bit error rate (BER). We demonstrate through numerical examples that the proposed scheme provides a compromise between the SES and the BES schemes. © 2012 IEEE.
On Optimization Control Parameters in an Adaptive Error-Control Scheme in Satellite Networks
Ranko Vojinović
2011-09-01
Full Text Available This paper presents a method for optimization of control parameters of an adaptive GBN scheme in error-prone satellite channel. Method is based on the channel model with three state, where channel have the variable noise level.
Towards Adaptive High-Resolution Images Retrieval Schemes
Kourgli, A.; Sebai, H.; Bouteldja, S.; Oukil, Y.
2016-06-01
Nowadays, content-based image-retrieval techniques constitute powerful tools for archiving and mining of large remote sensing image databases. High spatial resolution images are complex and differ widely in their content, even in the same category. All images are more or less textured and structured. During the last decade, different approaches for the retrieval of this type of images have been proposed. They differ mainly in the type of features extracted. As these features are supposed to efficiently represent the query image, they should be adapted to all kind of images contained in the database. However, if the image to recognize is somewhat or very structured, a shape feature will be somewhat or very effective. While if the image is composed of a single texture, a parameter reflecting the texture of the image will reveal more efficient. This yields to use adaptive schemes. For this purpose, we propose to investigate this idea to adapt the retrieval scheme to image nature. This is achieved by making some preliminary analysis so that indexing stage becomes supervised. First results obtained show that by this way, simple methods can give equal performances to those obtained using complex methods such as the ones based on the creation of bag of visual word using SIFT (Scale Invariant Feature Transform) descriptors and those based on multi scale features extraction using wavelets and steerable pyramids.
Quick Local Repair Scheme using Adaptive Promiscuous Mode in Mobile Ad Hoc Networks
Joo-Sang Youn
2006-05-01
Full Text Available In mobile ad hoc networks (MANETs, there is frequently disconnected a route consisting of multi- hop from a source to a destination because of the dynamic nature such as the topology change caused by nodes’ mobility. To overcome this situation, existing routing protocols for MANETs have performed route repair scheme to repair the disconnected route. However, existing reactive routing protocols have the problem which is that a source node unnecessarily performs re-discovers the whole path when just one node moves, even if the rest of path needs not to be re-arranged. Therefore, the time for re-discovery of the whole path may often take too long. To solve the problem, we propose a new local repair scheme using promiscuous mode. Our scheme is mainly composed of two parts: adaptive promiscuous mode and quick local repair scheme. Adaptive promiscuous mode is to repeat the switching processes between promiscuous mode and nonpromiscuous mode to overcome energy limit caused by using promiscuous mode in overall time and quick local repair scheme is to fast perform the local re-route discovery process with the information of the active connection in the local area acquired by promiscuous mode. With simulation in the various number of connection, We demonstrate the better network performances achieved with the proposed schemes as compared with AODV as reference model that do not provide local repair scheme.
Residual Distribution Schemes for Conservation Laws Via Adaptive Quadrature
Barth, Timothy; Abgrall, Remi; Biegel, Bryan (Technical Monitor)
2000-01-01
This paper considers a family of nonconservative numerical discretizations for conservation laws which retains the correct weak solution behavior in the limit of mesh refinement whenever sufficient order numerical quadrature is used. Our analysis of 2-D discretizations in nonconservative form follows the 1-D analysis of Hou and Le Floch. For a specific family of nonconservative discretizations, it is shown under mild assumptions that the error arising from non-conservation is strictly smaller than the discretization error in the scheme. In the limit of mesh refinement under the same assumptions, solutions are shown to satisfy an entropy inequality. Using results from this analysis, a variant of the "N" (Narrow) residual distribution scheme of van der Weide and Deconinck is developed for first-order systems of conservation laws. The modified form of the N-scheme supplants the usual exact single-state mean-value linearization of flux divergence, typically used for the Euler equations of gasdynamics, by an equivalent integral form on simplex interiors. This integral form is then numerically approximated using an adaptive quadrature procedure. This renders the scheme nonconservative in the sense described earlier so that correct weak solutions are still obtained in the limit of mesh refinement. Consequently, we then show that the modified form of the N-scheme can be easily applied to general (non-simplicial) element shapes and general systems of first-order conservation laws equipped with an entropy inequality where exact mean-value linearization of the flux divergence is not readily obtained, e.g. magnetohydrodynamics, the Euler equations with certain forms of chemistry, etc. Numerical examples of subsonic, transonic and supersonic flows containing discontinuities together with multi-level mesh refinement are provided to verify the analysis.
An Adaptive Motion Estimation Scheme for Video Coding
Pengyu Liu
2014-01-01
Full Text Available The unsymmetrical-cross multihexagon-grid search (UMHexagonS is one of the best fast Motion Estimation (ME algorithms in video encoding software. It achieves an excellent coding performance by using hybrid block matching search pattern and multiple initial search point predictors at the cost of the computational complexity of ME increased. Reducing time consuming of ME is one of the key factors to improve video coding efficiency. In this paper, we propose an adaptive motion estimation scheme to further reduce the calculation redundancy of UMHexagonS. Firstly, new motion estimation search patterns have been designed according to the statistical results of motion vector (MV distribution information. Then, design a MV distribution prediction method, including prediction of the size of MV and the direction of MV. At last, according to the MV distribution prediction results, achieve self-adaptive subregional searching by the new estimation search patterns. Experimental results show that more than 50% of total search points are dramatically reduced compared to the UMHexagonS algorithm in JM 18.4 of H.264/AVC. As a result, the proposed algorithm scheme can save the ME time up to 20.86% while the rate-distortion performance is not compromised.
An adaptive interpolation scheme for molecular potential energy surfaces.
Kowalewski, Markus; Larsson, Elisabeth; Heryudono, Alfa
2016-08-28
The calculation of potential energy surfaces for quantum dynamics can be a time consuming task-especially when a high level of theory for the electronic structure calculation is required. We propose an adaptive interpolation algorithm based on polyharmonic splines combined with a partition of unity approach. The adaptive node refinement allows to greatly reduce the number of sample points by employing a local error estimate. The algorithm and its scaling behavior are evaluated for a model function in 2, 3, and 4 dimensions. The developed algorithm allows for a more rapid and reliable interpolation of a potential energy surface within a given accuracy compared to the non-adaptive version. PMID:27586901
An adaptive interpolation scheme for molecular potential energy surfaces
Kowalewski, Markus; Heryudono, Alfa
2016-01-01
The calculation of potential energy surfaces for quantum dynamics can be a time consuming task -- especially when a high level of theory for the electronic structure calculation is required. We propose an adaptive interpolation algorithm based on polyharmonic splines combined with a partition of unity approach. The adaptive node refinement allows to greatly reduce the number of sample points by employing a local error estimate. The algorithm and its scaling behavior is evaluated for a model function in 2, 3 and 4 dimensions. The developed algorithm allows for a more rapid and reliable interpolation of a potential energy surface within a given accuracy compared to the non-adaptive version.
Hyun, Jaeyub; Kook, Junghwan; Wang, Semyung
2015-01-01
This study proposes an efficient and stable model reduction scheme for the numerical simulation of broadband, inhomogeneous, and anisotropic acoustic systems. Unlike a conventional model reduction scheme, the proposed model reduction scheme uses the adaptive quasi-static Ritz vector (AQSRV) as a ...
A Self-Adaptive Behavior-Aware Recruitment Scheme for Participatory Sensing
Yuanyuan Zeng
2015-09-01
Full Text Available Participatory sensing services utilizing the abundant social participants with sensor-enabled handheld smart device resources are gaining high interest nowadays. One of the challenges faced is the recruitment of participants by fully utilizing their daily activity behavior with self-adaptiveness toward the realistic application scenarios. In the paper, we propose a self-adaptive behavior-aware recruitment scheme for participatory sensing. People are assumed to join the sensing tasks along with their daily activity without pre-defined ground truth or any instructions. The scheme is proposed to model the tempo-spatial behavior and data quality rating to select participants for participatory sensing campaign. Based on this, the recruitment is formulated as a linear programming problem by considering tempo-spatial coverage, data quality, and budget. The scheme enables one to check and adjust the recruitment strategy adaptively according to application scenarios. The evaluations show that our scheme provides efficient sensing performance as stability, low-cost, tempo-spatial correlation and self-adaptiveness.
A Self-Adaptive Behavior-Aware Recruitment Scheme for Participatory Sensing.
Zeng, Yuanyuan; Li, Deshi
2015-01-01
Participatory sensing services utilizing the abundant social participants with sensor-enabled handheld smart device resources are gaining high interest nowadays. One of the challenges faced is the recruitment of participants by fully utilizing their daily activity behavior with self-adaptiveness toward the realistic application scenarios. In the paper, we propose a self-adaptive behavior-aware recruitment scheme for participatory sensing. People are assumed to join the sensing tasks along with their daily activity without pre-defined ground truth or any instructions. The scheme is proposed to model the tempo-spatial behavior and data quality rating to select participants for participatory sensing campaign. Based on this, the recruitment is formulated as a linear programming problem by considering tempo-spatial coverage, data quality, and budget. The scheme enables one to check and adjust the recruitment strategy adaptively according to application scenarios. The evaluations show that our scheme provides efficient sensing performance as stability, low-cost, tempo-spatial correlation and self-adaptiveness. PMID:26389910
Adaptive Decision-Making Scheme for Cognitive Radio Networks
Alqerm, Ismail
2014-05-01
Radio resource management becomes an important aspect of the current wireless networks because of spectrum scarcity and applications heterogeneity. Cognitive radio is a potential candidate for resource management because of its capability to satisfy the growing wireless demand and improve network efficiency. Decision-making is the main function of the radio resources management process as it determines the radio parameters that control the use of these resources. In this paper, we propose an adaptive decision-making scheme (ADMS) for radio resources management of different types of network applications including: power consuming, emergency, multimedia, and spectrum sharing. ADMS exploits genetic algorithm (GA) as an optimization tool for decision-making. It consists of the several objective functions for the decision-making process such as minimizing power consumption, packet error rate (PER), delay, and interference. On the other hand, maximizing throughput and spectral efficiency. Simulation results and test bed evaluation demonstrate ADMS functionality and efficiency.
An adaptive additive inflation scheme for Ensemble Kalman Filters
Sommer, Matthias; Janjic, Tijana
2016-04-01
Data assimilation for atmospheric dynamics requires an accurate estimate for the uncertainty of the forecast in order to obtain an optimal combination with available observations. This uncertainty has two components, firstly the uncertainty which originates in the the initial condition of that forecast itself and secondly the error of the numerical model used. While the former can be approximated quite successfully with an ensemble of forecasts (an additional sampling error will occur), little is known about the latter. For ensemble data assimilation, ad-hoc methods to address model error include multiplicative and additive inflation schemes, possibly also flow-dependent. The additive schemes rely on samples for the model error e.g. from short-term forecast tendencies or differences of forecasts with varying resolutions. However since these methods work in ensemble space (i.e. act directly on the ensemble perturbations) the sampling error is fixed and can be expected to affect the skill substiantially. In this contribution we show how inflation can be generalized to take into account more degrees of freedom and what improvements for future operational ensemble data assimilation can be expected from this, also in comparison with other inflation schemes.
A well-balanced numerical scheme for shallow water simulation on adaptive grids
The efficiency of solving two-dimensional shallow-water equations (SWEs) is vital for simulation of large-scale flood inundation. For flood flows over real topography, local high-resolution method, which uses adaptable grids, is required in order to prevent the loss of accuracy of the flow pattern while saving computational cost. This paper introduces an adaptive grid model, which uses an adaptive criterion calculated on the basis of the water lever. The grid adaption is performed by manipulating subdivision levels of the computation grids. As the flow feature varies during the shallow wave propagation, the local grid density changes adaptively and the stored information of neighbor relationship updates correspondingly, achieving a balance between the model accuracy and running efficiency. In this work, a well-balanced (WB) scheme for solving SWEs is introduced. In reconstructions of Riemann state, the definition of the unique bottom elevation on grid interfaces is modified, and the numerical scheme is pre-balanced automatically. By the validation against two idealist test cases, the proposed model is applied to simulate flood inundation due to a dam-break of Zhanghe Reservoir, Hubei province, China. The results show that the presented model is robust and well-balanced, has nice computational efficiency and numerical stability, and thus has bright application prospects.
Teyssier, Romain; Fromang, Sébastien; Dormy, Emmanuel
2006-10-01
We propose to extend the well-known MUSCL-Hancock scheme for Euler equations to the induction equation modeling the magnetic field evolution in kinematic dynamo problems. The scheme is based on an integral form of the underlying conservation law which, in our formulation, results in a “finite-surface” scheme for the induction equation. This naturally leads to the well-known “constrained transport” method, with additional continuity requirement on the magnetic field representation. The second ingredient in the MUSCL scheme is the predictor step that ensures second order accuracy both in space and time. We explore specific constraints that the mathematical properties of the induction equations place on this predictor step, showing that three possible variants can be considered. We show that the most aggressive formulations (referred to as C-MUSCL and U-MUSCL) reach the same level of accuracy as the other one (referred to as Runge Kutta), at a lower computational cost. More interestingly, these two schemes are compatible with the adaptive mesh refinement (AMR) framework. It has been implemented in the AMR code RAMSES. It offers a novel and efficient implementation of a second order scheme for the induction equation. We have tested it by solving two kinematic dynamo problems in the low diffusion limit. The construction of this scheme for the induction equation constitutes a step towards solving the full MHD set of equations using an extension of our current methodology.
ADAPTIVE LIFTING BASED IMAGE COMPRESSION SCHEME WITH PARTICLE SWARM OPTIMIZATION TECHNIQUE
Nishat kanvel; Dr.S.Letitia,; Dr.Elwin Chandra Monie
2010-01-01
This paper presents an adaptive lifting scheme with Particle Swarm Optimization technique for image compression. Particle swarm Optimization technique is used to improve the accuracy of the predictionfunction used in the lifting scheme. This scheme is applied in Image compression and parameters such as PSNR, Compression Ratio and the visual quality of the image is calculated .The proposed scheme iscompared with the existing methods.
An adaptive blind watermarking scheme utilizing neural network for synchronization
WU Jian-zhen; XIE Jian-ying; YANG Yu-pu
2007-01-01
An important problem constraining the practical implementation of robust watermarking technology is the low robustness of existing algorithms against geometrical distortions. An adaptive blind watermarking scheme utilizing neural network for synchronization is proposed in this paper,which allows to recover watermark even if the image has been subjected to generalized geometrical transforms. Through classification of image's brightness, texture and contrast sensitivity utilizing fuzzy clustering theory and human visual system, more robust watermark is adaptively embedded in DWT domain. In order to register rotation, scaling and translation parameters, feedforward neural network is utilized to learn image geometric pattern represented by six combined low order image moments. The distortion can be inverted after determining the affine distortion applied to the image and watermark can be extracted in a standard way without original image. It only needs a trained neural network. Experimental results demonstrate its advantages over previous method in terms of computational effectiveness and parameter estimation accuracy. It can embed more robust watermark under certain visual distance, and effectively resist JPEG compression, noise and geometric attacks.
Adaptive QoS Class Allocation Schemes in Multi-Domain Path-Based Networks
Ogino, Nagao; Nakamura, Hajime
MPLS-based path technology shows promise as a means of realizing reliable IP networks. Real-time services such as VoIP and video-conference supplied through a multi-domain MPLS network must be able to guarantee end-to-end QoS of the inter-domain paths. Thus, it is important to allocate an appropriate QoS class to the inter-domain paths in each domain traversed by the inter-domain paths. Because each domain has its own policy for QoS class allocation, it is necessary to adaptively allocate the optimum QoS class based on estimation of the QoS class allocation policies in other domains. This paper proposes two kinds of adaptive QoS class allocation schemes, assuming that the arriving inter-domain path requests include the number of downstream domains traversed by the inter-domain paths and the remaining QoS value toward the destination nodes. First, a measurement-based scheme, based on measurement of the loss rates of inter-domain paths in the downstream domains, is proposed. This scheme estimates the QoS class allocation policies in the downstream domains, using the measured loss rates of path requests. Second, a state-dependent type scheme, based on measurement of the arrival rates of path requests in addition to the loss rates of paths in the downstream domains, is also proposed. This scheme allows an appropriate QoS class to be allocated according to the domain state. This paper proposes an application of the Markov decision theory to the modeling of state-dependent type scheme. The performances of the proposed schemes are evaluated and compared with those of the other less complicated non-adaptive schemes using a computer simulation. The results of the comparison reveal that the proposed schemes can adaptively increase the number of inter-domain paths accommodated in the considered domain, even when the QoS class allocation policies change in the other domains and the arrival pattern of path requests varies in the considered domain.
New Adaptive Data Transmission Scheme Over HF Radio
Adil H. Ahmad
2008-01-01
Full Text Available Acceptable Bit Error rate can be maintained by adapting some of the design parameters such as modulation, symbol rate, constellation size, and transmit power according to the channel state.An estimate of HF propagation effects can be used to design an adaptive data transmission system over HF link. The proposed system combines the well known Automatic Link Establishment (ALE together with variable rate transmission system. The standard ALE is modified to suite the required goal of selecting the best carrier frequency (channel for a given transmission. This is based on measuring SINAD (Signal plus Noise plus Distortion to Noise plus Distortion, RSL (Received Signal Level, multipath phase distortion and BER (Bit Error Rate for each channel in the frequency list. Channel condition evaluation is done by two arrangements. In the first an FFT analysis is used where a pilot signal is transmitted over the channel, while the data itself is used in the second arrangement. Passive channel assessment is used to avoid bad channels hence limiting the frequency pool size to be used in the point to point communication and the time required for scanning and linking. An exchange of channel information between the transmitting and receiving stations is considered to select the modulation scheme for transmission. Mainly MPSK and MFSK are considered with different levels giving different data rate according to the channel condition. The results of the computer simulation have shown that when transmitting at a fixed channel symbol rate of 1200 symbol/sec, the information rate ranges from 2400 bps using 4FSK up to 3600 bps using 8PSK for SNR ranges from 11dB up to 26dB.
An adaptive nonlinear solution scheme for reservoir simulation
Lett, G.S. [Scientific Software - Intercomp, Inc., Denver, CO (United States)
1996-12-31
Numerical reservoir simulation involves solving large, nonlinear systems of PDE with strongly discontinuous coefficients. Because of the large demands on computer memory and CPU, most users must perform simulations on very coarse grids. The average properties of the fluids and rocks must be estimated on these grids. These coarse grid {open_quotes}effective{close_quotes} properties are costly to determine, and risky to use, since their optimal values depend on the fluid flow being simulated. Thus, they must be found by trial-and-error techniques, and the more coarse the grid, the poorer the results. This paper describes a numerical reservoir simulator which accepts fine scale properties and automatically generates multiple levels of coarse grid rock and fluid properties. The fine grid properties and the coarse grid simulation results are used to estimate discretization errors with multilevel error expansions. These expansions are local, and identify areas requiring local grid refinement. These refinements are added adoptively by the simulator, and the resulting composite grid equations are solved by a nonlinear Fast Adaptive Composite (FAC) Grid method, with a damped Newton algorithm being used on each local grid. The nonsymmetric linear system of equations resulting from Newton`s method are in turn solved by a preconditioned Conjugate Gradients-like algorithm. The scheme is demonstrated by performing fine and coarse grid simulations of several multiphase reservoirs from around the world.
On-line Adaptive and Intelligent Distance Relaying Scheme for Power Network
Dubey, Rahul; Samantaray, S. R.; Panigrahi, B. K.; Venkoparao, G. V.
2015-10-01
The paper presents an on-line sequential extreme learning machine (OS-ELM) based fast and accurate adaptive distance relaying scheme (ADRS) for transmission line protection. The proposed method develops an adaptive relay characteristics suitable to the changes in the physical conditions of the power systems. This can efficiently update the trained model on-line by partial training on the new data to reduce the model updating time whenever a new special case occurs. The effectiveness of the proposed method is validated on simulation platform for test system with two terminal parallel transmission lines with complex mutual coupling. The test results, considering wide variations in operating conditions of the faulted power network, indicate that the proposed adaptive relay setting provides significant improvement in the relay performance.
Adaptive Covariance Inflation in a Multi-Resolution Assimilation Scheme
Hickmann, K. S.; Godinez, H. C.
2015-12-01
When forecasts are performed using modern data assimilation methods observation and model error can be scaledependent. During data assimilation the blending of error across scales can result in model divergence since largeerrors at one scale can be propagated across scales during the analysis step. Wavelet based multi-resolution analysiscan be used to separate scales in model and observations during the application of an ensemble Kalman filter. However,this separation is done at the cost of implementing an ensemble Kalman filter at each scale. This presents problemswhen tuning the covariance inflation parameter at each scale. We present a method to adaptively tune a scale dependentcovariance inflation vector based on balancing the covariance of the innovation and the covariance of observations ofthe ensemble. Our methods are demonstrated on a one dimensional Kuramoto-Sivashinsky (K-S) model known todemonstrate non-linear interactions between scales.
Adaptive multi-objective Optimization scheme for cognitive radio resource management
Alqerm, Ismail
2014-12-01
Cognitive Radio is an intelligent Software Defined Radio that is capable to alter its transmission parameters according to predefined objectives and wireless environment conditions. Cognitive engine is the actuator that performs radio parameters configuration by exploiting optimization and machine learning techniques. In this paper, we propose an Adaptive Multi-objective Optimization Scheme (AMOS) for cognitive radio resource management to improve spectrum operation and network performance. The optimization relies on adapting radio transmission parameters to environment conditions using constrained optimization modeling called fitness functions in an iterative manner. These functions include minimizing power consumption, Bit Error Rate, delay and interference. On the other hand, maximizing throughput and spectral efficiency. Cross-layer optimization is exploited to access environmental parameters from all TCP/IP stack layers. AMOS uses adaptive Genetic Algorithm in terms of its parameters and objective weights as the vehicle of optimization. The proposed scheme has demonstrated quick response and efficiency in three different scenarios compared to other schemes. In addition, it shows its capability to optimize the performance of TCP/IP layers as whole not only the physical layer.
Qian Hu
2011-04-01
Full Text Available The MAC protocol for wireless sensor networks is different from traditional wireless MACs such as IEEE 802.11. Energy conservation is one of the most important goals, while per-node fairness and latency are less important. This paper proposes an energy efficient MAC protocol with adaptive transmit power scheme based on SMAC/AL named ATPM (Adaptive Transmit Power MAC. In SMAC/AL, all the nodes transmit data with a fixed power level, no matter how close the involved nodes are. The proposed ATPM can calculate the distance between the sender and the receiver by measuring the received power, and then adaptively decide the appropriate transmit power level according to the propagation model and distance. Simulations have been done to evaluate the performance of the proposed new protocol, by which we can find out that ATPM can really reduce energy consumption compared with SMAC/AL.
Automated adaptive sliding mode control scheme for a class of real complicated systems
M Shahi; A H Mazinan
2015-02-01
A class of real complicated systems, including chemical reactions, biological systems, information processing, laser systems, electrical circuits, information exchange, brain activities modelling, secure communication and other related ones can be presented through nonlinear and non-identical hyper-chaotic systems. The main goal of the present investigation is to synchronize two non-identical hyperchaotic master/slave systems, which are given as the models of the complicated systems, based on the realization of an efficient automated adaptive sliding mode control scheme. In the research presented here, the mentioned systems need to be dealt with through the proposed control scheme, since two non-identical systems are completely synchronized. In one such case, the whole of the chosen states of the master and slave systems should be coincided after a few time steps, as long as the effect of the external disturbance, uncertainty and unknown parameters could truly be ignored. Due to the fact that the investigated hyper-chaotic systems have taken into consideration as the representation of a number of complicated processes under mentioned external disturbance, uncertainty and unknown parameters, the traditional control approaches cannot actually be realized, in satisfactory manners.With this purpose, the proposed control scheme has been designed to cope with synchronization error, in a reasonable amount of time, in order to drive applicable hyper-chaotic systems. Consequently, the performance of the proposed control scheme is considered and verified through the numerical simulations.
ADAPTATIVE IMAGE WATERMARKING SCHEME BASED ON NEURAL NETWORK
BASSEL SOLAIMANE
2011-01-01
Full Text Available Digital image watermarking has been proposed as a method to enhance medical data security, confidentiality and integrity. Medical image watermarking requires extreme care when embedding additional data, given their importance to clinical diagnosis, treatment, and research. In this paper, a novel image watermarking approach based on the human visual system (HVS model and neural network technique is proposed. The watermark was inserted into the middle frequency coefficients of the cover image’s blocked DCT based transform domain. In order to make the watermark stronger and less susceptible to different types of attacks, it is essential to find the maximum amount of interested watermark before the watermark becomes visible. In this paper, neural networks are used to implement an automated system of creating maximum-strength watermarks. The experimental results show that such method can survive of common image processing operations and has good adaptability for automated watermark embedding.
A novel adaptive classification scheme for digital modulations in satellite communication
Wu Dan; Gu Xuemai; Guo Qing
2007-01-01
To make the modulation classification system more suitable for signals in a wide range of signal to noise ratios (SNRs) , a novel adaptive modulation classification scheme is presented in this paper. Different from traditional schemes, the proposed scheme employs a new SNR estimation algorithm for small samples before modulation classification, which makes the modulation classifier work adaptively according to estimated SNRs. Furthermore, it uses three efficient features and support vector machines (SVM) in modulation classification. Computer simulation shows that the scheme can adaptively classify ten digital modulation types (i.e. 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, 16QAM, TFM, π/4QPSK and OQPSK) at SNRS ranging from OdB to 25 dB and success rates are over 95% when SNR is not lower than 3dB. Accuracy, efficiency and simplicity of the proposed scheme are obviously improved, which make it more adaptive to engineering applications.
A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm
Wah Ching Lee; Kim Fung Tsang; Hao Ran Chi; Faan Hei Hung; Chung Kit Wu; Kwok Tai Chui; Wing Hong Lau; Yat Wah Leung
2015-01-01
A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity fo...
Subset Optimization of Adaptive Coding and Modulation Schemes for Broadband Satellite Systems
Boussemart, Vincent; Brandt, Hartmut; Berioli, Matteo
2010-01-01
The number of Coding and Modulation Schemes suggested for the two standards DVB-S2 and DVB-RCS (in its "advanced" version) is clearly overdimensioned; a subset of schemes can be used by reducing the overall system performance negligibly. This paper presents the investigations performed on this rain fading mitigation technique, called Adaptive Coding and Modulation (ACM), supported by the DVB-S2 standard and shows how the sets of modulation and coding schemes, considered in the forward- and in...
The new Exponential Directional Iterative (EDI) 3-D Sn scheme for parallel adaptive differencing
The new Exponential Directional Iterative (EDI) discrete ordinates (Sn) scheme for 3-D Cartesian Coordinates is presented. The EDI scheme is a logical extension of the positive, efficient Exponential Directional Weighted (EDW) Sn scheme currently used as the third level of the adaptive spatial differencing algorithm in the PENTRAN parallel discrete ordinates solver. Here, the derivation and advantages of the EDI scheme are presented; EDI uses EDW-rendered exponential coefficients as initial starting values to begin a fixed point iteration of the exponential coefficients. One issue that required evaluation was an iterative cutoff criterion to prevent the application of an unstable fixed point iteration; although this was needed in some cases, it was readily treated with a default to EDW. Iterative refinement of the exponential coefficients in EDI typically converged in fewer than four fixed point iterations. Moreover, EDI yielded more accurate angular fluxes compared to the other schemes tested, particularly in streaming conditions. Overall, it was found that the EDI scheme was up to an order of magnitude more accurate than the EDW scheme on a given mesh interval in streaming cases, and is potentially a good candidate as a fourth-level differencing scheme in the PENTRAN adaptive differencing sequence. The 3-D Cartesian computational cost of EDI was only about 20% more than the EDW scheme, and about 40% more than Diamond Zero (DZ). More evaluation and testing are required to determine suitable upgrade metrics for EDI to be fully integrated into the current adaptive spatial differencing sequence in PENTRAN. (author)
Performance analysis of joint diversity combining, adaptive modulation, and power control schemes
Qaraqe, Khalid A.
2011-01-01
Adaptive modulation and diversity combining represent very important adaptive solutions for future generations of wireless communication systems. Indeed, in order to improve the performance and the efficiency of these systems, these two techniques have been recently used jointly in new schemes named joint adaptive modulation and diversity combining (JAMDC) schemes. Considering the problem of finding low hardware complexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario and capitalizing on some of these recently proposed JAMDC schemes, we propose and analyze in this paper three joint adaptive modulation, diversity combining, and power control (JAMDCPC) schemes where a constant-power variable-rate adaptive modulation technique is used with an adaptive diversity combining scheme and a common power control process. More specifically, the modulation constellation size, the number of combined diversity paths, and the needed power level are jointly determined to achieve the highest spectral efficiency with the lowest possible processing power consumption quantified in terms of the average number of combined paths, given the fading channel conditions and the required bit error rate (BER) performance. In this paper, the performance of these three JAMDCPC schemes is analyzed in terms of their spectral efficiency, processing power consumption, and error-rate performance. Selected numerical examples show that these schemes considerably increase the spectral efficiency of the existing JAMDC schemes with a slight increase in the average number of combined paths for the low signal-to-noise ratio range while maintaining compliance with the BER performance and a low radiated power which yields to a substantial decrease in interference to co-existing users and systems. © 2011 IEEE.
A stable adaptive synchronization scheme for uncertain chaotic systems via observer
A novel observer-based adaptive synchronization scheme is presented which is used in a chaos communication system. Also, a new nonlinear stochastic adaptive sliding mode observer is extended to reconstruct the states of the stochastic chaotic transmitter at the receiver. The observer is able to overcome the effect of model and parameters uncertainties as well as transmitter, channel and measurement noises. Moreover, a theorem is presented to prove the stability in probability of the proposed observer using stochastic Lyapunov stability criterion. The time-varying adaptation gains of the observer resulted from the proposed theorem ensure fast convergence of the estimated states. Adaptation gains are bounded and do not have any singularity problem especially when the mean value of the observer states' error. In this paper, the parameters of the transmitter are unknown or are changed intermittently to increase the security of the message transmission. Performance of the message reconstruction in the receiver is enhanced using the scalar transmitted signal to estimate the parameters of the transmitter.
A stable adaptive synchronization scheme for uncertain chaotic systems via observer
Ayati, Moosa [Department of Electrical Engineering, K.N. Toosi University of Technology, Tehran (Iran, Islamic Republic of)], E-mail: ayati@dena.kntu.ac.ir; Khaloozadeh, Hamid [Department of Electrical Engineering, K.N. Toosi University of Technology, Tehran (Iran, Islamic Republic of)
2009-11-30
A novel observer-based adaptive synchronization scheme is presented which is used in a chaos communication system. Also, a new nonlinear stochastic adaptive sliding mode observer is extended to reconstruct the states of the stochastic chaotic transmitter at the receiver. The observer is able to overcome the effect of model and parameters uncertainties as well as transmitter, channel and measurement noises. Moreover, a theorem is presented to prove the stability in probability of the proposed observer using stochastic Lyapunov stability criterion. The time-varying adaptation gains of the observer resulted from the proposed theorem ensure fast convergence of the estimated states. Adaptation gains are bounded and do not have any singularity problem especially when the mean value of the observer states' error. In this paper, the parameters of the transmitter are unknown or are changed intermittently to increase the security of the message transmission. Performance of the message reconstruction in the receiver is enhanced using the scalar transmitted signal to estimate the parameters of the transmitter.
Adaptive nonseparable vector lifting scheme for digital holographic data compression.
Xing, Yafei; Kaaniche, Mounir; Pesquet-Popescu, Béatrice; Dufaux, Frédéric
2015-01-01
Holographic data play a crucial role in recent three-dimensional imaging as well as microscopic applications. As a result, huge amounts of storage capacity will be involved for this kind of data. Therefore, it becomes necessary to develop efficient hologram compression schemes for storage and transmission purposes. In this paper, we focus on the shifted distance information, obtained by the phase-shifting algorithm, where two sets of difference data need to be encoded. More precisely, a nonseparable vector lifting scheme is investigated in order to exploit the two-dimensional characteristics of the holographic contents. Simulations performed on different digital holograms have shown the effectiveness of the proposed method in terms of bitrate saving and quality of object reconstruction. PMID:25967029
A spectrally efficient detect-and-forward scheme with two-tier adaptive cooperation
Benjillali, Mustapha
2011-09-01
We propose a simple relay-based adaptive cooperation scheme to improve the spectral efficiency of "Detect-and-Forward" (DetF) half-duplex relaying in fading channels. In a new common framework, we show that the proposed scheme offers considerable gainsin terms of the achievable information ratescompared to conventional DetF relaying schemes for both orthogonal and non-orthogonal source/relay transmissions. The analysis leads on to a general adaptive cooperation strategy based on the maximization of information rates at the destination which needs to observe only the average signal-to-noise ratios of the links. © 2006 IEEE.
An adaptive sampling scheme for deep-penetration calculation
As we know, the deep-penetration problem has been one of the important and difficult problems in shielding calculation with Monte Carlo Method for several decades. In this paper, an adaptive Monte Carlo method under the emission point as a sampling station for shielding calculation is investigated. The numerical results show that the adaptive method may improve the efficiency of the calculation of shielding and might overcome the under-estimation problem easy to happen in deep-penetration calculation in some degree
Adaptive Wide-Area Damping Control Scheme for Smart Grids with Consideration of Signal Time Delay
Deyou Yang
2013-09-01
Full Text Available As an important part of the smart grid, a wide-area measurement system (WAMS provides the key technical support for power system monitoring, protection and control. But 20 uncertainties in system parameters and signal transmission time delay could worsen the damping effect and deteriorate the system stability. In the presented study, the subspace system identification technique (SIT is used to firstly derive a low-order linear model of a power system from the measurements. Then, a novel adaptive wide-area damping control scheme for online tuning of the wide-area damping controller (WADC parameters using the residue method is proposed. In order to eliminate the effects of the time delay to the signal transmission, a simple and practical time delay compensation algorithm is proposed to compensate the time delay in each wide-area control signal. Detailed examples, inspired by the IEEE test system under various disturbance scenarios, have been used to verify the effectiveness of the proposed adaptive wide-area damping control scheme.
Multiwavelets and the lifting scheme are two important developments of wavelet theory. Multiwavelets outperform scalar wavelets in many applications due to their better properties. The lifting scheme is a method to construct a new wavelet with prescribed properties. In this paper, multiwavelets are integrated with the lifting scheme, synthesizing their advantages. Due to multiple wavelet bases, the lifting scheme of multiwavelets is more flexible than that of scalar wavelets. With supplement of a symmetric condition, a novel adaptive symmetric lifting scheme of multiwavelets is presented. Kurtosis is chosen to be the performance measurement of lifting coefficients, and the genetic algorithm is used to optimize the free parameters in the lifting scheme. The proposed method, constructing a new multiwavelet via an adaptive lifting scheme, is applied to analyze the simulation of a rolling bearing and gearbox vibration signals. The results demonstrate that the adaptive symmetric lifting of multiwavelets is more effective in extracting fault features of rotating machinery than conventional diagnosis techniques with scalar wavelets and non-adaptive multiwavelets
On the feedback error compensation for adaptive modulation and coding scheme
Choi, Seyeong
2011-11-25
In this paper, we consider the effect of feedback error on the performance of the joint adaptive modulation and diversity combining (AMDC) scheme which was previously studied with an assumption of perfect feedback channels. We quantify the performance of two joint AMDC schemes in the presence of feedback error, in terms of the average spectral efficiency, the average number of combined paths, and the average bit error rate. The benefit of feedback error compensation with adaptive combining is also quantified. Selected numerical examples are presented and discussed to illustrate the effectiveness of the proposed feedback error compensation strategy with adaptive combining. Copyright (c) 2011 John Wiley & Sons, Ltd.
Shunfu Jin
2013-01-01
Full Text Available In cognitive radio networks, if all the secondary user (SU packets join the system without any restrictions, the average latency of the SU packets will be greater, especially when the traffic load of the system is higher. For this, we propose an adaptive admission control scheme with a system access probability for the SU packets in this paper. We suppose the system access probability is inversely proportional to the total number of packets in the system and introduce an Adaptive Factor to adjust the system access probability. Accordingly, we build a discrete-time preemptive queueing model with adjustable joining rate. In order to obtain the steady-state distribution of the queueing model exactly, we construct a two-dimensional Markov chain. Moreover, we derive the formulas for the blocking rate, the throughput, and the average latency of the SU packets. Afterwards, we provide numerical results to investigate the influence of the Adaptive Factor on different performance measures. We also give the individually optimal strategy and the socially optimal strategy from the standpoints of the SU packets. Finally, we provide a pricing mechanism to coordinate the two optimal strategies.
Design of an Adaptive Scheme to Enable Green Localization
Estelrich Moreno, Rafel
2011-01-01
[ANGLÈS] The use of localization attached to any kind of devices is a common feature nowadays. In the case of sensors, the combination of sampling, connectivity and localization bring a world of possibilities. However, those small devices lack of enough energy resources due its size. To resolve the problem, a protocol named High Configurable Protocol was implemented in order to adapt the operation to the user needs, while focusing on energy savings. The problem comes from, once configured, th...
Welding Adaptive Functions Performed Through Infrared (IR) Simplified Vision Schemes
Begin, Ghlslain; Boillot, Jean-Paul
1984-02-01
An ideal integrated robotic welding system should incorporate off-line programmation with the possibility of real time modifications of a given welding programme. Off-line programmation makes possible the optimization of the various sequences of a programme by simulation and therefore promotes increased welding station duty cycle. Real time modifications of a given programme, generated either by an off-line programmation scheme or by a learn mode on a first piece of a series, are essential because on many occasions, the cumulative dimensional tolerances and the distorsions associated with the process, build up a misfit beetween the programmed welding path and the real joint to be welded, to the extent that welding defects occur.
Hybrid adaptive control of a dragonfly model
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.
A multilevel adaptive mesh generation scheme using Kd-trees
Alfonso Limon
2009-04-01
Full Text Available We introduce a mesh refinement strategy for PDE based simulations that benefits from a multilevel decomposition. Using Harten's MRA in terms of Schroder-Pander linear multiresolution analysis [20], we are able to bound discontinuities in $mathbb{R}$. This MRA is extended to $mathbb{R}^n$ in terms of n-orthogonal linear transforms and utilized to identify cells that contain a codimension-one discontinuity. These refinement cells become leaf nodes in a balanced Kd-tree such that a local dyadic MRA is produced in $mathbb{R}^n$, while maintaining a minimal computational footprint. The nodes in the tree form an adaptive mesh whose density increases in the vicinity of a discontinuity.
Efficient Pseudorecursive Evaluation Schemes for Non-adaptive Sparse Grids
Buse, Gerrit
2014-01-01
In this work we propose novel algorithms for storing and evaluating sparse grid functions, operating on regular (not spatially adaptive), yet potentially dimensionally adaptive grid types. Besides regular sparse grids our approach includes truncated grids, both with and without boundary grid points. Similar to the implicit data structures proposed in Feuersänger (Dünngitterverfahren für hochdimensionale elliptische partielle Differntialgleichungen. Diploma Thesis, Institut für Numerische Simulation, Universität Bonn, 2005) and Murarasu et al. (Proceedings of the 16th ACM Symposium on Principles and Practice of Parallel Programming. Cambridge University Press, New York, 2011, pp. 25–34) we also define a bijective mapping from the multi-dimensional space of grid points to a contiguous index, such that the grid data can be stored in a simple array without overhead. Our approach is especially well-suited to exploit all levels of current commodity hardware, including cache-levels and vector extensions. Furthermore, this kind of data structure is extremely attractive for today’s real-time applications, as it gives direct access to the hierarchical structure of the grids, while outperforming other common sparse grid structures (hash maps, etc.) which do not match with modern compute platforms that well. For dimensionality d ≤ 10 we achieve good speedups on a 12 core Intel Westmere-EP NUMA platform compared to the results presented in Murarasu et al. (Proceedings of the International Conference on Computational Science—ICCS 2012. Procedia Computer Science, 2012). As we show, this also holds for the results obtained on Nvidia Fermi GPUs, for which we observe speedups over our own CPU implementation of up to 4.5 when dealing with moderate dimensionality. In high-dimensional settings, in the order of tens to hundreds of dimensions, our sparse grid evaluation kernels on the CPU outperform any other known implementation.
A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm
Wah Ching Lee
2015-01-01
Full Text Available A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day.
A high fuel consumption efficiency management scheme for PHEVs using an adaptive genetic algorithm.
Lee, Wah Ching; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei; Wu, Chung Kit; Chui, Kwok Tai; Lau, Wing Hong; Leung, Yat Wah
2015-01-01
A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day. PMID:25587974
Adaptive numerical algorithms in space weather modeling
Tóth, Gábor; van der Holst, Bart; Sokolov, Igor V.; De Zeeuw, Darren L.; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Najib, Dalal; Powell, Kenneth G.; Stout, Quentin F.; Glocer, Alex; Ma, Ying-Juan; Opher, Merav
2012-02-01
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 relevant physics in different domains. A multi-physics system can be modeled by a software framework comprising 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 Solarwind Roe-type Upwind Scheme (BATS-R-US) code that can solve various forms of the magnetohydrodynamic (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
Adaptive numerical algorithms in space weather modeling
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 relevant physics in different domains. A multi-physics system can be modeled by a software framework comprising 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 Solarwind Roe-type Upwind Scheme (BATS-R-US) code that can solve various forms of the magnetohydrodynamic (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
Fromang, S.; Hennebelle, P.; Teyssier, R.
2006-01-01
In this paper, we present a new method to perform numerical simulations of astrophysical MHD flows using the Adaptive Mesh Refinement framework and Constrained Transport. The algorithm is based on a previous work in which the MUSCL--Hancock scheme was used to evolve the induction equation. In this paper, we detail the extension of this scheme to the full MHD equations and discuss its properties. Through a series of test problems, we illustrate the performances of this new code using two diffe...
An Adaptive Soft Handover Scheme Using Fuzzy Load Balancing for WCDMA Systems
Yang, Kemeng; Qiu, Bin; Dooley, Laurence S.
2006-01-01
In cellular systems, user distribution variations can cause load imbalance between cells. Embedding a load balancing strategy within the handover scheme means that ensuing traffic congestion can be alleviated by dynamically reallocating load between neighbouring cells. An adaptive soft handover scheme for multimedia cellular communication systems is proposed in this paper, that considers both the cell load factors as well as the pilot channel signal-to-interference-and-noise-ratio (SINR) for ...
A low order adaptive control scheme for hydraulic servo systems
Andersen, Torben Ole; Pedersen, Henrik Clemmensen; Bech, Michael Møller;
2015-01-01
This paper deals with high-performance position control of hydraulics servo systems in general. The hydraulic servo system used is a two link robotic manipulator actuated by two hydraulic servo cylinders. A non-linear model of the hydraulic system and a Newton-Euler based model of the mechanical...
Benaskeur, Abder R.; Roy, Jean
2001-08-01
Sensor Management (SM) has to do with how to best manage, coordinate and organize the use of sensing resources in a manner that synergistically improves the process of data fusion. Based on the contextual information, SM develops options for collecting further information, allocates and directs the sensors towards the achievement of the mission goals and/or tunes the parameters for the realtime improvement of the effectiveness of the sensing process. Conscious of the important role that SM has to play in modern data fusion systems, we are currently studying advanced SM Concepts that would help increase the survivability of the current Halifax and Iroquois Class ships, as well as their possible future upgrades. For this purpose, a hierarchical scheme has been proposed for data fusion and resource management adaptation, based on the control theory and within the process refinement paradigm of the JDL data fusion model, and taking into account the multi-agent model put forward by the SASS Group for the situation analysis process. The novelty of this work lies in the unified framework that has been defined for tackling the adaptation of both the fusion process and the sensor/weapon management.
An Energy Efficient Semi-static Power Control and Link Adaptation Scheme in UMTS HSDPA
Huang, Yi; Qiu, Ling
2012-01-01
High speed downlink packet access (HSDPA) has been successfully applied in commercial systems and improves user experience significantly. However, it incurs substantial energy consumption. In this paper, we address this issue by proposing a novel energy efficient semi-static power control and link adaptation scheme in HSDPA. Through estimating the EE under different modulation and coding schemes (MCSs) and corresponding transmit power, the proposed scheme can determine the most energy efficient MCS level and transmit power at the Node B. And then the Node B configure the optimal MCS level and transmit power. In order to decrease the signaling overhead caused by the configuration, a dual trigger mechanism is employed. After that, we extend the proposed scheme to the multiple input multiple output (MIMO) scenarios. Simulation results confirm the significant EE improvement of our proposed scheme. Finally, we give a discussion on the potential EE gain and challenge of the energy efficient mode switching between s...
Analysis of an Adaptive P-Persistent MAC Scheme for WLAN Providing Delay Fairness
Yen, Chih-Ming; Chang, Chung-Ju; Chen, Yih-Shen; Huang, Ching Yao
The paper proposes and analyzes an adaptive p-persistent-based (APP) medium access control (MAC) scheme for IEEE 802.11 WLAN. The APP MAC scheme intends to support delay fairness for every station in each access, denoting small delay variance. It differentiates permission probabilities of transmission for stations which are incurred with various packet delays. This permission probability is designed as a function of the numbers of retransmissions and re-backoffs so that stations with larger packet delay are endowed with higher permission probability. Also, the scheme is analyzed by a Markov-chain analysis, where the collision probability, the system throughput, and the average delay are successfully obtained. Numerical results show that the proposed APP MAC scheme can attain lower mean delay and higher mean throughput. In the mean time, simulation results are given to justify the validity of the analysis, and also show that the APP MAC scheme can achieve more delay fairness than conventional algorithms.
Joint multiuser switched diversity and adaptive modulation schemes for spectrum sharing systems
Qaraqe, Marwa
2012-12-01
In this paper, we develop multiuser access schemes for spectrum sharing systems whereby secondary users are allowed to share the spectrum with primary users under the condition that the interference observed at the primary receiver is below a predetermined threshold. In particular, we devise two schemes for selecting a user among those that satisfy the interference constraint and achieve an acceptable signal-to-noise ratio level. The first scheme selects the user that reports the best channel quality. In order to alleviate the high feedback load associated with the first scheme, we develop a second scheme based on the concept of switched diversity where the base station scans the users in a sequential manner until an acceptable user is found. In addition to these two selection schemes, we consider two power adaptive settings at the secondary users based on the amount of interference available at the secondary transmitter. In the On/Off power setting, users are allowed to transmit based on whether the interference constraint is met or not, while in the full power adaptive setting, the users are allowed to vary their transmission power to satisfy the interference constraint. Finally, we present numerical results for our proposed algorithms where we show the trade-off between the average spectral efficiency and average feedback load for both schemes. © 2012 IEEE.
Yin, Jun; Yang, Yuwang; Wang, Lei
2016-01-01
Joint design of compressed sensing (CS) and network coding (NC) has been demonstrated to provide a new data gathering paradigm for multi-hop wireless sensor networks (WSNs). By exploiting the correlation of the network sensed data, a variety of data gathering schemes based on NC and CS (Compressed Data Gathering-CDG) have been proposed. However, these schemes assume that the sparsity of the network sensed data is constant and the value of the sparsity is known before starting each data gathering epoch, thus they ignore the variation of the data observed by the WSNs which are deployed in practical circumstances. In this paper, we present a complete design of the feedback CDG scheme where the sink node adaptively queries those interested nodes to acquire an appropriate number of measurements. The adaptive measurement-formation procedure and its termination rules are proposed and analyzed in detail. Moreover, in order to minimize the number of overall transmissions in the formation procedure of each measurement, we have developed a NP-complete model (Maximum Leaf Nodes Minimum Steiner Nodes-MLMS) and realized a scalable greedy algorithm to solve the problem. Experimental results show that the proposed measurement-formation method outperforms previous schemes, and experiments on both datasets from ocean temperature and practical network deployment also prove the effectiveness of our proposed feedback CDG scheme. PMID:27043574
A Self-Adaptive Behavior-Aware Recruitment Scheme for Participatory Sensing
Yuanyuan Zeng; Deshi Li
2015-01-01
Participatory sensing services utilizing the abundant social participants with sensor-enabled handheld smart device resources are gaining high interest nowadays. One of the challenges faced is the recruitment of participants by fully utilizing their daily activity behavior with self-adaptiveness toward the realistic application scenarios. In the paper, we propose a self-adaptive behavior-aware recruitment scheme for participatory sensing. People are assumed to join the sensing tasks along wi...
An Adaptive WLAN Interference Mitigation Scheme for ZigBee Sensor Networks
Jo Woon Chong; Chae Ho Cho; Ho Young Hwang; Dan Keun Sung
2015-01-01
We propose an adaptive interference avoidance scheme that enhances the performance of ZigBee networks by adapting ZigBees' transmissions to measured wireless local area network (WLAN) interference. Our proposed algorithm is based on a stochastic analysis of ZigBee operation that is interfered with by WLAN transmission, given ZigBee and WLAN channels are overlaid in the industrial, scientific, and medical (ISM) band. We assume that WLAN devices have higher transmission power than ZigBee device...
ADAPTATIVE IMAGE WATERMARKING SCHEME BASED ON NEURAL NETWORK
BASSEL SOLAIMANE; ADNENE CHERIF; SAMEH OUESLATI,
2011-01-01
Digital image watermarking has been proposed as a method to enhance medical data security, confidentiality and integrity. Medical image watermarking requires extreme care when embedding additional data, given their importance to clinical diagnosis, treatment, and research. In this paper, a novel image watermarking approach based on the human visual system (HVS) model and neural network technique is proposed. The watermark was inserted into the middle frequency coefficients of the cover image’...
A Formal Model for the Security of Proxy Signature Schemes
GU Chun-xiang; ZHU Yue-fei; ZHANG Ya-juan
2005-01-01
This paper provides theoretical foundations for the secure proxy signature primitive. We present a formal model for the security of proxy signature schemes, which defines the capabilities of the adversary and the security goals to capture which mean for a proxy signature scheme to be secure. Then, we present an example of proxy signature scheme that can be proven secure in the standard model.
Teyssier, R.; Fromang, S.; Dormy, E.
2006-01-01
We propose to extend the well-known MUSCL-Hancock scheme for Euler equations to the induction equation modeling the magnetic field evolution in kinematic dynamo problems. The scheme is based on an integral form of the underlying conservation law which, in our formulation, results in a ``finite-surface'' scheme for the induction equation. This naturally leads to the well-known ``constrained transport'' method, with additional continuity requirement on the magnetic field representation. The sec...
Multi-dimensional upwind fluctuation splitting scheme with mesh adaption for hypersonic viscous flow
Wood, William Alfred, III
production is shown relative to DMFDSFV. Remarkably the fluctuation splitting scheme shows grid converged skin friction coefficients with only five points in the boundary layer for this case. A viscous Mach 17.6 (perfect gas) cylinder case demonstrates solution monotonicity and heat transfer capability with the fluctuation splitting scheme. While fluctuation splitting is recommended over DMFDSFV, the difference in performance between the schemes is not so great as to obsolete DMFDSFV. The second half of the dissertation develops a local, compact, anisotropic unstructured mesh adaption scheme in conjunction with the multi-dimensional upwind solver, exhibiting a characteristic alignment behavior for scalar problems. This alignment behavior stands in contrast to the curvature clustering nature of the local, anisotropic unstructured adaption strategy based upon a posteriori error estimation that is used for comparison. The characteristic alignment is most pronounced for linear advection, with reduced improvement seen for the more complex non-linear advection and advection-diffusion cases. The adaption strategy is extended to the two-dimensional and axisymmetric Navier-Stokes equations of motion through the concept of fluctuation minimization. The system test case for the adaption strategy is a sting mounted capsule at Mach-10 wind tunnel conditions, considered in both two-dimensional and axisymmetric configurations. For this complex flowfield the adaption results are disappointing since feature alignment does not emerge from the local operations. Aggressive adaption is shown to result in a loss of robustness for the solver, particularly in the bow shock/stagnation point interaction region. Reducing the adaption strength maintains solution robustness but fails to produce significant improvement in the surface heat transfer predictions.
An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks
Ali Safa Sadiq
2014-01-01
Full Text Available We propose an adaptive handover prediction (AHP scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches.
An adaptive short-term prediction scheme for wind energy storage management
Research highlights: → We develop a real time algorithm for grid-connected wind energy storage management. → The method aims to guarantee, with ±5% error margin, the power sent to the grid. → Dynamic scheduling of energy storage is based on short-term energy prediction. → Accurate predictions reduce the need in storage capacity. -- Abstract: Efficient forecasting scheme that includes some information on the likelihood of the forecast and based on a better knowledge of the wind variations characteristics along with their influence on power output variation is of key importance for the optimal integration of wind energy in island's power system. In the Guadeloupean archipelago (French West-Indies), with a total wind power capacity of 25 MW; wind energy can represent up to 5% of the instantaneous electricity production. At this level, wind energy contribution can be equivalent to the current network primary control reserve, which causes balancing difficult. The share of wind energy is due to grow even further since the objective is set to reach 118 MW by 2020. It is an absolute evidence for the network operator that due to security concerns of the electrical grid, the share of wind generation should not increase unless solutions are found to solve the prediction problem. The University of French West-Indies and Guyana has developed a short-term wind energy prediction scheme that uses artificial neural networks and adaptive learning procedures based on Bayesian approach and Gaussian approximation. This paper reports the results of the evaluation of the proposed approach; the improvement with respect to the simple persistent prediction model was globally good. A discussion on how such a tool combined with energy storage capacity could help to smooth the wind power variation and improve the wind energy penetration rate into island utility network is also proposed.
Adapted nested force-gradient integrators for the Schwinger model
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.
Chuan Zhu
2014-01-01
Full Text Available This paper exploits sink mobility to prolong the lifetime of sensor networks while maintaining the data transmission delay relatively low. A location predictive and time adaptive data gathering scheme is proposed. In this paper, we introduce a sink location prediction principle based on loose time synchronization and deduce the time-location formulas of the mobile sink. According to local clocks and the time-location formulas of the mobile sink, nodes in the network are able to calculate the current location of the mobile sink accurately and route data packets timely toward the mobile sink by multihop relay. Considering that data packets generating from different areas may be different greatly, an adaptive dwelling time adjustment method is also proposed to balance energy consumption among nodes in the network. Simulation results show that our data gathering scheme enables data routing with less data transmission time delay and balance energy consumption among nodes.
WANG Jing; TAN Zhen-Yu; MA Xi-Kui; GAO Jin-Feng
2009-01-01
A novel adaptive observer-based control scheme is presented for synchronization and suppression of a class of uncertain chaotic system. First, an adaptive observer based on an orthogonal neural network is designed. Subsequently, the sliding mode controllers via the proposed adaptive observer are proposed for synchronization and suppression of the uncertain chaotic systems. Theoretical analysis and numerical simulation show the effectiveness of the proposed scheme.
Dimassi, Habib; Loría, Antonio; Belghith, Safya
2012-09-01
We present a new scheme for the secured transmission of information based on master-slave synchronization of chaotic systems, using unknown-input observers. Our approach improves upon state-of-the-art schemes by being compatible with information of relatively large amplitude while improving security against intruders through an intricate encryption system. In addition, our approach is robust to channel noise. The main idea is to separate the encryption and synchronization operations by using two cascaded chaotic systems in the transmitter. Technically, the scheme is based on smooth adaptive unknown-input observers; these have the advantage to estimate the (master) states and to reconstruct the unknown inputs simultaneously. The performance of the communication system is illustrated in numerical simulation.
NOUROLLAH, SARA; PIRAYESH, ABOLFAZL; DIVSHALI, PORIA HASANPOR
2015-01-01
This paper proposes sharing active and reactive power in autonomous voltage source inverter (VSI)-based microgrids with no physical communication links. In decentralized VSI-based microgrids, when the demand or generation changes, the output voltage of distributed generation units and the frequency of the system will also change. This study presents a novel adaptive nonlinear droop (ANLD) scheme for preserving network stability, improving the system's dynamics, and controlling power shar...
Adapting Parcellation Schemes to Study Fetal Brain Connectivity in Serial Imaging Studies
Cheng, Xi; Wilm, Jakob; Seshamani, Sharmishtaa;
2013-01-01
developing fetal brain such functional and associated structural markers are not consistently present over time. In this study we adapt two non-atlas based parcellation schemes to study the development of connectivity networks of a fetal monkey brain using Diffusion Weighted Imaging techniques. Results...... demonstrate that the fetal brain network exhibits small-world characteristics and a pattern of increased cluster coefficients and decreased global efficiency. These findings may provide a route to creating a new biomarker for healthy fetal brain development....
Cuthbert Laurie
2011-01-01
Full Text Available Abstract A downlink adaptive distributed precoding scheme is proposed for coordinated multi-point (CoMP transmission systems. The serving base station (BS obtains the optimal precoding vector via user feedback. Meanwhile, the precoding vector of each coordinated BS is determined by adaptive gradient iteration according to the perturbation vector and the adjustment factor based on the vector perturbation method. In each transmission frame, the CoMP user feeds the precoding matrix index back to the serving BS, and feeds back the adjustment factor index to the coordinated BSs, which can reduce the uplink feedback overhead. The selected adjustment factor for each coordinated BS is obtained via the precoding vector of the coordinated BS used in the previous frame and the preferred precoding vector of the serving BS in this frame. The proposed scheme takes advantage of the spatial non-correlation and temporal correlation of the distributed MIMO channel. The design of the adjustment factor set is given and the channel feedback delay is considered. The system performance of the proposed scheme is verified with and without feedback delay respectively and the system feedback overhead is analyzed. Simulation results show that the proposed scheme has a good trade-off between system performance and the system control information overhead on feedback.
Electronic scheme simulator usage for pmt model creation
Бочаров, Олег Александрович
2011-01-01
This article grounds necessity of photomultiplier tube (PMT) model creation by means of computer circuit simulator, basic departure data for model creation are given, model scheme and results of it testing by means of computer circuit simulator are present
Iterative Schemes for Bump Solutions in a Neural Field Model
Oleynik, Anna; Ponosov, Arcady; Wyller, John
2013-01-01
We develop two iteration schemes for construction of localized stationary solutions (bumps) of a one-population Wilson-Cowan model with a smoothed Heaviside firing rate function. The first scheme is based on the fixed point formulation of the stationary Wilson-Cowan model. The second one is formulated in terms of the excitation width of a bump. Using the theory of monotone operators in ordered Banach spaces we justify convergence of both iteration schemes.
Multiple Regressive Model Adaptive Control
Garipov, Emil; Stoilkov, Teodor; Kalaykov, Ivan
2008-01-01
The essence of the ideas applied to this text consists in the development of the strategy for control of the arbitrary in complexity continuous plant by means of a set of discrete timeinvariant linear controllers. Their number and tuned parameters correspond to the number and parameters of the linear time-invariant regressive models in the model bank, which approximate the complex plant dynamics in different operating points. Described strategy is known as Multiple Regressive Model Adaptive C...
A novel power swing blocking scheme using adaptive neuro-fuzzy inference system
Zadeh, Hassan Khorashadi; Li, Zuyi [Illinois Institute of Technology, Department of Electrical and Computer Engineering, 3301 S. Dearborn Street, Chicago, IL 60616 (United States)
2008-07-15
A power swing may be caused by any sudden change in the configuration or the loading of an electrical network. During a power swing, the impedance locus moves along an impedance circle with possible encroachment into the distance relay zone, which may cause an unnecessary tripping. In order to prevent the distance relay from tripping under such condition, a novel power swing blocking (PSB) scheme is proposed in this paper. The proposed scheme uses an adaptive neuro-fuzzy inference systems (ANFIS) for preventing distance relay from tripping during power swings. The input signals to ANFIS, include the change of positive sequence impedance, positive and negative sequence currents, and power swing center voltage. Extensive tests show that the proposed PSB has two distinct features that are advantageous over existing schemes. The first is that the proposed scheme is able to detect various kinds of power swings thus block distance relays during power swings, even if the power swings are fast or the power swings occur during single pole open conditions. The second distinct feature is that the proposed scheme is able to clear the blocking if faults occur within the relay trip zone during power swings, even if the faults are high resistance faults, or the faults occur at the power swing center, or the faults occur when the power angle is close to 180 . (author)
Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding.
Lai, Hong; Zhang, Jun; Luo, Ming-Xing; Pan, Lei; Pieprzyk, Josef; Xiao, Fuyuan; Orgun, Mehmet A
2016-01-01
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. PMID:27515908
Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding
Lai, Hong; Zhang, Jun; Luo, Ming-Xing; Pan, Lei; Pieprzyk, Josef; Xiao, Fuyuan; Orgun, Mehmet A.
2016-01-01
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. PMID:27515908
A massively parallel adaptive scheme for melt migration in geodynamics computations
Dannberg, Juliane; Heister, Timo; Grove, Ryan
2016-04-01
Melt generation and migration are important processes for the evolution of the Earth's interior and impact the global convection of the mantle. While they have been the subject of numerous investigations, the typical time and length-scales of melt transport are vastly different from global mantle convection, which determines where melt is generated. This makes it difficult to study mantle convection and melt migration in a unified framework. In addition, modelling magma dynamics poses the challenge of highly non-linear and spatially variable material properties, in particular the viscosity. We describe our extension of the community mantle convection code ASPECT that adds equations describing the behaviour of silicate melt percolating through and interacting with a viscously deforming host rock. We use the original compressible formulation of the McKenzie equations, augmented by an equation for the conservation of energy. This approach includes both melt migration and melt generation with the accompanying latent heat effects, and it incorporates the individual compressibilities of the solid and the fluid phase. For this, we derive an accurate and stable Finite Element scheme that can be combined with adaptive mesh refinement. This is particularly advantageous for this type of problem, as the resolution can be increased in mesh cells where melt is present and viscosity gradients are high, whereas a lower resolution is sufficient in regions without melt. Together with a high-performance, massively parallel implementation, this allows for high resolution, 3d, compressible, global mantle convection simulations coupled with melt migration. Furthermore, scalable iterative linear solvers are required to solve the large linear systems arising from the discretized system. Finally, we present benchmarks and scaling tests of our solver up to tens of thousands of cores, show the effectiveness of adaptive mesh refinement when applied to melt migration and compare the
Auzinger, Winfried
2016-07-28
We present a number of new contributions to the topic of constructing efficient higher-order splitting methods for the numerical integration of evolution equations. Particular schemes are constructed via setup and solution of polynomial systems for the splitting coefficients. To this end we use and modify a recent approach for generating these systems for a large class of splittings. In particular, various types of pairs of schemes intended for use in adaptive integrators are constructed.
Saghri, John A.
2010-05-01
A computationally efficient adaptive two-stage Karhunen-Loeve transform (KLT) scheme for spectral decorrelation in hyperspectral lossy bandwidth compression is presented. The component decorrelation of the JPEG 2000 (extension 2) is replaced with an adaptive two-stage KLT scheme. The data are partitioned into small subsets. The spectral correlation within each partition is removed via a first-stage KLT. The interpartition spectral correlation is removed using a second-stage KLT applied to the resulting top few sets of equilevel principal component (PC) images. Since only a fraction of each equilevel first-stage PC images are used in the second stage, the KLT transformation matrices will have smaller sizes, leading to further improvement in computational complexity and coding efficiency. The computation of the proposed approach is parametrically quantified. It is shown that reconstructed image quality, as measured via statistical and/or machine-based exploitation measures, is improved by using a smaller partition size in the first-stage KLT. A criterion based on the components of the eigenvectors of the cross-covariance matrix is established to select first-stage PC images, which are used in the second-stage KLT. The proposed scheme also reduces the overhead bits required to transmit the covariance information to the receiver in conjunction with the coding bitstream.
Adaptive transmission schemes for MISO spectrum sharing systems: Tradeoffs and performance analysis
Bouida, Zied
2014-10-01
In this paper, we propose a number of adaptive transmission techniques in order to improve the performance of the secondary link in a spectrum sharing system. We first introduce the concept of minimum-selection maximum ratio transmission (MS-MRT) as an adaptive variation of the existing MRT (MRT) technique. While in MRT all available antennas are used for transmission, MS-MRT uses the minimum subset of antennas verifying both the interference constraint (IC) to the primary user and the bit error rate (BER) requirements. Similar to MRT, MS-MRT assumes that perfect channel state information (CSI) is available at the secondary transmitter (ST), which makes this scheme challenging from a practical point of view. To overcome this challenge, we propose another transmission technique based on orthogonal space-time block codes with transmit antenna selection (TAS). This technique uses the full-rate full-diversity Alamouti scheme in order to maximize the secondary\\'s transmission rate. The performance of these techniques is analyzed in terms of the average spectral efficiency (ASE), average number of transmit antennas, average delay, average BER, and outage performance. In order to give the motivation behind these analytical results, the tradeoffs offered by the proposed schemes are summarized and then demonstrated through several numerical examples.
Fromang, S; Teyssier, R
2006-01-01
In this paper, we present a new method to perform numerical simulations of astrophysical MHD flows using the Adaptive Mesh Refinement framework and Constrained Transport. The algorithm is based on a previous work in which the MUSCL--Hancock scheme was used to evolve the induction equation. In this paper, we detail the extension of this scheme to the full MHD equations and discuss its properties. Through a series of test problems, we illustrate the performances of this new code using two different MHD Riemann solvers (Lax-Friedrich and Roe) and the need of the Adaptive Mesh Refinement capabilities in some cases. Finally, we show its versatility by applying it to two completely different astrophysical situations well studied in the past years: the growth of the magnetorotational instability in the shearing box and the collapse of magnetized cloud cores. We have implemented this new Godunov scheme to solve the ideal MHD equations in the AMR code RAMSES. It results in a powerful tool that can be applied to a grea...
Fromang, S.; Hennebelle, P.; Teyssier, R.
2006-10-01
Aims. In this paper, we present a new method to perform numerical simulations of astrophysical MHD flows using the Adaptive Mesh Refinement framework and Constrained Transport. Methods: . The algorithm is based on a previous work in which the MUSCL-Hancock scheme was used to evolve the induction equation. In this paper, we detail the extension of this scheme to the full MHD equations and discuss its properties. Results: . Through a series of test problems, we illustrate the performances of this new code using two different MHD Riemann solvers (Lax-Friedrich and Roe) and the need of the Adaptive Mesh Refinement capabilities in some cases. Finally, we show its versatility by applying it to two completely different astrophysical situations well studied in the past years: the growth of the magnetorotational instability in the shearing box and the collapse of magnetized cloud cores. Conclusions: . We have implemented a new Godunov scheme to solve the ideal MHD equations in the AMR code RAMSES. We have shown that it results in a powerful tool that can be applied to a great variety of astrophysical problems, ranging from galaxies formation in the early universe to high resolution studies of molecular cloud collapse in our galaxy.
A Trust-Based Adaptive Probability Marking and Storage Traceback Scheme for WSNs.
Liu, Anfeng; Liu, Xiao; Long, Jun
2016-01-01
Security is a pivotal issue for wireless sensor networks (WSNs), which are emerging as a promising platform that enables a wide range of military, scientific, industrial and commercial applications. Traceback, a key cyber-forensics technology, can play an important role in tracing and locating a malicious source to guarantee cybersecurity. In this work a trust-based adaptive probability marking and storage (TAPMS) traceback scheme is proposed to enhance security for WSNs. In a TAPMS scheme, the marking probability is adaptively adjusted according to the security requirements of the network and can substantially reduce the number of marking tuples and improve network lifetime. More importantly, a high trust node is selected to store marking tuples, which can avoid the problem of marking information being lost. Experimental results show that the total number of marking tuples can be reduced in a TAPMS scheme, thus improving network lifetime. At the same time, since the marking tuples are stored in high trust nodes, storage reliability can be guaranteed, and the traceback time can be reduced by more than 80%. PMID:27043566
An Adaptive Loss-Aware Flow Control Scheme for Delay-Sensitive Applications in OBS Networks
Jeong, Hongkyu; Choi, Jungyul; Mo, Jeonghoon; Kang, Minho
Optical Burst Switching (OBS) is one of the most promising switching technologies for next generation optical networks. As delay-sensitive applications such as Voice-over-IP (VoIP) have recently become popular, OBS networks should guarantee stringent Quality of Service (QoS) requirements for such applications. Thus, this paper proposes an Adaptive Loss-aware Flow Control (ALFC) scheme, which adaptively decides on the burst offset time based on loss-rate information delivered from core nodes for assigning a high priority to delay-sensitive application traffic. The proposed ALFC scheme also controls the upper-bounds of the factors inducing delay and jitter for guaranteeing the delay and jitter requirements of delay-sensitive application traffic. Moreover, a piggybacking method used in the proposed scheme accelerates the guarantee of the loss, delay, and jitter requirements because the response time for flow control can be extremely reduced up to a quarter of the Round Trip Time (RTT) on average while minimizing the signaling overhead. Simulation results show that our mechanism can guarantee a 10-3 loss-rate under any traffic load while offering satisfactory levels of delay and jitter for delay-sensitive applications.
SIMULATION MODELS OF CALL ADMISSION CONTROL SCHEMES USING GPSS
Vassilya ABDULOVA
2014-01-01
Full Text Available In cellular wireless networks, a variety of channel allocation schemes have been developed for achieving high capacity with minimal interference. The choice of channel allocation scheme impacts the performance of the system, particularly as how calls are managed when a mobile user is handed off from one cell to another. Call Admission Control schemes take into account the effect of handoffs in the performance of the system, particularly call blocking probability and call dropping probability. In this study, we present simulation models and programs of some popular Call Admission Control schemes using GPSS simulation tool.
Fast Adaptive S-ALOHA Scheme for Event-driven Machine-to-Machine Communications
Wu, Huasen; La, Richard J; Liu, Xin; Zhang, Youguang
2012-01-01
Machine-to-Machine (M2M) communication is now playing a market-changing role in a wide range of business world. However, in event-driven M2M communications, a large number of devices activate within a short period of time, which in turn causes high radio congestions and severe access delay. To solve this problem, we propose a Fast Adaptive S-ALOHA (FASA) scheme for M2M communication systems with bursty traffic. The statistics of consecutive idle and collision slots are used in FASA to accelerate the tracking process of network status, instead of observing in a single slot. Furthermore, the fast convergence property of FASA is guaranteed by using drift analysis. Simulation results demonstrate that the proposed FASA scheme achieves near-optimal performance in reducing access delay, which outperforms that of traditional additive schemes such as PB-ALOHA. Moreover, compared to multiplicative schemes, FASA shows its robust performance even under heavy traffic load in addition to better delay performance.
SMR-Based Adaptive Mobility Management Scheme in Hierarchical SIP Networks
KwangHee Choi
2014-10-01
Full Text Available In hierarchical SIP networks, paging is performed to reduce location update signaling cost for mobility management. However, the cost efficiency largely depends on each mobile node’s session-to-mobility-ratio (SMR, which is defined as a ratio of the session arrival rate to the movement rate. In this paper, we propose the adaptive mobility management scheme that can determine the policy regarding to each mobile node’s SMR. Each mobile node determines whether the paging is applied or not after comparing its SMR with the threshold. In other words, the paging is applied to a mobile node when a mobile node’s SMR is less than the threshold. Therefore, the proposed scheme provides a way to minimize signaling costs according to each mobile node’s SMR. We find out the optimal threshold through performance analysis, and show that the proposed scheme can reduce signaling cost than the existing SIP and paging schemes in hierarchical SIP networks.
A general hybrid radiation transport scheme for star formation simulations on an adaptive grid
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...
A RSS Based Adaptive Hand-Off Management Scheme In Heterogeneous Networks
Debabrata Sarddar
2010-11-01
Full Text Available Mobility management, integration and interworking of existing wireless systems are important factors to obtain seamless roaming and services continuity in Next Generation Wireless Systems (NGWS.So it is important to have a handoff scheme that takes into account the heterogeneity of the network. In this work we propose a handoff scheme which takes handoff decision adaptively based on the type of network it presently resides and the one it is attempting handoff with through some predefined rules. It also relies on the speed of the mobile terminal to make a decision of the handoff initiation received signal strength (RSS threshold value. Finally simulations have been done to show the importance of taking these factors into account for handoff decisions rather than having a fixed threshold value of handoff for different scenarios.
Schaal, Kevin; Chandrashekar, Praveen; Pakmor, Rüdiger; Klingenberg, Christian; Springel, Volker
2015-01-01
Solving the Euler equations of ideal hydrodynamics as accurately and efficiently as possible is a key requirement in many astrophysical simulations. It is therefore important to continuously advance the numerical methods implemented in current astrophysical codes, especially also in light of evolving computer technology, which favours certain computational approaches over others. Here we introduce the new adaptive mesh refinement (AMR) code TENET, which employs a high-order Discontinuous Galerkin (DG) scheme for hydrodynamics. The Euler equations in this method are solved in a weak formulation with a polynomial basis by means of explicit Runge-Kutta time integration and Gauss-Legendre quadrature. This approach offers significant advantages over commonly employed finite volume (FV) solvers. In particular, the higher order capability renders it computationally more efficient, in the sense that the same precision can be obtained at significantly less computational cost. Also, the DG scheme inherently conserves a...
Decentralized & Adaptive Load-Frequency Control Scheme of Variable Speed Wind Turbines
Hoseinzadeh, Bakhtyar; Silva, Filipe Miguel Faria da; Bak, Claus Leth
2014-01-01
In power systems with high penetration of Wind Power (WP), transferring a part of Load Frequency Control (LFC) burden to variable speed Wind Turbines (WTs) is inevitable. The conventional LFC schemes merely rely on frequency information and since frequency is a common variable throughout...... and therefore determining the contribution factor of each individual WT to gain an adaptive LFC approach. The Electrical Distance (ED) concept confirms that the locally measured voltage decay is a proper criterion of closeness to the disturbance place. Numerical simulations carried out in DigSilent Power...
SMR-Based Adaptive Mobility Management Scheme in Hierarchical SIP Networks
KwangHee Choi; Joon-Min Gil
2014-01-01
In hierarchical SIP networks, paging is performed to reduce location update signaling cost for mobility management. However, the cost efficiency largely depends on each mobile node’s session-to-mobility-ratio (SMR), which is defined as a ratio of the session arrival rate to the movement rate. In this paper, we propose the adaptive mobility management scheme that can determine the policy regarding to each mobile node’s SMR. Each mobile node determines whether the paging is applied or not after...
The Nonlinear Sigma Model With Distributed Adaptive Mesh Refinement
Liebling, Steven 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.
Parallel Adaptive Simulation of Detonation Waves Using a Weighted Essentially Non-Oscillatory Scheme
McMahon, Sean
The purpose of this thesis was to develop a code that could be used to develop a better understanding of the physics of detonation waves. First, a detonation was simulated in one dimension using ZND theory. Then, using the 1D solution as an initial condition, a detonation was simulated in two dimensions using a weighted essentially non-oscillatory scheme on an adaptive mesh with the smallest lengthscales being equal to 2-3 flamelet lengths. The code development in linking Chemkin for chemical kinetics to the adaptive mesh refinement flow solver was completed. The detonation evolved in a way that, qualitatively, matched the experimental observations, however, the simulation was unable to progress past the formation of the triple point.
An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks
Zichuan Xu
2010-10-01
Full Text Available A high degree of reliability for critical data transmission is required in body sensor networks (BSNs. However, BSNs are usually vulnerable to channel impairments due to body fading effect and RF interference, which may potentially cause data transmission to be unreliable. In this paper, an adaptive and flexible fault-tolerant communication scheme for BSNs, namely AFTCS, is proposed. AFTCS adopts a channel bandwidth reservation strategy to provide reliable data transmission when channel impairments occur. In order to fulfill the reliability requirements of critical sensors, fault-tolerant priority and queue are employed to adaptively adjust the channel bandwidth allocation. Simulation results show that AFTCS can alleviate the effect of channel impairments, while yielding lower packet loss rate and latency for critical sensors at runtime.
Hybrid flux-splitting schemes for a common two-fluid model
The aim of this paper is to construct hybrid flux vector splitting (FVS) and flux difference splitting (FDS) schemes for a commonly used two-fluid model consisting of two separate momentum equations. This is done by refining ideas previously applied to develop hybrid FVS/FDS schemes for a simpler two-phase model consisting of a mixture momentum equation [J. Comput. Phys. 175 (2002) 674]. More specifically, we seek to construct upwind type of schemes which are not based on calculations of the full eigenstructure of Jacobi matrices as needed by approximate Riemann solvers like the Roe scheme. Based on a crude approximation of the eigenstructure of the model, we derive schemes of the van Leer and FVS type. We demonstrate that these schemes possess desirable stability properties, but are excessively diffusive. By adapting ideas originally suggested by Wada and Liou [SIAM J. Sci. Comput. 18 (1997) 633] for the Euler equations, we suggest a mechanism for removing numerical dissipation. We present numerical simulations where we compare the performance of the resulting schemes with that of the Roe scheme, and by that shed light on the issues of accuracy, efficiency, and robustness of the proposed schemes. Particularly, we consider the classical water faucet problem as well as a stiff separation problem which locally involves transition from two-phase to single-phase flow. Results from these test cases show that we are able to construct hybrid FVS/FDS schemes which properly combine the accuracy of FDS in the resolution of sharp mass fronts and the robustness of FVS which ensures stability under stiff conditions
Conceptual Model of User Adaptive Enterprise Application
Inese Šūpulniece
2015-07-01
Full Text Available The user adaptive enterprise application is a software system, which adapts its behavior to an individual user on the basis of nontrivial inferences from information about the user. The objective of this paper is to elaborate a conceptual model of the user adaptive enterprise applications. In order to conceptualize the user adaptive enterprise applications, their main characteristics are analyzed, the meta-model defining the key concepts relevant to these applications is developed, and the user adaptive enterprise application and its components are defined in terms of the meta-model. Modeling of the user adaptive enterprise application incorporates aspects of enterprise modeling, application modeling, and design of adaptive characteristics of the application. The end-user and her expectations are identified as two concepts of major importance not sufficiently explored in the existing research. Understanding these roles improves the adaptation result in the user adaptive applications.
Yu, Ya-Huei; Ho, Chien-Peng; Tsai, Chun-Jen
2007-12-01
Scalable video coding (SVC) has been an active research topic for the past decade. In the past, most SVC technologies were based on a coarse-granularity scalable model which puts many scalability constraints on the encoded bitstreams. As a result, the application scenario of adapting a preencoded bitstream multiple times along the distribution chain has not been seriously investigated before. In this paper, a model-based multiple-adaptation framework based on a wavelet video codec, MC-EZBC, is proposed. The proposed technology allows multiple adaptations on both the video data and the content-adaptive FEC protection codes. For multiple adaptations of video data, rate-distortion information must be embedded within the video bitstream in order to allow rate-distortion optimized operations for each adaptation. Experimental results show that the proposed method reduces the amount of side information by more than 50% on average when compared to the existing technique. It also reduces the number of iterations required to perform the tier-2 entropy coding by more than 64% on average. In addition, due to the nondiscrete nature of the rate-distortion model, the proposed framework also enables multiple adaptations of content-adaptive FEC protection scheme for more flexible error-resilient transmission of bitstreams.
Peano—A Traversal and Storage Scheme for Octree-Like Adaptive Cartesian Multiscale Grids
Weinzierl, Tobias
2011-01-01
Almost all approaches to solving partial differential equations (PDEs) are based upon a spatial discretization of the computational domain-a grid. This paper presents an algorithm to generate, store, and traverse a hierarchy of d-dimensional Cartesian grids represented by a (k = 3)- spacetree, a generalization of the well-known octree concept, and it also shows the correctness of the approach. These grids may change their adaptive structure throughout the traversal. The algorithm uses 2d + 4 stacks as data structures for both cells and vertices, and the storage requirements for the pure grid reduce to one bit per vertex for both the complete grid connectivity structure and the multilevel grid relations. Since the traversal algorithm uses only stacks, the algorithm\\'s cache hit rate is continually higher than 99.9 percent, and the runtime per vertex remains almost constant; i.e., it does not depend on the overall number of vertices or the adaptivity pattern. We use the algorithmic approach as the fundamental concept for a mesh management for d-dimensional PDEs and for a matrix-free PDE solver represented by a compact discrete 3 d-point operator. In the latter case, one can implement a Jacobi smoother, a Krylov solver, or a geometric multigrid scheme within the presented traversal scheme which inherits the low memory requirements and the good memory access characteristics directly. © 2011 Society for Industrial and Applied Mathematics.
A fault detection and isolation scheme for industrial systems based on multiple operating models
Rodrigues, Mickael; THEILLIOL, DIDIER; Adam Medina, Manuel; Sauter, Dominique
2008-01-01
In this paper, a fault diagnosis method is developed for systems described by multi- models. The main contribution consists in the design of a new Fault Detection and Isolation scheme (FDI) through an adaptive filter for such systems. Based on the assumption that dynamic behavior of the process is described by a multi-model approach around different operating points, a set of residual is established in order to generate weighting functions robust to faults. These robust weighting functions ar...
Q-phonon scheme in the collective nuclear model
The Q-phonon scheme developed in the framework of the algebraic collective nuclear model is discussed. It is shown that in the framework of this scheme the low-lying collective states of the even-even nuclei can be presented with an accuracy better than 90% of the norm using one or maximum two components of the Q-phonon basis constructed by an action of the fixed number of the quadrupole operators Q on the exact ground state of the system. Different applications of this approximate scheme are discussed. It is shown that using this scheme the relations between several E2-transition probabilities or between the energies of the collective states can be derived. It is shown also that the Q-phonon scheme can be used to extract an information about the equilibrium shapes of nuclei and their fluctuations from the data on the E2-transition probabilities
An adaptive high-order hybrid scheme for compressive, viscous flows with detailed chemistry
Ziegler, Jack L.; Deiterding, Ralf; Shepherd, Joseph E.; Pullin, D. I.
2011-08-01
A hybrid weighted essentially non-oscillatory (WENO)/centered-difference numerical method, with low numerical dissipation, high-order shock-capturing, and structured adaptive mesh refinement (SAMR), has been developed for the direct numerical simulation of the multicomponent, compressible, reactive Navier-Stokes equations. The method enables accurate resolution of diffusive processes within reaction zones. The approach combines time-split reactive source terms with a high-order, shock-capturing scheme specifically designed for diffusive flows. A description of the order-optimized, symmetric, finite difference, flux-based, hybrid WENO/centered-difference scheme is given, along with its implementation in a high-order SAMR framework. The implementation of new techniques for discontinuity flagging, scheme-switching, and high-order prolongation and restriction is described. In particular, the refined methodology does not require upwinded WENO at grid refinement interfaces for stability, allowing high-order prolongation and thereby eliminating a significant source of numerical diffusion within the overall code performance. A series of one-and two-dimensional test problems is used to verify the implementation, specifically the high-order accuracy of the diffusion terms. One-dimensional benchmarks include a viscous shock wave and a laminar flame. In two-space dimensions, a Lamb-Oseen vortex and an unstable diffusive detonation are considered, for which quantitative convergence is demonstrated. Further, a two-dimensional high-resolution simulation of a reactive Mach reflection phenomenon with diffusive multi-species mixing is presented.
Teyssier, R; Fromang, S
2006-01-01
We propose to extend the well-known MUSCL-Hancock scheme for Euler equations to the induction equation modeling the magnetic field evolution in kinematic dynamo problems. The scheme is based on an integral form of the underlying conservation law which, in our formulation, results in a ``finite-surface'' scheme for the induction equation. This naturally leads to the well-known ``constrained transport'' method, with additional continuity requirement on the magnetic field representation. The second ingredient in the MUSCL scheme is the predictor step that ensures second order accuracy both in space and time. We explore specific constraints that the mathematical properties of the induction equations place on this predictor step, showing that three possible variants can be considered. We show that the most aggressive formulations (referred to as C-MUSCL and U-MUSCL) reach the same level of accuracy as the other one (referred to as Runge-Kutta), at a lower computational cost. More interestingly, these two schemes a...
Patre, Parag; Joshi, Suresh M.
2011-01-01
Decentralized adaptive control is considered for systems consisting of multiple interconnected subsystems. It is assumed that each subsystem s parameters are uncertain and the interconnection parameters are not known. In addition, mismatch can exist between each subsystem and its reference model. A strictly decentralized adaptive control scheme is developed, wherein each subsystem has access only to its own state but has the knowledge of all reference model states. The mismatch is estimated online for each subsystem and the mismatch estimates are used to adaptively modify the corresponding reference models. The adaptive control scheme is extended to the case with actuator failures in addition to mismatch.
Jie Chen; Junwei Sun; Ming Chi; Xin-Ming Cheng
2014-01-01
The drive system can synchronize with the response system by the scaling factor in the traditional projective synchronization. This paper proposes a novel adaptive hybrid dislocated synchronization with uncertain parameters scheme for chaos synchronization using the Lyapunov stability theory. The drive system is synchronized by the sum of hybrid dislocated state variables for the response system. By designing effective hybrid dislocated adaptive controller and hybrid dislocated adaptive law o...
Adaptive resolution simulation of polarizable supramolecular coarse-grained water models
Zavadlav, Julija; Melo, Manuel N.; Marrink, Siewert J.; Praprotnik, Matej
2015-01-01
Multiscale simulations methods, such as adaptive resolution scheme, are becoming increasingly popular due to their significant computational advantages with respect to conventional atomistic simulations. For these kind of simulations, it is essential to develop accurate multiscale water models that
Clark, Martyn P.; Kavetski, Dmitri
2010-10-01
A major neglected weakness of many current hydrological models is the numerical method used to solve the governing model equations. This paper thoroughly evaluates several classes of time stepping schemes in terms of numerical reliability and computational efficiency in the context of conceptual hydrological modeling. Numerical experiments are carried out using 8 distinct time stepping algorithms and 6 different conceptual rainfall-runoff models, applied in a densely gauged experimental catchment, as well as in 12 basins with diverse physical and hydroclimatic characteristics. Results show that, over vast regions of the parameter space, the numerical errors of fixed-step explicit schemes commonly used in hydrology routinely dwarf the structural errors of the model conceptualization. This substantially degrades model predictions, but also, disturbingly, generates fortuitously adequate performance for parameter sets where numerical errors compensate for model structural errors. Simply running fixed-step explicit schemes with shorter time steps provides a poor balance between accuracy and efficiency: in some cases daily-step adaptive explicit schemes with moderate error tolerances achieved comparable or higher accuracy than 15 min fixed-step explicit approximations but were nearly 10 times more efficient. From the range of simple time stepping schemes investigated in this work, the fixed-step implicit Euler method and the adaptive explicit Heun method emerge as good practical choices for the majority of simulation scenarios. In combination with the companion paper, where impacts on model analysis, interpretation, and prediction are assessed, this two-part study vividly highlights the impact of numerical errors on critical performance aspects of conceptual hydrological models and provides practical guidelines for robust numerical implementation.
Iteration schemes for parallelizing models of superconductivity
Gray, P.A. [Michigan State Univ., East Lansing, MI (United States)
1996-12-31
The time dependent Lawrence-Doniach model, valid for high fields and high values of the Ginzburg-Landau parameter, is often used for studying vortex dynamics in layered high-T{sub c} superconductors. When solving these equations numerically, the added degrees of complexity due to the coupling and nonlinearity of the model often warrant the use of high-performance computers for their solution. However, the interdependence between the layers can be manipulated so as to allow parallelization of the computations at an individual layer level. The reduced parallel tasks may then be solved independently using a heterogeneous cluster of networked workstations connected together with Parallel Virtual Machine (PVM) software. Here, this parallelization of the model is discussed and several computational implementations of varying degrees of parallelism are presented. Computational results are also given which contrast properties of convergence speed, stability, and consistency of these implementations. Included in these results are models involving the motion of vortices due to an applied current and pinning effects due to various material properties.
Kumar, Navneet; Raj Chelliah, Thanga; Srivastava, S P
2015-07-01
Model Based Control (MBC) is one of the energy optimal controllers used in vector-controlled Induction Motor (IM) for controlling the excitation of motor in accordance with torque and speed. MBC offers energy conservation especially at part-load operation, but it creates ripples in torque and speed during load transition, leading to poor dynamic performance of the drive. This study investigates the opportunity for improving dynamic performance of a three-phase IM operating with MBC and proposes three control schemes: (i) MBC with a low pass filter (ii) torque producing current (iqs) injection in the output of speed controller (iii) Variable Structure Speed Controller (VSSC). The pre and post operation of MBC during load transition is also analyzed. The dynamic performance of a 1-hp, three-phase squirrel-cage IM with mine-hoist load diagram is tested. Test results are provided for the conventional field-oriented (constant flux) control and MBC (adjustable excitation) with proposed schemes. The effectiveness of proposed schemes is also illustrated for parametric variations. The test results and subsequent analysis confer that the motor dynamics improves significantly with all three proposed schemes in terms of overshoot/undershoot peak amplitude of torque and DC link power in addition to energy saving during load transitions. PMID:25820090
Liu Yu
2014-10-01
Full Text Available The paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic systems for improvement of accuracy and consistency. An efficient new algorithm called the adaptive Gaussian-sum square-root cubature Kalman filter (AGSSCKF with a split-merge scheme is proposed. It is developed based on the squared-root extension of newly introduced cubature Kalman filter (SCKF and is built within a Gaussian-sum framework. Based on the condition that the probability density functions of process noises and initial state are denoted by a Gaussian sum using optimization method, a bank of SCKF are used as the sub-filters to estimate state of system with the corresponding weights respectively, which is adaptively updated. The new algorithm consists of an adaptive splitting and merging procedure according to a proposed split-decision model based on the nonlinearity degree of measurement. The results of two simulation scenarios (one-dimensional state estimation and bearings-only tracking show that the proposed filter demonstrates comparable performance to the particle filter with significantly reduced computational cost.
Liu Yu; Dong Kai; Wang Haipeng; Liu Jun; He You; Pan Lina
2014-01-01
The paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic systems for improvement of accuracy and consistency. An efficient new algorithm called the adaptive Gaussian-sum square-root cubature Kalman filter (AGSSCKF) with a split-merge scheme is proposed. It is developed based on the squared-root extension of newly introduced cuba-ture Kalman filter (SCKF) and is built within a Gaussian-sum framework. Based on the condition that the probability density functions of process noises and initial state are denoted by a Gaussian sum using optimization method, a bank of SCKF are used as the sub-filters to estimate state of sys-tem with the corresponding weights respectively, which is adaptively updated. The new algorithm consists of an adaptive splitting and merging procedure according to a proposed split-decision model based on the nonlinearity degree of measurement. The results of two simulation scenarios (one-dimensional state estimation and bearings-only tracking) show that the proposed filter demon-strates comparable performance to the particle filter with significantly reduced computational cost.
Schaal, Kevin; Bauer, Andreas; Chandrashekar, Praveen; Pakmor, Rüdiger; Klingenberg, Christian; Springel, Volker
2015-11-01
Solving the Euler equations of ideal hydrodynamics as accurately and efficiently as possible is a key requirement in many astrophysical simulations. It is therefore important to continuously advance the numerical methods implemented in current astrophysical codes, especially also in light of evolving computer technology, which favours certain computational approaches over others. Here we introduce the new adaptive mesh refinement (AMR) code TENET, which employs a high-order discontinuous Galerkin (DG) scheme for hydrodynamics. The Euler equations in this method are solved in a weak formulation with a polynomial basis by means of explicit Runge-Kutta time integration and Gauss-Legendre quadrature. This approach offers significant advantages over commonly employed second-order finite-volume (FV) solvers. In particular, the higher order capability renders it computationally more efficient, in the sense that the same precision can be obtained at significantly less computational cost. Also, the DG scheme inherently conserves angular momentum in regions where no limiting takes place, and it typically produces much smaller numerical diffusion and advection errors than an FV approach. A further advantage lies in a more natural handling of AMR refinement boundaries, where a fall-back to first order can be avoided. Finally, DG requires no wide stencils at high order, and offers an improved data locality and a focus on local computations, which is favourable for current and upcoming highly parallel supercomputers. We describe the formulation and implementation details of our new code, and demonstrate its performance and accuracy with a set of two- and three-dimensional test problems. The results confirm that DG schemes have a high potential for astrophysical applications.
A general hybrid radiation transport scheme for star formation simulations on an adaptive grid
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.
An Adaptive Multimedia-Oriented Handoff Scheme for IEEE 802.11 WLANs
Rebai, Ahmed Riadh; 10.5121/ijwmn.2011.3114
2011-01-01
Previous studies have shown that the actual handoff schemes employed in the IEEE 802.11 Wireless LANs (WLANs) do not meet the strict delay constraints placed by many multimedia applications like Voice over IP. Both the active and the passive supported scan modes in the standard handoff procedure have important delay that affects the Quality of Service (QoS) required by the real-time communications over 802.11 networks. In addition, the problem is further compounded by the fact that limited coverage areas of Access Points (APs) occupied in 802.11 infrastructure WLANs create frequent handoffs. We propose a new optimized and fast handoff scheme that decrease both handoff latency and occurrence by performing a seamless prevent scan process and an effective next-AP selection. Through simulations and performance evaluation, we show the effectiveness of the new adaptive handoff that reduces the process latency and adds new context-based parameters. The Results illustrate a QoS delay-respect required by applications ...
A general hybrid radiation transport scheme for star formation simulations on an adaptive grid
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.
A General Hybrid Radiation Transport Scheme for Star Formation Simulations on an Adaptive Grid
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.
Kreis, Karsten; Tuckerman, Mark E; Donadio, Davide; Kremer, Kurt; Potestio, Raffaello
2016-07-12
Quantum delocalization of atomic nuclei affects the physical properties of many hydrogen-rich liquids and biological systems even at room temperature. In computer simulations, quantum nuclei can be modeled via the path-integral formulation of quantum statistical mechanics, which implies a substantial increase in computational overhead. By restricting the quantum description to a small spatial region, this cost can be significantly reduced. Herein, we derive a bottom-up, rigorous, Hamiltonian-based scheme that allows molecules to change from quantum to classical and vice versa on the fly as they diffuse through the system, both reducing overhead and making quantum grand-canonical simulations possible. The method is validated via simulations of low-temperature parahydrogen. Our adaptive resolution approach paves the way to efficient quantum simulations of biomolecules, membranes, and interfaces. PMID:27214610
Inflationary gravitational waves in collapse scheme models
Mauro Mariani
2016-01-01
Full Text Available The inflationary paradigm is an important cornerstone of the concordance cosmological model. However, standard inflation cannot fully address the transition from an early homogeneous and isotropic stage, to another one lacking such symmetries corresponding to our present universe. In previous works, a self-induced collapse of the wave function has been suggested as the missing ingredient of inflation. Most of the analysis regarding the collapse hypothesis has been solely focused on the characteristics of the spectrum associated to scalar perturbations, and within a semiclassical gravity framework. In this Letter, working in terms of a joint metric-matter quantization for inflation, we calculate, for the first time, the tensor power spectrum and the tensor-to-scalar ratio corresponding to the amplitude of primordial gravitational waves resulting from considering a generic self-induced collapse.
Diffusion coefficient adaptive correction in Lagrangian puff model
Lagrangian puff model is widely used in the decision support system for nuclear emergency management. The diffusion coefficient is one of the key parameters impacting puff model. An adaptive method was proposed in this paper, which could correct the diffusion coefficient in Lagrangian puff model, and it aimed to improve the accuracy of calculating the nuclide concentration distribution. This method used detected concentration data, meteorological data and source release data to estimate the actual diffusion coefficient with least square method. The diffusion coefficient adaptive correction method was evaluated by Kincaid data in MVK, and was compared with traditional Pasquill-Gifford (P-G) diffusion scheme method. The results indicate that this diffusion coefficient adaptive correction method can improve the accuracy of Lagrangian puff model. (authors)
Models of the group schemes of roots of unity
Mézard, Ariane; Tossici, Dajano
2011-01-01
Let O_K be a discrete valuation ring of mixed characteristics (0,p), with residue field k. Using work of Sekiguchi and Suwa, we construct some finite flat O_K-models of the group scheme \\mu_{p^n,K} of p^n-th roots of unity, which we call Kummer group schemes. We set carefully the general framework and algebraic properties of this construction. When k is perfect and O_K is a complete totally ramified extension of the ring of Witt vectors W(k), we provide a parallel study of the Breuil-Kisin modules of finite flat models of \\mu_{p^n,K}, in such a way that the construction of Kummer groups and Breuil-Kisin modules can be compared. We compute these objects for n < 4. This leads us to conjecture that all finite flat models of \\mu_{p^n,K} are Kummer group schemes.
Complex Modelling Scheme Of An Additive Manufacturing Centre
Popescu, Liliana Georgeta
2015-09-01
This paper presents a modelling scheme sustaining the development of an additive manufacturing research centre model and its processes. This modelling is performed using IDEF0, the resulting model process representing the basic processes required in developing such a centre in any university. While the activities presented in this study are those recommended in general, changes may occur in specific existing situations in a research centre.
A High-Capacity Image Data Hiding Scheme Using Adaptive LSB Substitution
H. Yang
2009-12-01
Full Text Available Many existing steganographic methods hide more secret data into edged areas than smooth areas in the host image, which does not differentiate textures from edges and causes serious degradation in actual edge areas. To avoid abrupt changes in image edge areas, as well as to achieve better quality of the stego-image, a novel image data hiding technique by adaptive Least Significant Bits (LSBs substitution is proposed in this paper. The scheme exploits the brightness, edges, and texture masking of the host image to estimate the number k of LSBs for data hiding. Pixels in the noise non-sensitive regions are embedded by a k-bit LSB substitution with a lager value of k than that of the pixels in noise sensitive regions. Moreover, an optimal pixel adjustment process is used to enhance stego-image visual quality obtained by simple LSB substitution method. To ensure that the adaptive number k of LSBs remains unchanged after pixel modification, the LSBs number is computed by the high-order bits rather than all the bits of the image pixel value. The theoretical analyses and experiment results show that the proposed method achieves higher embedding capacity and better stegoimage quality compared with some existing LSB methods.
Subjective quality assessment of an adaptive video streaming model
Tavakoli, Samira; Brunnström, Kjell; Wang, Kun; Andrén, Börje; Shahid, Muhammad; Garcia, Narciso
2014-01-01
With the recent increased popularity and high usage of HTTP Adaptive Streaming (HAS) techniques, various studies have been carried out in this area which generally focused on the technical enhancement of HAS technology and applications. However, a lack of common HAS standard led to multiple proprietary approaches which have been developed by major Internet companies. In the emerging MPEG-DASH standard the packagings of the video content and HTTP syntax have been standardized; but all the details of the adaptation behavior are left to the client implementation. Nevertheless, to design an adaptation algorithm which optimizes the viewing experience of the enduser, the multimedia service providers need to know about the Quality of Experience (QoE) of different adaptation schemes. Taking this into account, the objective of this experiment was to study the QoE of a HAS-based video broadcast model. The experiment has been carried out through a subjective study of the end user response to various possible clients' behavior for changing the video quality taking different QoE-influence factors into account. The experimental conclusions have made a good insight into the QoE of different adaptation schemes which can be exploited by HAS clients for designing the adaptation algorithms.
A general scheme for training and optimization of the Grenander deformable template model
Fisker, Rune; Schultz, Nette; Duta, N.; Carstensen, Jens Michael
2000-01-01
parameters, a very fast general initialization algorithm and an adaptive likelihood model based on local means. The model parameters are trained by a combination of a 2D shape learning algorithm and a maximum likelihood based criteria. The fast initialization algorithm is based on a search approach using a...... applying the general deformable template model proposed by (Grenander et al., 1991) to a new problem with minimal manual interaction, beside supplying a training set, which can be done by a non-expert user. The main contributions compared to previous work are a supervised learning scheme for the model...
He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Chen, Ying
2014-05-01
A multimodal biometric system has been considered a promising technique to overcome the defects of unimodal biometric systems. We have introduced a fusion scheme to gain a better understanding and fusion method for a face-iris-fingerprint multimodal biometric system. In our case, we use particle swarm optimization to train a set of adaptive Gabor filters in order to achieve the proper Gabor basic functions for each modality. For a closer analysis of texture information, two different local Gabor features for each modality are produced by the corresponding Gabor coefficients. Next, all matching scores of the two Gabor features for each modality are projected to a single-scalar score via a trained, supported, vector regression model for a final decision. A large-scale dataset is formed to validate the proposed scheme using the Facial Recognition Technology database-fafb and CASIA-V3-Interval together with FVC2004-DB2a datasets. The experimental results demonstrate that as well as achieving further powerful local Gabor features of multimodalities and obtaining better recognition performance by their fusion strategy, our architecture also outperforms some state-of-the-art individual methods and other fusion approaches for face-iris-fingerprint multimodal biometric systems.
A tightly bound soil-water scheme within an atmosphere-land-surface model
White, Rachel; Toumi, Ralf
2012-07-01
SummaryThe concept of tightly bound water, in which a reservoir of soil water is bound tightly within small soil pores but is still available for evapotranspiration, is parameterised for the first time within the land surface scheme of a fully-coupled regional-scale atmosphere-land surface model. The Weather Research and Forecasting (WRF) regional climate model and the NOAH land surface scheme are selected and a case study is performed on the Olifants River Basin in the Limpopo region of South Africa. Accurate knowledge of water availability in this water-stressed region is of great importance for adaptation and future water policy. Results of a simulation forced by ERA40 re-analysis show that the standard land surface scheme is unable to reproduce the observed runoff despite rainfall and atmospheric conditions similar to observed. This version of the model over-estimates mean annual runoff by 120%. The tightly bound water scheme shows a significant improvement, reducing the bias to 22%. The inclusion of the tightly bound water scheme has little effect on the basin average annual rainfall despite increasing annual evapotranspiration. The tightly bound water physics dampens the response of runoff to precipitation and provides additional de-coupling between precipitation and runoff, increasing the variability in this relationship. Simulations with the WRF model forced with both 1980s and 2040s CCSM3 data show that the tightly bound water scheme significantly reduces runoff in different climates and projects a greater relative future decrease in runoff, from 4% to 10% for the same precipitation decrease of 2.5%. The scheme also affects the projected changes in spatially averaged 100-year return precipitation and runoff with significance at the 0.9 confidence level.
Plant adaptive behaviour in hydrological models (Invited)
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
Masmoudi, Atef; Zouari, Sonia; Ghribi, Abdelaziz
2015-11-01
We propose a new adaptive block-wise lossless image compression algorithm, which is based on the so-called alphabet reduction scheme combined with an adaptive arithmetic coding (AC). This new encoding algorithm is particularly efficient for lossless compression of images with sparse and locally sparse histograms. AC is a very efficient technique for lossless data compression and produces a rate that is close to the entropy; however, a compression performance loss occurs when encoding images or blocks with a limited number of active symbols by comparison with the number of symbols in the nominal alphabet, which consists in the amplification of the zero frequency problem. Generally, most methods add one to the frequency count of each symbol from the nominal alphabet, which leads to a statistical model distortion, and therefore reduces the efficiency of the AC. The aim of this work is to overcome this drawback by assigning to each image block the smallest possible set including all the existing symbols called active symbols. This is an alternative of using the nominal alphabet when applying the conventional arithmetic encoders. We show experimentally that the proposed method outperforms several lossless image compression encoders and standards including the conventional arithmetic encoders, JPEG2000, and JPEG-LS.
Bouida, Zied
2012-12-01
Under the scenario of an underlay cognitive radio network, we propose in this paper two adaptive schemes using switched transmit diversity and adaptive modulation in order to increase the spectral efficiency of the secondary link and maintain a desired performance for the primary link. The proposed switching efficient scheme (SES) and bandwidth efficient scheme (BES) use the scan and wait combining technique (SWC) where a transmission occurs only when a branch with an acceptable performance is found, otherwise data is buffered. In these schemes, the modulation constellation size and the used transmit branch are determined to minimize the average number of switched branches and to achieve the highest spectral efficiency given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver (PR). For delay-sensitive applications, we also propose two variations of the SES and BES schemes using power control (SES-PC and BES-PC) where the secondary transmitter (ST) starts sending data using a nominal power level which is selected in order to minimize the average delay introduced by the SWC technique. We demonstrate through numerical examples that the BES scheme increases the capacity of the secondary link when compared to the SES scheme. This spectral efficiency improvement comes at the expense of an increased average number of switched branches and thus an increased average delay. We also show that the SES-PC and the BES-PC schemes minimize the average delay while satisfying the same spectral efficiency as the SES and BES schemes, respectively. © 2012 IEEE.
Marie Ramon
2009-01-01
Full Text Available Systematic lossy error protection (SLEP is a robust error resilient mechanism based on principles of Wyner-Ziv (WZ coding for video transmission over error-prone networks. In an SLEP scheme, the video bitstream is separated into two parts: a systematic part consisting of a video sequence transmitted without channel coding, and additional information consisting of a WZ supplementary stream. This paper presents an adaptive SLEP scheme in which the WZ stream is obtained by frequency filtering in the transform domain. Additionally, error resilience varies adaptively depending on the characteristics of compressed video. We show that the proposed SLEP architecture achieves graceful degradation of reconstructed video quality in the presence of increasing transmission errors. Moreover, it provides good performances in terms of error protection as well as reconstructed video quality if compared to solutions based on coarser quantization, while offering an interesting embedded scheme to apply digital video format conversion.
Jie Chen
2014-01-01
Full Text Available The drive system can synchronize with the response system by the scaling factor in the traditional projective synchronization. This paper proposes a novel adaptive hybrid dislocated synchronization with uncertain parameters scheme for chaos synchronization using the Lyapunov stability theory. The drive system is synchronized by the sum of hybrid dislocated state variables for the response system. By designing effective hybrid dislocated adaptive controller and hybrid dislocated adaptive law of the parameters estimation, we investigate the synchronization of two identical memristor chaotic oscillator systems and two different memristor chaotic oscillator systems with uncertain parameters. Finally, the numerical simulation examples are provided to show the effectiveness of our method.
An Adaptive Control Scheme for Nonholonomic Mobile Robot with Parametric Uncertainty
F. Touati
2008-11-01
Full Text Available This paper addresses the problem of stabilizing the dynamic model of a nonholonomic mobile robot. A discontinuous adaptive state feedback controller is derived to achieve global stability and convergence of the trajectories of the of the closed loop system in the presence of parameter modeling uncertainty. This task is achieved by a non smooth transformation in the original system followed by the derivation of a smooth time invariant control in the new coordinates. The stability and convergence analysis is built on Lyapunov stability theory.
Completing and adapting models of biological processes
Margaria, Tiziana; Hinchey, Michael G.; Raffelt, Harald; Rash, James L.; Rouff, Christopher A.; Steffen, Bernhard
2006-01-01
We present a learning-based method for model completion and adaptation, which is based on the combination of two approaches: 1) R2D2C, a technique for mechanically transforming system requirements via provably equivalent models to running code, and 2) automata learning-based model extrapolation. The intended impact of this new combination is to make model completion and adaptation accessible to experts of the field, like biologists or engineers. The principle is briefly illustrated by gene...
A dual adaptive watermarking scheme in contourlet domain for DICOM images
Rabbani Hossein
2011-06-01
Full Text Available Abstract Background Nowadays, medical imaging equipments produce digital form of medical images. In a modern health care environment, new systems such as PACS (picture archiving and communication systems, use the digital form of medical image too. The digital form of medical images has lots of advantages over its analog form such as ease in storage and transmission. Medical images in digital form must be stored in a secured environment to preserve patient privacy. It is also important to detect modifications on the image. These objectives are obtained by watermarking in medical image. Methods In this paper, we present a dual and oblivious (blind watermarking scheme in the contourlet domain. Because of importance of ROI (region of interest in interpretation by medical doctors rather than RONI (region of non-interest, we propose an adaptive dual watermarking scheme with different embedding strength in ROI and RONI. We embed watermark bits in singular value vectors of the embedded blocks within lowpass subband in contourlet domain. Results The values of PSNR (peak signal-to-noise ratio and SSIM (structural similarity measure index of ROI for proposed DICOM (digital imaging and communications in medicine images in this paper are respectively larger than 64 and 0.997. These values confirm that our algorithm has good transparency. Because of different embedding strength, BER (bit error rate values of signature watermark are less than BER values of caption watermark. Our results show that watermarked images in contourlet domain have greater robustness against attacks than wavelet domain. In addition, the qualitative analysis of our method shows it has good invisibility. Conclusions The proposed contourlet-based watermarking algorithm in this paper uses an automatically selection for ROI and embeds the watermark in the singular values of contourlet subbands that makes the algorithm more efficient, and robust against noise attacks than other transform
An Empirical Cumulus Parameterization Scheme for a Global Spectral Model
Rajendran, K.; Krishnamurti, T. N.; Misra, V.; Tao, W.-K.
2004-01-01
Realistic vertical heating and drying profiles in a cumulus scheme is important for obtaining accurate weather forecasts. A new empirical cumulus parameterization scheme based on a procedure to improve the vertical distribution of heating and moistening over the tropics is developed. The empirical cumulus parameterization scheme (ECPS) utilizes profiles of Tropical Rainfall Measuring Mission (TRMM) based heating and moistening derived from the European Centre for Medium- Range Weather Forecasts (ECMWF) analysis. A dimension reduction technique through rotated principal component analysis (RPCA) is performed on the vertical profiles of heating (Q1) and drying (Q2) over the convective regions of the tropics, to obtain the dominant modes of variability. Analysis suggests that most of the variance associated with the observed profiles can be explained by retaining the first three modes. The ECPS then applies a statistical approach in which Q1 and Q2 are expressed as a linear combination of the first three dominant principal components which distinctly explain variance in the troposphere as a function of the prevalent large-scale dynamics. The principal component (PC) score which quantifies the contribution of each PC to the corresponding loading profile is estimated through a multiple screening regression method which yields the PC score as a function of the large-scale variables. The profiles of Q1 and Q2 thus obtained are found to match well with the observed profiles. The impact of the ECPS is investigated in a series of short range (1-3 day) prediction experiments using the Florida State University global spectral model (FSUGSM, T126L14). Comparisons between short range ECPS forecasts and those with the modified Kuo scheme show a very marked improvement in the skill in ECPS forecasts. This improvement in the forecast skill with ECPS emphasizes the importance of incorporating realistic vertical distributions of heating and drying in the model cumulus scheme. This
OMEGA: The operational multiscale environment model with grid adaptivity
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.
Asymptotic-Preserving Schemes for Fluid Models of Plasmas
Degond, Pierre
2011-01-01
These notes summarize a series of works related to the numerical approximation of plasma fluid problems. We construct so-called 'Asymptotic-Preserving' schemes which are valid for a large range of values (from very small to order unity) of the dimensionless parameters that appear in plasma fluid models. Specifically, we are interested in two parameters, the scaled Debye length which quantifies how close to quasi-neutrality the plasma is, and the scaled cyclotron period, which is inversely pro...
Secure communication scheme based on asymptotic model of deterministic randomness
In this Letter, we introduce a new cryptosystem by integrating the asymptotic model of deterministic randomness with the one-way coupled map lattice (OCML) system. The key space, the encryption efficiency, and the security under various attacks are investigated. With the properties of deterministic randomness and spatiotemporal dynamics, the new scheme can improve the security to the order of computational precision, even when the lattice size is three only. Meanwhile, all the lattices can be fully utilized to increase the encryption speed
An Industrial Model Based Disturbance Feedback Control Scheme
Kawai, Fukiko; Nakazawa, Chikashi; Vinther, Kasper;
2014-01-01
This paper presents a model based disturbance feedback control scheme. Industrial process systems have been traditionally controlled by using relay and PID controller. However these controllers are affected by disturbances and model errors and these effects degrade control performance. The authors...... propose a new control method that can decrease the negative impact of disturbance and model errors. The control method is motivated by industrial practice by Fuji Electric. Simulation tests are examined with a conventional PID controller and the disturbance feedback control. The simulation results...
Stateless Transitive Signature Schemes
MA Chun-guang; CAI Man-chun; YANG Yi-xian
2004-01-01
A new practical method is introduced to transform the stateful transitive signature scheme to stateless one without the loss of security. According to the approach, two concrete stateless transitive signature schemes based on Factoring and RSA are presented respectively. Under the assumption of the hardness of factoring and one-more- RSA-inversion problem, both two schemes are secure under the adaptive chosen-message attacks in random oracle model.
Ho-Nien Shou
2012-02-01
Full Text Available This paper presents a genetic-based control scheme that not only utilizes evolutionary characteristics to find the signal acquisition parameters, but also employs an adaptive scheme to control the search space and avoid the genetic control converging to local optimal value so as to acquire the desired signal precisely and rapidly. Simulations and experiment results show that the proposed method can improve the precision of signal parameters and take less signal acquisition time than traditional serial search methods for global navigation satellite system (GNSS signals.
Unobtrusive user modeling for adaptive hypermedia
H.J. Holz; K. Hofmann; C. Reed
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
Adaptive MIMO-OFDM Scheme with Reduced Computational Complexity and Improved Capacity
L. C. Siddanna Gowd
2011-03-01
Full Text Available The general multidimensional linear channel model adequately represents a plethora of communication system models which utilize multidimensional transmit-receive signals for attaining increased rates and reliability in the presence of fading. The logarithmic dependence of the spectral efficiency of the transmitted power makes it extremely expensive to increase the capacity solely by radiating more power. Also, increasing the transmitted power in a mobile terminal is not advisable due to possible violation of regulatory power masks and possible electromagnetic radiation effects. Alternately, MIMO schemes if properly exploited can exhibit a linearly increasing capacity, due to the presence of a rich scattering environment that provides independent transmission paths from each transmit to each receive antenna. An Idealized practical communication system assumes perfect channel state information (CSI and uses a linear transmitter to maximize the reliability of the wireless multi-antenna link. However, in actual practice the CSI is incomplete. As a result of this, there is a necessity to deal with ergodic and compound capacity formulations and these factors are strongly dependent on the model utilized to characterize the channel. Practical system models include quasi-static multiple-input multipleoutput (MIMO, MIMO-OFDM, ISI, amplify-andforward (AF, decode-and-forward (DF, and MIMO automatic repeat request (ARQ models. Each of the above models introduces its own structure, its own error performance limits, and its own requirements on coding and decoding schemes. Finding general purpose transceiver structures with (provably good performance in these scenarios, and with a reasonable computational complexity, is challenging. Existing MIMO systems are able to provide either high spectral efficiency (spatial multiplexing or low error rate (high diversity via exploiting multiple degrees of freedom available in the channel, but not both simultaneously as
Ryerson, F. J.; Ezzedine, S. M.; Antoun, T.
2013-12-01
equation for the distribution of k is solved, provided that Cauchy data are appropriately assigned. In the next stage, only a limited number of passive measurements are provided. In this case, the forward and inverse PDEs are solved simultaneously. This is accomplished by adding regularization terms and filtering the pressure gradients in the inverse problem. Both the forward and the inverse problem are either simultaneously or sequentially coupled and solved using implicit schemes, adaptive mesh refinement, Galerkin finite elements. The final case arises when P, k, and Q data only exist at producing wells. This exceedingly ill posed problem calls for additional constraints on the forward-inverse coupling to insure that the production rates are satisfied at the desired locations. Results from all three cases are presented demonstrating stability and accuracy of the proposed approach and, more importantly, providing some insights into the consequences of data under sampling, uncertainty propagation and quantification. We illustrate the advantages of this novel approach over the common UQ forward drivers on several subsurface energy problems in either porous or fractured or/and faulted reservoirs. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Adaptive finite difference for seismic wavefield modelling in acoustic media.
Yao, Gang; Wu, Di; Debens, Henry Alexander
2016-01-01
Efficient numerical seismic wavefield modelling is a key component of modern seismic imaging techniques, such as reverse-time migration and full-waveform inversion. Finite difference methods are perhaps the most widely used numerical approach for forward modelling, and here we introduce a novel scheme for implementing finite difference by introducing a time-to-space wavelet mapping. Finite difference coefficients are then computed by minimising the difference between the spatial derivatives of the mapped wavelet and the finite difference operator over all propagation angles. Since the coefficients vary adaptively with different velocities and source wavelet bandwidths, the method is capable to maximise the accuracy of the finite difference operator. Numerical examples demonstrate that this method is superior to standard finite difference methods, while comparable to Zhang's optimised finite difference scheme. PMID:27491333
Multiple models adaptive feedforward decoupling controller
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.
Multi-dimensional Upwind Fluctuation Splitting Scheme with Mesh Adaption for Hypersonic Viscous Flow
Wood, William Alfred
2001-01-01
A multi-dimensional upwind fluctuation splitting scheme is developed and implemented for two-dimensional and axisymmetric formulations of the Navier-Stokes equations on unstructured meshes. Key features of the scheme are the compact stencil, full upwinding, and non-linear discretization which allow for second-order accuracy with enforced positivity. Throughout, the fluctuation splitting scheme is compared to a current state-of-the-art finite volume approach, a second-orde...
Kabi Prasad Pokhrel
2013-01-01
This paper is an attempt to evaluate the socio-economic as well as environmental impacts of small irrigation schemes in different parts of Nepal so as to help in formulating future policies on small irrigation schemes and subsidy programs. The paper has clearly pointed out the operation and management structure in each of the selected schemes have been playing significant role to increase the farm resource productivity, reduce poverty level, improve farmer participation and to manage availabl...
Liu Yu; Dong Kai; Wang Haipeng; Liu Jun; He You; Pan Lina
2014-01-01
The paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic systems for improvement of accuracy and consistency. An efficient new algorithm called the adaptive Gaussian-sum square-root cubature Kalman filter (AGSSCKF) with a split-merge scheme is proposed. It is developed based on the squared-root extension of newly introduced cubature Kalman filter (SCKF) and is built within a Gaussian-sum framework. Based on the condition that the probability density functions o...
A New Mobile Learning Adaptation Model
Mohamd Hassan Hassan; Jehad Al-Sadi
2009-01-01
This paper introduces a new model for m- Learning context adaptation due to the need of utilizing mobile technology in education. Mobile learning; m-Learning for short; in considered to be one of the hottest topics in the educational community, many researches had been done to conceptualize this new form of learning. We are presenting a promising design for a model to adapt the learning content in mobile learning applications in order to match the learner context, preferences and the educatio...
Modelling of transient dynamic bundle deformation using time integration scheme
The BOW code has been examined whether its modeling capability can be extended to the simulation of interactions (i.e., fretting) between neighbouring fuel elements in a fuel bundle and between the fuel bundle and the pressure tube in a fuel channel. The current BOW code is specialized in simulating the static problems, such as the deflection of each element and interactions between neighbouring elements in a fuel bundle, and interactions between neighbouring bundles and between a bundle and the pressure tube in a fuel channel. The Wilson θ time integration scheme has been implemented in the BOW code, for the extension of its capability to modelling dynamic contact problems. As part of verification to ensure that the modification in the code functions exactly as designed, the dynamic-modelling capability of the BOW code has been applied to simple support beam cases subjected to a uniform step load at the middle of the beam. The calculation results confirmed that the modified BOW code, where the contact algorithm is implemented in the step-by-step integration manner using the Wilson θ time integration scheme, can solve the dynamic problem with unconditional convergence. This paper describes the theory and models for the new capabilities of the BOW code. (author)
Image segmentation based on adaptive mixture model
As an important research field, image segmentation has attracted considerable attention. The classical geodesic active contour (GAC) model tends to produce fake edges in smooth regions, while the Chan–Vese (CV) model cannot effectively detect images with holes and obtain the precise boundary. To address the above issues, this paper proposes an adaptive mixture model synthesizing the GAC model and the CV model by a weight function. According to image characteristics, the proposed model can adaptively adjust the weight function. In this way, the model exploits the advantages of the GAC model in regions with rich textures or edges, while exploiting the advantages of the CV model in smooth local regions. Moreover, the proposed model is extended to vector-valued images. Through experiments, it is verified that the proposed model obtains better results than the traditional models. (paper)
A UPFC damping control scheme using Lead-Lag and ANN based Adaptive controllers
D. Ramesh
2012-09-01
Full Text Available Low Frequency Oscillations (LFO occur inpower systems because of lack of the damping torque inorder to dominance to power system disturbances aschange in mechanical input power. In the recent pastPower System Stabilizer (PSS was used to damp LFO.FACTs devices, such as Unified Power Flow Controller(UPFC, can control power flow and increase transientstability. So UPFC may be used to damp LFO instead ofPSS. UPFC damps LFO through direct control of voltageand power. In this research the linearized model ofsynchronous machine (Heffron-Philips connected toinfinite bus (Single Machine-Infinite Bus: SMIB withUPFC is used and also in order to damp LFO, adaptiveANN damping controller for UPFC is designed andsimulated. Simulation is performed for various types ofloads and for different disturbances. Simulation resultsdemonstrate that the developed ANN damping controllerwould be more effective in damping electromechanicaloscillations in comparison with the conventional lead-lagcontroller.
Asymptotic-Preserving Schemes for Fluid Models of Plasmas
Degond, Pierre
2011-01-01
These notes summarize a series of works related to the numerical approximation of plasma fluid problems. We construct so-called 'Asymptotic-Preserving' schemes which are valid for a large range of values (from very small to order unity) of the dimensionless parameters that appear in plasma fluid models. Specifically, we are interested in two parameters, the scaled Debye length which quantifies how close to quasi-neutrality the plasma is, and the scaled cyclotron period, which is inversely proportional to the magnetic field strength. We will largely focus on the ideas, in order to enable the reader to apply these concepts to other situations.
An integration scheme for stiff solid-gas reactor models
Bjarne A. Foss
2001-04-01
Full Text Available Many dynamic models encounter numerical integration problems because of a large span in the dynamic modes. In this paper we develop a numerical integration scheme for systems that include a gas phase, and solid and liquid phases, such as a gas-solid reactor. The method is based on neglecting fast dynamic modes and exploiting the structure of the algebraic equations. The integration method is suitable for a large class of industrially relevant systems. The methodology has proven remarkably efficient. It has in practice performed excellent and been a key factor for the success of the industrial simulator for electrochemical furnaces for ferro-alloy production.
Bajc, Iztok; Hecht, Frédéric; Žumer, Slobodan
2016-09-01
This paper presents a 3D mesh adaptivity strategy on unstructured tetrahedral meshes by a posteriori error estimates based on metrics derived from the Hessian of a solution. The study is made on the case of a nonlinear finite element minimization scheme for the Landau-de Gennes free energy functional of nematic liquid crystals. Newton's iteration for tensor fields is employed with steepest descent method possibly stepping in. Aspects relating the driving of mesh adaptivity within the nonlinear scheme are considered. The algorithmic performance is found to depend on at least two factors: when to trigger each single mesh adaptation, and the precision of the correlated remeshing. Each factor is represented by a parameter, with its values possibly varying for every new mesh adaptation. We empirically show that the time of the overall algorithm convergence can vary considerably when different sequences of parameters are used, thus posing a question about optimality. The extensive testings and debugging done within this work on the simulation of systems of nematic colloids substantially contributed to the upgrade of an open source finite element-oriented programming language to its 3D meshing possibilities, as also to an outer 3D remeshing module.
Moura, R. C.; Silva, A. F. C.; Bigarella, E. D. V.; Fazenda, A. L.; Ortega, M. A.
2016-08-01
This paper proposes two important improvements to shock-capturing strategies using a discontinuous Galerkin scheme, namely, accurate shock identification via finite-time Lyapunov exponent (FTLE) operators and efficient shock treatment through a point-implicit discretization of a PDE-based artificial viscosity technique. The advocated approach is based on the FTLE operator, originally developed in the context of dynamical systems theory to identify certain types of coherent structures in a flow. We propose the application of FTLEs in the detection of shock waves and demonstrate the operator's ability to identify strong and weak shocks equally well. The detection algorithm is coupled with a mesh refinement procedure and applied to transonic and supersonic flows. While the proposed strategy can be used potentially with any numerical method, a high-order discontinuous Galerkin solver is used in this study. In this context, two artificial viscosity approaches are employed to regularize the solution near shocks: an element-wise constant viscosity technique and a PDE-based smooth viscosity model. As the latter approach is more sophisticated and preferable for complex problems, a point-implicit discretization in time is proposed to reduce the extra stiffness introduced by the PDE-based technique, making it more competitive in terms of computational cost.
Adaptations in a Community-Based Family Intervention: Replication of Two Coding Schemes.
Cooper, Brittany Rhoades; Shrestha, Gitanjali; Hyman, Leah; Hill, Laura
2016-02-01
Although program adaptation is a reality in community-based implementations of evidence-based programs, much of the discussion about adaptation remains theoretical. The primary aim of this study was to replicate two coding systems to examine adaptations in large-scale, community-based disseminations of the Strengthening Families Program for Parents and Youth 10-14, a family-based substance use prevention program. Our second aim was to explore intersections between various dimensions of facilitator-reported adaptations from these two coding systems. Our results indicate that only a few types of adaptations and a few reasons accounted for a majority (over 70 %) of all reported adaptations. We also found that most adaptations were logistical, reactive, and not aligned with program's goals. In many ways, our findings replicate those of the original studies, suggesting the two coding systems are robust even when applied to self-reported data collected from community-based implementations. Our findings on the associations between adaptation dimensions can inform future studies assessing the relationship between adaptations and program outcomes. Studies of local adaptations, like the present one, should help researchers, program developers, and policymakers better understand the issues faced by implementers and guide efforts related to program development, transferability, and sustainability. PMID:26661413
Kabi Prasad Pokhrel
2013-04-01
Full Text Available This paper is an attempt to evaluate the socio-economic as well as environmental impacts of small irrigation schemes in different parts of Nepal so as to help in formulating future policies on small irrigation schemes and subsidy programs. The paper has clearly pointed out the operation and management structure in each of the selected schemes have been playing significant role to increase the farm resource productivity, reduce poverty level, improve farmer participation and to manage available environmental resources in sustainable way. Furthermore, the functions and effectiveness of the Irrigation Management Committees (IMCs and Water Users Groups (WUGs, farmers groups (FG and cooperatives have been actively participated in the overall activities of small scale irrigation schemes to implement effectively.
An adaptive model-free fuzzy controller
In this paper, we present an adaptive, stable fuzzy controller whose parameters are optimized via a genetic algorithm. The controller model is capable of building itself on the basis of measured plant data and then of adapting to new dynamics. The stability of the overall system, made up of the plant and the controller, is guaranteed by Lyapunov's theory. As a case study, the stable adaptive fuzzy controller is employed to drive the narrow water level of a simulated Steam Generator (SG) to a desired reference trajectory. The numerical results confirm that the controller bears good performances in terms of small oscillations and fast settling time even in presence of external disturbances. (authors)
Contaminated groundwater transport using an adaptive 3-D finite element model
A three-dimensional, h-adapting finite element model has been developed to calculate subsurface transport and dispersion of contaminant. The model is based on a hybrid finite element scheme previously developed for two-dimensional groundwater and species transport
Particle systems for adaptive, isotropic meshing of CAD models.
Bronson, Jonathan R; Levine, Joshua A; Whitaker, Ross T
2012-10-01
We present a particle-based approach for generating adaptive triangular surface and tetrahedral volume meshes from computer-aided design models. Input shapes are treated as a collection of smooth, parametric surface patches that can meet non-smoothly on boundaries. Our approach uses a hierarchical sampling scheme that places particles on features in order of increasing dimensionality. These particles reach a good distribution by minimizing an energy computed in 3D world space, with movements occurring in the parametric space of each surface patch. Rather than using a pre-computed measure of feature size, our system automatically adapts to both curvature as well as a notion of topological separation. It also enforces a measure of smoothness on these constraints to construct a sizing field that acts as a proxy to piecewise-smooth feature size. We evaluate our technique with comparisons against other popular triangular meshing techniques for this domain. PMID:23162181
Numerical schemes for one-point closure turbulence models
First-order Reynolds Averaged Navier-Stokes (RANS) turbulence models are studied in this thesis. These latter consist of the Navier-Stokes equations, supplemented with a system of balance equations describing the evolution of characteristic scalar quantities called 'turbulent scales'. In so doing, the contribution of the turbulent agitation to the momentum can be determined by adding a diffusive coefficient (called 'turbulent viscosity') in the Navier-Stokes equations, such that it is defined as a function of the turbulent scales. The numerical analysis problems, which are studied in this dissertation, are treated in the frame of a fractional step algorithm, consisting of an approximation on regular meshes of the Navier-Stokes equations by the nonconforming Crouzeix-Raviart finite elements, and a set of scalar convection-diffusion balance equations discretized by the standard finite volume method. A monotone numerical scheme based on the standard finite volume method is proposed so as to ensure that the turbulent scales, like the turbulent kinetic energy (k) and its dissipation rate (ε), remain positive in the case of the standard k - ε model, as well as the k - ε RNG and the extended k - ε - ν2 models. The convergence of the proposed numerical scheme is then studied on a system composed of the incompressible Stokes equations and a steady convection-diffusion equation, which are both coupled by the viscosities and the turbulent production term. This reduced model allows to deal with the main difficulty encountered in the analysis of such problems: the definition of the turbulent production term leads to consider a class of convection-diffusion problems with an irregular right-hand side belonging to L1. Finally, to step towards the unsteady problem, the convergence of the finite volume scheme for a model convection-diffusion equation with L1 data is proved. The a priori estimates on the solution and on its time derivative are obtained in discrete norms, for
Adaptive Q-V Scheme for the Voltage Control of a DFIG-Based Wind Power Plant
Kim, Jinho; Seok, Jul-Ki; Muljadi, Eduard; Kang, Yong Cheol
2016-05-01
Wind generators within a wind power plant (WPP) will produce different amounts of active power because of the wake effect, and therefore, they have different reactive power capabilities. This paper proposes an adaptive reactive power to the voltage (Q-V) scheme for the voltage control of a doubly fed induction generator (DFIG)-based WPP. In the proposed scheme, the WPP controller uses a voltage control mode and sends a voltage error signal to each DFIG. The DFIG controller also employs a voltage control mode utilizing the adaptive Q-V characteristics depending on the reactive power capability such that a DFIG with a larger reactive power capability will inject more reactive power to ensure fast voltage recovery. Test results indicate that the proposed scheme can recover the voltage within a short time, even for a grid fault with a small short-circuit ratio, by making use of the available reactive power of a WPP and differentiating the reactive power injection in proportion to the reactive power capability. This will, therefore, help to reduce the additional reactive power and ensure fast voltage recovery.
Modeling and Analysis of Source Management Routing Scheme for BGP
Shu Wang
2010-05-01
Full Text Available Source management routing scheme called SMR is a new approach that provides a backup routing path for BGP on AS-level. In SMR, each AS in the virtual ring just is defined by a node which owns a unique identifier. It is a novel way to integrate some physical topology into virtual topology to shorten the routes greatly. And then, we present a theoretical model of virtual ring SMR to describe the routing mechanism and the impacts on the routing performance. We evaluate the performance of SMR by simulations on a real BGP topology. In the case of each AS only maintaining a route to one virtual neighbor, virtual ring SMR still provides a path to destination with low overhead. Furthermore, our theoretical model fit the process of SMR well, and provides the insight for us to improve the virtual ring SMR.
An adaptive stochastic model for financial markets
An adaptive stochastic model is introduced to simulate the behavior of real asset markets. The model adapts itself by changing its parameters automatically on the basis of the recent historical data. The basic idea underlying the model is that a random variable uniformly distributed within an interval with variable extremes can replicate the histograms of asset returns. These extremes are calculated according to the arrival of new market information. This adaptive model is applied to the daily returns of three well-known indices: Ibex35, Dow Jones and Nikkei, for three complete years. The model reproduces the histograms of the studied indices as well as their autocorrelation structures. It produces the same fat tails and the same power laws, with exactly the same exponents, as in the real indices. In addition, the model shows a great adaptation capability, anticipating the volatility evolution and showing the same volatility clusters observed in the assets. This approach provides a novel way to model asset markets with internal dynamics which changes quickly with time, making it impossible to define a fixed model to fit the empirical observations.
Qaraqe, Marwa
2014-04-01
This paper focuses on the development of multiuser access schemes for spectrum sharing systems whereby secondary users are allowed to share the spectrum with primary users under the condition that the interference observed at the primary receiver is below a predetermined threshold. In particular, two scheduling schemes are proposed for selecting a user among those that satisfy the interference constraint and achieve an acceptable signal-to-noise ratio level. The first scheme focuses on optimizing the average spectral efficiency by selecting the user that reports the best channel quality. In order to alleviate the relatively high feedback required by the first scheme, a second scheme based on the concept of switched diversity is proposed, where the base station (BS) scans the secondary users in a sequential manner until a user whose channel quality is above an acceptable predetermined threshold is found. We develop expressions for the statistics of the signal-to-interference and noise ratio as well as the average spectral efficiency, average feedback load, and the delay at the secondary BS. We then present numerical results for the effect of the number of users and the interference constraint on the optimal switching threshold and the system performance and show that our analysis results are in perfect agreement with the numerical results. © 2014 John Wiley & Sons, Ltd.
Adaptive Partially Hidden Markov Models
Forchhammer, Søren Otto; Rasmussen, Tage
1996-01-01
Partially Hidden Markov Models (PHMM) have recently been introduced. The transition and emission probabilities are conditioned on the past. In this report, the PHMM is extended with a multiple token version. The different versions of the PHMM are applied to bi-level image coding.......Partially Hidden Markov Models (PHMM) have recently been introduced. The transition and emission probabilities are conditioned on the past. In this report, the PHMM is extended with a multiple token version. The different versions of the PHMM are applied to bi-level image coding....
A shock-adaptive Godunov scheme based on the generalised Lagrangian formulation
Lepage, C.Y. [Univ. of Waterloo, Ontario (Canada); Hui, W.H. [Hong Kong Univ. of Science & Technology, Clear Water Bay, Kowloon (Hong Kong)
1995-12-01
Application of the Godunov scheme to the Euler equations of gas dynamics based on the Eulerian formulation of flow smears discontinuities, sliplines especially, over several computational cells, while the accuracy in the smooth flow region is of the order 0 (h),where h is the cell width. Based on the generalised Lagrangian formulation (GLF) of Hui et al., the Godunov scheme yields superior accuracy. By the use of coordinate streamlines in the GLF, the slip-line - itself a streamline - is resolved crisply. Infinite shock resolution is achieved through the splitting of shock-cells. An improved entropy-conservation formulation of the governing equations is also proposed for computations in smooth flow regions. Finally, the use of the GLF substantially simplifies the programming logic resulting in a very robust, accurate, and efficient scheme. 15 refs., 6 figs.
G.G Rajput
2015-04-01
Full Text Available Adaptive update lifting scheme based Interactive artificial bee colony algorithm is proposed in this paper. Wavelet transform based compression technique is used for images and multimedia files. Approximation and detail coefficients are extracted from the signal by filtering in wavelet transform. To increase frequency resolution both approximation and detail coefficients are re-decomposed up to some level. Artificial bee colony algorithm by local search finds different update coefficients to get quality of compressed image by choosing optimally best update coefficient. In IABC, the affection between employed bees and the onlooker bees is found by considering the concept of universal gravitation. By passing on control parameter different values, the universal gravitation involved in the IABC has a single onlooker bee & variety of quantities of employed bees. As a result, IABC compared with existing image compression schemes such as wavelet transform and Artificial Bee colony Algorithm, the proposed work gives better PSNR.
Li, Ning; Cao, Jinde
2015-01-01
In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results. PMID:25299765
The authors investigated a new method to optimize artificial neural networks (ANNs) with adaptive filtering used in computer-assisted detection schemes in digitized mammograms and to assess performance changes when averaging classification scores from three sets of optimized schemes. Two independent training and testing image databases involving 978 and 830 digitized mammograms, respectively, were used in this study. In the training data set, initial filtering and subtraction resulted in the identification of 592 mass regions and 3790 suspicious, but actually negative regions. These regions (including both true-positive and negative regions) were segmented into three subsets three times based on the calculation of the values of three features as segmentation indices. The indices were 'mass' size multiplied by their digital value contrast, conspicuity, and circularity. Nine ANN-based classifiers were separately optimized using a genetic algorithm for each subset of regions. Each region was assigned three classification scores after applying the three adaptive ANNs. The performance gain of the CAD scheme after averaging the three scores for each suspicious region was tested using an independent data set and a ROC methodology. The experimental results showed that the areas under ROC curves (Az) for the testing database using three sets of optimized ANNs individually were 0.84±0.01, 0.83±0.01, and 0.84±0.01, respectively. The between-index correlations of three Az values were 0.013, -0.007, and 0.086. Similar to averaging diagnostic ratings from independent observers, by averaging three ANN-generated scores for each testing region, the performance of the CAD scheme was significantly improved (pz value of 0.95±0.01
Intelligent CAD Methodology Research of Adaptive Modeling
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.
Provisioning of adaptability to variable topologies for routing schemes in MANETs
Jiang, Shengming; Liu, Yaoda; Jiang, Yuming;
2004-01-01
.g., low, medium, and high mobility) have been proposed in the,literature. However, since a mobile node should not be limited to operate in a particular MANET assumed by-a routing scheme, an important issue is how to enable, a mobile node to achieve routing performance as high as possible when it roams...
A Conservative Scheme for Vlasov Poisson Landau modeling collisional plasmas
Zhang, Chenglong
2016-01-01
We have developed a deterministic conservative solver for the inhomogeneous Fokker-Planck-Landau equation coupled with Poisson equation, which is a rather realistic and primary model for collisional plasmas. Two subproblems, i.e Vlasov-Poisson problem and homogeneous Landau problem, are obtained through time-splitting methods, and treated separately by Runge-Kutta Dis- continuous Galerkin method and conservative spectral method, respectively. To ensure conservation when projecting between the two different computing grids, a special conservation routine is designed to link the two solutions to these two subproblems. The entire numerical scheme is implemented with parallelization with hybrid MPI and OpenMP. Numerical experiments are provided to study linear and nonlinear Landau Damping problems and two- stream flow problem as well.
Reference model decomposition in direct adaptive control
Butler, H.; Honderd, G.; Amerongen, van, W.E.
1991-01-01
This paper introduces the method of reference model decomposition as a way to improve the robustness of model reference adaptive control systems (MRACs) with respect to unmodelled dynamics with a known structure. Such unmodelled dynamics occur when some of the nominal plant dynamics are purposely neglected in the controller design with the aim of keeping the controller order low. One of the effects of such undermodelling of the controller is a violation of the perfect model-matching condition...
Modeling Marine Stratocumulus with a Detailed Microphysical Scheme
ZHAO Chunsheng(赵春生); Yutaka ISHIZAKA
2004-01-01
A one-dimensional 3rd-order turbulence closure model with size-resolved microphysics and radiative transfer has been developed for investigating aerosol and cloud interactions of the stratocumulus-topped marine boundary layer.A new method is presented for coupling between the dynamical model and the microphysical model.This scheme allows the liquid water related correlations to be directly calculated rather than parameterized.On 21 April 2001,a marine stratocumulus was observed by the Caesar aircraft over the west Pacific Rim south of Japan during the 2001 APEX/ACE-Asia field measurements.This cloud is simulated by the model we present here.The model results show that the general features of the stratocumulus-topped marine boundary layer predicted by the model are in agreement with the measurements.A new onboard cloud condensation nuclei (CCN) counter provides not only total CC Nnumber concentration (as the traditional CCN counters do at a certain supersaturation) but also the CCN size distribution information.Using these CCN data,model responses to different CCN initial concentrations are examined.The model results are consistent with both observations and expectations.The numerical results show that the cloud microphysical properties are changed fundamentally by differentinitial CCN concentrations but the cloud liquid water content does not differ significantly.Different initial CCN loadings have large impacts on the evolution of cloud microstructure and radiation transfer while they have a modest effect on thermodynamics.Increased CCN concentration leads to significant decrease of cloud effective radius.
Adaptive System Modeling for Spacecraft Simulation
Thomas, Justin
2011-01-01
This invention introduces a methodology and associated software tools for automatically learning spacecraft system models without any assumptions regarding system behavior. Data stream mining techniques were used to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). Evaluation on historical ISS telemetry data shows that adaptive system modeling reduces simulation error anywhere from 50 to 90 percent over existing approaches. The purpose of the methodology is to outline how someone can create accurate system models from sensor (telemetry) data. The purpose of the software is to support the methodology. The software provides analysis tools to design the adaptive models. The software also provides the algorithms to initially build system models and continuously update them from the latest streaming sensor data. The main strengths are as follows: Creates accurate spacecraft system models without in-depth system knowledge or any assumptions about system behavior. Automatically updates/calibrates system models using the latest streaming sensor data. Creates device specific models that capture the exact behavior of devices of the same type. Adapts to evolving systems. Can reduce computational complexity (faster simulations).
Uncertainty of establishment scheme in the Community Land Model-Dynamic Global Vegetation Model
Song, X.; Zeng, X.
2010-12-01
Dynamic global vegetation models are very important tools to simulate and predict the relationship between terrestrial ecosystem processes and climate change. They usually consist of several main sub-models, such as establishment, growth, mortality due to stress, competition, reproductive and so forth. In this study, we focus on the establishment sub-model. Establishment sub-model describes the processes of germination of tree seeds and establishment of seedlings. However, due to the complexity of the ecological process and the lack of observation data, current DGVMs use different parameterization schemes of establishment, and the uncertainties of these establishment scheme as well as their impacts on vegetation distribution remain largely unknown. Our work is to introduce several new different establishment schemes, each based on different physical and ecological considerations, into a modified Community Land Model - Dynamic Global Vegetation Model (CLM-DGVM). The sensitivities of the vegetation distribution to different establishment schemes and some essential parameters in the schemes are investigated in different vegetation zones. Our research indicates that establishment scheme has remarkable effects not only on the percent of coverage and population density of different plant functional types (PFTs) but also the community structure such as coexistence of PFTs and even the dominant vegetation. Such changes will alter the ecosystem functioning, and hence have further impacts on climate through the vegetation-atmosphere feedback.
Modelling and (adaptive) control of greenhouse climates
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
Traffic Prediction Scheme based on Chaotic Models in Wireless Networks
Xiangrong Feng
2013-09-01
Full Text Available Based on the local support vector algorithm of chaotic time series analysis, the Hannan-Quinn information criterion and SAX symbolization are introduced. Then a novel prediction algorithm is proposed, which is successfully applied to the prediction of wireless network traffic. For the correct prediction problems of short-term flow with smaller data set size, the weakness of the algorithms during model construction is analyzed by study and comparison to LDK prediction algorithm. It is verified the Hannan-Quinn information principle can be used to calculate the number of neighbor points to replace pervious empirical method, which uses the number of neighbor points to acquire more accurate prediction model. Finally, actual flow data is applied to confirm the accuracy rate of the proposed algorithm LSDHQ. It is testified by our experiments that it also has higher performance in adaptability than that of LSDHQ algorithm.
Regenerative and Adaptive schemes Based on Network Coding for Wireless Relay Network
Ahmed Hassan M. Hassan
2012-06-01
Full Text Available Recent technological advances in wireless communications offer new opportunities and challenges for relay network. To enhance system performance, Demodulate-Network Coding (Dm-NC scheme has been examined at relay node; it works directly to De-map the received signals and after that forward the mixture to the destination. Simulation analysis has been proven that the performance of Dm-NC has superiority over analog-NC. In addition, the Quantize-Decode-NC scheme (QDF-NC has been introduced. The presented simulation results clearly provide that the QDF-NC perform better than analog-NC. The toggle between analogNC and QDF-NC is simulated in order to investigate delay and power consumption reduction at relay node.
Semantic models for adaptive interactive systems
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
Arturo Torres-González; Jose Ramiro Martinez-de Dios; Anibal Ollero
2014-01-01
This work is motivated by robot-sensor network cooperation techniques where sensor nodes (beacons) are used as landmarks for range-only (RO) simultaneous localization and mapping (SLAM). This paper presents a RO-SLAM scheme that actuates over the measurement gathering process using mechanisms that dynamically modify the rate and variety of measurements that are integrated in the SLAM filter. It includes a measurement gathering module that can be configured to collect direct robot-beacon and i...
Adaptive Backbone and Link Correlation based Data Transmission Schemes for Wireless Sensor Networks
Weerasinghe, Thilina Nuwan
2015-01-01
One of the main challenges faced by modern wireless sensor networks (WSN) is rapid energy depletion of individual sensor nodes. In many applications, sensor nodes are deployed in outdoor environments and it is difficult to replace or recharge node batteries. Depending on network topology and the transmission schemes implemented, certain nodes could have higher energy consumption compared with other nodes. In highly unbalanced load distributions this could lead to early total energ...
Zeng, Yuanyuan; Sreenan, Cormac J; Sitanayah, Lanny; Xiong, Naixue; Park, Jong Hyuk; Zheng, Guilin
2011-01-01
Fire hazard monitoring and evacuation for building environments is a novel application area for the deployment of wireless sensor networks. In this context, adaptive routing is essential in order to ensure safe and timely data delivery in building evacuation and fire fighting resource applications. Existing routing mechanisms for wireless sensor networks are not well suited for building fires, especially as they do not consider critical and dynamic network scenarios. In this paper, an emergency-adaptive, real-time and robust routing protocol is presented for emergency situations such as building fire hazard applications. The protocol adapts to handle dynamic emergency scenarios and works well with the routing hole problem. Theoretical analysis and simulation results indicate that our protocol provides a real-time routing mechanism that is well suited for dynamic emergency scenarios in building fires when compared with other related work. PMID:22163774
Guilin Zheng
2011-03-01
Full Text Available Fire hazard monitoring and evacuation for building environments is a novel application area for the deployment of wireless sensor networks. In this context, adaptive routing is essential in order to ensure safe and timely data delivery in building evacuation and fire fighting resource applications. Existing routing mechanisms for wireless sensor networks are not well suited for building fires, especially as they do not consider critical and dynamic network scenarios. In this paper, an emergency-adaptive, real-time and robust routing protocol is presented for emergency situations such as building fire hazard applications. The protocol adapts to handle dynamic emergency scenarios and works well with the routing hole problem. Theoretical analysis and simulation results indicate that our protocol provides a real-time routing mechanism that is well suited for dynamic emergency scenarios in building fires when compared with other related work.
Yuanyuan Zeng
2010-06-01
Full Text Available Fire hazard monitoring and evacuation for building environments is a novel application area for the deployment of wireless sensor networks. In this context, adaptive routing is essential in order to ensure safe and timely data delivery in building evacuation and fire fighting resource applications. Existing routing mechanisms for wireless sensor networks are not well suited for building fires, especially as they do not consider critical and dynamic network scenarios. In this paper, an emergency-adaptive, real-time and robust routing protocol is presented for emergency situations such as building fire hazard applications. The protocol adapts to handle dynamic emergency scenarios and works well with the routing hole problem. Theoretical analysis and simulation results indicate that our protocol provides a real-time routing mechanism that is well suited for dynamic emergency scenarios in building fires when compared with other related work.
Automated adaptive inference of phenomenological dynamical models
Daniels, Bryan C.; Nemenman, Ilya
2015-08-01
Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.
Adaptive Modeling for Security Infrastructure Fault Response
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.
Wang, Cheng; Dong, XinZhuang; Shu, Chi-Wang
2015-10-01
For numerical simulation of detonation, computational cost using uniform meshes is large due to the vast separation in both time and space scales. Adaptive mesh refinement (AMR) is advantageous for problems with vastly different scales. This paper aims to propose an AMR method with high order accuracy for numerical investigation of multi-dimensional detonation. A well-designed AMR method based on finite difference weighted essentially non-oscillatory (WENO) scheme, named as AMR&WENO is proposed. A new cell-based data structure is used to organize the adaptive meshes. The new data structure makes it possible for cells to communicate with each other quickly and easily. In order to develop an AMR method with high order accuracy, high order prolongations in both space and time are utilized in the data prolongation procedure. Based on the message passing interface (MPI) platform, we have developed a workload balancing parallel AMR&WENO code using the Hilbert space-filling curve algorithm. Our numerical experiments with detonation simulations indicate that the AMR&WENO is accurate and has a high resolution. Moreover, we evaluate and compare the performance of the uniform mesh WENO scheme and the parallel AMR&WENO method. The comparison results provide us further insight into the high performance of the parallel AMR&WENO method.
Adaptive Cruise Control and Driver Modeling
Bengtsson, Johan
2001-01-01
Many vehicle manufacturers have lately introduced advance driver support in some of their automobiles. One of those new features is Adaptive Cruise Control DACCE, which extends the conventional cruise control system to control of relative speed and distance to other vehicles. In order to design an ACC controller it is suitable to have a model of driver behavior. The approach in the thesis is to use system identification methodology to obtain dynamic models of driver behavior useful for ACC ap...
Robust Adaptive Output Feedback Control Scheme for Chaos Synchronization with Input Nonlinearity
Xiaomeng Li; Zhanshan Zhao; Jing Zhang; Meixia Zhu
2016-01-01
This paper proposes a robust adaptive output feedback control strategy which can automatically regulate control gain for chaos synchronization. Chaotic systems with input nonlinearities, delayed nonlinear coupling, and external disturbance can achieve synchronization by applying this strategy. Utilizing Lyapunov method and LMI technique, the conditions ensuring chaos synchronization are obtained. Finally, simulations are given to show the effectiveness of our control strategy.
A Distributed Taxation Based Rank Adaptation Scheme for 5G Small Cells
Catania, Davide; Cattoni, Andrea Fabio; Mahmood, Nurul Huda;
2015-01-01
The further densification of small cells impose high and undesirable levels of inter-cell interference. Multiple Input Multiple Output (MIMO) systems along with advanced receiver techniques provide us with extra degrees of freedom to combat such a problem. With such tools, rank adaptation algorit...
New Digital Signature Scheme Attaining Immunity to Adaptive Chosen Message Attack
ZHU Huafei
2001-01-01
A new signature provably secureagainst adaptive chosen message attack is developedin this report. It is state-free and the proof of secu-rity is based on "strong RSA (Rivest-shamir-adleman)assumption, collision free hash algorithm as well as in-tractability of" discrete logarithm problem.
Adaptive-network models of swarm dynamics
Huepe, Cristian [614 N Paulina Street, Chicago, IL 60622-6062 (United States); Zschaler, Gerd; Do, Anne-Ly; Gross, Thilo, E-mail: cristian@northwestern.edu [Max-Planck-Institut fuer Physik komplexer Systeme, Noethnitzer Strasse 38, 01187 Dresden (Germany)
2011-07-15
We propose a simple adaptive-network model describing recent swarming experiments. Exploiting an analogy with human decision making, we capture the dynamics of the model using a low-dimensional system of equations permitting analytical investigation. We find that the model reproduces several characteristic features of swarms, including spontaneous symmetry breaking, noise- and density-driven order-disorder transitions that can be of first or second order, and intermittency. Reproducing these experimental observations using a non-spatial model suggests that spatial geometry may have less of an impact on collective motion than previously thought.
Adaptive-network models of swarm dynamics
We propose a simple adaptive-network model describing recent swarming experiments. Exploiting an analogy with human decision making, we capture the dynamics of the model using a low-dimensional system of equations permitting analytical investigation. We find that the model reproduces several characteristic features of swarms, including spontaneous symmetry breaking, noise- and density-driven order-disorder transitions that can be of first or second order, and intermittency. Reproducing these experimental observations using a non-spatial model suggests that spatial geometry may have less of an impact on collective motion than previously thought.
Adaptive Behaviour Assessment System: Indigenous Australian Adaptation Model (ABAS: IAAM)
du Plessis, Santie
2015-01-01
The study objectives were to develop, trial and evaluate a cross-cultural adaptation of the Adaptive Behavior Assessment System-Second Edition Teacher Form (ABAS-II TF) ages 5-21 for use with Indigenous Australian students ages 5-14. This study introduced a multiphase mixed-method design with semi-structured and informal interviews, school…
A video coding scheme based on joint spatiotemporal and adaptive prediction.
Jiang, Wenfei; Latecki, Longin Jan; Liu, Wenyu; Liang, Hui; Gorman, Ken
2009-05-01
We propose a video coding scheme that departs from traditional Motion Estimation/DCT frameworks and instead uses Karhunen-Loeve Transform (KLT)/Joint Spatiotemporal Prediction framework. In particular, a novel approach that performs joint spatial and temporal prediction simultaneously is introduced. It bypasses the complex H.26x interframe techniques and it is less computationally intensive. Because of the advantage of the effective joint prediction and the image-dependent color space transformation (KLT), the proposed approach is demonstrated experimentally to consistently lead to improved video quality, and in many cases to better compression rates and improved computational speed. PMID:19342337
CIELAB-driven adaptive quantization scheme for DCT-based compression of CMYK images
De Neve, Peter; Denecker, Koen N.; Lemahieu, Ignace L.
1999-05-01
In todays digital prepress workflow images are most often sorted in the CMYK color representation. In the lossy compression of CMYK color imags, most techniques do not take the tonal correlation between the color channels into account or they are not able to perform a proper color decorrelation in four dimensions. In a first stage a compression method has been developed that takes this type of redundancy into account. The basic idea is to divide the image into blocks. The color information in those blocks is then transformed from the original CMYK color space into a decorrelated color space. In this new color space not all components are of the same magnitude so here the gain for compression purposes becomes clear. After the color transformation step any regular compression scheme meant to reduce the spatial redundancy can be applied. In this paper a more advanced approach for the utilization procedure in the compression algorithm is presented. The proposed scheme tries to control the quantization parameters differently for all blocks and color components. Therefore the influence on the CIELab (Delta) E measure is investigated when making a small shift in the four main directions of the decorrelated color space.
DOAS: device-oriented adaptive multimedia scheme for 3GPP LTE systems
Zou, Longhao; Trestian, Ramona; Muntean, Gabriel-Miro
2013-01-01
peer-reviewed The growing popularity of the high-end mobile computing devices ??? smartphones, tablets, notebooks and more ??? equipped with high-speed network access, enables the mobile user to watch multimedia content from any source on any screen, at any time, while on the move or stationary. In this context, the network operators must ensure smooth video streaming with the lowest service delay, jitter, and packet loss. This paper proposes a resource efficient Device-Oriented Adaptive M...
Incompressible Turbulent Flow Simulation Using the κ-ɛ Model and Upwind Schemes
V. G. Ferreira
2007-01-01
Full Text Available In the computation of turbulent flows via turbulence modeling, the treatment of the convective terms is a key issue. In the present work, we present a numerical technique for simulating two-dimensional incompressible turbulent flows. In particular, the performance of the high Reynolds κ-ɛ model and a new high-order upwind scheme (adaptative QUICKEST by Kaibara et al. (2005 is assessed for 2D confined and free-surface incompressible turbulent flows. The model equations are solved with the fractional-step projection method in primitive variables. Solutions are obtained by using an adaptation of the front tracking GENSMAC (Tomé and McKee (1994 methodology for calculating fluid flows at high Reynolds numbers. The calculations are performed by using the 2D version of the Freeflow simulation system (Castello et al. (2000. A specific way of implementing wall functions is also tested and assessed. The numerical procedure is tested by solving three fluid flow problems, namely, turbulent flow over a backward-facing step, turbulent boundary layer over a flat plate under zero-pressure gradients, and a turbulent free jet impinging onto a flat surface. The numerical method is then applied to solve the flow of a horizontal jet penetrating a quiescent fluid from an entry port beneath the free surface.
A modified symplectic scheme for seismic wave modeling
Liu, Shaolin; Li, Xiaofan; Wang, Wenshuai; Xu, Ling; Li, Bingfei
2015-05-01
Symplectic integrators are well known for their excellent performance in solving partial differential equation of dynamical systems because they are capable of preserving some conservative properties of dynamic equations. However, there are not enough high-order, for example third-order symplectic schemes, which are suitable for seismic wave equations. Here, we propose a strategy to construct a symplectic scheme that is based on a so-called high-order operator modification method. We first employ a conventional two-stage Runge-Kutta-Nyström (RKN) method to solve the ordinary differential equations, which are derived from the spatial discretization of the seismic wave equations. We then add a high-order term to the RKN method. Finally, we obtain a new third-order symplectic scheme with all positive symplectic coefficients, and it is defined based on the order condition, the symplectic condition, the stability condition and the dispersion relation. It is worth noting that the new scheme is independent of the spatial discretization type used, and we simply apply some finite difference operators to approximate the spatial derivatives of the isotropic elastic equations for a straightforward discussion. For the theoretical analysis, we obtain the semi-analytic stability conditions of our scheme with various orders of spatial approximation. The stability and dispersion properties of our scheme are also compared with conventional schemes to illustrate the favorable numerical behaviors of our scheme in terms of precision, stability and dispersion characteristics. Finally, three numerical experiments are employed to further demonstrate the validity of our method. The modified strategy that is proposed in this paper can be used to construct other explicit symplectic schemes.
High-performance adaptive intelligent Direct Torque Control schemes for induction motor drives
Vasudevan M.
2005-01-01
Full Text Available This paper presents a detailed comparison between viable adaptive intelligent torque control strategies of induction motor, emphasizing advantages and disadvantages. The scope of this paper is to choose an adaptive intelligent controller for induction motor drive proposed for high performance applications. Induction motors are characterized by complex, highly non-linear, time varying dynamics, inaccessibility of some states and output for measurements and hence can be considered as a challenging engineering problem. The advent of torque and flux control techniques have partially solved induction motor control problems, because they are sensitive to drive parameter variations and performance may deteriorate if conventional controllers are used. Intelligent controllers are considered as potential candidates for such an application. In this paper, the performance of the various sensor less intelligent Direct Torque Control (DTC techniques of Induction motor such as neural network, fuzzy and genetic algorithm based torque controllers are evaluated. Adaptive intelligent techniques are applied to achieve high performance decoupled flux and torque control. This paper contributes: i Development of Neural network algorithm for state selection in DTC; ii Development of new algorithm for state selection using Genetic algorithm principle; and iii Development of Fuzzy based DTC. Simulations have been performed using the trained state selector neural network instead of conventional DTC and Fuzzy controller instead of conventional DTC controller. The results show agreement with those of the conventional DTC.
A numerical scheme for coastal morphodynamic modelling on unstructured grids
Guerin, Thomas; Bertin, Xavier; Dodet, Guillaume
2016-08-01
Over the last decade, modelling systems based on unstructured grids have been appearing increasingly attractive to investigate the dynamics of coastal zones. However, the resolution of the sediment continuity equation to simulate bed evolution is a complex problem which often leads to the development of numerical oscillations. To overcome this problem, addition of artificial diffusion or bathymetric filters are commonly employed methods, although these techniques can potentially over-smooth the bathymetry. This study aims to present a numerical scheme based on the Weighted Essentially Non-Oscillatory (WENO) formalism to solve the bed continuity equation on unstructured grids in a finite volume formulation. The new solution is compared against a classical method, which combines a basic node-centered finite volume method with artificial diffusion, for three idealized test cases. This comparison reveals that a higher accuracy is obtained with our new method while the addition of diffusion appears inappropriate mainly due to the arbitrary choice of the diffusion coefficient. Moreover, the increased computation time associated with the WENO-based method to solve the bed continuity equation is negligible when considering a fully-coupled simulation with tides and waves. Finally, the application of the new method to the pluri-monthly evolution of an idealized inlet subjected to tides and waves shows the development of realistic bed features (e.g. secondary flood channels, ebb-delta sandbars, or oblique sandbars at the adjacent beaches), that are smoothed or nonexistent when using additional diffusion.
Adaptive Learning Models of Consumer Behavior
Hopkins, Ed
2007-01-01
In a model of dynamic duopoly, optimal price policies are characterized assuming consumers learn adaptively about the relative quality of the two products. A contrast is made between belief-based and reinforcement learning. Under reinforcement learning, consumers can become locked into the habit of purchasing inferior goods. Such lock-in permits the existence of multiple history-dependent asymmetric steady states in which one firm dominates. In contrast, belief-based learning rules must lead ...
Bayesian Network Models for Adaptive Testing
Plajner, Martin; Vomlel, Jiří
Achen: Sun SITE Central Europe, 2016 - (Agosta, J.; Carvalho, R.), s. 24-33. (CEUR Workshop Proceedings. Vol 1565). ISSN 1613-0073. [The Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015). Amsterdam (NL), 16.07.2015] R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : Bayesian networks * Computerized adaptive testing Subject RIV: JD - Computer Applications, Robotics http://library.utia.cas.cz/separaty/2016/MTR/plajner-0458062.pdf
Reinforcement Learning Using Local Adaptive Models
Borga, Magnus
1995-01-01
In this thesis, the theory of reinforcement learning is described and its relation to learning in biological systems is discussed. Some basic issues in reinforcement learning, the credit assignment problem and perceptual aliasing, are considered. The methods of temporal difference are described. Three important design issues are discussed: information representation and system architecture, rules for improving the behaviour and rules for the reward mechanisms. The use of local adaptive models...
Adaptive human behavior in epidemiological models.
Fenichel, Eli P; Castillo-Chavez, Carlos; Ceddia, M G; Chowell, Gerardo; Parra, Paula A Gonzalez; Hickling, Graham J; Holloway, Garth; Horan, Richard; Morin, Benjamin; Perrings, Charles; Springborn, Michael; Velazquez, Leticia; Villalobos, Cristina
2011-04-12
The science and management of infectious disease are entering a new stage. Increasingly public policy to manage epidemics focuses on motivating people, through social distancing policies, to alter their behavior to reduce contacts and reduce public disease risk. Person-to-person contacts drive human disease dynamics. People value such contacts and are willing to accept some disease risk to gain contact-related benefits. The cost-benefit trade-offs that shape contact behavior, and hence the course of epidemics, are often only implicitly incorporated in epidemiological models. This approach creates difficulty in parsing out the effects of adaptive behavior. We use an epidemiological-economic model of disease dynamics to explicitly model the trade-offs that drive person-to-person contact decisions. Results indicate that including adaptive human behavior significantly changes the predicted course of epidemics and that this inclusion has implications for parameter estimation and interpretation and for the development of social distancing policies. Acknowledging adaptive behavior requires a shift in thinking about epidemiological processes and parameters. PMID:21444809
Direct model reference adaptive control of a flexible robotic manipulator
Meldrum, D. R.
1985-01-01
Quick, precise control of a flexible manipulator in a space environment is essential for future Space Station repair and satellite servicing. Numerous control algorithms have proven successful in controlling rigid manipulators wih colocated sensors and actuators; however, few have been tested on a flexible manipulator with noncolocated sensors and actuators. In this thesis, a model reference adaptive control (MRAC) scheme based on command generator tracker theory is designed for a flexible manipulator. Quicker, more precise tracking results are expected over nonadaptive control laws for this MRAC approach. Equations of motion in modal coordinates are derived for a single-link, flexible manipulator with an actuator at the pinned-end and a sensor at the free end. An MRAC is designed with the objective of controlling the torquing actuator so that the tip position follows a trajectory that is prescribed by the reference model. An appealing feature of this direct MRAC law is that it allows the reference model to have fewer states than the plant itself. Direct adaptive control also adjusts the controller parameters directly with knowledge of only the plant output and input signals.
Junling LI; Xuejun XIE; Wei CHEN
2008-01-01
For a large class of discrete-time multivariable plants with arbitrary relative degrees.the design and analysis of the direct model reference adaptive control scheme are investigated under less restrictive assumptions.The algorithm is based on a new parametrization dedved from the high frequency gain matrix factorization Kp=LDU under the condition that the signs of the leading principal minors of Kp are known.By reproving the discrete-time Lp and L2δ norm relationship between inputs and outputs,establishing the properties of discrete-time adaptive law,defining the normalizing signal.and relating the signal with all signals in the closed-loop system.the stability and convergence of the discrete-time multivariable model reference adaptive control scheme are analyzed rigorously in a systematic fashion as in the continuous-time case.
Automated detection scheme of architectural distortion in mammograms using adaptive Gabor filter
Yoshikawa, Ruriha; Teramoto, Atsushi; Matsubara, Tomoko; Fujita, Hiroshi
2013-03-01
Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting architectural distortion. Our method consists of the analysis of the mammary gland structure, detection of the distorted region, and reduction of false positive results. We developed the adaptive Gabor filter for analyzing the mammary gland structure that decides filter parameters depending on the thickness of the gland structure. As for post-processing, healthy mammary glands that run from the nipple to the chest wall are eliminated by angle analysis. Moreover, background mammary glands are removed based on the intensity output image obtained from adaptive Gabor filter. The distorted region of the mammary gland is then detected as an initial candidate using a concentration index followed by binarization and labeling. False positives in the initial candidate are eliminated using 23 types of characteristic features and a support vector machine. In the experiments, we compared the automated detection results with interpretations by a radiologist using 50 cases (200 images) from the Digital Database of Screening Mammography (DDSM). As a result, true positive rate was 82.72%, and the number of false positive per image was 1.39. There results indicate that the proposed method may be useful for detecting architectural distortion in mammograms.
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 simulate colloid–polymer composites with high resolution regions close to the colloids. The hybrid simulations are significantly faster than reference simulations of a pure particle-based model, and the results are in good agreement. (paper)
Zhou, Yanlai; Guo, Shenglian; Xu, Chong-Yu; Liu, Dedi; Chen, Lu; Ye, Yushi
2015-12-01
Due to the adaption, dynamic and multi-objective characteristics of complex water resources system, it is a considerable challenge to manage water resources in an efficient, equitable and sustainable way. An integrated optimal allocation model is proposed for complex adaptive system of water resources management. The model consists of three modules: (1) an agent-based module for revealing evolution mechanism of complex adaptive system using agent-based, system dynamic and non-dominated sorting genetic algorithm II methods, (2) an optimal module for deriving decision set of water resources allocation using multi-objective genetic algorithm, and (3) a multi-objective evaluation module for evaluating the efficiency of the optimal module and selecting the optimal water resources allocation scheme using project pursuit method. This study has provided a theoretical framework for adaptive allocation, dynamic allocation and multi-objective optimization for a complex adaptive system of water resources management.
Linear Models Based on Noisy Data and the Frisch Scheme*
Ning, Lipeng; Georgiou, Tryphon T.; Tannenbaum, Allen; Boyd, Stephen P.
2016-01-01
We address the problem of identifying linear relations among variables based on noisy measurements. This is a central question in the search for structure in large data sets. Often a key assumption is that measurement errors in each variable are independent. This basic formulation has its roots in the work of Charles Spearman in 1904 and of Ragnar Frisch in the 1930s. Various topics such as errors-in-variables, factor analysis, and instrumental variables all refer to alternative viewpoints on this problem and on ways to account for the anticipated way that noise enters the data. In the present paper we begin by describing certain fundamental contributions by the founders of the field and provide alternative modern proofs to certain key results. We then go on to consider a modern viewpoint and novel numerical techniques to the problem. The central theme is expressed by the Frisch–Kalman dictum, which calls for identifying a noise contribution that allows a maximal number of simultaneous linear relations among the noise-free variables—a rank minimization problem. In the years since Frisch’s original formulation, there have been several insights, including trace minimization as a convenient heuristic to replace rank minimization. We discuss convex relaxations and theoretical bounds on the rank that, when met, provide guarantees for global optimality. A complementary point of view to this minimum-rank dictum is presented in which models are sought leading to a uniformly optimal quadratic estimation error for the error-free variables. Points of contact between these formalisms are discussed, and alternative regularization schemes are presented. PMID:27168672
Xie, Hua; Bosshard, John C.; Hill, Jason E.; Wright, Steven M.; Mitra, Sunanda
2016-03-01
Magnetic Resonance Imaging (MRI) offers noninvasive high resolution, high contrast cross-sectional anatomic images through the body. The data of the conventional MRI is collected in spatial frequency (Fourier) domain, also known as kspace. Because there is still a great need to improve temporal resolution of MRI, Compressed Sensing (CS) in MR imaging is proposed to exploit the sparsity of MR images showing great potential to reduce the scan time significantly, however, it poses its own unique problems. This paper revisits wavelet-encoded MR imaging which replaces phase encoding in conventional MRI data acquisition with wavelet encoding by applying wavelet-shaped spatially selective radiofrequency (RF) excitation, and keeps the readout direction as frequency encoding. The practicality of wavelet encoded MRI by itself is limited due to the SNR penalties and poor time resolution compared to conventional Fourier-based MRI. To compensate for those disadvantages, this paper first introduces an undersampling scheme named significance map for sparse wavelet-encoded k-space to speed up data acquisition as well as allowing for various adaptive imaging strategies. The proposed adaptive wavelet-encoded undersampling scheme does not require prior knowledge of the subject to be scanned. Multiband (MB) parallel imaging is also incorporated with wavelet-encoded MRI by exciting multiple regions simultaneously for further reduction in scan time desirable for medical applications. The simulation and experimental results are presented showing the feasibility of the proposed approach in further reduction of the redundancy of the wavelet k-space data while maintaining relatively high quality.
Young's experiment scheme modification for a possible observation of "soliton" interference model
Ekomasov, E. G.; Salimov, R. K.
2015-01-01
We consider the "soliton" interference model that complements the usual wave and corpuscular models of two-slit interference. The scheme of the experiment to verify such "soliton" interference model has been suggested.
CLUSTERING BASED ADAPTIVE IMAGE COMPRESSION SCHEME USING PARTICLE SWARM OPTIMIZATION TECHNIQUE
M.Mohamed Ismail,
2010-10-01
Full Text Available This paper presents an image compression scheme with particle swarm optimization technique for clustering. The PSO technique is a powerful general purpose optimization technique that uses the concept of fitness.It provides a mechanism such that individuals in the swarm communicate and exchange information which is similar to the social behaviour of insects & human beings. Because of the mimicking the social sharing of information ,PSO directs particle to search the solution more efficiently.PSO is like a GA in that the population isinitialized with random potential solutions.The adjustment towards the best individual experience (PBEST and the best social experience (GBEST.Is conceptually similar to the cross over operaton of the GA.However it is unlike a GA in that each potential solution , called a particle is flying through the solution space with a velocity.Moreover the particles and the swarm have memory,which does not exist in the populatiom of GA.This optimization technique is used in Image compression and better results have obtained in terms of PSNR, CR and the visual quality of the image when compared to other existing methods.
P. Hari Krishnan
2014-08-01
Full Text Available Image segmentation is the foremost process in medical image processing. It aids the diagnostic and clinical analysis of MRI (Magnetic Resonance Imaging images that were acquired through the most complex procedures of medical diagnostics. The earliest soft computing techniques in segmenting images were carried out through Fuzzy C-Means (FCM and similar extensions of various clustering algorithms. In this paper, we introduced an innovative method that uses Gabor energy filter with adaptive features to pre-extract the information of various regions of a brain image, obtained either from a MRI or CT scanner. The noise-reduced image with blurred features was then made to undergo modifications by applying unsupervised learning methods such as FCM technique, whose output has efficient exclusion of certain strength of noise elements resulting in better classified pixels.
Electronic Structure Calculations and Adaptation Scheme in Multi-core Computing Environments
Seshagiri, Lakshminarasimhan; Sosonkina, Masha; Zhang, Zhao
2009-05-20
Multi-core processing environments have become the norm in the generic computing environment and are being considered for adding an extra dimension to the execution of any application. The T2 Niagara processor is a very unique environment where it consists of eight cores having a capability of running eight threads simultaneously in each of the cores. Applications like General Atomic and Molecular Electronic Structure (GAMESS), used for ab-initio molecular quantum chemistry calculations, can be good indicators of the performance of such machines and would be a guideline for both hardware designers and application programmers. In this paper we try to benchmark the GAMESS performance on a T2 Niagara processor for a couple of molecules. We also show the suitability of using a middleware based adaptation algorithm on GAMESS on such a multi-core environment.
Human lymphocytes exposed to low doses of X-rays, become less susceptible to the induction of chromosome aberrations by subsequent exposure to high doses of X-rays. This has been termed the radioadaptive response. One of the most important questions in the adaptive response studies was that of the possible existence of an optimum adapting dose. Early experiments indicated that this response could be induced by low doses of X-rays from 1 cGy to 20 cGy. Recently, it has been interestingly shown that the time scheme of exposure to adapting and challenge doses plays an important role in determination of the magnitude of the induced adaptive response. In this study, using the optimum irradiation time scheme (24-48), we have monitored the cytogenetic endpoint of chromosome aberrations to assess the magnitude of adaptation to ionizing radiation in the cultured human lymphocytes. Lymphocytes were pre-exposed to an adapting dose of 1-20 cGy at 24 hours, before an acute challenge dose of 1 or 2 Gy at 48 hours. Cells were fixed at 54 hours. Lymphocytes, which were pretreated with 5 as well as 10 cGy adapting doses, had significantly fewer chromosome aberrations. In spite of the fact that lymphocytes of some of our blood donors which were pre-treated with 1 or 20 cGy adapting doses, showed an adaptive response, the pooled data (all donors) indicated that such an induction of adaptive response can not be observed in these lymphocytes. The overall pattern of the induced adaptive response, indicated that in human lymphocyte (at least under the above mentioned irradiation scheme), 5 cGy and 10 cGy adapting doses are the optimum doses. (author)
Kayastha, Nagendra; Solomatine, Dimitri; Lal Shrestha, Durga; van Griensven, Ann
2013-04-01
In recent years, a lot of attention in the hydrologic literature is given to model parameter uncertainty analysis. The robustness estimation of uncertainty depends on the efficiency of sampling method used to generate the best fit responses (outputs) and on ease of use. This paper aims to investigate: (1) how sampling strategies effect the uncertainty estimations of hydrological models, (2) how to use this information in machine learning predictors of models uncertainty. Sampling of parameters may employ various algorithms. We compared seven different algorithms namely, Monte Carlo (MC) simulation, generalized likelihood uncertainty estimation (GLUE), Markov chain Monte Carlo (MCMC), shuffled complex evolution metropolis algorithm (SCEMUA), differential evolution adaptive metropolis (DREAM), partical swarm optimization (PSO) and adaptive cluster covering (ACCO) [1]. These methods were applied to estimate uncertainty of streamflow simulation using conceptual model HBV and Semi-distributed hydrological model SWAT. Nzoia catchment in West Kenya is considered as the case study. The results are compared and analysed based on the shape of the posterior distribution of parameters, uncertainty results on model outputs. The MLUE method [2] uses results of Monte Carlo sampling (or any other sampling shceme) to build a machine learning (regression) model U able to predict uncertainty (quantiles of pdf) of a hydrological model H outputs. Inputs to these models are specially identified representative variables (past events precipitation and flows). The trained machine learning models are then employed to predict the model output uncertainty which is specific for the new input data. The problem here is that different sampling algorithms result in different data sets used to train such a model U, which leads to several models (and there is no clear evidence which model is the best since there is no basis for comparison). A solution could be to form a committee of all models U and
BOT schemes as financial model of hydro power projects
Build-operate-transfer (BOT) schemes are the latest methods adopted in the developing infrastructure projects. This paper outlines the project financing through BOT schemes and briefly focuses on the factors particularly relevant to hydro power projects. Hydro power development provides not only the best way to produce electricity, it can also solve problems in different fields, such as navigation problems in case of run-of-the river plants, ground water management systems and flood control etc. This makes HPP projects not cheaper, but hydro energy is a clean and renewable energy and the hydro potential worldwide will play a major role to meet the increased demand in future. 5 figs
An adaptive contextual quantum language model
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.
Model reference adaptive control and adaptive stability augmentation
Henningsen, Arne; Ravn, Ole
1993-01-01
A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...
Model reference adaptive control and adaptive stability augmentation
Henningsen, Arne; Ravn, Ole
A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...
Malgarinos, Ilias; Nikolopoulos, Nikolaos; Gavaises, Manolis
2015-11-01
This study presents the implementation of an interface sharpening scheme on the basis of the Volume of Fluid (VOF) method, as well as its application in a number of theoretical and real cases usually modelled in literature. More specifically, the solution of an additional sharpening equation along with the standard VOF model equations is proposed, offering the advantage of "restraining" interface numerical diffusion, while also keeping a quite smooth induced velocity field around the interface. This sharpening equation is solved right after volume fraction advection; however a novel method for its coupling with the momentum equation has been applied in order to save computational time. The advantages of the proposed sharpening scheme lie on the facts that a) it is mass conservative thus its application does not have a negative impact on one of the most important benefits of VOF method and b) it can be used in coarser grids as now the suppression of the numerical diffusion is grid independent. The coupling of the solved equation with an adaptive local grid refinement technique is used for further decrease of computational time, while keeping high levels of accuracy at the area of maximum interest (interface). The numerical algorithm is initially tested against two theoretical benchmark cases for interface tracking methodologies followed by its validation for the case of a free-falling water droplet accelerated by gravity, as well as the normal liquid droplet impingement onto a flat substrate. Results indicate that the coupling of the interface sharpening equation with the HRIC discretization scheme used for volume fraction flux term, not only decreases the interface numerical diffusion, but also allows the induced velocity field to be less perturbed owed to spurious velocities across the liquid-gas interface. With the use of the proposed algorithmic flow path, coarser grids can replace finer ones at the slight expense of accuracy.
Nie, Suping; Zhu, Jiang; Luo, Yong
2010-05-01
The purpose of this study is to explore the performances of different model error scheme in soil moisture data assimilation. Based on the ensemble Kalman filter (EnKF) and the atmosphere-vegetation interaction model (AVIM), point-scale analysis results for three schemes, 1) covariance inflation (CI), 2) direct random disturbance (DRD), and 3) error source random disturbance (ESRD), are combined under conditions of different observational error estimations, different observation layers, and different observation intervals using a series of idealized experiments. The results shows that all these schemes obtain good assimilation results when the assumed observational error is an accurate statistical representation of the actual error used to perturb the original truth value, and the ESRD scheme has the least root mean square error (RMSE). Overestimation or underestimation of the observational errors can affect the assimilation results of CI and DRD schemes sensitively. The performances of these two schemes deteriorate obviously while the ESRD scheme keeps its capability well. When the observation layers or observation interval increase, the performances of both CI and DRD schemes decline evidently. But for the ESRD scheme, as it can assimilate multi-layer observations coordinately, the increased observations improve the assimilation results further. Moreover, as the ESRD scheme contains a certain amount of model error estimation functions in its assimilation process, it also has a good performance in assimilating sparse-time observations.
Zanotti, Olindo; Dumbser, Michael; Hidalgo, Arturo
2015-01-01
In this paper we present a novel arbitrary high order accurate discontinuous Galerkin (DG) finite element method on space-time adaptive Cartesian meshes (AMR) for hyperbolic conservation laws in multiple space dimensions, using a high order \\aposteriori sub-cell ADER-WENO finite volume \\emph{limiter}. Notoriously, the original DG method produces strong oscillations in the presence of discontinuous solutions and several types of limiters have been introduced over the years to cope with this problem. Following the innovative idea recently proposed in \\cite{Dumbser2014}, the discrete solution within the troubled cells is \\textit{recomputed} by scattering the DG polynomial at the previous time step onto a suitable number of sub-cells along each direction. Relying on the robustness of classical finite volume WENO schemes, the sub-cell averages are recomputed and then gathered back into the DG polynomials over the main grid. In this paper this approach is implemented for the first time within a space-time adaptive ...
A novel adaptive control scheme for dynamic performance improvement of DFIG-Based wind turbines
A novel adaptive current controller for DFIG-based wind turbines is introduced in this paper. The attractiveness of the proposed strategy results from its ability to actively estimate and actively compensate for the plant dynamics and external disturbances in real time. Thus, the control strategy can successfully drive the rotor current to track the reference value, ensuring that the performance degradation caused by grid disturbances, cross-coupling terms and parameter uncertainties can be successfully suppressed. Besides, the two-parameter tuning feature makes the control strategy practical and easy to implement in commercial wind turbines. To quantify the controller performances, the transfer function description of the controller is derived. General disturbance rejection, robustness against parameter uncertainties, bandwidth and stability are also addressed. Simulation results, together with the time-domain responses, proved the stability and the strong robustness of the control system against parameter uncertainties and grid disturbances. Significant tracking and disturbance rejection performances are achieved. -- Highlights: ► The controller can compensate for plant dynamics and external disturbances. ► Performance degradation caused by disturbance can be successfully suppressed. ► General disturbance rejection of the proposed strategy is addressed. ► The stability and the strong robustness of the control system are proved.
Modification of cumulus convection and planetary boundary layer schemes in the GRAPES global model
Liu, Kun; Chen, Qiying; Sun, Jian
2015-10-01
Cumulus convection is a key linkage between hydrological cycle and large-scale atmospheric circulation. Cumulus parameterization scheme is an important component in numerical weather and climate modeling studies. In the Global/Regional Assimilation and Prediction Enhanced System (GRAPES), turbulent mixing and diffusion approach is applied in its shallow convection scheme. This method overestimates the vertical transport of heat and moisture fluxes but underestimates cloud water mixing ratio over the region of stratocumulus clouds. As a result, the simulated low stratocumulus clouds are less than observations. To overcome this problem, a mass flux method is employed in the shallow convection scheme to replace the original one. Meanwhile, the deep convection scheme is adjusted correspondingly. This modification is similar to that in the US NCEP Global Forecast System (GFS), which uses the simplified Arakawa Schubert Scheme (SAS). The planetary boundary layer scheme (PBL) is also revised by considering the coupling between the PBL and stratocumulus clouds. With the modification of both the cumulus and PBL schemes, the GRAPES simulation of shallow convective heating rate becomes more reasonable; total amounts of stratocumulus clouds simulated over the eastern Pacific and their vertical structure are more consistent with observations; the underestimation of stratocumulus clouds simulated by original schemes is less severe with the revised schemes. Precipitation distribution in the tropics becomes more reasonable and spurious precipitation is effectively suppressed. The westward extension and northward movement of the western Pacific subtropical high simulated with the revised schemes are more consistent with Final Operational Global Analysis (FNL) than that simulated with the original schemes. The statistical scores for the global GRAPES forecast are generally improved with the revised schemes, especially for the simulation of geopotential height in the Northern
Adaptive MIMO-OFDM Scheme with Reduced Computational Complexity and Improved Capacity
L. C. Siddanna Gowd; A. R. Rajini
2011-01-01
The general multidimensional linear channel model adequately represents a plethora of communication system models which utilize multidimensional transmit-receive signals for attaining increased rates and reliability in the presence of fading. The logarithmic dependence of the spectral efficiency of the transmitted power makes it extremely expensive to increase the capacity solely by radiating more power. Also, increasing the transmitted power in a mobile terminal is not advisable due to possi...
Neural model-based adaptive control for systems with unknown Preisach-type hysteresis
Chuntao LI; Yonghong TAN
2004-01-01
An adaptive control scheme is presented for systems with unknown hysteresis. In order to handle the case where the hysteresis output is unmeasurale, a novel model is firstly developed to describe the characteristic of hysteresis. This model is motivated by Preisach model but implemented by using neural networks (NN). The main advantage is that it is easily used for controller design. Then, the adaptive controller based on the proposed model is presented for a class of SISO nonlinear systems preceded by unknown hysteresis, which is estimated by the proposed model. The laws for model updating and the control laws for the neural adaptive controller are derived from Lyapunov stability theorem, therefore the semi- global stability of the closed-loop system is guaranteed. At last, the simulation results are illustrated.
Adaptive Genetic Algorithm Model for Intrusion Detection
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.
A Model for Dynamic Adaptive Coscheduling
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.
Adaptive model training system and method
Bickford, Randall L; Palnitkar, Rahul M; Lee, Vo
2014-04-15
An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.
Adaptive model training system and method
Bickford, Randall L; Palnitkar, Rahul M
2014-11-18
An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.
A Positive and Entropy-Satisfying Finite Volume Scheme for the Baer-Nunziato Model
Coquel, Frédéric; Saleh, Khaled; Seguin, Nicolas
2016-01-01
We present a relaxation scheme for approximating the entropy dissipating weak solutions of the Baer-Nunziato two-phase flow model. This relaxation scheme is straightforwardly obtained as an extension of the relaxation scheme designed in the reference [16] for the isentropic Baer-Nunziato model and consequently inherits its main properties. Up to our knowledge, this is the only existing scheme for which the approximated phase fractions, phase densities and phase pressures are proven to remain positive without any restrictive condition other than a classical fully computable CFL condition. It is also the only scheme for which a discrete entropy inequality is proven, under a CFL condition derived from the natural sub-characteristic condition associated with the relaxation approximation. These two properties of the numerical scheme (discrete positivity and entropy inequality) are satisfied for any admissible equation of state. We provide a numerical study for the convergence of the approximate solutions towards s...
Adaptive dynamics for physiologically structured population models.
Durinx, Michel; Metz, J A J Hans; Meszéna, Géza
2008-05-01
We develop a systematic toolbox for analyzing the adaptive dynamics of multidimensional traits in physiologically structured population models with point equilibria (sensu Dieckmann et al. in Theor. Popul. Biol. 63:309-338, 2003). Firstly, we show how the canonical equation of adaptive dynamics (Dieckmann and Law in J. Math. Biol. 34:579-612, 1996), an approximation for the rate of evolutionary change in characters under directional selection, can be extended so as to apply to general physiologically structured population models with multiple birth states. Secondly, we show that the invasion fitness function (up to and including second order terms, in the distances of the trait vectors to the singularity) for a community of N coexisting types near an evolutionarily singular point has a rational form, which is model-independent in the following sense: the form depends on the strategies of the residents and the invader, and on the second order partial derivatives of the one-resident fitness function at the singular point. This normal form holds for Lotka-Volterra models as well as for physiologically structured population models with multiple birth states, in discrete as well as continuous time and can thus be considered universal for the evolutionary dynamics in the neighbourhood of singular points. Only in the case of one-dimensional trait spaces or when N = 1 can the normal form be reduced to a Taylor polynomial. Lastly we show, in the form of a stylized recipe, how these results can be combined into a systematic approach for the analysis of the (large) class of evolutionary models that satisfy the above restrictions. PMID:17943289
Adapting a weather forecast model for greenhouse gas simulation
Polavarapu, S. M.; Neish, M.; Tanguay, M.; Girard, C.; de Grandpré, J.; Gravel, S.; Semeniuk, K.; Chan, D.
2015-12-01
The ability to simulate greenhouse gases on the global domain is useful for providing boundary conditions for regional flux inversions, as well as for providing reference data for bias correction of satellite measurements. Given the existence of operational weather and environmental prediction models and assimilation systems at Environment Canada, it makes sense to use these tools for greenhouse gas simulations. In this work, we describe the adaptations needed to reasonably simulate CO2 with a weather forecast model. The main challenges were the implementation of a mass conserving advection scheme, and the careful implementation of a mixing ratio defined with respect to dry air. The transport of tracers through convection was also added, and the vertical mixing through the boundary layer was slightly modified. With all these changes, the model conserves CO2 mass well on the annual time scale, and the high resolution (0.9 degree grid spacing) permits a good description of synoptic scale transport. The use of a coupled meteorological/tracer transport model also permits an assessment of approximations needed in offline transport model approaches, such as the neglect of water vapour mass when computing a tracer mixing ratio with respect to dry air.
Hong, Qianying; Lai, Ming-Jun; Wang, Jingyue
2013-01-01
We present a convergence analysis of a finite difference scheme for the time dependent partial different equation called gradient flow associated with the Rudin-Osher-Fatemi model. We devise an iterative algorithm to compute the solution of the finite difference scheme and prove the convergence of the iterative algorithm. Finally computational experiments are shown to demonstrate the convergence of the finite difference scheme. An application for image denoising is given.
Innovation Model of the Concept of Professional Adaptation of Personnel
Kurina Nataliya S.; Darchenko Nataliya D.
2013-01-01
The article considers the essence and types of adaptation as an important element of the modern theory of personnel management. It analyses problems of practical adaptation of personnel at domestic and Russian enterprises. It proves urgency and offers a concept of professional adaptation – adaptation management. It describes main moments of the model-concept of professional adaptation of young specialists, possibilities and prospects of its introduction, risks and weaknesses. It shows innovat...
Godunov-type schemes for hydrodynamic and magnetohydrodynamic modeling
Vides Higueros, Jeaniffer
2014-01-01
The main objective of this thesis concerns the study, design and numerical implementation of finite volume schemes based on the so-Called Godunov-Type solvers for hyperbolic systems of nonlinear conservation laws, with special attention given to the Euler equations and ideal MHD equations. First, we derive a simple and genuinely two-Dimensional Riemann solver for general conservation laws that can be regarded as an actual 2D generalization of the HLL approach, relying heavily on the consisten...
Highlights: • V&V studies with CASMO/SIMULATE/MCNPX computation scheme are described. • Fixed-source modeling is used for PWR ex-core Monte Carlo neutron transport. • The reference data includes activity measurements and fluence estimations. • Adjusting the calculation models for the specific validation data sets is discussed. • Obtained results and findings of associated sensitivity studies are reported. - Abstract: At the Paul Scherrer Institute (PSI), a computational scheme aimed at high fidelity fast neutron fluence estimations for Light-Water-Reactors (LWRs) was in previous years developed. In this scheme, the neutron transport calculations are performed with the stochastic Monte Carlo N-Particle Transport Code MCNPX using as basis a three-dimensional pin-level volumetric source obtained from validated deterministic CASMO/SIMULATE models. While first validation studies confirmed a satisfactory performance, the strategy is to continually add new validation cases in order to achieve an enlarged and comprehensive qualification basis that also integrates latest advances in methods and/or nuclear data. Thereby, new sets of experimental data from a Swiss operating pressurized water reactor plant that became available recently were adopted for a further validation of the scheme. The first set consists of 54Mn and 93mNb activity measurements from so-called gradient probes located at an elevation corresponding to the top end of active fuel and increasing thereby the computational challenges because of very strong axial flux gradients. The second set consists of fluence estimates derived from 54Mn and 93mNb activity measurements of scraping samples extracted from the reactor pressure vessel. All dosimeters have been analyzed after the 27th cycle of operation of the reactor, providing thereby an opportunity to assess the computational methodology for modern fuel management schemes. This paper presents the validation study of the PSI fast neutron fluence scheme
An Importance Sampling Scheme on Dual Factor Graphs. I. Models in a Strong External Field
Molkaraie, Mehdi
2014-01-01
We propose an importance sampling scheme to estimate the partition function of the two-dimensional ferromagnetic Ising model and the two-dimensional ferromagnetic $q$-state Potts model, both in the presence of an external magnetic field. The proposed scheme operates in the dual Forney factor graph and is capable of efficiently computing an estimate of the partition function under a wide range of model parameters. In particular, we consider models that are in a strong external magnetic field.
Advanced radar detection schemes under mismatched signal models
Bandiera, Francesco
2009-01-01
Adaptive detection of signals embedded in correlated Gaussian noise has been an active field of research in the last decades. This topic is important in many areas of signal processing such as, just to give some examples, radar, sonar, communications, and hyperspectral imaging. Most of the existing adaptive algorithms have been designed following the lead of the derivation of Kelly's detector which assumes perfect knowledge of the target steering vector. However, in realistic scenarios, mismatches are likely to occur due to both environmental and instrumental factors. When a mismatched signal
Glocer, A.; Toth, G.; Ma, Y.; Gombosi, T.; Zhang, J.-C.; Kistler, L. M.
2009-01-01
The magnetosphere contains a significant amount of ionospheric O+, particularly during geomagnetically active times. The presence of ionospheric plasma in the magnetosphere has a notable impact on magnetospheric composition and processes. We present a new multifluid MHD version of the Block-Adaptive-Tree Solar wind Roe-type Upwind Scheme model of the magnetosphere to track the fate and consequences of ionospheric outflow. The multifluid MHD equations are presented as are the novel techniques for overcoming the formidable challenges associated with solving them. Our new model is then applied to the May 4, 1998 and March 31, 2001 geomagnetic storms. The results are juxtaposed with traditional single-fluid MHD and multispecies MHD simulations from a previous study, thereby allowing us to assess the benefits of using a more complex model with additional physics. We find that our multifluid MHD model (with outflow) gives comparable results to the multispecies MHD model (with outflow), including a more strongly negative Dst, reduced CPCP, and a drastically improved magnetic field at geosynchronous orbit, as compared to single-fluid MHD with no outflow. Significant differences in composition and magnetic field are found between the multispecies and multifluid approach further away from the Earth. We further demonstrate the ability to explore pressure and bulk velocity differences between H+ and O+, which is not possible when utilizing the other techniques considered
Adaptive nonparametric instrumental regression by model selection
Johannes, Jan
2010-01-01
We consider the problem of estimating the structural function in nonparametric instrumental regression, where in the presence of an instrument W a response Y is modeled in dependence of an endogenous explanatory variable Z. The proposed estimator is based on dimension reduction and additional thresholding. The minimax optimal rate of convergence of the estimator is derived assuming that the structural function belongs to some ellipsoids which are in a certain sense linked to the conditional expectation operator of Z given W. We illustrate these results by considering classical smoothness assumptions. However, the proposed estimator requires an optimal choice of a dimension parameter depending on certain characteristics of the unknown structural function and the conditional expectation operator of Z given W, which are not known in practice. The main issue addressed in our work is a fully adaptive choice of this dimension parameter using a model selection approach under the restriction that the conditional expe...
Adaptation dynamics of the quasispecies model
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.
Verification and comparison of four numerical schemes for a 1D viscoelastic blood flow model.
Wang, Xiaofei; Fullana, Jose-Maria; Lagrée, Pierre-Yves
2015-01-01
A reliable and fast numerical scheme is crucial for the 1D simulation of blood flow in compliant vessels. In this paper, a 1D blood flow model is incorporated with a Kelvin-Voigt viscoelastic arterial wall. This leads to a nonlinear hyperbolic-parabolic system, which is then solved with four numerical schemes, namely: MacCormack, Taylor-Galerkin, monotonic upwind scheme for conservation law and local discontinuous Galerkin. The numerical schemes are tested on a single vessel, a simple bifurcation and a network with 55 arteries. The numerical solutions are checked favorably against analytical, semi-analytical solutions or clinical observations. Among the numerical schemes, comparisons are made in four important aspects: accuracy, ability to capture shock-like phenomena, computational speed and implementation complexity. The suitable conditions for the application of each scheme are discussed. PMID:25145651
A Markov Chain Model for the Analysis of Round-Robin Scheduling Scheme
D. Shukla
2009-07-01
Full Text Available In the literature of Round-Robin scheduling scheme, each job is processed, one after the another after giving a fix quantum. In case of First-come first-served, each process is executed, if the previously arrived processed is completed. Both these scheduling schemes are used in this paper as its special cases. A Markov chain model is used to compare several scheduling schemes of the class. An index measure is defined to compare the model based efficiency of different scheduling schemes. One scheduling scheme which is the mixture of FIFO and round robin is found efficient in terms of model based study. The system simulation procedure is used to derive the conclusion of the content.
Towards a large-scale scalable adaptive heart model using shallow tree meshes
Krause, Dorian; Dickopf, Thomas; Potse, Mark; Krause, Rolf
2015-10-01
Electrophysiological heart models are sophisticated computational tools that place high demands on the computing hardware due to the high spatial resolution required to capture the steep depolarization front. To address this challenge, we present a novel adaptive scheme for resolving the deporalization front accurately using adaptivity in space. Our adaptive scheme is based on locally structured meshes. These tensor meshes in space are organized in a parallel forest of trees, which allows us to resolve complicated geometries and to realize high variations in the local mesh sizes with a minimal memory footprint in the adaptive scheme. We discuss both a non-conforming mortar element approximation and a conforming finite element space and present an efficient technique for the assembly of the respective stiffness matrices using matrix representations of the inclusion operators into the product space on the so-called shallow tree meshes. We analyzed the parallel performance and scalability for a two-dimensional ventricle slice as well as for a full large-scale heart model. Our results demonstrate that the method has good performance and high accuracy.
Modeling and Simulation of Handover Scheme in Integrated EPON-WiMAX Networks
Yan, Ying; Dittmann, Lars
2011-01-01
In this paper, we tackle the seamless handover problem in integrated optical wireless networks. Our model applies for the convergence network of EPON and WiMAX and a mobilityaware signaling protocol is proposed. The proposed handover scheme, Integrated Mobility Management Scheme (IMMS), is assisted...
DANA: distributed numerical and adaptive modelling framework.
Rougier, Nicolas P; Fix, Jérémy
2012-01-01
DANA is a python framework ( http://dana.loria.fr ) whose computational paradigm is grounded on the notion of a unit that is essentially a set of time dependent values varying under the influence of other units via adaptive weighted connections. The evolution of a unit's value are defined by a set of differential equations expressed in standard mathematical notation which greatly ease their definition. The units are organized into groups that form a model. Each unit can be connected to any other unit (including itself) using a weighted connection. The DANA framework offers a set of core objects needed to design and run such models. The modeler only has to define the equations of a unit as well as the equations governing the training of the connections. The simulation is completely transparent to the modeler and is handled by DANA. This allows DANA to be used for a wide range of numerical and distributed models as long as they fit the proposed framework (e.g. cellular automata, reaction-diffusion system, decentralized neural networks, recurrent neural networks, kernel-based image processing, etc.). PMID:22994650
An Adaptive Learning Model in Coordination Games
Naoki Funai
2013-11-01
Full Text Available In this paper, we provide a theoretical prediction of the way in which adaptive players behave in the long run in normal form games with strict Nash equilibria. In the model, each player assigns subjective payoff assessments to his own actions, where the assessment of each action is a weighted average of its past payoffs, and chooses the action which has the highest assessment. After receiving a payoff, each player updates the assessment of his chosen action in an adaptive manner. We show almost sure convergence to a Nash equilibrium under one of the following conditions: (i that, at any non-Nash equilibrium action profile, there exists a player who receives a payoff, which is less than his maximin payoff; (ii that all non-Nash equilibrium action profiles give the same payoff. In particular, the convergence is shown in the following games: the battle of the sexes game, the stag hunt game and the first order statistic game. In the game of chicken and market entry games, players may end up playing the action profile, which consists of each player’s unique maximin action.
O Shallow Cumulus Parameterization Schemes for General Circulation Model Planetary Boundary Layers
Li, Jui-Lin Frank
Shallow non-precipitating cumulus clouds play an important role in atmospheric boundary layers and global energetics. It is very important that a shallow cumulus scheme should be able to represent these clouds under different kinds of weather in a GCM. The objectives of this study are to test different parameterization schemes recently used in GCMs, develop modified schemes based on them, and create a new cumulus eddy diffusion scheme. A one-dimensional PBL model representing small-scale turbulence and cumulus effects is used to perform a series of high resolution numerical integrations. Data sets for undisturbed quasi -steady tradewind conditions during BOMEX and ATEX are used for comparisons. The simulation of stronger cumulus regimes is achieved by increasing sea surface temperature and studying idealized cold air flow over a warmer sea. Dry turbulence diffusion is represented by either an explicit dry turbulent diffusion scheme (Louis, 1982) used in the ECMWF grid level model, or a nonlocal convective scheme proposed by Holtslag and Moeng (1991). The high vertical resolution (50m) PBL model is then integrated in time with several shallow cumulus parameterization schemes: a simple cumulus mass flux model, Betts-Miller adjustment (1986), simple K-theory (Tiedtke, 1984), modifications of each of them, and a new cumulus diffusion scheme, respectively. The modified cumulus mass flux scheme decreases cumulus mass flux linearly from the cloud base to mid-subcloud layer to represent cloud root effects. The modified Betts-Miller schemes are defined by considering subcloud layer adjustment and curved approximate reference profiles with a constraint of constant virtual potential temperature in the subcloud layer. A new cumulus diffusion scheme estimates the cumulus eddy diffusivities from entrained cloud available potential energy and formulates the nonlocal cumulus flux by coupling the cumulus-scale fluxes with large-scale dry thermals at the cloud base. The results show
Adaptable Authentication Model: Exploring Security with Weaker Attacker Models
Ahmed, Naveed; Jensen, Christian D.
2011-01-01
; 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...
Biohybrid control of general linear systems using the adaptive filter model of cerebellum
Emma D. Wilson
2015-07-01
Full Text Available The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems such as the vestibulo-ocular reflex (VOR and to sensory processing problems such as the adaptive cancellation of reafferent noise. It has also been successfully applied to problems in robotics such as adaptive camera stabilisation and sensor noise cancellation. In previous applications to inverse control problems the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity control of this plant results in unstable learning and control. To be more generally useful in engineering problems it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC scheme, which stabilises the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.
Backeberg, B. C.; Bertino, L.; J. A. Johannessen
2009-01-01
A 4th order advection scheme is applied in a nested eddy-resolving Hybrid Coordinate Ocean Model (HYCOM) of the greater Agulhas Current system for the purpose of testing advanced numerics as a means for improving the model simulation for eventual operational implementation. Model validation techniques comparing sea surface height variations, sea level skewness and variogram analyses to satellite altimetry measurements quantify that generally the 4th order advection scheme improves the realism...
Constructing an Urban Population Model for Medical Insurance Scheme Using Microsimulation Techniques
Linping Xiong
2012-01-01
Full Text Available China launched a pilot project of medical insurance reform in 79 cities in 2007 to cover urban nonworking residents. An urban population model was created in this paper for China’s medical insurance scheme using microsimulation model techniques. The model made it clear for the policy makers the population distributions of different groups of people, the potential urban residents entering the medical insurance scheme. The income trends of units of individuals and families were also obtained. These factors are essential in making the challenging policy decisions when considering to balance the long-term financial sustainability of the medical insurance scheme.
Enhanced Physics-Based Numerical Schemes for Two Classes of Turbulence Models
Leo G. Rebholz
2009-01-01
Full Text Available We present enhanced physics-based finite element schemes for two families of turbulence models, the NS- models and the Stolz-Adams approximate deconvolution models. These schemes are delicate extensions of a method created for the Navier-Stokes equations in Rebholz (2007, that achieve high physical fidelity by admitting balances of both energy and helicity that match the true physics. The schemes' development requires carefully chosen discrete curl, discrete Laplacian, and discrete filtering operators, in order to permit the necessary differential operator commutations.
An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation
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.
Adaptable Multivariate Calibration Models for Spectral Applications
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.
Multiple model adaptive tracking of airborne targets
Norton, John E.
1988-12-01
Over the past ten years considerable work has been accomplished at the Air Force Institute of Technology (AFIT) towards improving the ability of tracking airborne targets. Motivated by the performance advantages in using established models of tracking environment variables within a Kalman filter, an advanced tracking algorithm has been developed based on adaptive estimation filter structures. A multiple model bank of filters that have been designed for various target dynamics, which each accounting for atmospheric disturbance of the Forward Looking Infrared (FLIR) sensor data and mechanical vibrations of the sensor platform, outperforms a correlator tracker. The bank of filters provides the estimation capability to guide the pointing mechanisms of a shared aperture laser/sensor system. The data is provided to the tracking algorithm via an (8 x 8)-pixel tracking Field of View (FOV) from the FLIR image plane. Data at each sample period is compared by an enhanced correlator to a target template. These offsets are measurements to a bank of linear Kalman filters which provide estimates of the target's location in azimuth and elevation coordinates based on a Gauss-Markov acceleration model, and a reduced form of the atmospheric jitter model for the disturbance in the IR wavefront carrying future measurements.
Godunov-type schemes for hydrodynamic and magnetohydrodynamic modeling
The main objective of this thesis concerns the study, design and numerical implementation of finite volume schemes based on the so-Called Godunov-Type solvers for hyperbolic systems of nonlinear conservation laws, with special attention given to the Euler equations and ideal MHD equations. First, we derive a simple and genuinely two-Dimensional Riemann solver for general conservation laws that can be regarded as an actual 2D generalization of the HLL approach, relying heavily on the consistency with the integral formulation and on the proper use of Rankine-Hugoniot relations to yield expressions that are simple enough to be applied in the structured and unstructured contexts. Then, a comparison between two methods aiming to numerically maintain the divergence constraint of the magnetic field for the ideal MHD equations is performed and we show how the 2D Riemann solver can be employed to obtain robust divergence-Free simulations. Next, we derive a relaxation scheme that incorporates gravity source terms derived from a potential into the hydrodynamic equations, an important problem in astrophysics, and finally, we review the design of finite volume approximations in curvilinear coordinates, providing a fresher view on an alternative discretization approach. Throughout this thesis, numerous numerical results are shown. (author)
ADAPTIVE TCHEBICHEF MOMENT TRANSFORM IMAGE COMPRESSION USING PSYCHOVISUAL MODEL
Ferda Ernawan
2013-01-01
Full Text Available An extension of the standard JPEG image compression known as JPEG-3 allows rescaling of the quantization matrix to achieve a certain image output quality. Recently, Tchebichef Moment Transform (TMT has been introduced in the field of image compression. TMT has been shown to perform better than the standard JPEG image compression. This study presents an adaptive TMT image compression. This task is obtained by generating custom quantization tables for low, medium and high image output quality levels based on a psychovisual model. A psychovisual model is developed to approximate visual threshold on Tchebichef moment from image reconstruction error. The contribution of each moment will be investigated and analyzed in a quantitative experiment. The sensitivity of TMT basis functions can be measured by evaluating their contributions to image reconstruction for each moment order. The psychovisual threshold model allows a developer to design several custom TMT quantization tables for a user to choose from according to his or her target output preference. Consequently, these quantization tables produce lower average bit length of Huffman code while still retaining higher image quality than the extended JPEG scaling scheme.
Guojin Liu; Qian Zhang; Yuyuan Yang; Zhenzhi Yin; Bin Zhu
2015-01-01
Recent years have witnessed pilot deployments of inexpensive wireless sensor networks (WSNs) for volcanic eruption detection, where the volcano-seismic signals were collected and processed by sensor nodes. However, it is faced with the limitation of energy resources and the transmission bottleneck of sensors in WSN. In this paper, a Model-Based Adaptive Iterative Hard Thresholding (MAIHT) compressive sensing scheme is developed, where a large number of inexpensive sensors are used to collect ...
SEMPATH Ontology: modeling multidisciplinary treatment schemes utilizing semantics.
Alexandrou, Dimitrios Al; Pardalis, Konstantinos V; Bouras, Thanassis D; Karakitsos, Petros; Mentzas, Gregoris N
2012-03-01
A dramatic increase of demand for provided treatment quality has occurred during last decades. The main challenge to be confronted, so as to increase treatment quality, is the personalization of treatment, since each patient constitutes a unique case. Healthcare provision encloses a complex environment since healthcare provision organizations are highly multidisciplinary. In this paper, we present the conceptualization of the domain of clinical pathways (CP). The SEMPATH (SEMantic PATHways) Oontology comprises three main parts: 1) the CP part; 2) the business and finance part; and 3) the quality assurance part. Our implementation achieves the conceptualization of the multidisciplinary domain of healthcare provision, in order to be further utilized for the implementation of a Semantic Web Rules (SWRL rules) repository. Finally, SEMPATH Ontology is utilized for the definition of a set of SWRL rules for the human papillomavirus) disease and its treatment scheme. PMID:21768052
Analyses of models for promotion schemes and ownership arrangements
Hansen, Lise-Lotte Pade; Schröder, Sascha Thorsten; Münster, Marie;
2011-01-01
based microCHP will be able to contribute to an innovative system where the customer produces his own heat and partly his own electricity. Furthermore, stationary fuel cells as a part of a distributed generation system are also regarded as a potential to improve the national security of supply as well...... as increase the national competitiveness. The stationary fuel cell technology is still in a rather early stage of development and faces a long list of challenges and barriers of which some are linked directly to the technology through the need of cost decrease and reliability improvements. Others are...... contribute to assuring that the investors face long term planning perspectives and regulation in the field has to be clear and contribute to creating the market opportunities e.g. through investments in R&D. In this work package, we address the issues of necessary support schemes and the effect on the future...
Adaptive model predictive control of the hybrid dynamics of a fuel cell system
Fiacchini, Mirko; Alamo, Teodoro; Albea-Sanchez, Carolina; Fernandez Camacho, Eduardo
2007-01-01
International audience In this paper, an adaptive control scheme for the safe operation of a fuel cell system is presented. The aim of the control design is to guarantee that the oxygen ratio do not reach dangerous values. A first level of control is given by a feedforward control. An improved behavior is obtained using an adaptive predictive controller to determine the voltage to be applied to the air compressor. An admissible robust control invariant set for the PWA model of the system i...
Man, Jun; Li, Weixuan; Zeng, Lingzao; Wu, Laosheng
2016-06-01
The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a sufficiently large ensemble size is usually required to guarantee the accuracy. As an alternative approach, the probabilistic collocation based Kalman filter (PCKF) employs the polynomial chaos expansion (PCE) to represent and propagate the uncertainties in parameters and states. However, PCKF suffers from the so-called "curse of dimensionality". Its computational cost increases drastically with the increasing number of parameters and system nonlinearity. Furthermore, PCKF may fail to provide accurate estimations due to the joint updating scheme for strongly nonlinear models. Motivated by recent developments in uncertainty quantification and EnKF, we propose a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problems. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected at each assimilation step; the "restart" scheme is utilized to eliminate the inconsistency between updated model parameters and states variables. The performance of RAPCKF is systematically tested with numerical cases of unsaturated flow models. It is shown that the adaptive approach and restart scheme can significantly improve the performance of PCKF. Moreover, RAPCKF has been demonstrated to be more efficient than EnKF with the same computational cost.
Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model
Xie, Bo; Fung, Jimmy C. H.; Chan, Allen; Lau, Alexis
2012-06-01
A realistic reproduction of planetary boundary layer (PBL) structure and its evolution is critical to numerical simulation of regional meteorology and air quality. Conversely, insufficient realism in the simulated physical properties often leads to degraded meteorological and air quality prognostic skills. This study employed the Weather Research and Forecasting model (WRF) to evaluate model performance and to quantify meteorological prediction differences produced by four widely used PBL schemes. Evaluated were two nonlocal PBL schemes, YSU and ACM2, and two local PBL schemes, MYJ and Boulac. The model grid comprised four nested domains at horizontal resolutions of 27 km, 9 km, 3 km and 1 km respectively. Simulated surface variables 2 m temperature and 10 m wind at 1 km resolution were compared to measurements collected in Hong Kong. A detailed analysis of land-atmosphere energy balance explicates heat flux and temperature variability among the PBL schemes. Differences in vertical profiles of horizontal velocity, potential temperature, bulk Richardson number and water vapor mixing ratio were examined. Diagnosed PBL heights, estimated by scheme specific formulations, exhibited the large intrascheme variance. To eliminate formulation dependence in PBL height estimation, lidar measurements and a unified diagnosis were jointly used to reanalyze PBL heights. The diagnosis showed that local PBL schemes produced shallower PBL heights than those of nonlocal PBL schemes. It is reasonable to infer that WRF, coupled with the ACM2 PBL physics option can be a viable producer of meteorological forcing to regional air quality modeling in the Pearl River Delta (PRD) Region.
Soft rotator model and {sup 246}Cm low-lying level scheme
Porodzinskij, Yu.V.; Sukhovitskij, E.Sh. [Radiation Physics and Chemistry Problems Inst., Minsk-Sosny (Belarus)
1997-03-01
Non-axial soft rotator nuclear model is suggested as self-consistent approach for interpretation of level schemes, {gamma}-transition probabilities and neutron interaction with even-even nuclei. (author)
Peng, Wei-Tao
2014-01-01
We examine the performance of the asymptotically corrected model potential scheme on the two lowest singlet excitation energies of acenes with different number of linearly fused benzene rings (up to 5), employing both the real-time time-dependent density functional theory and the frequency-domain formulation of linear-response time-dependent density functional theory. The results are compared with the experimental data and those calculated by long-range corrected hybrid functionals and others. The long-range corrected hybrid scheme is shown to outperform the asymptotically corrected model potential scheme for charge-transfer-like excitations.
Solute based Lagrangian scheme in modeling the drying process of soft matter solutions.
Meng, Fanlong; Luo, Ling; Doi, Masao; Ouyang, Zhongcan
2016-02-01
We develop a new dynamical model to study the drying process of a droplet of soft matter solutions. The model includes the processes of solute diffusion, gel-layer formation and cavity creation. A new scheme is proposed to handle the diffusion dynamics taking place in such processes. In this scheme, the dynamics is described by the motion of material points taken on solute. It is convenient to apply this scheme to solve problems that involve moving boundaries and phase changes. As an example, we show results of a numerical calculation for a drying spherical droplet, and discuss how initial concentration and evaporation rate affect the structural evolution of the droplet. PMID:26920525
An adaptive time-stepping strategy for solving the phase field crystal model
In this work, we will propose an adaptive time step method for simulating the dynamics of the phase field crystal (PFC) model. The numerical simulation of the PFC model needs long time to reach steady state, and then large time-stepping method is necessary. Unconditionally energy stable schemes are used to solve the PFC model. The time steps are adaptively determined based on the time derivative of the corresponding energy. It is found that the use of the proposed time step adaptivity cannot only resolve the steady state solution, but also the dynamical development of the solution efficiently and accurately. The numerical experiments demonstrate that the CPU time is significantly saved for long time simulations
A Finite Difference Scheme for Pricing American Put Options under Kou's Jump-Diffusion Model
Jian Huang; Zhongdi Cen; Anbo Le
2013-01-01
We present a stable finite difference scheme on a piecewise uniform mesh along with a penalty method for pricing American put options under Kou's jump-diffusion model. By adding a penalty term, the partial integrodifferential complementarity problem arising from pricing American put options under Kou's jump-diffusion model is transformed into a nonlinear parabolic integro-differential equation. Then a finite difference scheme is proposed to solve the penalized integrodiffere...
Unifying design and runtime software adaptation using aspect models
Parra, Carlos; Blanc, Xavier; Cleve, Anthony; Duchien, Laurence
2011-01-01
Software systems are seen more and more as evolutive systems. At the design phase, software is constantly in adaptation by the building process itself, and at runtime, it can be adapted in response to changing conditions in the executing environment such as location or resources. Adaptation is generally difficult to specify because of its crosscutting impact on software. This article introduces an approach to unify adaptation at design and at runtime based on Aspect Oriented Modeling. Our app...
Adaptive control using a hybrid-neural model: application to a polymerisation reactor
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.
Adaptation in Cones: A General Model
Dawis, Stevan M.; Purple, Richard L.
1982-01-01
Three features appear to characterize steady-state light adaptation in vertebrate cone photoreceptors: (a) the shape of the “log intensity-response” curve at different levels of adaptation is the same, the only change with adaptation is in the position of the point on the curve about which the cones operate; (b) at high adapting intensities the operating point becomes fixed in position; (c) this fixed position is at the steepest point of the log intensity-response curve. These three features ...
Zeeshan Ahmad; Meng Jun; Muhammad Abdullah; Mazhar Nadeem Ishaq; Majid Lateef; Imran Khan
2015-01-01
This paper used the modern evaluation method of DEA (Data Envelopment Analysis) to assess the comparative efficiency and then on the basis of this among multiple schemes chose the optimal scheme of agricultural production structure adjustment. Based on the results of DEA model, we dissected scale advantages of each discretionary scheme or plan. We examined scale advantages of each discretionary scheme, tested profoundly a definitive purpose behind not-DEA efficient, which elucidated the system and methodology to enhance these discretionary plans. At the end, another method had been proposed to rank and select the optimal scheme. The research was important to guide the practice if the modification of agricultural production industrial structure was carried on.
Mathematical modelling and study of the encoding readout scheme for position sensitive detectors
Yue, Xiaoguang; Zeng, Ming; Zeng, Zhi; Wang, Yi; Wang, Xuewu; Zhao, Ziran; Cheng, Jianping; Kang, Kejun
2016-04-01
Encoding readout methods based on different schemes have been successfully developed and tested with different types of position-sensitive detectors with strip-readout structures. However, how to construct an encoding scheme in a more general and systematic way is still under study. In this paper, we present a graph model for the encoding scheme. With this model, encoding schemes can be studied in a more systematic way. It is shown that by using an encoding readout method, a maximum of n (n - 1)/2 + 1 strips can be processed with n channels if n is odd, while a maximum of n (n - 2)/2 + 2 strips can be processed with n channels if n is even. Furthermore, based on the model, the encoding scheme construction problem can be translated into a problem in graph theory, the aim of which is to construct an Eulerian trail such that the length of the shortest subcycle is as long as possible. A more general approach to constructing the encoding scheme is found by solving the associated mathematical problem. In addition, an encoding scheme prototype has been constructed, and verified with MRPC detectors.
STOCHASTIC ADAPTIVE SWITCHING CONTROL BASED ON MULTIPLE MODELS
ZHANG Yanxia; GUO Lei
2002-01-01
It is well known that the transient behaviors of the traditional adaptive control may be very poor in general, and that the adaptive control designed based on switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances. In this paper, we shall prove that for a typical class of linear systems disturbed by random noises, the multiple model based least-squares (LS)adaptive switching control is stable and convergent, and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators. Moreover,the mixed case combining adaptive models with fixed models is also considered.
Sensitivity of a Cloud-Resolving Model to the Bulk and Explicit Bin Microphysical Schemes
Li, Xiao-Wen; Tao, Wei-Kuo; Khain, Alexander P.; Simpson, Joanne
2004-01-01
A cloud-resolving model is used to study sensitivities of two different microphysical schemes, one is the traditional bulk type, and the other is an explicit bin scheme, in simulating a mid-latitude squall line case (PRE-STORM, June 10-1 1,1985). Simulations using different microphysical schemes are compared with each other and also with the observations. Both the bulk and bin models reproduce the general features during the developing and mature stage of the system. Furthermore, the observations and the well-proven bulk scheme simulation serve as validations for the newly incorporated bin scheme. However, it is also shown that the bulk and bin simulations have distinct differences, most notably in the stratiform region of the squall line system. Weak convective cells exist in the stratiform region in the bulk simulation, but not in the bin simulation. These weak convective cells in the stratiform region simulated in the bulk scheme model are remnants of the stronger convections previously at the leading edge of the system, sustained by horizontal vorticity generated by its own cool pool near the surface. The bin simulation, on the other hand, has a horizontally homogeneous stratiform cloud structure, which agrees better with the observations. Examinations of the downdraft core strength, the potential temperature perturbation, and the evaporative cooling rate show that the differences between the bulk and bin models are due mainly to the stronger low-level evaporative cooling in the convective zone simulated in the bulk microphysical scheme, which is unrealistic because of the assumptions made in raindrop size distribution. Further sensitivity tests that reduce the evaporation rate in bulk scheme artificially produce more upright convective core and less weak cores in stratiform region. However, they produce weaker upper level outflow and consequently less stratiform rain area. The addition of a more realistic raindrop breakup scheme in the bin scheme results more
Adapting the ALP Model for Student and Institutional Needs
Sides, Meredith
2016-01-01
With the increasing adoption of accelerated models of learning comes the necessary step of adapting these models to fit the unique needs of the student population at each individual institution. One such college adapted the ALP (Accelerated Learning Program) model and made specific changes to the target population, structure and scheduling, and…
Flexible Cure Rate Modeling Under Latent Activation Schemes
Cooner, Freda; Banerjee, Sudipto; Bradley P. Carlin; Sinha, Debajyoti
2007-01-01
With rapid improvements in medical treatment and health care, many datasets dealing with time to relapse or death now reveal a substantial portion of patients who are cured (i.e., who never experience the event). Extended survival models called cure rate models account for the probability of a subject being cured and can be broadly classified into the classical mixture models of Berkson and Gage (BG type) or the stochastic tumor models pioneered by Yakovlev and extended to a hierarchical fram...
Quantum transport modelling of silicon nanobeams using heterogeneous computing scheme
Harb, M.; Michaud-Rioux, V.; Zhu, Y.; Liu, L.; Zhang, L.; Guo, H.
2016-03-01
We report the development of a powerful method for quantum transport calculations of nanowire/nanobeam structures with large cross sectional area. Our approach to quantum transport is based on Green's functions and tight-binding potentials. A linear algebraic formulation allows us to harness the massively parallel nature of Graphics Processing Units (GPUs) and our implementation is based on a heterogeneous parallel computing scheme with traditional processors and GPUs working together. Using our software tool, the electronic and quantum transport properties of silicon nanobeams with a realistic cross sectional area of ˜22.7 nm2 and a length of ˜81.5 nm—comprising 105 000 Si atoms and 24 000 passivating H atoms in the scattering region—are investigated. The method also allows us to perform significant averaging over impurity configurations—all possible configurations were considered in the case of single impurities. Finally, the effect of the position and number of vacancy defects on the transport properties was considered. It is found that the configurations with the vacancies lying closer to the local density of states (LDOS) maxima have lower transmission functions than the configurations with the vacancies located at LDOS minima or far away from LDOS maxima, suggesting both a qualitative method to tune or estimate optimal impurity configurations as well as a physical picture that accounts for device variability. Finally, we provide performance benchmarks for structures as large as ˜42.5 nm2 cross section and ˜81.5 nm length.
A Knowledge-Based Representation Scheme for Environmental Science Models
Keller, Richard M.; Dungan, Jennifer L.; Lum, Henry, Jr. (Technical Monitor)
1994-01-01
One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.
A numerical scheme for modelling reacting flow with detailed chemistry and transport.
Knio, Omar M. (The Johns Hopkins University, Baltimore, MD); Najm, Habib N.; Paul, Phillip H. (Eksigent Technologies LLC, Livermore, CA)
2003-09-01
An efficient projection scheme is developed for the simulation of reacting flow with detailed kinetics and transport. The scheme is based on a zero-Mach-number formulation of the compressible conservation equations for an ideal gas mixture. It is a modified version of the stiff operator-split scheme developed by Knio, Najm & Wyckoff (1999, J. Comput. Phys. 154, 428). Similar to its predecessor, the new scheme relies on Strang splitting of the discrete evolution equations, where diffusion is integrated in two half steps that are symmetrically distributed around a single stiff step for the reaction source terms. The diffusive half-step is integrated using an explicit single-step, multistage, Runge-Kutta-Chebyshev (RKC) method, which replaces the explicit, multi-step, fractional sub-step approach used in the previous formulation. This modification maintains the overall second-order convergence properties of the scheme and enhances the efficiency of the computations by taking advantage of the extended real-stability region of the RKC scheme. Two additional efficiency-enhancements are also explored, based on an extrapolation procedure for the transport coefficients and on the use of approximate Jacobian data evaluated on a coarse mesh. By including these enhancement schemes, performance tests using 2D computations with a detailed C{sub 1}C{sub 2} methane-air mechanism and a detailed mixture-averaged transport model indicate that speedup factors of about 15 are achieved over the previous split-stiff scheme.
Neural Network Based Multi-level Fuzzy Evaluation Model for Mechanical Kinematic Scheme
BO Ruifeng; LI Ruiqin
2006-01-01
To implement a quantificational evaluation for mechanical kinematic scheme more effectively, a multi-level and multi-objective evaluation model is presented using neural network and fuzzy theory. Firstly, the structure of evaluation model is constructed according to evaluation indicator system. Then evaluation samples are generated and provided to train this model. Thus it can reflect the relation between attributive value and evaluation result, as well as the weight of evaluation indicator. Once evaluation indicators of each candidate are fuzzily quantified and fed into the trained network model, the corresponding evaluation result is outputted and the best alternative can be selected. Under this model, expert knowledge can be effectively acquired and expressed, and the quantificational evaluation can be implemented for kinematic scheme with multi-level evaluation indicator system. Several key problems on this model are discussed and an illustration has demonstrated that this model is feasible and can be regarded as a new idea for solving kinematic scheme evaluation.
A hybrid convection scheme for use in non-hydrostatic numerical weather prediction models
Volker Kuell
2008-12-01
Full Text Available The correct representation of convection in numerical weather prediction (NWP models is essential for quantitative precipitation forecasts. Due to its small horizontal scale convection usually has to be parameterized, e.g. by mass flux convection schemes. Classical schemes originally developed for use in coarse grid NWP models assume zero net convective mass flux, because the whole circulation of a convective cell is confined to the local grid column and all convective mass fluxes cancel out. However, in contemporary NWP models with grid sizes of a few kilometers this assumption becomes questionable, because here convection is partially resolved on the grid. To overcome this conceptual problem we propose a hybrid mass flux convection scheme (HYMACS in which only the convective updrafts and downdrafts are parameterized. The generation of the larger scale environmental subsidence, which may cover several grid columns, is transferred to the grid scale equations. This means that the convection scheme now has to generate a net convective mass flux exerting a direct dynamical forcing to the grid scale model via pressure gradient forces. The hybrid convection scheme implemented into the COSMO model of Deutscher Wetterdienst (DWD is tested in an idealized simulation of a sea breeze circulation initiating convection in a realistic manner. The results are compared with analogous simulations with the classical Tiedtke and Kain-Fritsch convection schemes.
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
Post-processing scheme for modelling the lithospheric magnetic field
V. Lesur
2013-03-01
Full Text Available We investigated how the noise in satellite magnetic data affects magnetic lithospheric field models derived from these data in the special case where this noise is correlated along satellite orbit tracks. For this we describe the satellite data noise as a perturbation magnetic field scaled independently for each orbit, where the scaling factor is a random variable, normally distributed with zero mean. Under this assumption, we have been able to derive a model for errors in lithospheric models generated by the correlated satellite data noise. Unless the perturbation field is known, estimating the noise in the lithospheric field model is a non-linear inverse problem. We therefore proposed an iterative post-processing technique to estimate both the lithospheric field model and its associated noise model. The technique has been successfully applied to derive a lithospheric field model from CHAMP satellite data up to spherical harmonic degree 120. The model is in agreement with other existing models. The technique can, in principle, be extended to all sorts of potential field data with "along-track" correlated errors.
A Positivity-Preserving Numerical Scheme for Nonlinear Option Pricing Models
Shengwu Zhou
2012-01-01
Full Text Available A positivity-preserving numerical method for nonlinear Black-Scholes models is developed in this paper. The numerical method is based on a nonstandard approximation of the second partial derivative. The scheme is not only unconditionally stable and positive, but also allows us to solve the discrete equation explicitly. Monotone properties are studied in order to avoid unwanted oscillations of the numerical solution. The numerical results for European put option and European butterfly spread are compared to the standard finite difference scheme. It turns out that the proposed scheme is efficient and reliable.
Silva, Filipe da, E-mail: tanatos@ipfn.ist.utl.pt [Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa (Portugal); Pinto, Martin Campos, E-mail: campos@ann.jussieu.fr [CNRS, UMR 7598, Laboratoire Jacques-Louis Lions, F-75005, Paris (France); Sorbonne Universités, UPMC Univ Paris 06, UMR 7598, Laboratoire Jacques-Louis Lions, F-75005, Paris (France); Després, Bruno, E-mail: despres@ann.jussieu.fr [Sorbonne Universités, UPMC Univ Paris 06, UMR 7598, Laboratoire Jacques-Louis Lions, F-75005, Paris (France); CNRS, UMR 7598, Laboratoire Jacques-Louis Lions, F-75005, Paris (France); Heuraux, Stéphane, E-mail: stephane.heuraux@univ-lorraine.fr [Institut Jean Lamour, UMR 7198, CNRS – University Lorraine, Vandoeuvre (France)
2015-08-15
This work analyzes the stability of the Yee scheme for non-stationary Maxwell's equations coupled with a linear current model with density fluctuations. We show that the usual procedure may yield unstable scheme for physical situations that correspond to strongly magnetized plasmas in X-mode (TE) polarization. We propose to use first order clustered discretization of the vectorial product that gives back a stable coupling. We validate the schemes on some test cases representative of direct numerical simulations of X-mode in a magnetic fusion plasma including turbulence.
This work analyzes the stability of the Yee scheme for non-stationary Maxwell's equations coupled with a linear current model with density fluctuations. We show that the usual procedure may yield unstable scheme for physical situations that correspond to strongly magnetized plasmas in X-mode (TE) polarization. We propose to use first order clustered discretization of the vectorial product that gives back a stable coupling. We validate the schemes on some test cases representative of direct numerical simulations of X-mode in a magnetic fusion plasma including turbulence
Wood adhesion cell segmentation scheme based on GVF-Snake model
Zhao, Lei; Ma, Yan
2010-08-01
In order to extract the characteristic parameters of the wood cells accurately, this paper presents an efficient scheme for wood cell segmentation. This scheme is mainly based on GVF-Snake model and the method of image thinning. Firstly, computing the Category Roundness of every connectivity domain is done in order to get the degree of adhesion. Secondly, image thinning helps to get the skeleton of the cell. Finally, according to the location coordinates of skeleton and contour, it can determine the location of segmentation. Experimental results demonstrate the scheme for precise extraction with limited human intervention; it can also determine the correct edge of segmentation. Comparatively speaking, the inaccuracy is rather limited.
In this paper a new finite element model is constructed combining an r- refinement scheme with the CCAU method. The new formulation gives better approximation for boundary and internal layers compared to the standard CCAU, without increasing computer codes. (author)
Evaluation of nourishment schemes based on long-term morphological modeling
Grunnet, Nicholas; Kristensen, Sten Esbjørn; Drønen, Nils;
2012-01-01
A recently developed long-term morphological modeling concept is applied to evaluate the impact of nourishment schemes. The concept combines detailed two-dimensional morphological models and simple one-line models for the coastline evolution and is particularly well suited for long-term simulation...
Chek, Mohd Zaki Awang; Ahmad, Abu Bakar; Ridzwan, Ahmad Nur Azam Ahmad; Jelas, Imran Md.; Jamal, Nur Faezah; Ismail, Isma Liana; Zulkifli, Faiz; Noor, Syamsul Ikram Mohd
2012-09-01
The main objective of this study is to forecast the future claims amount of Invalidity Pension Scheme (IPS). All data were derived from SOCSO annual reports from year 1972 - 2010. These claims consist of all claims amount from 7 benefits offered by SOCSO such as Invalidity Pension, Invalidity Grant, Survivors Pension, Constant Attendance Allowance, Rehabilitation, Funeral and Education. Prediction of future claims of Invalidity Pension Scheme will be made using Univariate Forecasting Models to predict the future claims among workforce in Malaysia.
Evaluating agri-environmental schemes using a spatially explicit agent-based modelling approach
Schouten, M.A.H.; Polman, N.B.P.; Westerhof, E.J.G.M.; Opdam, P.F.M.
2012-01-01
Networks of nature reserves are being proposed as a solution when the degree of fragmentation is considered to endanger the long-term persistence of species diversity. Agri-environmental schemes are supposed to make a positive contribution to these networks. The spatially explicit agent-based model presented in this chapter combines spatial dynamics in land ownership, land use and the importance of agri-environmental schemes in conserving biodiversity by capturing the heterogeneity of individ...
Narski Jacek; Negulescu Claudia; Maldarella Dario; Degond Pierre; Deluzet Fabrice; Parisot Martin
2011-01-01
International audience In this paper a strategy is investigated for the spatial coupling of an asymptotic preserving scheme with the asymptotic limit model, associated to a singularly perturbed, highly anisotropic, ellip-tic problem. This coupling strategy appears to be very advantageous as compared with the numerical discretization of the initial singular perturbation model or the purely asymptotic preserving scheme introduced in previous works [3, 5]. The model problem addressed in this ...
Engineering Adaptive Model-Driven User Interfaces
Akiki, Pierre A.; Bandara, Arosha K.; Yu, Yijun
2016-01-01
Software applications that are very large-scale, can encompass hundreds of complex user interfaces (UIs). Such applications are commonly sold as feature-bloated off-the-shelf products to be used by people with variable needs in the required features and layout preferences. Although many UI adaptation approaches were proposed, several gaps and limitations including: extensibility and integration in legacy systems, still need to be addressed in the state-of-the-art adaptive UI development syste...
A Lattice-Based Identity-Based Proxy Blind Signature Scheme in the Standard Model
Lili Zhang
2014-01-01
Full Text Available A proxy blind signature scheme is a special form of blind signature which allowed a designated person called proxy signer to sign on behalf of original signers without knowing the content of the message. It combines the advantages of proxy signature and blind signature. Up to date, most proxy blind signature schemes rely on hard number theory problems, discrete logarithm, and bilinear pairings. Unfortunately, the above underlying number theory problems will be solvable in the postquantum era. Lattice-based cryptography is enjoying great interest these days, due to implementation simplicity and provable security reductions. Moreover, lattice-based cryptography is believed to be hard even for quantum computers. In this paper, we present a new identity-based proxy blind signature scheme from lattices without random oracles. The new scheme is proven to be strongly unforgeable under the standard hardness assumption of the short integer solution problem (SIS and the inhomogeneous small integer solution problem (ISIS. Furthermore, the secret key size and the signature length of our scheme are invariant and much shorter than those of the previous lattice-based proxy blind signature schemes. To the best of our knowledge, our construction is the first short lattice-based identity-based proxy blind signature scheme in the standard model.
Evaluation of radiation scheme performance within chemistry climate models
Forster, P. M.; Mayer, B.; et, al.
2011-01-01
This paper evaluates global mean radiatively important properties of chemistry climate models (CCMs). We evaluate stratospheric temperatures and their 1980Ã¢Â�Â�2000 trends, January clear sky irradiances, heating rates, and greenhouse gas radiative forcings from an offline comparison of CCM radiation codes with lineÃ¢Â�Â�byÃ¢Â�Â�line models, and CCMsÃ¢Â�Â� representation of the solar cycle. CCM global mean temperatures and their change can give an indication of errors in radiative trans...
A novel interacting multiple model based network intrusion detection scheme
Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry
2006-04-01
In today's information age, information and network security are of primary importance to any organization. Network intrusion is a serious threat to security of computers and data networks. In internet protocol (IP) based network, intrusions originate in different kinds of packets/messages contained in the open system interconnection (OSI) layer 3 or higher layers. Network intrusion detection and prevention systems observe the layer 3 packets (or layer 4 to 7 messages) to screen for intrusions and security threats. Signature based methods use a pre-existing database that document intrusion patterns as perceived in the layer 3 to 7 protocol traffics and match the incoming traffic for potential intrusion attacks. Alternately, network traffic data can be modeled and any huge anomaly from the established traffic pattern can be detected as network intrusion. The latter method, also known as anomaly based detection is gaining popularity for its versatility in learning new patterns and discovering new attacks. It is apparent that for a reliable performance, an accurate model of the network data needs to be established. In this paper, we illustrate using collected data that network traffic is seldom stationary. We propose the use of multiple models to accurately represent the traffic data. The improvement in reliability of the proposed model is verified by measuring the detection and false alarm rates on several datasets.
Gradient-based adaptation of continuous dynamic model structures
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.
ADAPTIVE MODEL REFINEMENT FOR THE IONOSPHERE AND THERMOSPHERE
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...
Evaluation of Parameterization Schemes in the WRF Model for Estimation of Mixing Height
R. Shrivastava
2014-01-01
Full Text Available This paper deals with the evaluation of parameterization schemes in the WRF model for estimation of mixing height. Numerical experiments were performed using various combinations of parameterization schemes and the results were compared with the mixing height estimated using the radiosonde observations taken by the India Meteorological Department (IMD at Mangalore site for selected days of the warm and cold season in the years 2004–2007. The results indicate that there is a large variation in the mixing heights estimated by the model using various combinations of parameterization schemes. It was seen that the physics option consisting of Mellor Yamada Janjic (Eta as the PBL scheme, Monin Obukhov Janjic (Eta as the surface layer scheme, and Noah land surface model performs reasonably well in reproducing the observed mixing height at this site for both the seasons as compared to the other combinations tested. This study also showed that the choice of the land surface model can have a significant impact on the simulation of mixing height by a prognostic model.
An Adaptive Code for Radial Stellar Model Pulsations
Buchler, J. Robert; Kolláth, Zoltán; Marom, Ariel
1997-09-01
We describe an implicit 1-D adaptive mesh hydrodynamics code that is specially tailored for radial stellar pulsations. In the Lagrangian limit the code reduces to the well tested Fraley scheme. The code has the useful feature that unwanted, long lasting transients can be avoided by smoothly switching on the adaptive mesh features starting from the Lagrangean code. Thus, a limit cycle pulsation that can readily be computed with the relaxation method of Stellingwerf will converge in a few tens of pulsation cycles when put into the adaptive mesh code. The code has been checked with two shock problems, viz. Noh and Sedov, for which analytical solutions are known, and it has been found to be both accurate and stable. Superior results were obtained through the solution of the total energy (gravitational + kinetic + internal) equation rather than that of the internal energy only.
(t, n Secret Sharing Scheme Based on Cylinder Model in Wireless Sensor Networks
Haiping Huang
2012-07-01
Full Text Available Since the existence of characteristics of heterogeneity, limited energy, complexity and so forth, it turns into a research hot spot on the security mechanism of wireless sensor networks (WSN, especially the problems on the key management. On regard of the deficiency of extant secret sharing schemes, we develop a (t, n threshold secret sharing scheme which is based on the cylinder model, including the procedures of master-key reconfiguration and sub-key updating. This scheme enables several nodes to be responsible for the security of key together, and by the mean time, we introduce a monitoring mechanism to improve the capability of anti-capturing. With the security theoretical analysis and the comparison with the performance on B-PCGR, GKD simulation experiment, it reveals that our scheme satisfies the security requirement of key management in wireless sensor networks, and can effectively reduce the cost on communication and computation.
A New Framework to Compare Mass-Flux Schemes Within the AROME Numerical Weather Prediction Model
Riette, Sébastien; Lac, Christine
2016-08-01
In the Application of Research to Operations at Mesoscale (AROME) numerical weather forecast model used in operations at Météo-France, five mass-flux schemes are available to parametrize shallow convection at kilometre resolution. All but one are based on the eddy-diffusivity-mass-flux approach, and differ in entrainment/detrainment, the updraft vertical velocity equation and the closure assumption. The fifth is based on a more classical mass-flux approach. Screen-level scores obtained with these schemes show few discrepancies and are not sufficient to highlight behaviour differences. Here, we describe and use a new experimental framework, able to compare and discriminate among different schemes. For a year, daily forecast experiments were conducted over small domains centred on the five French metropolitan radio-sounding locations. Cloud base, planetary boundary-layer height and normalized vertical profiles of specific humidity, potential temperature, wind speed and cloud condensate were compared with observations, and with each other. The framework allowed the behaviour of the different schemes in and above the boundary layer to be characterized. In particular, the impact of the entrainment/detrainment formulation, closure assumption and cloud scheme were clearly visible. Differences mainly concerned the transport intensity thus allowing schemes to be separated into two groups, with stronger or weaker updrafts. In the AROME model (with all interactions and the possible existence of compensating errors), evaluation diagnostics gave the advantage to the first group.
Gong, Wei; Duan, Qingyun; Li, Jianduo; Wang, Chen; Di, Zhenhua; Ye, Aizhong; Miao, Chiyuan; Dai, Yongjiu
2016-03-01
Parameter specification is an important source of uncertainty in large, complex geophysical models. These models generally have multiple model outputs that require multiobjective optimization algorithms. Although such algorithms have long been available, they usually require a large number of model runs and are therefore computationally expensive for large, complex dynamic models. In this paper, a multiobjective adaptive surrogate modeling-based optimization (MO-ASMO) algorithm is introduced that aims to reduce computational cost while maintaining optimization effectiveness. Geophysical dynamic models usually have a prior parameterization scheme derived from the physical processes involved, and our goal is to improve all of the objectives by parameter calibration. In this study, we developed a method for directing the search processes toward the region that can improve all of the objectives simultaneously. We tested the MO-ASMO algorithm against NSGA-II and SUMO with 13 test functions and a land surface model - the Common Land Model (CoLM). The results demonstrated the effectiveness and efficiency of MO-ASMO.
A Simplified Scheme of the Generalized Layered Radiative Transfer Model
无
2007-01-01
In this paper, firstly, a simplified version (SGRTM) of the generalized layered radiative transfer model (GRTM) within the canopy, developed by us, is presented. It reduces the information requirement of inputted sky diffuse radiation, as well as of canopy morphology, and in turn saves computer resources. Results from the SGRTM agree perfectly with those of the GRTM. Secondly, by applying the linear superposition principle of the optics and by using the basic solutions of the GRTM for radiative transfer within the canopy under the condition of assumed zero soil reflectance, two sets of explicit analytical solutions of radiative transfer within the canopy with any soil reflectance magnitude are derived: one for incident diffuse, and the other for direct beam radiation. The explicit analytical solutions need two sets of basic solutions of canopy reflectance and transmittance under zero soil reflectance, run by the model for both diffuse and direct beam radiation. One set of basic solutions is the canopy reflectance αf (written as α1 for direct beam radiation) and transmittance βf (written as β1 for direction beam radiation) with zero soil reflectance for the downward radiation from above the canopy (i.e. sky), and the other set is the canopy reflectance (αb) and transmittanceβb for the upward radiation from below the canopy (i.e., ground). Under the condition of the same plant architecture in the vertical layers, and the same leaf adaxial and abaxial optical properties in the canopies for the uniform diffuse radiation, the explicit solutions need only one set of basic solutions, because under this condition the two basic solutions are equal, i.e., αf = αb and βf = βb. Using the explicit analytical solutions, the fractions of any kind of incident solar radiation reflected from (defined as surface albedo, or canopy reflectance),transmitted through (defined as canopy transmittance), and absorbed by (defined as canopy absorptance)the canopy and other properties
Barriopedro, D. [Universidade de Lisboa, CGUL-IDL, Faculdade de Ciencias, Ed. C-8, Lisbon (Portugal); Universidad de Extremadura, Departamento de Fisica, Facultad de Ciencias, Badajoz (Spain); Garcia-Herrera, R. [Universidad Complutense de Madrid, Departamento de Fisica de la Tierra II, Facultad de C.C. Fisicas, Madrid (Spain); Trigo, R.M. [Universidade de Lisboa, CGUL-IDL, Faculdade de Ciencias, Ed. C-8, Lisbon (Portugal)
2010-12-15
This paper aims to provide a new blocking definition with applicability to observations and model simulations. An updated review of previous blocking detection indices is provided and some of their implications and caveats discussed. A novel blocking index is proposed by reconciling two traditional approaches based on anomaly and absolute flows. Blocks are considered from a complementary perspective as a signature in the anomalous height field capable of reversing the meridional jet-based height gradient in the total flow. The method succeeds in identifying 2-D persistent anomalies associated to a weather regime in the total flow with blockage of the westerlies. The new index accounts for the duration, intensity, extension, propagation, and spatial structure of a blocking event. In spite of its increased complexity, the detection efficiency of the method is improved without hampering the computational time. Furthermore, some misleading identification problems and artificial assumptions resulting from previous single blocking indices are avoided with the new approach. The characteristics of blocking for 40 years of reanalysis (1950-1989) over the Northern Hemisphere are described from the perspective of the new definition and compared to those resulting from two standard blocking indices and different critical thresholds. As compared to single approaches, the novel index shows a better agreement with reported proxies of blocking activity, namely climatological regions of simultaneous wave amplification and maximum band-pass filtered height standard deviation. An additional asset of the method is its adaptability to different data sets. As critical thresholds are specific of the data set employed, the method is useful for observations and model simulations of different resolutions, temporal lengths and time variant basic states, optimizing its value as a tool for model validation. Special attention has been paid on the devise of an objective scheme easily applicable
Central upwind scheme for a compressible two-phase flow model.
Munshoor Ahmed
Full Text Available In this article, a compressible two-phase reduced five-equation flow model is numerically investigated. The model is non-conservative and the governing equations consist of two equations describing the conservation of mass, one for overall momentum and one for total energy. The fifth equation is the energy equation for one of the two phases and it includes source term on the right-hand side which represents the energy exchange between two fluids in the form of mechanical and thermodynamical work. For the numerical approximation of the model a high resolution central upwind scheme is implemented. This is a non-oscillatory upwind biased finite volume scheme which does not require a Riemann solver at each time step. Few numerical case studies of two-phase flows are presented. For validation and comparison, the same model is also solved by using kinetic flux-vector splitting (KFVS and staggered central schemes. It was found that central upwind scheme produces comparable results to the KFVS scheme.
Adaptive Finite Element Approximations for Kohn-Sham Models
Chen, Huajie; Dai, Xiaoying; Gong, Xingao; He, Lianhua; Zhou, Aihui
2013-01-01
The Kohn-Sham equation is a powerful, widely used approach for computation of ground state electronic energies and densities in chemistry, materials science, biology, and nanosciences. In this paper, we study the adaptive finite element approximations for the Kohn-Sham model. Based on the residual type a posteriori error estimators proposed in this paper, we introduce an adaptive finite element algorithm with a quite general marking strategy and prove the convergence of the adaptive finite el...
Bachrach, Yoram; Graepel, Thore; Minka, Tom; Guiver, John
2012-01-01
We propose a new probabilistic graphical model that jointly models the difficulties of questions, the abilities of participants and the correct answers to questions in aptitude testing and crowdsourcing settings. We devise an active learning/adaptive testing scheme based on a greedy minimization of expected model entropy, which allows a more efficient resource allocation by dynamically choosing the next question to be asked based on the previous responses. We present experimental results that...
THE SCHEME FOR THE DATABASE BUILDING AND UPDATING OF 1:10 000 DIGITAL ELEVATION MODELS
无
2000-01-01
The National Bureau of Surveying and Mapping of China has planned to speed up the development of spatial data infrastructure (SDI) in the coming few years. This SDI consists of four types of digital products, i. e., digital orthophotos, digital elevation models,digital line graphs and digital raster graphs. For the DEM,a scheme for the database building and updating of 1:10 000 digital elevation models has been proposed and some experimental tests have also been accomplished. This paper describes the theoretical (and/or technical)background and reports some of the experimental results to support the scheme. Various aspects of the scheme such as accuracy, data sources, data sampling, spatial resolution, terrain modeling, data organization, etc are discussed.
Confirmation of the performance of the SIT with FD should be based on thermal-hydraulic analysis of LBLOCA and an adequate and physical model simulating the SIT/FD should be used in the LBLOCA calculation. To develop such a physical model on SIT/FD, simulation of the major phenomena including flow distribution of by standpipe and FD should be justified by full scale experiment and/or plant preoperational testing. Author's previous study indicated that an approximation of SIT/FD phenomena could be obtained by a typical system transient code, MARS-KS, and using 'accumulator' component model, however, that additional improvement on modeling scheme of the FD and standpipe flow paths was needed for a reasonable prediction. One problem was a depressurizing behavior after switchover to low flow injection phase. Also a potential to release of nitrogen gas from the SIT to the downstream pipe and then reactor core through flow paths of FD and standpipe has been concerned. The intrusion of noncondensible gas may have an effect on LBLOCA thermal response. Therefore, a more reliable model on SIT/FD has been requested to get a more accurate prediction and a confidence of the evaluation of LBLOCA. The present paper is to discuss an improvement of modeling scheme from the previous study. Compared to the existing modeling, effect of the present modeling scheme on LBLOCA cladding thermal response is discussed. The present study discussed the modeling scheme of SIT with FD for a realistic simulation of LBLOCA of APR1400. Currently, the SIT blowdown test can be best simulated by the modeling scheme using 'pipe' component with dynamic area reduction. The LBLOCA analysis adopting the modeling scheme showed the PCT increase of 23K when compared to the case of 'accumulator' component model, which was due to the flow rate decrease at transition phase low flow injection and intrusion of nitrogen gas to the core. Accordingly, the effect of SIT/FD modeling
A Log-Based 3D Model Retrieval Relevance Feedback Scheme Using Biased SVMs
Zhiyong Zhang
2010-12-01
Full Text Available Retrieval relevance feedback is an iterative search technique to bridge the semantic gap between the high level user intention and low level data representation. This technique interactively determines a user's desired output or query concept by asking the user whether certain proposed 3D models are relevant or not. In the past, most research efforts in 3D model retrieval field have focused on designing algorithms for traditional relevance feedback. Given a 3D model retrieval system, it can collect and store users’ relevance feedback information in a history log, 3D model retrieval system can take advantage of the log data of users’ feedback to enhance its retrieval performance. In this paper, we propose a unified 3D model retrieval relevance feedback framework that integrates the log data into the traditional relevance feedback schemes to learn effectively the correlation between low-level 3D model features and high-level concepts. In this 3D model retrieval relevance feedback scheme, we use a learning technique for relevance feedback, named biased support vector machine based relevance feedback. Experimental results show that this log-based scheme can achieves higher search accuracy than traditional query refinement schemes.
A Secret 3D Model Sharing Scheme with Reversible Data Hiding Based on Space Subdivision
Tsai, Yuan-Yu
2016-03-01
Secret sharing is a highly relevant research field, and its application to 2D images has been thoroughly studied. However, secret sharing schemes have not kept pace with the advances of 3D models. With the rapid development of 3D multimedia techniques, extending the application of secret sharing schemes to 3D models has become necessary. In this study, an innovative secret 3D model sharing scheme for point geometries based on space subdivision is proposed. Each point in the secret point geometry is first encoded into a series of integer values that fall within [0, p - 1], where p is a predefined prime number. The share values are derived by substituting the specified integer values for all coefficients of the sharing polynomial. The surface reconstruction and the sampling concepts are then integrated to derive a cover model with sufficient model complexity for each participant. Finally, each participant has a separate 3D stego model with embedded share values. Experimental results show that the proposed technique supports reversible data hiding and the share values have higher levels of privacy and improved robustness. This technique is simple and has proven to be a feasible secret 3D model sharing scheme.
Modeling Family Adaptation to Fragile X Syndrome
Raspa, Melissa; Bailey, Donald, Jr.; Bann, Carla; Bishop, Ellen
2014-01-01
Using data from a survey of 1,099 families who have a child with Fragile X syndrome, we examined adaptation across 7 dimensions of family life: parenting knowledge, social support, social life, financial impact, well-being, quality of life, and overall impact. Results illustrate that although families report a high quality of life, they struggle…
An Importance Sampling Scheme on Dual Factor Graphs. II. Models with Strong Couplings
Molkaraie, Mehdi
2014-01-01
We consider the problem of estimating the partition function of the two-dimensional ferromagnetic Ising model in an external magnetic field. The estimation is done via importance sampling in the dual of the Forney factor graph representing the model. We present importance sampling schemes that can efficiently compute an estimate of the partition function in a wide range of model parameters. Emphasis is on models in which a subset of the coupling parameters is strong.
Labour supply modelling in Italy when minimum income scheme is an option
Narazani, Edlira; Shima, Isilda
2008-01-01
In this paper we analyze the effects of Minimum Guaranteed Income (MGI) schemes on labour supply of Italian married couples by applying a behavioural micro-simulation tax-benefit model. The Tax-Benefit Model applied is the static micro-simulation model of EUROMOD. A household labour supply model is simulated with different tax rules where MGI is an option. The simulated tax regimes are Negative Income Tax (NIT), Workfare Tax (WF) and Universal Basic Income (UBI). These exercises of behavioura...
Wang, K.-Y.; Pyle, J. A.; Sanderson, M. G.; Bridgeman, C.
1999-10-01
A convective atmospheric boundary layer (ABL) scheme for the transport of trace gases in the lower troposphere has been implemented from the Community Climate Model, Version 2 [Hack et al., 1993] into a tropospheric chemistry transport model [Wang, 1998]. The atmospheric boundary layer scheme includes the calculation of atmospheric radiative transfer, surface energy balance, and land surface temperature and has a specified annual variation of sea surface temperature. The calculated diurnal variation of the height of the boundary layer is similar to the results of Troen and Mahrt [1986] and is in a good agreement with Holtslag and Boville [1993]. The modeled height of the boundary layer shows a seasonal shift between land and sea in the Northern Hemisphere. In summer (June-July-August), the height of the boundary layer is deeper over land (850-2250 m) and shallower over sea (50-850 m); while in winter (December-January-February), it is shallower over land (50-850 m) and deeper over sea (850-2850 m). The coupled ABL-chemical transport model is verified against measurements of radon 222 and methane. Comparison of the coupled model with a non-ABL model indicates significant differences between these model simulations and a better agreement between the coupled model and measurements. There is a significant effect on the trace gas distribution when the ABL model is compared with the non-ABL schemes. For example, the ABL scheme shows more O3 transported from the middle troposphere down to the surface, while more CO is pumped up from the surface into the middle troposphere. The seasonal cycle of modeled CH4 is significantly improved with the inclusion of the new ABL scheme, especially in regions which are not remote from methane sources.
A gradient stable scheme for a phase field model for the moving contact line problem
Gao, Min
2012-02-01
In this paper, an efficient numerical scheme is designed for a phase field model for the moving contact line problem, which consists of a coupled system of the Cahn-Hilliard and Navier-Stokes equations with the generalized Navier boundary condition [1,2,4]. The nonlinear version of the scheme is semi-implicit in time and is based on a convex splitting of the Cahn-Hilliard free energy (including the boundary energy) together with a projection method for the Navier-Stokes equations. We show, under certain conditions, the scheme has the total energy decaying property and is unconditionally stable. The linearized scheme is easy to implement and introduces only mild CFL time constraint. Numerical tests are carried out to verify the accuracy and stability of the scheme. The behavior of the solution near the contact line is examined. It is verified that, when the interface intersects with the boundary, the consistent splitting scheme [21,22] for the Navier Stokes equations has the better accuracy for pressure. © 2011 Elsevier Inc.
The application of flux-form semi-Lagrangian transport scheme in a spectral atmosphere model
Wang, Xiaocong; Liu, Yimin; Wu, Guoxiong; Lin, Shian-Jiann; Bao, Qing
2013-01-01
A flux-form semi-Lagrangian transport scheme (FFSL) was implemented in a spectral atmospheric GCM developed and used at IAP/LASG. Idealized numerical experiments show that the scheme is good at shape preserving with less dissipation and dispersion, in comparison with other conventional schemes. Importantly, FFSL can automatically maintain the positive definition of the transported tracers, which was an underlying problem in the previous spectral composite method (SCM). To comprehensively investigate the impact of FFSL on GCM results, we conducted sensitive experiments. Three main improvements resulted: first, rainfall simulation in both distribution and intensity was notably improved, which led to an improvement in precipitation frequency. Second, the dry bias in the lower troposphere was significantly reduced compared with SCM simulations. Third, according to the Taylor diagram, the FFSL scheme yields simulations that are superior to those using the SCM: a higher correlation between model output and observation data was achieved with the FFSL scheme, especially for humidity in lower troposphere. However, the moist bias in the middle and upper troposphere was more pronounced with the FFSL scheme. This bias led to an over-simulation of precipitable water in comparison with reanalysis data. Possible explanations, as well as solutions, are discussed herein.
Improved simulation of precipitation in the tropics using a modified BMJ scheme in WRF model
R. Fonseca
2015-05-01
Full Text Available The successful modelling of the observed precipitation, a very important variable for a wide range of climate applications, continues to be one of the major challenges that climate scientists face today. When the Weather Research and Forecasting (WRF model is used to dynamically downscale the Climate Forecast System Reanalysis (CFSR over the Indo-Pacific region, with analysis (grid-point nudging, it is found that the cumulus scheme used, Betts–Miller–Janjić (BMJ, produces excessive rainfall suggesting that it has to be modified for this region. Experimentation has shown that the cumulus precipitation is not very sensitive to changes in the cloud efficiency but varies greatly in response to modifications of the temperature and humidity reference profiles. A new version of the scheme, denominated "modified BMJ" scheme, where the humidity reference profile is more moist, was developed and in tropical belt simulations it was found to give a better estimate of the observed precipitation, as given by the Tropical Rainfall Measuring Mission (TRMM 3B42 dataset, than the default BMJ scheme for the whole tropics and both monsoon seasons. In fact, in some regions the model even outperforms CFSR. The advantage of modifying the BMJ scheme to produce better rainfall estimates lies in the final dynamical consistency of the rainfall with other dynamical and thermodynamical variables of the atmosphere.
The hybrid model, and adaptive educational hypermedia frameworks
Zakaria, Mohamed Ramzy
2004-01-01
The amount of information on the web is characterised by being enormous, as is the number of users with different goals and interests. User models have been utilized by adaptive hypermedia systems generally and adaptive educational hypermedia systems (AEHS) particularly to personalize the amount of information they have with respect to each individual's knowledge, background and goals. As a result of the research described herein, a user model called the Hybrid Model has been developed. Th...
ADAPTIVE GUIDANCE MODEL BASED SIMILARITY FOR SOFTWARE PROCESS DEVELOPMENT
Hamid Khemissa; Mohamed Ahmed-nacer; Abdelkader Belkhir
2014-01-01
This paper describes a modeling approach SAGM (Similarity for Adaptive Guidance Model) that provides adaptive and recursive guidance for software process development. This approach, in accordance to developer needs, allows specific tailored guidance regarding the profile of developers. A profile is partially or completely defined from a model of developers, through their roles, their qualifications, and through the relationships between the context of the current activity and the ...
Discrete Model Reference Adaptive Control System for Automatic Profiling Machine
Peng Song; Guo-kai Xu; Xiu-chun Zhao
2012-01-01
Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules...
The ADAPT design model: towards instructional control of transfer
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 that transfer of training can be attributed to procedure overlap between the original training task and the transfer task, as well as to analogy between new problem solving situations and acquired co...
Litta, A. J.; Chakrapani, B.; Mohankumar, K.
2007-07-01
Heavy rainfall events become significant in human affairs when they are combined with hydrological elements. The problem of forecasting heavy precipitation is especially difficult since it involves making a quantitative precipitation forecast, a problem well recognized as challenging. Chennai (13.04°N and 80.17°E) faced incessant and heavy rain about 27 cm in 24 hours up to 8.30 a.m on 27th October 2005 completely threw life out of gear. This torrential rain caused by deep depression which lay 150km east of Chennai city in Bay of Bengal intensified and moved west north-west direction and crossed north Tamil Nadu and south Andhra Pradesh coast on 28th morning. In the present study, we investigate the predictability of the MM5 mesoscale model using different cumulus parameterization schemes for the heavy rainfall event over Chennai. MM5 Version 3.7 (PSU/NCAR) is run with two-way triply nested grids using Lambert Conformal Coordinates (LCC) with a nest ratio of 3:1 and 23 vertical layers. Grid sizes of 45, 15 and 5 km are used for domains 1, 2 and 3 respectively. The cumulus parameterization schemes used in this study are Anthes-Kuo scheme (AK), the Betts-Miller scheme (BM), the Grell scheme (GR) and the Kain-Fritsch scheme (KF). The present study shows that the prediction of heavy rainfall is sensitive to cumulus parameterization schemes. In the time series of rainfall, Grell scheme is in good agreement with observation. The ideal combination of the nesting domains, horizontal resolution and cloud parameterization is able to simulate the heavy rainfall event both qualitatively and quantitatively.
White, Jeremy T.; Langevin, Christian D.; Hughes, Joseph D.
2010-01-01
Calibration of highly‐parameterized numerical models typically requires explicit Tikhonovtype regularization to stabilize the inversion process. This regularization can take the form of a preferred parameter values scheme or preferred relations between parameters, such as the preferred equality scheme. The resulting parameter distributions calibrate the model to a user‐defined acceptable level of model‐to‐measurement misfit, and also minimize regularization penalties on the total objective function. To evaluate the potential impact of these two regularization schemes on model predictive ability, a dataset generated from a synthetic model was used to calibrate a highly-parameterized variable‐density SEAWAT model. The key prediction is the length of time a synthetic pumping well will produce potable water. A bi‐objective Pareto analysis was used to explicitly characterize the relation between two competing objective function components: measurement error and regularization error. Results of the Pareto analysis indicate that both types of regularization schemes affect the predictive ability of the calibrated model.
Shun-Yuan Wang
2015-03-01
Full Text Available This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC in the speed sensorless vector control of an induction motor (IM drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.
Adapted Lethality: What We Can Learn from Guinea Pig-Adapted Ebola Virus Infection Model
S. V. Cheresiz
2016-01-01
Full Text Available Establishment of small animal models of Ebola virus (EBOV infection is important both for the study of genetic determinants involved in the complex pathology of EBOV disease and for the preliminary screening of antivirals, production of therapeutic heterologic immunoglobulins, and experimental vaccine development. Since the wild-type EBOV is avirulent in rodents, the adaptation series of passages in these animals are required for the virulence/lethality to emerge in these models. Here, we provide an overview of our several adaptation series in guinea pigs, which resulted in the establishment of guinea pig-adapted EBOV (GPA-EBOV variants different in their characteristics, while uniformly lethal for the infected animals, and compare the virologic, genetic, pathomorphologic, and immunologic findings with those obtained in the adaptation experiments of the other research groups.
ADAPTIVE CONFIGURATION META-MODEL OF A GUIDANCE PROCESS
Hamid Khemissa
2016-06-01
Full Text Available The current technology tend leads us to recognize the need for adaptive guidance process for all process of software development. The new needs generated by the mobility context for software development led these guidance processes to be adapted. In order to improve the performance of the deployed software development, it is useful to manage the configuration of its evolving aspects. This paper deals with the configuration management of guidance process or its ability to be adapted to specific development contexts. The proposed adaptive configuration Meta-model is worked out on the basis of a Y description for adaptive guidance process. This description focuses on three dimensions defined by the material/software platform, the adaptation form and provided guidance service. Each dimension considers several factors to develop a coherent configuration strategy and provide automatically the appropriate guidance process to a current development context.
Recursive Gaussian Process Regression Model for Adaptive Quality Monitoring in Batch Processes
Le Zhou
2015-01-01
Full Text Available In chemical batch processes with slow responses and a long duration, it is time-consuming and expensive to obtain sufficient normal data for statistical analysis. With the persistent accumulation of the newly evolving data, the modelling becomes adequate gradually and the subsequent batches will change slightly owing to the slow time-varying behavior. To efficiently make use of the small amount of initial data and the newly evolving data sets, an adaptive monitoring scheme based on the recursive Gaussian process (RGP model is designed in this paper. Based on the initial data, a Gaussian process model and the corresponding SPE statistic are constructed at first. When the new batches of data are included, a strategy based on the RGP model is used to choose the proper data for model updating. The performance of the proposed method is finally demonstrated by a penicillin fermentation batch process and the result indicates that the proposed monitoring scheme is effective for adaptive modelling and online monitoring.
Bishop, R. F.; Li, P. H. Y.
2011-04-01
An approximation hierarchy, called the lattice-path-based subsystem (LPSUBm) approximation scheme, is described for the coupled-cluster method (CCM). It is applicable to systems defined on a regular spatial lattice. We then apply it to two well-studied prototypical (spin-(1)/(2) Heisenberg antiferromagnetic) spin-lattice models, namely, the XXZ and the XY models on the square lattice in two dimensions. Results are obtained in each case for the ground-state energy, the ground-state sublattice magnetization, and the quantum critical point. They are all in good agreement with those from such alternative methods as spin-wave theory, series expansions, quantum Monte Carlo methods, and the CCM using the alternative lattice-animal-based subsystem (LSUBm) and the distance-based subsystem (DSUBm) schemes. Each of the three CCM schemes (LSUBm, DSUBm, and LPSUBm) for use with systems defined on a regular spatial lattice is shown to have its own advantages in particular applications.
An approximation hierarchy, called the lattice-path-based subsystem (LPSUBm) approximation scheme, is described for the coupled-cluster method (CCM). It is applicable to systems defined on a regular spatial lattice. We then apply it to two well-studied prototypical (spin-(1/2) Heisenberg antiferromagnetic) spin-lattice models, namely, the XXZ and the XY models on the square lattice in two dimensions. Results are obtained in each case for the ground-state energy, the ground-state sublattice magnetization, and the quantum critical point. They are all in good agreement with those from such alternative methods as spin-wave theory, series expansions, quantum Monte Carlo methods, and the CCM using the alternative lattice-animal-based subsystem (LSUBm) and the distance-based subsystem (DSUBm) schemes. Each of the three CCM schemes (LSUBm, DSUBm, and LPSUBm) for use with systems defined on a regular spatial lattice is shown to have its own advantages in particular applications.
Exploring the adaptive voter model dynamics with a mathematical triple jump
Progress in theoretical physics is often made by the investigation of toy models, the model organisms of physics, which provide benchmarks for new methodologies. For complex systems, one such model is the adaptive voter model. Despite its simplicity, the model is hard to analyze. Only inaccurate results are obtained from well-established approximation schemes that work well on closely-related models. We use the adaptive voter model to illustrate a new approach that combines (a) the use of a heterogeneous moment expansion to approximate the network model by an infinite system of ordinary differential equations (ODEs), (b) generating functions to map the ODE system to a two-dimensional partial differential equation (PDE), and (c) solution of this partial differential equation by the tools of PDE-theory. Beyond the adaptive voter models, the proposed approach establishes a connection between network science and the theory of PDEs and is widely applicable to the dynamics of networks with discrete node-states. (paper)
Context aware adaptive security service model
Tunia, Marcin A.
2015-09-01
Present systems and devices are usually protected against different threats concerning digital data processing. The protection mechanisms consume resources, which are either highly limited or intensively utilized by many entities. The optimization of these resources usage is advantageous. The resources that are saved performing optimization may be utilized by other mechanisms or may be sufficient for longer time. It is usually assumed that protection has to provide specific quality and attack resistance. By interpreting context situation of business services - users and services themselves, it is possible to adapt security services parameters to countermeasure threats associated with current situation. This approach leads to optimization of used resources and maintains sufficient security level. This paper presents architecture of adaptive security service, which is context-aware and exploits quality of context data issue.
Primdahl, Jørgen; Vesterager, Jens Peter; Finn, John A.;
2010-01-01
Agri-Environment Schemes (AES) to maintain or promote environmentally-friendly farming practices were implemented on about 25% of all agricultural land in the EU by 2002. This article analyses and discusses the actual and potential use of impact models in supporting the design, implementation and...... depended on whether scheme objectives were related to natural resources, biodiversity or landscape. A higher proportion of schemes dealing with natural resources (primarily water) were based on quantitative impact models, compared to whole-farm schemes and broad, horizontal schemes. We conclude that...
Ensuring confidence in predictions: A scheme to assess the scientific validity of in silico models.
Hewitt, Mark; Ellison, Claire M; Cronin, Mark T D; Pastor, Manuel; Steger-Hartmann, Thomas; Munoz-Muriendas, Jordi; Pognan, Francois; Madden, Judith C
2015-06-23
The use of in silico tools within the drug development process to predict a wide range of properties including absorption, distribution, metabolism, elimination and toxicity has become increasingly important due to changes in legislation and both ethical and economic drivers to reduce animal testing. Whilst in silico tools have been used for decades there remains reluctance to accept predictions based on these methods particularly in regulatory settings. This apprehension arises in part due to lack of confidence in the reliability, robustness and applicability of the models. To address this issue we propose a scheme for the verification of in silico models that enables end users and modellers to assess the scientific validity of models in accordance with the principles of good computer modelling practice. We report here the implementation of the scheme within the Innovative Medicines Initiative project "eTOX" (electronic toxicity) and its application to the in silico models developed within the frame of this project. PMID:25794480
Performance of the Goddard multiscale modeling framework with Goddard ice microphysical schemes
Chern, Jiun-Dar; Tao, Wei-Kuo; Lang, Stephen E.; Matsui, Toshihisa; Li, J.-L. F.; Mohr, Karen I.; Skofronick-Jackson, Gail M.; Peters-Lidard, Christa D.
2016-03-01
The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.
Ireyuwa E. Igbinosa
2015-10-01
Full Text Available Due to the ever growing need for spectrum, the cognitive radio (CR has been proposed to improve the radio spectrum utilization. In this scenario, the secondary users (SU are permitted to share spectrum with the licensed primary users (SU with a strict condition that they do not cause harmful interference to the cognitive network. In this work, we have proposed an interference model for cognitive radio network that utilizes power or contention control interference management schemes. We derived the probability density function (PDF with the power control scheme, where the power of transmission of the CR transmitter is guided by the power control law and also with contention control scheme that has a fixed transmission power for all CR transmitter controlled by a contention control protocol. This protocol makes a decision on which CR transmitter can transmit at any point in time. In this work, we have shown that power and contention control schemes are good candidates for interference modeling in cognitive radio system. The impact of the unknown location of the primary receiver on the resulting interference generated by the CR transmitters was investigated and the results shows that the challenges of the hidden primary receivers lead to higher CR-primary interference in respect to higher mean and variance. Finally, the presented results show power control and the contention control scheme are good candidates in reducing the interference generated by the cognitive radio network.
Wang, Zhi-Hua; Bou-Zeid, Elie; Smith, James A.
2011-02-01
In the urban environment, surface temperatures and conductive heat fluxes through solid media (roofs, walls, roads and vegetated surfaces) are of paramount importance for the comfort of residents (indoors) and for microclimatic conditions (outdoors). Fully discrete numerical methods are currently used to model heat transfer in these solid media in parametrisations of built surfaces commonly used in weather prediction models. These discrete methods usually use finite difference schemes in both space and time. We propose a spatially-analytical scheme where the temperature field and conductive heat fluxes are solved analytically in space. Spurious numerical oscillations due to temperature discontinuities at the sublayer interfaces can be avoided since the method does not involve spatial discretisation. The proposed method is compared to the fully discrete method for a test case of one-dimensional heat conduction with sinusoidal forcing. Subsequently, the analytical scheme is incorporated into the offline version of the current urban canopy model (UCM) used in the Weather Research and Forecasting model and the new UCM is validated against field measurements using a wireless sensor network and other supporting measurements over a suburban area under real-world conditions. Results of the comparison clearly show the advantage of the proposed scheme over the fully discrete model, particularly for more complicated cases.
A Dynamic Cordon Pricing Scheme combining a Macroscopic and an Agent-based traffic Models
Zheng, Nan; Waraich, Rashid A.; Axhausen, Kay W.; Geroliminis, Nikolaos
2012-01-01
Pricing is considered an effective management policy to reduce traffic congestion in transportation networks. In this paper we combine a macroscopic model of traffic congestion in urban networks with an agent-based simulator to study congestion pricing schemes. The macroscopic model, which has been tested with real data in previous studies, represents an accurate and robust approach to model the dynamics of congestion. The agent-based simulator can reproduce the complexity of travel behavior ...
FAN Zhisong; SHANG Zhenqi; ZHANG Shanwu; HU Ruijin; LIU Hailong
2015-01-01
Based on the theoretical spectral model of inertial internal wave breaking (fine structure) proposed previ-ously, in which the effects of the horizontal Coriolis frequency component f-tilde on a potential isopycnal are taken into account, a parameterization scheme of vertical mixing in the stably stratified interior be-low the surface mixed layer in the ocean general circulation model (OGCM) is put forward preliminarily in this paper. Besides turbulence, the impact of sub-mesoscale oceanic processes (including inertial internal wave breaking product) on oceanic interior mixing is emphasized. We suggest that adding the inertial inter-nal wave breaking mixing scheme (F-scheme for short) put forward in this paper to the turbulence mixing scheme of Canuto et al. (T-scheme for short) in the OGCM, except the region from 15°S to 15°N. The numeri-cal results of F-scheme by using WOA09 data and an OGCM (LICOM, LASG/IAP climate system ocean model) over the global ocean are given. A notable improvement in the simulation of salinity and temperature over the global ocean is attained by using T-scheme adding F-scheme, especially in the mid- and high-latitude regions in the simulation of the intermediate water and deep water. We conjecture that the inertial internal wave breaking mixing and inertial forcing of wind might be one of important mechanisms maintaining the ventilation process. The modeling strength of the Atlantic meridional overturning circulation (AMOC) by using T-scheme adding F-scheme may be more reasonable than that by using T-scheme alone, though the physical processes need to be further studied, and the overflow parameterization needs to be incorporated. A shortcoming in F-scheme is that in this paper the error of simulated salinity and temperature by using T-scheme adding F-scheme is larger than that by using T-scheme alone in the subsurface layer.
RELAP5 two-phase fluid model and numerical scheme for economic LWR system simulation
The RELAP5 two-phase fluid model and the associated numerical scheme are summarized. The experience accrued in development of a fast running light water reactor system transient analysis code is reviewed and example of the code application are given
Recent models for adaptive personality differences: a review
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 ...
Adaptive Guidance based on Context Profile for Software Process Modeling
Hamid Khemissa
2012-07-01
Full Text Available This paper aims to define an adaptive guidance for software process modeling. The proposed guidance approach is based on development’s profile context (actor’s role in the process, actor’s qualification and related activities in progress. We introduce new guidance concepts through adaptive guidance meta-model (AGM allowing specific assistance interventions (corrective, constructive and automatic guidance. We illustrate our guidance approach using SPEM formalism extended with these new guidance concepts.
TRAFFIC FLOW MODEL BASED ON CELLULAR AUTOMATION WITH ADAPTIVE DECELERATION
Shinkarev, A. A.
2016-01-01
This paper describes continuation of the authors’ work in the field of traffic flow mathematical models based on the cellular automata theory. The refactored representation of the multifactorial traffic flow model based on the cellular automata theory is used for a representation of an adaptive deceleration step implementation. The adaptive deceleration step in the case of a leader deceleration allows slowing down smoothly but not instantly. Concepts of the number of time steps without confli...
Post-Revolution Egypt: The Roy Adaptation Model in Community.
Buckner, Britton S; Buckner, Ellen B
2015-10-01
The 2011 Arab Spring swept across the Middle East creating profound instability in Egypt, a country already challenged with poverty and internal pressures. To respond to this crisis, Catholic Relief Services led a community-based program called "Egypt Works" that included community improvement projects and psychosocial support. Following implementation, program outcomes were analyzed using the middle-range theory of adaptation to situational life events, based on the Roy adaptation model. The comprehensive, community-based approach facilitated adaptation, serving as a model for applying theory in post-crisis environments. PMID:26396214
Turing pattern dynamics and adaptive discretization for a super-diffusive Lotka-Volterra model.
Bendahmane, Mostafa; Ruiz-Baier, Ricardo; Tian, Canrong
2016-05-01
In this paper we analyze the effects of introducing the fractional-in-space operator into a Lotka-Volterra competitive model describing population super-diffusion. First, we study how cross super-diffusion influences the formation of spatial patterns: a linear stability analysis is carried out, showing that cross super-diffusion triggers Turing instabilities, whereas classical (self) super-diffusion does not. In addition we perform a weakly nonlinear analysis yielding a system of amplitude equations, whose study shows the stability of Turing steady states. A second goal of this contribution is to propose a fully adaptive multiresolution finite volume method that employs shifted Grünwald gradient approximations, and which is tailored for a larger class of systems involving fractional diffusion operators. The scheme is aimed at efficient dynamic mesh adaptation and substantial savings in computational burden. A numerical simulation of the model was performed near the instability boundaries, confirming the behavior predicted by our analysis. PMID:26219250
Zhou, Yanlai; Guo, Shenglian; Xu, Chong-Yu; Liu, Dedi; Chen, Lu; Wang, Dong
2015-12-01
Climate change, rapid economic development and increase of the human population are considered as the major triggers of increasing challenges for water resources management. This proposed integrated optimal allocation model (IOAM) for complex adaptive system of water resources management is applied in Dongjiang River basin located in the Guangdong Province of China. The IOAM is calibrated and validated under baseline period 2010 year and future period 2011-2030 year, respectively. The simulation results indicate that the proposed model can make a trade-off between demand and supply for sustainable development of society, economy, ecology and environment and achieve adaptive management of water resources allocation. The optimal scheme derived by multi-objective evaluation is recommended for decision-makers in order to maximize the comprehensive benefits of water resources management.
Li, Wenkai; Guo, Weidong; Xue, Yongkang; Fu, Congbin; Qiu, Bo
2015-12-01
Land surface processes play an important role in the East Asian Summer Monsoon (EASM) system. Parameterization schemes of land surface processes may cause uncertainties in regional climate model (RCM) studies for the EASM. In this paper, we investigate the sensitivity of a RCM to land surface parameterization (LSP) schemes for long-term simulation of the EASM. The Weather Research and Forecasting (WRF) Model coupled with four different LSP schemes (Noah-MP, CLM4, Pleim-Xiu and SSiB), hereafter referred to as Sim-Noah, Sim-CLM, Sim-PX and Sim-SSiB respectively, have been applied for 22-summer EASM simulations. The 22-summer averaged spatial distributions and strengths of downscaled large-scale circulation, 2-m temperature and precipitation are comprehensively compared with ERA-Interim reanalysis and dense station observations in China. Results show that the downscaling ability of RCM for the EASM is sensitive to LSP schemes. Furthermore, this study confirms that RCM does add more information to the EASM compared to reanalysis that imposes the lateral boundary conditions (LBC) because it provides 2-m temperature and precipitation that are with higher resolution and more realistic compared to LBC. For 2-m temperature and monsoon precipitation, Sim-PX and Sim-SSiB simulations are more consistent with observation than simulations of Sim-Noah and Sim-CLM. To further explore the physical and dynamic mechanisms behind the RCM sensitivity to LSP schemes, differences in the surface energy budget between simulations of Ens-Noah-CLM (ensemble mean averaging Sim-Noah and Sim-CLM) and Ens-PX-SSiB (ensemble mean averaging Sim-PX and Sim-SSiB) are investigated and their subsequent impacts on the atmospheric circulation are analyzed. It is found that the intensity of simulated sensible heat flux over Asian continent in Ens-Noah-CLM is stronger than that in Ens-PX-SSiB, which induces a higher tropospheric temperature in Ens-Noah-CLM than in Ens-PX-SSiB over land. The adaptive
Adaptive multiresolution methods
Schneider Kai
2011-12-01
Full Text Available These lecture notes present adaptive multiresolution schemes for evolutionary PDEs in Cartesian geometries. The discretization schemes are based either on finite volume or finite difference schemes. The concept of multiresolution analyses, including Harten’s approach for point and cell averages, is described in some detail. Then the sparse point representation method is discussed. Different strategies for adaptive time-stepping, like local scale dependent time stepping and time step control, are presented. Numerous numerical examples in one, two and three space dimensions validate the adaptive schemes and illustrate the accuracy and the gain in computational efficiency in terms of CPU time and memory requirements. Another aspect, modeling of turbulent flows using multiresolution decompositions, the so-called Coherent Vortex Simulation approach is also described and examples are given for computations of three-dimensional weakly compressible mixing layers. Most of the material concerning applications to PDEs is assembled and adapted from previous publications [27, 31, 32, 34, 67, 69].
Adaptive Modeling of the International Space Station Electrical Power System
Thomas, Justin Ray
2007-01-01
Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.
A hybrid scheme for absorbing edge reflections in numerical modeling of wave propagation
Liu, Yang
2010-03-01
We propose an efficient scheme to absorb reflections from the model boundaries in numerical solutions of wave equations. This scheme divides the computational domain into boundary, transition, and inner areas. The wavefields within the inner and boundary areas are computed by the wave equation and the one-way wave equation, respectively. The wavefields within the transition area are determined by a weighted combination of the wavefields computed by the wave equation and the one-way wave equation to obtain a smooth variation from the inner area to the boundary via the transition zone. The results from our finite-difference numerical modeling tests of the 2D acoustic wave equation show that the absorption enforced by this scheme gradually increases with increasing width of the transition area. We obtain equally good performance using pseudospectral and finite-element modeling with the same scheme. Our numerical experiments demonstrate that use of 10 grid points for absorbing edge reflections attains nearly perfect absorption. © 2010 Society of Exploration Geophysicists.
Multi-model ensemble schemes for predicting northeast monsoon rainfall over peninsular India
Nachiketa Acharya; S C Kar; Makarand A Kulkarni; U C Mohanty; L N Sahoo
2011-10-01
The northeast (NE) monsoon season (October, November and December) is the major period of rainfall activity over south peninsular India. This study is mainly focused on the prediction of northeast monsoon rainfall using lead-1 products (forecasts for the season issued in beginning of September) of seven general circulation models (GCMs). An examination of the performances of these GCMs during hindcast runs (1982–2008) indicates that these models are not able to simulate the observed interannual variability of rainfall. Inaccurate response of the models to sea surface temperatures may be one of the probable reasons for the poor performance of these models to predict seasonal mean rainfall anomalies over the study domain. An attempt has been made to improve the accuracy of predicted rainfall using three different multi-model ensemble (MME) schemes, viz., simple arithmetic mean of models (EM), principal component regression (PCR) and singular value decomposition based multiple linear regressions (SVD). It is found out that among these three schemes, SVD based MME has more skill than other MME schemes as well as member models.
Adaptive Finite Element Methods for Continuum Damage Modeling
Min, J. B.; Tworzydlo, W. W.; Xiques, K. E.
1995-01-01
The paper presents an application of adaptive finite element methods to the modeling of low-cycle continuum damage and life prediction of high-temperature components. The major objective is to provide automated and accurate modeling of damaged zones through adaptive mesh refinement and adaptive time-stepping methods. The damage modeling methodology is implemented in an usual way by embedding damage evolution in the transient nonlinear solution of elasto-viscoplastic deformation problems. This nonlinear boundary-value problem is discretized by adaptive finite element methods. The automated h-adaptive mesh refinements are driven by error indicators, based on selected principal variables in the problem (stresses, non-elastic strains, damage, etc.). In the time domain, adaptive time-stepping is used, combined with a predictor-corrector time marching algorithm. The time selection is controlled by required time accuracy. In order to take into account strong temperature dependency of material parameters, the nonlinear structural solution a coupled with thermal analyses (one-way coupling). Several test examples illustrate the importance and benefits of adaptive mesh refinements in accurate prediction of damage levels and failure time.
Adapting Dynamic Mathematical Models to a Pilot Anaerobic Digestion Reactor
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.
Modeling Students' Memory for Application in Adaptive Educational Systems
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…
Narski Jacek
2011-11-01
Full Text Available In this paper a strategy is investigated for the spatial coupling of an asymptotic preserving scheme with the asymptotic limit model, associated to a singularly perturbed, highly anisotropic, elliptic problem. This coupling strategy appears to be very advantageous as compared with the numerical discretization of the initial singular perturbation model or the purely asymptotic preserving scheme introduced in previous works [3, 5]. The model problem addressed in this paper is well suited for the simulation of a plasma in the presence of a magnetic field, whose intensity may vary considerably within the simulation domain.
The Adaptation Fund: a model for the future?
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.
Market Model and Optimal Pricing Scheme of Big Data and Internet of Things (IoT)
Niyato, Dusit; Alsheikh, Mohammad Abu; Wang, Ping; Kim, Dong In; Han, Zhu
2016-01-01
Big data has been emerging as a new approach in utilizing large datasets to optimize complex system operations. Big data is fueled with Internet-of-Things (IoT) services that generate immense sensory data from numerous sensors and devices. While most current research focus of big data is on machine learning and resource management design, the economic modeling and analysis have been largely overlooked. This paper thus investigates the big data market model and optimal pricing scheme. We first...
Numerical scheme for multilayer shallow-water model in the low-Froude number regime
Parisot, Martin; Vila, Jean-Paul
2014-01-01
The aim of this note is to present a multi-dimensional numerical scheme approximating the solutions of the multilayer shallow water model in the low Froude number regime. The proposed strategy is based on a regularized model where the advection velocity is modified with a pressure gradient in both mass and momentum equations. The numerical solution satisfy the dissipation of energy, which act for mathematical entropy, and the main physical properties required for simulations within oceanic fl...
Scheme of Constructing CGE Model of China's Direct Grain Subsidy Policy
Wang, Can
2011-01-01
This paper introduces the model of China's direct grain subsidy policy, adopts computable general equilibrium (CGE) theory, and advances the scheme of constructing the model of China's direct grain subsidy policy. On the basis of some assumptions, such as conforming to the complete competition of market, inexistence of move of capital and labor forces among countries, unchanged exchange rate and incomplete substitution, and the main body of behavior comprising representative households, produ...
Adaptive Networks Theory, Models and Applications
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.
Impact of stochastic parametrisation schemes on the climate of the Community Earth System Model
Christensen, Hannah; Berner, Judith; Coleman, Dani; Palmer, Tim
2015-04-01
Stochastic parametrisations have been used for more than a decade in atmospheric models. They provide a way to represent model uncertainty through representing the variability of unresolved sub-grid processes, and have been shown to have a beneficial effect on the spread and mean state for medium- and extended-range forecasts (Buizza et al. 1999, Palmer et al. 2009). There is also increasing evidence that stochastic parametrisation of unresolved processes could be beneficial for the climate of an atmospheric model. There is evidence that including stochastic physics can reduce model biases through noise-induced drift (nonlinear rectification) (Berner et al. 2008), and that including stochastic physics enables the climate simulator to explore other flow regimes (Christensen et al. 2014; Dawson and Palmer 2014). It is also possible that, through representing the variability of unresolved sub-grid processes, stochastic parametrisation schemes could improve the internal variability of a model's climate. We present results showing the impact of including the Stochastic Kinetic Energy Backscatter Scheme (SKEBS) and the Stochastically Perturbed Parametrisation Tendencies scheme (SPPT) in coupled runs of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4) with historical forcing. The impact of the schemes in the coupled runs is compared to the impact in a similar set of AMIP runs. Both schemes have a beneficial impact on the model climate. The SKEBS scheme significantly reduces mean biases in several fields whereas SPPT results in a significant improvement in the variability of the modeled climate. In particular, SPPT results in a significant improvement to the representation of the El Nino-Southern Oscillation in CAM4, improving the power spectrum, as well as both the inter- and intra-annual variability of tropical pacific sea surface temperatures. References: Berner, J., Doblas-Reyes, F. J., Palmer, T. N., Shutts, G. J
Research on the Adaptive Object-Model Architecture Style
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.
A parameterization of convective dust storms for models with mass-flux convection schemes
Pantillon, Florian; Knippertz, Peter; Marsham, John; Birch, Cathryn
2015-04-01
Cold pool outflows, generated by downdrafts from moist convection, can generate strong winds and therefore uplift of mineral dust. These so-called ``haboob'' convective dust storms occur over all major dust source areas worldwide and contribute substantially to emissions in northern Africa, the world's largest source. Most large-scale models lack convective dust storms, because they do not resolve moist convection, relying instead on convection schemes. We suggest a parameterization of convective dust storms to account for their contribution in such large-scale models. The parameterization is based on a simple conceptual model, in which the downdraft mass flux from the convection scheme spreads out radially in a cylindrical cold pool. The parameterization is tested with a set of Unified Model runs for June and July 2006 over West Africa. It is calibrated with a convection-permitting run, and applied to a convection-parameterized run. The parameterization successfully produces the extensive area of dust-generating winds from cold pool outflows over the southern Sahara. However, this area extends farther to the east and dust generating winds occur earlier in the day than in the convection-permitting run. These biases are due to biases in the convection scheme. It is found that the location and timing of dust-generating winds are weakly sensitive to the parameters of the conceptual model. The results demonstrate that a simple parameterization has the potential to correct a major and long-standing limitation in global dust models.
Adaptive time stepping algorithm for Lagrangian transport models: Theory and idealised test cases
Shah, Syed Hyder Ali Muttaqi; Heemink, Arnold Willem; Gräwe, Ulf; Deleersnijder, Eric
2013-08-01
Random walk simulations have an excellent potential in marine and oceanic modelling. This is essentially due to their relative simplicity and their ability to represent advective transport without being plagued by the deficiencies of the Eulerian methods. The physical and mathematical foundations of random walk modelling of turbulent diffusion have become solid over the years. Random walk models rest on the theory of stochastic differential equations. Unfortunately, the latter and the related numerical aspects have not attracted much attention in the oceanic modelling community. The main goal of this paper is to help bridge the gap by developing an efficient adaptive time stepping algorithm for random walk models. Its performance is examined on two idealised test cases of turbulent dispersion; (i) pycnocline crossing and (ii) non-flat isopycnal diffusion, which are inspired by shallow-sea dynamics and large-scale ocean transport processes, respectively. The numerical results of the adaptive time stepping algorithm are compared with the fixed-time increment Milstein scheme, showing that the adaptive time stepping algorithm for Lagrangian random walk models is more efficient than its fixed step-size counterpart without any loss in accuracy.
Bellouin, N; Mann, G.W.; Woodhouse, M.T.; Johnson, C.; Carslaw, K. S.; Dalvi, M.
2012-01-01
The Hadley Centre Global Environmental Model (HadGEM) includes two aerosol schemes: the Coupled Large-scale Aerosol Simulator for Studies in Climate (CLASSIC), and the new Global Model of Aerosol Processes (GLOMAP-mode). GLOMAP-mode is a modal aerosol microphysics scheme that simulates not only aerosol mass but also aerosol number, represents internally-mixed particles, and includes aerosol microphysical processes such as nucleation. In this study, both schemes provide hindcast simulations of...
High dynamic adaptive mobility network model and performance analysis
LIU Hui; ZHANG Jun
2008-01-01
Since mobile networks are not currently deployed on a large scale, research in this area is mostly by simulation. Among other simulation parameters, the mobility model plays a very important role in determining the protocol performance in MANET. Based on random direction mobility model, a high dynamic adaptive mo-bility network model is proposed in the paper. The algorithms and modeling are mainly studied and explained in detail. The technique keystone is that normal dis-tribution is combined with uniform distribution and inertial feedback control is combined with kinematics, through the adaptive control on nodes speed and pre-diction tracking on nodes routes, an adaptive model is designed, which can be used in simulations to produce realistic and dynamic network scenarios. It is the adaptability that nodes mobile parameters can be adjusted randomly in three-dimensional space. As a whole, colony mobility can show some rules. Such ran-dom movement processes as varied speed and dwells are simulated realistically. Such problems as sharp turns and urgent stops are smoothed well. The model can be adapted to not only common dynamic scenarios, but also high dynamic sce-narios. Finally, the mobility model performance is analyzed and validated based on random dynamic scenarios simulations.
An integrated approach to modeling and adaptive control
HAN Zhi-gang
2006-01-01
In the book (Adaptive Identification,Prediction and Control-Multi Level Recursive Approach), the concept of dynamical linearization of nonlinear systems has been presented.This dynamical linearization is formal only,not a real linearization.From the linearization procedure,we can find a new approach of system identification,which is on-line real-time modeling and real-time feedback control correction.The modeling and real-time feedback control have been integrated in the identification approach,with the parameter adaptation model being abandoned.The structure adaptation of control systems has been achieved,which avoids the complex modeling steps.The objective of this paper is to introduce the approach of integrated modeling and control.
The Distance Field Model and Distance Constrained MAP Adaptation Algorithm
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-
A density-dependent matrix model and its applications in optimizing harvest schemes
Guofan Shao; WANG Fei; DAI Limin; BAI Jianwei; LI Yingshan
2006-01-01
Based on temporal data collected from 36 re-measured plots, transition probabilities of trees from a diameter class to a higher class were analyzed for the broadleaved-Korean pine forest in the Changbai Mountains. It was found that the transition probabilities were related not only to diameter size but also to the total basal area of trees with the diameter class. This paper demonstrates the development of a density-dependent matrix model, DM2, and a series of simulations with it for forest stands with different conditions under different harvest schemes. After validations with independent field data, this model proved a suitable tool for optimization analysis of harvest schemes on computers. The optimum harvest scheme(s) can be determined by referring to stand growth, total timbers harvested, and size diversity changes over time. Three user-friendly interfaces were built with a forest management decision support system FORESTAR(R) for easy operations of DM2 by forest managers. This paper also summarizes the advantages and disadvantages of DM2.
A study of the spreading scheme for viral marketing based on a complex network model
Yang, Jianmei; Yao, Canzhong; Ma, Weicheng; Chen, Guanrong
2010-02-01
Buzzword-based viral marketing, known also as digital word-of-mouth marketing, is a marketing mode attached to some carriers on the Internet, which can rapidly copy marketing information at a low cost. Viral marketing actually uses a pre-existing social network where, however, the scale of the pre-existing network is believed to be so large and so random, so that its theoretical analysis is intractable and unmanageable. There are very few reports in the literature on how to design a spreading scheme for viral marketing on real social networks according to the traditional marketing theory or the relatively new network marketing theory. Complex network theory provides a new model for the study of large-scale complex systems, using the latest developments of graph theory and computing techniques. From this perspective, the present paper extends the complex network theory and modeling into the research of general viral marketing and develops a specific spreading scheme for viral marking and an approach to design the scheme based on a real complex network on the QQ instant messaging system. This approach is shown to be rather universal and can be further extended to the design of various spreading schemes for viral marketing based on different instant messaging systems.
Comprehensive Evaluation Cloud Model for Ship Navigation Adaptability
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...
Model-based design of adaptive embedded systems
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...
Structured and Unstructured Cache Models for SMT Domain Adaptation
Louis, Annie; Webber, Bonnie L.
2014-01-01
We present a French to English translation system for Wikipedia biography articles. We use training data from out-of-domain corpora and adapt the system for biographies. We propose two forms of domain adaptation. The first biases the system towards words likely in biographies and encourages repetition of words across the document. Since biographies in Wikipedia follow a regular structure, our second model exploits this structure as a sequence of topic segments, where each segment discusses a ...
Adaptive Traffic Signalization Model using Neuro-Fuzzy Controllers
Devesh Batra; Pragya Verma
2014-01-01
Current traffic lights are pre-programmed and use daily signal timing schedules, which contribute to traffic congestion and delay. Thus, with the increase in the number of vehicles on road, need for adaptive signal technology arises which has the potential to adjust the timing of red, yellow and green lights in order to accommodate changing traffic patterns and ease traffic congestion. In this paper, we present a model for adaptive traffic signalization, which uses fuzzy neura...
Adaptive model based control for wastewater treatment plants
Niet, de, A.; Vrugt, van de, Noëlle Maria; Korving, Hans; Boucherie, Richard J.; Savic, D.A.; Kapelan, Z.; Butler, D.
2011-01-01
In biological wastewater treatment, nitrogen and phosphorous are removed by activated sludge. The process requires oxygen input via aeration of the activated sludge tank. Aeration is responsible for about 60% of the energy consumption of a treatment plant. Hence optimization of aeration can contribute considerably to the increase of energy-efficiency in wastewater treatment. To this end, we introduce an adaptive model based control strategy for aeration called adaptive WOMBAT. The strategy is...
Grapham: Graphical Models with Adaptive Random Walk Metropolis Algorithms
Vihola, Matti
2008-01-01
Recently developed adaptive Markov chain Monte Carlo (MCMC) methods have been applied successfully to many problems in Bayesian statistics. Grapham is a new open source implementation covering several such methods, with emphasis on graphical models for directed acyclic graphs. The implemented algorithms include the seminal Adaptive Metropolis algorithm adjusting the proposal covariance according to the history of the chain and a Metropolis algorithm adjusting the proposal scale based on the o...
Modeling Power Systems as Complex Adaptive Systems
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.
Adaptive, Nonlinear Model Predictive Control for Accelerator Feedback Control Systems
Variations in systems dynamics and modeling uncertainty(due to unmodeled systems behavior and/or presence of disturbances),have posed significant challenges to the effective luminosity and orbit control in accelerators.Problems of similar nature occur in a wide variety of other applications from chemical processes to power plants to financial systems.Adaptive control has long been pursued as a possible solution,but difficulties with online model identification and robust implementation of the adaptive control algorithms has prevented their widespread application.In general developing and maintaining appropriate models is the key to the success of any deployed control solution.Meanwhile the performance of the control system is contingent on the responsiveness of the control algorithm to the inevitable deviations of the model from the actual system.This project uses neural networks to detect significant changes in system behavior,and develops an optimal model-predictive-based adaptive control algorithm that enables the robust implementation of an effective control strategy that is applicable in a wide range of applications.Simulation studies were conducted to clearly demonstrate the feasibility and benefits of implementing model predictive control technology in accelerator control problems.The requirements for an effective commercial product that can meet the challenge of optimal model-predictive-based adaptive control technology were developed.A prototype for the optimal model-predictive-based adaptive control algorithm was developed for a well-known nonlinear temperature control problem for gas-phase reactors that proved the feasibility of the proposed approach.This research enables a commercial party to leverage the knowledge gained through collaboration with a national laboratory to develop new system identification and optimal model-predictive-based adaptive control software to address current and future challenges in process industries,power systems
STOCHASTIC ADAPTIVE SWITCHING CONTROL BASED ON MULTIPLE MODELS
ZHANGYanxia; GUOLei
2002-01-01
It is well known that the transient behaviors of the traditional adaptive control may be very poor in general,and that the adaptive control designed based in switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances.In this paper,we shall prove that for a typical class of linear systems disturbed by random noises,the multiple model based least-equares(LS)adaptive switching control is statble and convergent and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators.Moreover,the mixed case combining adative models with fixed models is also considered.
Decentralized model reference adaptive control of large flexible structures
Lee, Fu-Ming; Fong, I-Kong; Lin, Yu-Hwan
1988-01-01
A decentralized model reference adaptive control (DMRAC) method is developed for large flexible structures (LFS). The development follows that of a centralized model reference adaptive control for LFS that have been shown to be feasible. The proposed method is illustrated using a simply supported beam with collocated actuators and sensors. Results show that the DMRAC can achieve either output regulation or output tracking with adequate convergence, provided the reference model inputs and their time derivatives are integrable, bounded, and approach zero as t approaches infinity.
B. C. Backeberg
2009-02-01
Full Text Available A 4th order advection scheme is applied in a nested eddy-resolving Hybrid Coordinate Ocean Model (HYCOM of the greater Agulhas Current system for the purpose of testing advanced numerics as a means for improving the model simulation for eventual operational implementation. Model validation techniques comparing sea surface height variations, sea level skewness and variogram analyses to satellite altimetry measurements quantify that generally the 4th order advection scheme improves the realism of the model simulation. The most striking improvement over the standard 2nd order momentum advection scheme, is that the Southern Agulhas Current is simulated as a well-defined meandering current, rather than a train of successive eddies. A better vertical structure and stronger poleward transports in the Agulhas Current core contribute toward a better southwestward penetration of the current, and its temperature field, implying a stronger Indo-Atlantic inter-ocean exchange. It is found that the transport, and hence this exchange, is sensitive to the occurrences of mesoscale features originating upstream in the Mozambique Channel and Southern East Madagascar Current, and that the improved HYCOM simulation is well suited for further studies of these inter-actions.
B. C. Backeberg
2009-06-01
Full Text Available A 4th order advection scheme is applied in a nested eddy-resolving Hybrid Coordinate Ocean Model (HYCOM of the greater Agulhas Current system for the purpose of testing advanced numerics as a means for improving the model simulation for eventual operational implementation. Model validation techniques comparing sea surface height variations, sea level skewness and variogram analyses to satellite altimetry measurements quantify that generally the 4th order advection scheme improves the realism of the model simulation. The most striking improvement over the standard 2nd order momentum advection scheme, is that the southern Agulhas Current is simulated as a well-defined meandering current, rather than a train of successive eddies. A better vertical structure and stronger poleward transports in the Agulhas Current core contribute toward a better southwestward penetration of the current, and its temperature field, implying a stronger Indo-Atlantic inter-ocean exchange. It is found that the transport, and hence this exchange, is sensitive to the occurrences of mesoscale features originating upstream in the Mozambique Channel and southern East Madagascar Current, and that the improved HYCOM simulation is well suited for further studies of these inter-actions.
Backeberg, B. C.; Bertino, L.; Johannessen, J. A.
2009-06-01
A 4th order advection scheme is applied in a nested eddy-resolving Hybrid Coordinate Ocean Model (HYCOM) of the greater Agulhas Current system for the purpose of testing advanced numerics as a means for improving the model simulation for eventual operational implementation. Model validation techniques comparing sea surface height variations, sea level skewness and variogram analyses to satellite altimetry measurements quantify that generally the 4th order advection scheme improves the realism of the model simulation. The most striking improvement over the standard 2nd order momentum advection scheme, is that the southern Agulhas Current is simulated as a well-defined meandering current, rather than a train of successive eddies. A better vertical structure and stronger poleward transports in the Agulhas Current core contribute toward a better southwestward penetration of the current, and its temperature field, implying a stronger Indo-Atlantic inter-ocean exchange. It is found that the transport, and hence this exchange, is sensitive to the occurrences of mesoscale features originating upstream in the Mozambique Channel and southern East Madagascar Current, and that the improved HYCOM simulation is well suited for further studies of these inter-actions.
The Nominal Response Model in Computerized Adaptive Testing.
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…
Adaptive Simulated Annealing Based Protein Loop Modeling of Neurotoxins
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.
Revised and Extended Mobile Commerce Technology Adaption Model
Mohammad Othman Nassar; Feras Fares Al Mashagba; Mohammad Ali Habahbeh; Eman Fares Al Mashagba
2014-01-01
This research is designed to cover literature gaps in the intention to adopt mobile commerce in Jordan as development country. In one hand we explored and identified the non-technological factors that affect the intention to adopt mobile commerce. In the other hand we introduced a revised and extended mobile commerce technology adaption model based on the available literature and based on the Technology Acceptance Model (TAM). Our result shows that our proposed model is valid. Our model valid...
A Case Study of the Accounting Models for the Participants in an Emissions Trading Scheme
Marius Deac
2013-10-01
Full Text Available As emissions trading schemes are becoming more popular across the world, accounting has to keep up with these new economic developments. The absence of guidance regarding the accounting for greenhouse gases (GHGs emissions generated by the withdrawal of IFRIC 3- Emission Rights - is the main reason why there is a diversity of accounting practices. This diversity of accounting methods makes the financial statements of companies that are taking part in emissions trading schemes like EU ETS, difficult to compare. The present paper uses a case study that assumes the existence of three entities that have chosen three different accounting methods: the IFRIC 3 cost model, the IFRIC 3 revaluation model and the “off balance sheet” approach. This illustrates how the choice of an accounting method regarding GHGs emissions influences their interim and annual reports through the chances in the companies’ balance sheet and financial results.
Simplified prediction model for lighting energy consumption in office building scheme design
余琼; 周潇儒; 林波荣; 朱颖心
2009-01-01
At the scheme design stage,the potential of daylighting is significant due to the saving for electric lighting use. There are few simple tools for architects to optimize the daylighting design. Therefore,it is useful to develop a design guideline related to the evaluation of lighting energy saving potential and sunlight design strategies. This paper analyzes the impacts of different artificial lighting control methods and design parameters on daylighting. A direct correlation between lighting energy consumption and parameters such as orientations,window to wall ratio (WWR) and perimeter depth is established. A simplified prediction model is proposed to estimate lighting energy consumption with the given perimeter depth,WWR,and window transparency. Validation of the model is carried out compared with detailed lighting simulation software for an office building. After the variation analysis for these parameters,design advises for the daylighting design at scheme design phase are summarized.
Malgarinos, I.; Nikolopoulos, N.; Gavaises, M.
2015-01-01
This study presents the implementation of an interface sharpening scheme on the basis of the Volume of Fluid (VOF) method, as well as its application in a number of theoretical and real cases usually modelled in literature. More specifically, the solution of an additional sharpening equation along with the standard VOF model equations is proposed, offering the advantage of “restraining” interface numerical diffusion, while also keeping a quite smooth induced velocity field around the interfac...
DAI Fushan; YU Rucong; ZHANG Xuehong; YU Yongqiang
2005-01-01
In this study, a statistical cloud scheme is first introduced and coupled with a first-order turbulence scheme with second-order turbulence moments parameterized by the timescale of the turbulence dissipation and the vertical turbulent diffusion coefficient. Then the ability of the scheme to simulate cloud fraction at different relative humidity, vertical temperature profile, and the timescale of the turbulent dissipation is examined by numerical simulation. It is found that the simulated cloud fraction is sensitive to the parameter used in the statistical cloud scheme and the timescale of the turbulent dissipation. Based on the analyses, the introduced statistical cloud scheme is modified. By combining the modified statistical cloud scheme with a boundary layer cumulus scheme, a new statistically-based low-level cloud scheme is proposed and tentatively applied in NCAR (National Center for Atmospheric Research) CCM3 (Community Climate Model version3). It is found that the simulation of low-level cloud fraction is markedly improved and the centers with maximum low-level cloud fractions are well simulated in the cold oceans off the western coasts with the statistically-based low-level cloud scheme applied in CCM3. It suggests that the new statistically-based low-level cloud scheme has a great potential in the general circulation model for improving the low-level cloud parameterization.
Model-based fault diagnosis techniques design schemes, algorithms, and tools
Ding, Steven
2008-01-01
The objective of this book is to introduce basic model-based FDI schemes, advanced analysis and design algorithms, and the needed mathematical and control theory tools at a level for graduate students and researchers as well as for engineers. This is a textbook with extensive examples and references. Most methods are given in the form of an algorithm that enables a direct implementation in a programme. Comparisons among different methods are included when possible.
M.-C. Casabán
2012-01-01
Full Text Available A new discretization strategy is introduced for the numerical solution of partial integrodifferential equations appearing in option pricing jump diffusion models. In order to consider the unknown behaviour of the solution in the unbounded part of the spatial domain, a double discretization is proposed. Stability, consistency, and positivity of the resulting explicit scheme are analyzed. Advantages of the method are illustrated with several examples.
The two-dimensional Godunov scheme and what it means for macroscopic pedestrian flow models
Van Wageningen-Kessels, F.L.M.; Daamen, W.; Hoogendoorn, S. P.
2015-01-01
An efficient simulation method for two-dimensional continuum pedestrian flow models is introduced. It is a two-dimensional and multi-class extension of the Go-dunov scheme for one-dimensional road traffic flow models introduced in the mid 1990’s. The method can be applied to continuum pedestrian flow models in a wide range of applications from the design of train stations and other travel hubs to the study of crowd behaviour and safety at religious and cultural events. The combination of the ...
A new modeling and control scheme for thyristor-controlled series capacitor
Zhizhong MAO
2009-01-01
In order to design an optimal controller for the thyristor controlled series capacitor(TCSC),a novel TCSC control model is developed.In the model,the delay angle of thyristor valves is the input,and the inductor current is chosen as the output.Theoretical analysis and simulation studies show that TCSC is a non-linear system and its parameters vary with the operating point.In consideration of the special characteristics of the TCSC,an improved model algorithmic control (IMAC) scheme is proposed to control TCSC effectively.The good performance can be observed from simulation results when IMAC is applied to a series compensated radial system.
The Importance of Formalizing Computational Models of Face Adaptation Aftereffects
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
A Hamiltonian theory of adaptive resolution simulations of classical and quantum models of nuclei
Kreis, Karsten; Donadio, Davide; Kremer, Kurt; Potestio, Raffaello
2015-03-01
Quantum delocalization of atomic nuclei strongly affects the physical properties of low temperature systems, such as superfluid helium. However, also at room temperature nuclear quantum effects can play an important role for molecules composed by light atoms. An accurate modeling of these effects is possible making use of the Path Integral formulation of Quantum Mechanics. In simulations, this numerically expensive description can be restricted to a small region of space, while modeling the remaining atoms as classical particles. In this way the computational resources required can be significantly reduced. In the present talk we demonstrate the derivation of a Hamiltonian formulation for a bottom-up, theoretically solid coupling between a classical model and a Path Integral description of the same system. The coupling between the two models is established with the so-called Hamiltonian Adaptive Resolution Scheme, resulting in a fully adaptive setup in which molecules can freely diffuse across the classical and the Path Integral regions by smoothly switching their description on the fly. Finally, we show the validation of the approach by means of adaptive resolution simulations of low temperature parahydrogen. Graduate School Materials Science in Mainz, Staudinger Weg 9, 55128 Mainz, Germany.
Cirrus clouds in a global climate model with a statistical cirrus cloud scheme
M. Wang
2009-08-01
Full Text Available A statistical cirrus cloud scheme that accounts for mesoscale temperature perturbations is implemented into a coupled aerosol and atmospheric circulation model to better represent both cloud fraction and subgrid-scale supersaturation in global climate models. This new scheme is able to better simulate the observed probability distribution of relative humidity than the scheme that was implemented in an older version of the model. Heterogeneous ice nuclei (IN are shown to affect not only high level cirrus clouds through their effect on ice crystal number concentration but also low level liquid clouds through the moistening effect of settling and evaporating ice crystals. As a result, the change in the net cloud forcing is not very sensitive to the change in ice crystal concentrations associated with heterogeneous IN because changes in high cirrus clouds and low level liquid clouds tend to cancel. Nevertheless, the change in the net radiative flux at the top of the atmosphere due to changes in IN is still large because of changes in the greenhouse effect of water vapor caused by the changes in ice crystal number concentrations. Changes in the magnitude of the assumed mesoscale temperature perturbations by 25% alter the ice crystal number concentrations and radiative fluxes by an amount that is similar to that from a factor of 10 change in the heterogeneous IN number concentrations.
Adeniji-Fashola, A. A.
1988-07-01
A multiple-realization particle trajectory scheme has been developed and applied to the numerical prediction of confined turbulent fluid-particle flows. The example flows investigated include the vertical pipe upflow experimental data of Tsuji et al. and the experimental data of Leavitt for a coaxial jet flow, comprising a particle-laden central jet and a clean annular jet, into a large recirculation chamber. The results obtained from the numerical scheme agree well with the experimental data, lending confidence to the modeling approach. The multiple-realization particle trajectory turbulent flow modeling scheme is believed to be a more elegant and accurate approach to the extension of single-particle hydrodynamics to dilute multi-particle systems than the more commonly employed two-fluid modeling approach. It is also better able to incorporate additional force items such as lift, virtual mass and Bassett history terms directly into the particle equation of motion as appropriate. This makes it a suitable candidate for particle migration studies and an extension to situations involving liquid particulate phases with possible propulsion applications, such as in spray combustion, follows naturally.
Nonstandard finite difference scheme for SIRS epidemic model with disease-related death
Fitriah, Z.; Suryanto, A.
2016-04-01
It is well known that SIRS epidemic with disease-related death can be described by a system of nonlinear ordinary differential equations (NL ODEs). This model has two equilibrium points where their existence and stability properties are determined by the basic reproduction number [1]. Besides the qualitative properties, it is also often needed to solve the system of NL ODEs. Euler method and 4th order Runge-Kutta (RK4) method are often used to solve the system of NL ODEs. However, both methods may produce inconsistent qualitative properties of the NL ODEs such as converging to wrong equilibrium point, etc. In this paper we apply non-standard finite difference (NSFD) scheme (see [2,3]) to approximate the solution of SIRS epidemic model with disease-related death. It is shown that the discrete system obtained by NSFD scheme is dynamically consistent with the continuous model. By our numerical simulations, we find that the solutions of NSFD scheme are always positive, bounded and convergent to the correct equilibrium point for any step size of integration (h), while those of Euler or RK4 method have the same properties only for relatively small h.
Efficiently adapting graphical models for selectivity estimation
Tzoumas, Kostas; Deshpande, Amol; Jensen, Christian S.
2013-01-01
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 in estimation accuracy. We show how to efficiently construct such a graphical model from the database using only two-way join queries, and we show how to perform selectivity estimation in a highly efficient manner. We integrate our algorithms into the PostgreSQL DBMS. Experimental...... results indicate that estimation errors can be greatly reduced, leading to orders of magnitude more efficient query execution plans in many cases. Optimization time is kept in the range of tens of milliseconds, making this a practical approach for industrial-strength query optimizers....
Toth, Robert; Tiwari, Pallavi; Rosen, Mark; Reed, Galen; Kurhanewicz, John; Kalyanpur, Arjun; Pungavkar, Sona; Madabhushi, Anant
2011-04-01
Segmentation of the prostate boundary on clinical images is useful in a large number of applications including calculation of prostate volume pre- and post-treatment, to detect extra-capsular spread, and for creating patient-specific anatomical models. Manual segmentation of the prostate boundary is, however, time consuming and subject to inter- and intra-reader variability. T2-weighted (T2-w) magnetic resonance (MR) structural imaging (MRI) and MR spectroscopy (MRS) have recently emerged as promising modalities for detection of prostate cancer in vivo. MRS data consists of spectral signals measuring relative metabolic concentrations, and the metavoxels near the prostate have distinct spectral signals from metavoxels outside the prostate. Active Shape Models (ASM's) have become very popular segmentation methods for biomedical imagery. However, ASMs require careful initialization and are extremely sensitive to model initialization. The primary contribution of this paper is a scheme to automatically initialize an ASM for prostate segmentation on endorectal in vivo multi-protocol MRI via automated identification of MR spectra that lie within the prostate. A replicated clustering scheme is employed to distinguish prostatic from extra-prostatic MR spectra in the midgland. The spatial locations of the prostate spectra so identified are used as the initial ROI for a 2D ASM. The midgland initializations are used to define a ROI that is then scaled in 3D to cover the base and apex of the prostate. A multi-feature ASM employing statistical texture features is then used to drive the edge detection instead of just image intensity information alone. Quantitative comparison with another recent ASM initialization method by Cosio showed that our scheme resulted in a superior average segmentation performance on a total of 388 2D MRI sections obtained from 32 3D endorectal in vivo patient studies. Initialization of a 2D ASM via our MRS-based clustering scheme resulted in an average
Hou, Chieh; Ateshian, Gerard A
2016-06-01
Fibrous biological tissues may be modeled using a continuous fiber distribution (CFD) to capture tension-compression nonlinearity, anisotropic fiber distributions, and load-induced anisotropy. The CFD framework requires spherical integration of weighted individual fiber responses, with fibers contributing to the stress response only when they are in tension. The common method for performing this integration employs the discretization of the unit sphere into a polyhedron with nearly uniform triangular faces (finite element integration or FEI scheme). Although FEI has proven to be more accurate and efficient than integration using spherical coordinates, it presents three major drawbacks: First, the number of elements on the unit sphere needed to achieve satisfactory accuracy becomes a significant computational cost in a finite element (FE) analysis. Second, fibers may not be in tension in some regions on the unit sphere, where the integration becomes a waste. Third, if tensed fiber bundles span a small region compared to the area of the elements on the sphere, a significant discretization error arises. This study presents an integration scheme specialized to the CFD framework, which significantly mitigates the first drawback of the FEI scheme, while eliminating the second and third completely. Here, integration is performed only over the regions of the unit sphere where fibers are in tension. Gauss-Kronrod quadrature is used across latitudes and the trapezoidal scheme across longitudes. Over a wide range of strain states, fiber material properties, and fiber angular distributions, results demonstrate that this new scheme always outperforms FEI, sometimes by orders of magnitude in the number of computational steps and relative accuracy of the stress calculation. PMID:26291492
Adaptive Estimation of Heteroscedastic Money Demand Model of Pakistan
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.
Adaptive Model-Based Mammogram Enhancement
Haindl, Michal; Remeš, Václav
Los Alamitos, USA: IEEE Computer Society CPS, 2014 - (Yetongno, K.; Dipanda, A.; Chbeir, R.), s. 65-72 ISBN 978-1-4799-7978-3. [Tenth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2014). Marrakech (MA), 23.11.2014-27.11.2014] R&D Projects: GA ČR(CZ) GA14-10911S Institutional support: RVO:67985556 Keywords : mammography * image enhancement * MRF * textural models Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2014/RO/haindl-0436549.pdf
Adaptive plasticity model for bucket foundations
Ibsen, Lars Bo; Barari, Amin; Larsen, Kim A.
2014-01-01
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......, potential, and failure surfaces are found to be dependent on the embedment ratio (i.e., ratio of skirt length to the diameter) and load path. For the models tested, associated flow is observed to be plausible in the radial planes, whereas nonassociated flow is observed in the planes along the V-axis....
Adaptive Digital Image Watermarking Based on Combination of HVS Models
P. Foris
2009-09-01
Full Text Available In this paper two new blind adaptive digital watermarking methods of color images are presented. The adaptability is based on perceptual watermarking which exploits Human Visual System (HVS models. The first method performs watermark embedding in transform domain of DCT and the second method is based on DWT. Watermark is embedded into transform domain of a chosen color image component in a selected color space. Both methods use a combination of HVS models to select perceptually significant transform coefficients and at the same time to determine the bounds of modification of selected coefficients. The final HVS model consists of three parts. The first part is the HVS model in DCT (DWT domain. The second part is the HVS model based on Region of Interest and finally the third part is the HVS model based on Noise Visibility Function. Watermark has a form of a real number sequence with normal distribution.
Holdaway, Daniel; Kent, James
2015-01-01
The linearity of a selection of common advection schemes is tested and examined with a view to their use in the tangent linear and adjoint versions of an atmospheric general circulation model. The schemes are tested within a simple offline one-dimensional periodic domain as well as using a simplified and complete configuration of the linearised version of NASA's Goddard Earth Observing System version 5 (GEOS-5). All schemes which prevent the development of negative values and preserve the shape of the solution are confirmed to have nonlinear behaviour. The piecewise parabolic method (PPM) with certain flux limiters, including that used by default in GEOS-5, is found to support linear growth near the shocks. This property can cause the rapid development of unrealistically large perturbations within the tangent linear and adjoint models. It is shown that these schemes with flux limiters should not be used within the linearised version of a transport scheme. The results from tests using GEOS-5 show that the current default scheme (a version of PPM) is not suitable for the tangent linear and adjoint model, and that using a linear third-order scheme for the linearised model produces better behaviour. Using the third-order scheme for the linearised model improves the correlations between the linear and non-linear perturbation trajectories for cloud liquid water and cloud liquid ice in GEOS-5.
A multi-level adaptation model of circulation for the western Indian Ocean
Shaji, C.; Bahulayan, N.; Dube, S. K.; Rao, A. D.
1999-12-01
A three-dimensional, fully non-linear semi-diagnostic (adaptation) model is described. This model is used to compute the climatological mean circulation and to understand the role of local, steady forcing of the wind and thermohaline forcing on the observed circulation in the western tropical Indian Ocean. The model consists of equations of motion and continuity, sea surface topography, equations of state and temperature, and salinity diffusion equations. While the sea surface topography equation is solved by a successive overrelaxation technique, the other model equations are solved by a leap-frog numerical scheme. Two versions of the model, having 18 and 33 levels in the vertical direction, were prepared to study climatological mean circulation in the western tropical Indian Ocean. The first numerical experiment is carried out with the 18-level adaptation model to study the sensitivity of the solution to different values of eddy coefficients. The main scientific rationale behind these numerical experiments was to obtain the most appropriate values of the eddy coefficients for the realistic computation of climatological circulation in the western tropical Indian Ocean. Three numerical experiments were conducted for the month of February to understand the sensitivity of the model solution to different eddy coefficients. The model reproduced the circulation features during February, even with low values of horizontal and vertical eddy coefficients. In the second experiment, the adaptation model, with 33 levels in the vertical direction, is applied to study the seasonal mean climatological circulation at selected depths during Spring in the western tropical Indian Ocean. Adapted (steady state) results of currents, sea surface topography, temperature and salinity anomaly fields are presented. Reasonable agreement is obtained between the model results on currents and the observational data. The computed anomaly fields for temperature and salinity at selected depths
Alexandre Sokic
2007-01-01
This article highlights the strict association met in the literature between the adaptive expectations assumption and the correct running of the monetary model of hyperinflation. A complete resolution of the model is carried out under the adaptive expectations hypothesis. It is shown that the assumption of adaptive expectations is not sufficient to ensure the validity of the model for the explanation of monetary hyperinflation. This result raises the question of the field of validity of this ...
Mohammad Iranmanesh
2014-12-01
Full Text Available Many standard brands sell products under the volume discount scheme (VDS as more and more consumers are fond of purchasing products under this scheme. Despite volume discount being commonly practiced, there is a dearth of research, both conceptual and empirical, focusing on purchase characteristics factors and consumer internal evaluation concerning the purchase of products under VDS. To attempt to fill this void, this article develops a conceptual model on VDS with the intention of delineating the influence of the purchase characteristics factors on the consumer intention to purchase products under VDS and provides an explanation of their effects through consumer internal evaluation. Finally, the authors discuss the managerial implications of their research and offer guidelines for future empirical research.
Convergent and Correct Message Passing Schemes for Optimization Problems over Graphical Models
Ruozzi, Nicholas
2010-01-01
The max-product algorithm, which attempts to compute the most probable assignment (MAP) of a given probability distribution, has recently found applications in quadratic minimization and combinatorial optimization. Unfortunately, the max-product algorithm is not guaranteed to converge and, even if it does, is not guaranteed to produce the MAP assignment. In this work, we provide a simple derivation of a new family of message passing algorithms. We first show how to arrive at this general message passing scheme by "splitting" the factors of our graphical model and then we demonstrate that this construction can be extended beyond integral splitting. We prove that, for any objective function which attains its maximum value over its domain, this new family of message passing algorithms always contains a message passing scheme that guarantees correctness upon convergence to a unique estimate. We then adopt a serial message passing schedule and prove that, under mild assumptions, such a schedule guarantees the conv...
ZHU Shouxian; ZHANG Wenjing
2008-01-01
Much has been written of the error in computing the baroclinic pressure gradient (BPG) with sigma coordinates in ocean or atmos- pheric numerical models. The usual way to reduce the error is to subtract area-averaged density stratification of the whole computa- tion region. But if there is great difference between the area-averaged and the local averaged density stratification, the error will be obvious. An example is given to show that the error from this method may be larger than that from no correction sometimes. The definition of local area is put forward. Then, four improved BPG difference schemes of subtracting the local averaged density strat- ification are designed to reduce the error. Two of them are for diagnostic calculation (density field is fixed), and the others are for prognostic calculation (density field is not fixed). The results show that the errors from these schemes all significantly decrease.
Finite element model for linear-elastic mixed mode loading using adaptive mesh strategy
无
2008-01-01
An adaptive mesh finite element model has been developed to predict the crack propagation direction as well as to calculate the stress intensity factors (SIFs), under linear-elastic assumption for mixed mode loading application. The finite element mesh is generated using the advancing front method. In order to suit the requirements of the fracture analysis, the generation of the background mesh and the construction of singular elements have been added to the developed program. The adaptive remeshing process is carried out based on the posteriori stress error norm scheme to obtain an optimal mesh. Previous works of the authors have proposed techniques for adaptive mesh generation of 2D cracked models. Facilitated by the singular elements, the displacement extrapolation technique is employed to calculate the SIF. The fracture is modeled by the splitting node approach and the trajectory follows the successive linear extensions of each crack increment. The SIFs values for two different case studies were estimated and validated by direct comparisons with other researchers work.
Steger, J. L.; Dougherty, F. C.; Benek, J. A.
1983-01-01
A mesh system composed of multiple overset body-conforming grids is described for adapting finite-difference procedures to complex aircraft configurations. In this so-called 'chimera mesh,' a major grid is generated about a main component of the configuration and overset minor grids are used to resolve all other features. Methods for connecting overset multiple grids and modifications of flow-simulation algorithms are discussed. Computational tests in two dimensions indicate that the use of multiple overset grids can simplify the task of grid generation without an adverse effect on flow-field algorithms and computer code complexity.
Numerical Solutions of Traffic Flow on Networks : Using the LWR-Model and the Godunov Scheme
Bergersen, Bjørnar Dolva
2014-01-01
This paper shows how to create a simulationtool for traffic flow in a network using the Lighthill--Witham--Richards model and the Godunov scheme. First some basic rules about conservation laws are described and how to solve them using the method characteristics. This leads to the notion of weak solutions which can be solved by shock- and rarefractions-solutions. This is then used to describe how traffic behaves on a single road by using the LWR-model. The behavior of traffic at junctions is d...
Cirrus clouds in a global climate model with a statistical cirrus cloud scheme
M. Wang
2010-06-01
Full Text Available A statistical cirrus cloud scheme that accounts for mesoscale temperature perturbations is implemented in a coupled aerosol and atmospheric circulation model to better represent both subgrid-scale supersaturation and cloud formation. This new scheme treats the effects of aerosol on cloud formation and ice freezing in an improved manner, and both homogeneous freezing and heterogeneous freezing are included. The scheme is able to better simulate the observed probability distribution of relative humidity compared to the scheme that was implemented in an older version of the model. Heterogeneous ice nuclei (IN are shown to decrease the frequency of occurrence of supersaturation, and improve the comparison with observations at 192 hPa. Homogeneous freezing alone can not reproduce observed ice crystal number concentrations at low temperatures (<205 K, but the addition of heterogeneous IN improves the comparison somewhat. Increases in heterogeneous IN affect both high level cirrus clouds and low level liquid clouds. Increases in cirrus clouds lead to a more cloudy and moist lower troposphere with less precipitation, effects which we associate with the decreased convective activity. The change in the net cloud forcing is not very sensitive to the change in ice crystal concentrations, but the change in the net radiative flux at the top of the atmosphere is still large because of changes in water vapor. Changes in the magnitude of the assumed mesoscale temperature perturbations by 25% alter the ice crystal number concentrations and the net radiative fluxes by an amount that is comparable to that from a factor of 10 change in the heterogeneous IN number concentrations. Further improvements on the representation of mesoscale temperature perturbations, heterogeneous IN and the competition between homogeneous freezing and heterogeneous freezing are needed.
CLOUD COMPUTING AND ITS PRICING SCHEMES
Varun Kamra
2012-04-01
Full Text Available Cloud computing is a rapidly emerging technology which involves deployment of various services like software, web services and virtualized infrastructure, as a product on public, private or hybrid clouds on lease basis. These services are charged by the respective pricing scheme for the cloud. The price varies with the number and type of data structures used for query execution. In this paper we describe static and dynamic pricing schemes for cloud cache. In static pricing scheme the prices are fixed for different resources which remain constant with time. Static pricing scheme does not benefit the service provider because it does not reflect the current market value. The dynamic pricing scheme can adapt as the time changes. According to the demand of a resource the pricing is done in dynamic pricing scheme so as to maximize the profit of the service provider. In addition to this, our paper explains characteristics and the delivery models for cloud computing in short.
Stock market modeling and forecasting a system adaptation approach
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 ...
Student Modelling in Adaptive E-Learning Systems
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.
Wang, Jun; Cieplak, Piotr; Cai, Qin; Hsieh, Meng-Juei; Wang, Junmei; Duan, Yong
2012-01-01
As an integrated step towards a coherent polarizable force field for biomolecular modeling, we analyzed four polarizable water models to evaluate their consistencies with the Thole polarization screening schemes utilized in our latest Amber polarizable force field. Specifically, we studied the performance of both the Thole linear and exponential schemes in these water models to assess their abilities to reproduce experimental water properties. The analysis shows that the tested water models reproduce most of the room-temperature properties of liquid water reasonably well, but fall short of reproducing the dynamic properties and temperature-dependent properties. This study demonstrates the necessity to further fine-tune water polarizable potentials for more robust polarizable force fields for biomolecular simulations. PMID:22712654
Wang, Jun; Cieplak, Piotr; Cai, Qin; Hsieh, Meng-Juei; Wang, Junmei; Duan, Yong; Luo, Ray
2012-07-19
As an integrated step toward a coherent polarizable force field for biomolecular modeling, we analyzed four polarizable water models to evaluate their consistencies with the Thole polarization screening schemes utilized in our latest Amber polarizable force field. Specifically, we studied the performance of both the Thole linear and exponential schemes in these water models to assess their abilities to reproduce experimental water properties. The analysis shows that the tested water models reproduce most of the room-temperature properties of liquid water reasonably well but fall short of reproducing the dynamic properties and temperature-dependent properties. This study demonstrates the necessity to further fine-tune water polarizable potentials for more robust polarizable force fields for biomolecular simulations. PMID:22712654
Generalization of the Event-Based Carnevale-Hines Integration Scheme for Integrate-and-Fire Models
van Elburg, Ronald A. J.; van Ooyen, Arjen
2009-01-01
An event-based integration scheme for an integrate-and-fire neuron model with exponentially decaying excitatory synaptic currents and double exponential inhibitory synaptic currents has been introduced by Carnevale and Hines. However, the integration scheme imposes nonphysiological constraints on th
白翔; 毛玉明; 冷甦鹏; 毛建兵; 谢军
2009-01-01
针对IEEE 802.11e EDCA(enhanced distributed channel access)支持业务区分服务的特点,提出了一个基于AIFS(arbitration inter-frame space)区分的信道吞吐率分析模型,该模型将不同接入等级的业务统一到一个信道模型中进行分析.通过数值计算结果与仿真实验结果的对比,验证了该模型的准确性,尤其是在分析信道吞吐卒方面更优于Xiao的Markov链模型.根据提出的分析模型,研究了近似优化条件,使得各类优先级业务的发送概率平衡虚拟发送时间段中空闲时间与冲突持续时间对系统性能的影响,实现靠近最优的信道吞吐率,从而使计算复杂度大为减小.利用数值分析的方法验证了近似优化条件实现靠近最优信道吞吐率的可行性.最后,提出的DPS(dynamicparameter-tunjmg scheme)算法根据负载情况自适应地调整不同级别业务的相应参数,使得系统时时满足优化条件,在各种场景下都能实现最大信道吞吐率,同时又满足EDCA支持QoS区分的要求.仿真结果验证了DPS算法不仅能够根据竞争节点的数目变化对信道吞吐率进行优化,而且其性能也明显优于标准的IEEE 802.11e EDCA机制.
Coirier, William John
1994-01-01
A Cartesian, cell-based scheme for solving the Euler and Navier-Stokes equations in two dimensions is developed and tested. Grids about geometrically complicated bodies are generated automatically, by recursive subdivision of a single Cartesian cell encompassing the entire flow domain. Where the resulting cells intersect bodies, polygonal 'cut' cells are created. The geometry of the cut cells is computed using polygon-clipping algorithms. The grid is stored in a binary-tree data structure which provides a natural means of obtaining cell-to-cell connectivity and of carrying out solution-adaptive refinement. The Euler and Navier-Stokes equations are solved on the resulting grids using a finite-volume formulation. The convective terms are upwinded, with a limited linear reconstruction of the primitive variables used to provide input states to an approximate Riemann solver for computing the fluxes between neighboring cells. A multi-stage time-stepping scheme is used to reach a steady-state solution. Validation of the Euler solver with benchmark numerical and exact solutions is presented. An assessment of the accuracy of the approach is made by uniform and adaptive grid refinements for a steady, transonic, exact solution to the Euler equations. The error of the approach is directly compared to a structured solver formulation. A non smooth flow is also assessed for grid convergence, comparing uniform and adaptively refined results. Several formulations of the viscous terms are assessed analytically, both for accuracy and positivity. The two best formulations are used to compute adaptively refined solutions of the Navier-Stokes equations. These solutions are compared to each other, to experimental results and/or theory for a series of low and moderate Reynolds numbers flow fields. The most suitable viscous discretization is demonstrated for geometrically-complicated internal flows. For flows at high Reynolds numbers, both an altered grid-generation procedure and a
变压器主保护中的自适应方案%Self-adapting schemes in transformer main protections
刘世明; 林湘宁; 杨春明; 陈德树
2001-01-01
The paper proposes some self_adapting schemes to complete the functions of CT scale coefficients adjusting and CT polarity checking and correcting in transformer longitudinal differential protection, which makes micro-computer based protective relays more intelligent and can accomplish these works to be done automatically. And two draft resolutions were proposed trying to solve the problem of CT polarity checking in transformer zero-sequence differential protection.%针对变压器微机纵差保护中的电流互感器比例系数的调整以及互感器接线极性校对等问题，介绍了几种自适应方案。对于零序差动保护的CT极性检测和校对问题，文中提出了两种自适应参考方案以供探讨。
A novel scheme for global scattering center modeling of radar targets
2008-01-01
A novel scheme for extracting the global scattering center model of radar targets is proposed in this paper.The 2D/3D scattering center models can be recon structed based on the wideband measurements at different viewing angles.The sphere spreading of the 1D scattering center projections is exploited.The 1D-2D/3D scatterer map(OTSM)is designed to manifest the high dimensional scattering characteristic of radar targets.The Hough transform and the least squares method are used to extract the stable scattering centers and their scattering coefficients.This modeling method does not need a high density of the spatial grid,which greatly cuts down the necessary original data.The model built in this Way describes the stable point scattering mechanisms in a large spatial extent and can be extrapolated to other frequencies in the optical region.Examples verify the validity of both the model and the method.
Classrooms as Complex Adaptive Systems: A Relational Model
Burns, Anne; Knox, John S.
2011-01-01
In this article, we describe and model the language classroom as a complex adaptive system (see Logan & Schumann, 2005). We argue that linear, categorical descriptions of classroom processes and interactions do not sufficiently explain the complex nature of classrooms, and cannot account for how classroom change occurs (or does not occur), over…
Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies
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.
Water-energy modelling: Adaptation to water scarcity
Pereira-Cardenal, Silvio J.
2016-02-01
Combined water and power models are important to predict how changes in one resource will impact the other. A new global assessment of hydropower and thermoelectric power plants predicts future vulnerabilities arising from climate-change-induced water constraints and tests possible adaptation options.
Model-Driven Instructional Engineering to Generate Adaptable Learning Materials
Dodero, Juan Manuel; Díez, David
2006-01-01
Please, cite this publication as: Dodero, J. M. & Díez, D. (2006). Model-Driven Instructional Engineering to Generate Adaptable Learning Materials. Proceedings of ICALT2006. July, Kerkrade, The Netherlands: IEEE. Retrieved July 30th, 2006, from http://dspace.learningnetworks.org
Yannick Griep; Elfi Baillien; Wouter Vleugels; Sebastiaan Rothmann; Hans De Witte
2014-01-01
This study investigates affective experience as a function of unemployment duration in South Africa. The study contrasts two models. The stress reaction model proposes a linear decrease of affective experience as unemployment prolongs. The adaptation model assumes a curvilinear pattern between affective experience and unemployment duration. Analysis of variance (ANOVA) with contrast revealed no differences in affective experience between short-term (N = 101), long-term (N = 152) and very long...
Thornhill, Gill D.; Mason, David C.; Sarah L. Dance; Amos S. Lawless; Nichols, Nancy K.; Forbes, Heather R.
2012-01-01
This paper describes the implementation of a 3D variational (3D-Var) data assimilation scheme for a morphodynamic model applied to Morecambe Bay, UK. A simple decoupled hydrodynamic and sediment transport model is combined with a data assimilation scheme to investigate the ability of such methods to improve the accuracy of the predicted bathymetry. The inverse forecast error covariance matrix is modelled using a Laplacian approximation which is calibrated for the length scale parameter requir...
Mengelkamp, H.T.; Warrach, K.; Raschke, E. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Atmosphaerenphysik
1997-12-31
A soil-vegetation-atmosphere-transfer scheme is presented here which solves the coupled system of the Surface Energy and Water Balance (SEWAB) equations considering partly vegetated surfaces. It is based on the one-layer concept for vegetation. In the soil the diffusion equations for heat and moisture are solved on a multi-layer grid. SEWAB has been developed to serve as a land-surface scheme for atmospheric circulation models. Being forced with atmospheric data from either simulations or measurements it calculates surface and subsurface runoff that can serve as input to hydrologic models. The model has been validated with field data from the FIFE experiment and has participated in the PILPS project for intercomparison of land-surface parameterization schemes. From these experiments we feel that SEWAB reasonably well partitions the radiation and precipitation into sensible and latent heat fluxes as well as into runoff and soil moisture Storage. (orig.) [Deutsch] Ein Landoberflaechenschema wird vorgestellt, das den Transport von Waerme und Wasser zwischen dem Erdboden, der Vegetation und der Atmosphaere unter Beruecksichtigung von teilweise bewachsenem Boden beschreibt. Im Erdboden werden die Diffusionsgleichungen fuer Waerme und Feuchte auf einem Gitter mit mehreren Schichten geloest. Das Schema SEWAB (Surface Energy and Water Balance) beschreibt die Landoberflaechenprozesse in atmosphaerischen Modellen und berechnet den Oberflaechenabfluss und den Basisabfluss, die als Eingabedaten fuer hydrologische Modelle genutzt werden koennen. Das Modell wurde mit Daten des FIFE-Experiments kalibriert und hat an Vergleichsexperimenten fuer Landoberflaechen-Schemata im Rahmen des PILPS-Projektes teilgenommen. Dabei hat sich gezeigt, dass die Aufteilung der einfallenden Strahlung und des Niederschlages in den sensiblen und latenten Waermefluss und auch in Abfluss und Speicherung der Bodenfeuchte in SEWAB den beobachteten Daten recht gut entspricht. (orig.)
Improved Based on "Self-Adaptive Turning Rate" Model Algorithm
Xiuling He
2013-06-01
Full Text Available For tracking the object with tracking nonlinear, high maneuvering target，traditional interactive multiple model self-adaptive filter algorithm was usually adopted．The turning rate estimate was very important. However，the performance of turning rate algorithm was not so satisfactory in the model．Thus，a new the average value turning rate algorithm based on self-adaptive turning model was proposed．Aiming at additional device for turning rate estimation turning model, the parameters α and β were introduced to adjust the roughness of turning rate．Aiming at target constant turning movement and orthogonal turning rate unequal, estimates, turning rate was used the average value model to reduce the noise and error influence. Simulation results showed that the proposed algorithm was more suitable for the objects with Nonlinear, high maneuvering target tracking and could remarkably reduce the sample，and thus achieve much better tracking performance.
An adaptive multi-feature segmentation model for infrared image
Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa
2016-04-01
Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.
Complex Environmental Data Modelling Using Adaptive General Regression Neural Networks
Kanevski, Mikhail
2015-04-01
The research deals with an adaptation and application of Adaptive General Regression Neural Networks (GRNN) to high dimensional environmental data. GRNN [1,2,3] are efficient modelling tools both for spatial and temporal data and are based on nonparametric kernel methods closely related to classical Nadaraya-Watson estimator. Adaptive GRNN, using anisotropic kernels, can be also applied for features selection tasks when working with high dimensional data [1,3]. In the present research Adaptive GRNN are used to study geospatial data predictability and relevant feature selection using both simulated and real data case studies. The original raw data were either three dimensional monthly precipitation data or monthly wind speeds embedded into 13 dimensional space constructed by geographical coordinates and geo-features calculated from digital elevation model. GRNN were applied in two different ways: 1) adaptive GRNN with the resulting list of features ordered according to their relevancy; and 2) adaptive GRNN applied to evaluate all possible models N [in case of wind fields N=(2^13 -1)=8191] and rank them according to the cross-validation error. In both cases training were carried out applying leave-one-out procedure. An important result of the study is that the set of the most relevant features depends on the month (strong seasonal effect) and year. The predictabilities of precipitation and wind field patterns, estimated using the cross-validation and testing errors of raw and shuffled data, were studied in detail. The results of both approaches were qualitatively and quantitatively compared. In conclusion, Adaptive GRNN with their ability to select features and efficient modelling of complex high dimensional data can be widely used in automatic/on-line mapping and as an integrated part of environmental decision support systems. 1. Kanevski M., Pozdnoukhov A., Timonin V. Machine Learning for Spatial Environmental Data. Theory, applications and software. EPFL Press
Adaptive quasi-likelihood estimate in generalized linear models
CHEN Xia; CHEN Xiru
2005-01-01
This paper gives a thorough theoretical treatment on the adaptive quasilikelihood estimate of the parameters in the generalized linear models. The unknown covariance matrix of the response variable is estimated by the sample. It is shown that the adaptive estimator defined in this paper is asymptotically most efficient in the sense that it is asymptotic normal, and the covariance matrix of the limit distribution coincides with the one for the quasi-likelihood estimator for the case that the covariance matrix of the response variable is completely known.
Moussab eBennehar
2015-12-01
Full Text Available This paper deals with a new control scheme for Parallel Kinematic Manipulators (PKMs based on the L1 adaptive control theory. The original L1 adaptive controller is extended by including an adaptive loop based on the dynamics of the PKM. The additional model-based term is in charge of the compensation of the modeled nonlinear dynamics in the aim of improving the tracking performance. Moreover, the proposed controller is enhanced to reduce the internal forces, which may appear in the case of Redundantly Actuated PKMs (RA-PKMs. The generated control inputs are first regulated through a projection mechanism that reduces the antagonistic internal forces, before being applied to the manipulator. To validate the proposed controller and to show its effectiveness, real-time experiments are conducted on a new four degrees-of-freedom (4-DOFs RA-PKM developed in our laboratory.
Evaluating mallard adaptive management models with time series
Conn, P.B.; Kendall, W.L.
2004-01-01
Wildlife practitioners concerned with midcontinent mallard (Anas platyrhynchos) management in the United States have instituted a system of adaptive harvest management (AHM) as an objective format for setting harvest regulations. Under the AHM paradigm, predictions from a set of models that reflect key uncertainties about processes underlying population dynamics are used in coordination with optimization software to determine an optimal set of harvest decisions. Managers use comparisons of the predictive abilities of these models to gauge the relative truth of different hypotheses about density-dependent recruitment and survival, with better-predicting models giving more weight to the determination of harvest regulations. We tested the effectiveness of this strategy by examining convergence rates of 'predictor' models when the true model for population dynamics was known a priori. We generated time series for cases when the a priori model was 1 of the predictor models as well as for several cases when the a priori model was not in the model set. We further examined the addition of different levels of uncertainty into the variance structure of predictor models, reflecting different levels of confidence about estimated parameters. We showed that in certain situations, the model-selection process favors a predictor model that incorporates the hypotheses of additive harvest mortality and weakly density-dependent recruitment, even when the model is not used to generate data. Higher levels of predictor model variance led to decreased rates of convergence to the model that generated the data, but model weight trajectories were in general more stable. We suggest that predictive models should incorporate all sources of uncertainty about estimated parameters, that the variance structure should be similar for all predictor models, and that models with different functional forms for population dynamics should be considered for inclusion in predictor model! sets. All of these
Zubov, V.A.; Rozanov, E.V. [Main Geophysical Observatory, St.Petersburg (Russian Federation); Schlesinger, M.E.; Andronova, N.G. [Illinois Univ., Urbana-Champaign, IL (United States). Dept. of Atmospheric Sciences
1997-12-31
The problems of ozone depletion, climate change and atmospheric pollution strongly depend on the processes of production, destruction and transport of chemical species. A hybrid transport scheme was developed, consisting of the semi-Lagrangian scheme for horizontal advection and the Prather scheme for vertical transport, which have been used for the Atmospheric Chemical Transport model to calculate the distributions of different chemical species. The performance of the new hybrid scheme has been evaluated in comparison with other transport schemes on the basis of specially designed tests. The seasonal cycle of the distribution of N{sub 2}O simulated by the model, as well as the dispersion of NO{sub x} exhausted from subsonic aircraft, are in a good agreement with published data. (author) 8 refs.
ADAPTATION OF WOFOST MODEL FROM CGMS TO ROMANIAN CONDITIONS
LAZĂR CĂTĂLIN; BARUTH BETTINA; MICALE FABIO; LAZĂR DANIELA ANCA
2009-01-01
This preliminary study is an inventory of the main resources and difficulties in adaptation of the Crop Growth Monitoring System (CGMS) used by Agri4cast unit of IPSC from Joint Research Centre (JRC) - Ispra of European Commission to conditions of Romania.In contrast with the original model calibrated mainly with statistical average yields at national level, for local calibration of the model the statistical yields at lower administrative units (macroregion or county) must be used. In additio...
Supply Chain as Complex Adaptive System and Its Modeling
MingmingWang
2004-01-01
Supply chain is a complex, hierarchical, integrated, open and dynamic network.Every node in the network is an independent business unit that unites other organizations to develop its value, the competition and cooperation between these units are basic impetus of the development and evolution of the supply chain system. The characteristics of supply chain as a complex adaptive system and its modeling are discussed in this paper, and use an example demonstrating the feasibility of CAS modeling in supply chain management study.
Adaptive correction of deterministic models to produce probabilistic forecasts
Smith, P. J.; K. J. Beven; A. H. Weerts; D. Leedal
2012-01-01
This paper considers the correction of deterministic forecasts given by a flood forecasting model. A stochastic correction based on the evolution of an adaptive, multiplicative, gain is presented. A number of models for the evolution of the gain are considered and the quality of the resulting probabilistic forecasts assessed. The techniques presented offers a computationally efficient method for providing probabilistic forecasts based on existing flood forecasting system output.
A Framework for Adaptive Process Modeling and Execution (FAME)
Benjamin, Perakath; Erraguntla, Madhav; Mayer, Richard; Painter, Michael; Marshall, Charles
1999-01-01
This paper describes the architecture and concept of operation of a Framework for Adaptive Process Modeling and Execution (FAME). The research addresses the absence of robust methods for supporting the software process management life cycle. FAME employs a novel, model-based approach in providing automated support for different activities in the software development life cycle including project definition, process design, process analysis, process enactment, process execution status monitorin...
Human Adaptive Mechatronics and Human-System Modelling
Satoshi Suzuki; Hiroshi Igarashi; Harumi Kobayashi; Tetsuya Yasuda; Fumio Harashima
2013-01-01
Several topics in projects for mechatronics studies, which are ʹHuman Adaptive Mechatronics (HAM)ʹ and ʹHuman‐System Modelling (HSM)ʹ, are presented in this paper. The main research theme of the HAM project is a design strategy for a new intelligent mechatronics system, which enhances operatorsʹ skills during machine operation. Skill analyses and control system design have been addressed. In the HSM project, human modelling based on hierarchical classification of skills was studied, including...
Verification of the multi-layer SNOWPACK model with different water transport schemes
Wever, N.; Schmid, L.; Heilig, A.; Eisen, O.; Fierz, C.; Lehning, M.
2015-12-01
The widely used detailed SNOWPACK model has undergone constant development over the years. A notable recent extension is the introduction of a Richards equation (RE) solver as an alternative for the bucket-type approach for describing water transport in the snow and soil layers. In addition, continuous updates of snow settling and new snow density parameterizations have changed model behavior. This study presents a detailed evaluation of model performance against a comprehensive multiyear data set from Weissfluhjoch near Davos, Switzerland. The data set is collected by automatic meteorological and snowpack measurements and manual snow profiles. During the main winter season, snow height (RMSE: < 4.2 cm), snow water equivalent (SWE, RMSE: < 40 mm w.e.), snow temperature distributions (typical deviation with measurements: < 1.0 °C) and snow density (typical deviation with observations: < 50 kg m-3) as well as their temporal evolution are well simulated in the model and the influence of the two water transport schemes is small. The RE approach reproduces internal differences over capillary barriers but fails to predict enough grain growth since the growth routines have been calibrated using the bucket scheme in the original SNOWPACK model. However, the agreement in both density and grain size is sufficient to parameterize the hydraulic properties successfully. In the melt season, a pronounced underestimation of typically 200 mm w.e. in SWE is found. The discrepancies between the simulations and the field data are generally larger than the differences between the two water transport schemes. Nevertheless, the detailed comparison of the internal snowpack structure shows that the timing of internal temperature and water dynamics is adequately and better represented with the new RE approach when compared to the conventional bucket scheme. On the contrary, the progress of the meltwater front in the snowpack as detected by radar and the temporal evolution of the vertical
Extensions in adaptive model tracking with mitigated passivity conditions
Itzhak BARKANA
2013-01-01
Feasibility of nonlinear and adaptive control methodologies in multivariable linear timeinvariant systems with state space realization {A,B,C} has apparently been limited by the standard strict passivity (or positive realness) conditions that imply that the product CB must be positive definite symmetric.More recently the symmetry condition has been mitigated,requiring instead that the not necessarily symmetric matrix CB be diagonalizable and with positive real eigenvalues.However,although the mitigated conditions are useful in proving pure stabilizability with Adaptive Controllers,the Model Tracking question has remained open and counterexamples seem to demonstrate total divergence of standard model reference adaptive controllers when the regular passivity conditions are not fully satisfied.Therefore,this paper further extends the previous results,showing that the new passivity conditions do guarantee stability with adaptive model tracking.Examples show how the new conditions solve the case of flexible structures with unknown parameters when perfect collocation is not possible.Also,the so-called counterexamples become simple,well-behaved,examples.
Learning Adaptive Forecasting Models from Irregularly Sampled Multivariate Clinical Data
Liu, Zitao; Hauskrecht, Milos
2016-01-01
Building accurate predictive models of clinical multivariate time series is crucial for understanding of the patient condition, the dynamics of a disease, and clinical decision making. A challenging aspect of this process is that the model should be flexible and adaptive to reflect well patient-specific temporal behaviors and this also in the case when the available patient-specific data are sparse and short span. To address this problem we propose and develop an adaptive two-stage forecasting approach for modeling multivariate, irregularly sampled clinical time series of varying lengths. The proposed model (1) learns the population trend from a collection of time series for past patients; (2) captures individual-specific short-term multivariate variability; and (3) adapts by automatically adjusting its predictions based on new observations. The proposed forecasting model is evaluated on a real-world clinical time series dataset. The results demonstrate the benefits of our approach on the prediction tasks for multivariate, irregularly sampled clinical time series, and show that it can outperform both the population based and patient-specific time series prediction models in terms of prediction accuracy.
Missile guidance law design using adaptive cerebellar model articulation controller.
Lin, Chih-Min; Peng, Ya-Fu
2005-05-01
An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law. PMID:15940993
Swanson, R. C.; Rossow, C.-C.
2008-01-01
A three-stage Runge-Kutta (RK) scheme with multigrid and an implicit preconditioner has been shown to be an effective solver for the fluid dynamic equations. This scheme has been applied to both the compressible and essentially incompressible Reynolds-averaged Navier-Stokes (RANS) equations using the algebraic turbulence model of Baldwin and Lomax (BL). In this paper we focus on the convergence of the RK/implicit scheme when the effects of turbulence are represented by either the Spalart-Allmaras model or the Wilcox k-! model, which are frequently used models in practical fluid dynamic applications. Convergence behavior of the scheme with these turbulence models and the BL model are directly compared. For this initial investigation we solve the flow equations and the partial differential equations of the turbulence models indirectly coupled. With this approach we examine the convergence behavior of each system. Both point and line symmetric Gauss-Seidel are considered for approximating the inverse of the implicit operator of the flow solver. To solve the turbulence equations we use a diagonally dominant alternating direction implicit (DDADI) scheme. Computational results are presented for three airfoil flow cases and comparisons are made with experimental data. We demonstrate that the two-dimensional RANS equations and transport-type equations for turbulence modeling can be efficiently solved with an indirectly coupled algorithm that uses the RK/implicit scheme for the flow equations.
Purpose: The aim of this study was to show the benefit of a two-step intensity modulated radiotherapy (IMRT) method by examining geometric and dosimetric changes. Material and Methods: Twenty patients with pharyngeal cancers treated with two-step IMRT combined with chemotherapy were included. Treatment-planning CT was done twice before IMRT (CT-1) and at the third or fourth week of IMRT for boost IMRT (CT-2). Transferred plans recalculated initial plan on CT-2 were compared with the initial plans on CT-1. Dose parameters were calculated for a total dose of 70 Gy for each plan. Results: The volumes of primary tumors and parotid glands on CT-2 regressed significantly. Parotid glands shifted medially an average of 4.2 mm on CT-2. The mean doses of the parotid glands in the initial and transferred plans were 25.2 Gy and 30.5 Gy, respectively. D2 (dose to 2% of the volume) doses of the spinal cord were 37.1 Gy and 39.2 Gy per 70 Gy, respectively. Of 15 patients in whom xerostomia scores could be evaluated 1–2 years after IMRT, no patient complained of grade 2 or more xerostomia. Conclusions: This two-step IMRT method as an adaptive RT scheme could adapt to changes in body contour, target volumes and risk organs during IMRT
Braghiere, Renato; Quaife, Tristan; Black, Emily
2016-04-01
Incoming shortwave radiation is the primary source of energy driving the majority of the Earth's climate system. The partitioning of shortwave radiation by vegetation into absorbed, reflected, and transmitted terms is important for most of biogeophysical processes, including leaf temperature changes and photosynthesis, and it is currently calculated by most of land surface schemes (LSS) of climate and/or numerical weather prediction models. The most commonly used radiative transfer scheme in LSS is the two-stream approximation, however it does not explicitly account for vegetation architectural effects on shortwave radiation partitioning. Detailed three-dimensional (3D) canopy radiative transfer schemes have been developed, but they are too computationally expensive to address large-scale related studies over long time periods. Using a straightforward one-dimensional (1D) parameterisation proposed by Pinty et al. (2006), we modified a two-stream radiative transfer scheme by including a simple function of Sun zenith angle, so-called "structure factor", which does not require an explicit description and understanding of the complex phenomena arising from the presence of vegetation heterogeneous architecture, and it guarantees accurate simulations of the radiative balance consistently with 3D representations. In order to evaluate the ability of the proposed parameterisation in accurately represent the radiative balance of more complex 3D schemes, a comparison between the modified two-stream approximation with the "structure factor" parameterisation and state-of-art 3D radiative transfer schemes was conducted, following a set of virtual scenarios described in the RAMI4PILPS experiment. These experiments have been evaluating the radiative balance of several models under perfectly controlled conditions in order to eliminate uncertainties arising from an incomplete or erroneous knowledge of the structural, spectral and illumination related canopy characteristics typical
Basso, L; Chowdhury, D; Hirsch, M; Khalil, S; Moretti, S; O'Leary, B; Porod, W; Staub, F
2012-01-01
The SUSY Les Houches Accord (SLHA) 2 extended the first SLHA to include various generalisations of the Minimal Supersymmetric Standard Model (MSSM) as well as its simplest next-to-minimal version. Here, we propose further extensions to it, to include the most general and well-established see-saw descriptions (types I/II/III, inverse, and linear) in both an effective and a simple gauged extension of the MSSM framework. In addition, we generalise the PDG numbering scheme to reflect the properties of the particles.
Sreedhar Madichetty
2014-02-01
Full Text Available This article is devoted to the Multi-level inverters review and in particular to the form and function of modular multilevel inverters (MMI, with their different topologies, modulation, modeling and control schemes Detailed analysis with their functions of MMI has been made in comprehensive manner with existing literature available till date. All existing methods are compared in detail with proposal for the best methods available. The article has made strategic conclusions on MMI to make the system more robust in operation with less complexity in design and control.
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.
QIU Zhongfeng; Andrea M. DOGLIOLI; HE Yijun; Francois CARLOTTI
2011-01-01
This paper presents two comparisons or tests for a Lagrangian model of zooplankton dispersion: numerical schemes and time steps. Firstly, we compared three numerical schemes using idealized circulations. Results show that the precisions of the advanced Adams-Bashfold-Moulton (ABM) method and the Runge-Kutta (RK) method were in the same order and both were much higher than that of the Euler method. Furthermore, the advanced ABM method is more efficient than the RK method in computational memory requirements and time consumption. We therefore chose the advanced ABM method as the Lagrangian particle-tracking algorithm. Secondly, we performed a sensitivity test for time steps, using outputs of the hydrodynamic model, Symphonie. Results show that the time step choices depend on the fluid response time that is related to the spatial resolution of velocity fields. The method introduced by Oliveira et al. in 2002 is suitable for choosing time steps of Lagrangian particle-tracking models, at least when only considering advection.
HUA Zu-lin; XING Ling-hang; GU Li
2008-01-01
The modified QUICK scheme on unstructured grid was used to improve the advection flux approximation, and the depth-averaged turbulence model with the scheme based on FVM by SIMPLE series algorithm was established and applied to spur-dike flow computation. In this model, the over-relaxed approach was adopted to estimate the diffusion flux in view of its advantages in reducing errors and sustaining numerical stability usually encountered in non-orthogonal meshes. Two spur-dike cases with different defection angles (90oand 135o) were analyzed to validate the model. Computed results show that the predicted velocities and recirculation lengths are in good agreement with the observed data. Moreover, the computations on structured and unstructured grids were compared in terms of the approximately equivalent grid numbers. It can be concluded that the precision with unstructured grids is higher than that with structured grids in spite that the CPU time required is slightly more with unstructured grids. Thus, it is significant to apply the method to numerical simulation of practical hydraulic engineering.
A self-organized internal models architecture for coding sensory-motor schemes
Esaú eEscobar Juárez
2016-04-01
Full Text Available Cognitive robotics research draws inspiration from theories and models on cognition, as conceived by neuroscience or cognitive psychology, to investigate biologically plausible computational models in artificial agents. In this field, the theoretical framework of Grounded Cognition provides epistemological and methodological grounds for the computational modeling of cognition. It has been stressed in the literature that textit{simulation}, textit{prediction}, and textit{multi-modal integration} are key aspects of cognition and that computational architectures capable of putting them into play in a biologically plausible way are a necessity.Research in this direction has brought extensive empirical evidencesuggesting that textit{Internal Models} are suitable mechanisms forsensory-motor integration. However, current Internal Models architectures show several drawbacks, mainly due to the lack of a unified substrate allowing for a true sensory-motor integration space, enabling flexible and scalable ways to model cognition under the embodiment hypothesis constraints.We propose the Self-Organized Internal ModelsArchitecture (SOIMA, a computational cognitive architecture coded by means of a network of self-organized maps, implementing coupled internal models that allow modeling multi-modal sensory-motor schemes. Our approach addresses integrally the issues of current implementations of Internal Models.We discuss the design and features of the architecture, and provide empirical results on a humanoid robot that demonstrate the benefits and potentialities of the SOIMA concept for studying cognition in artificial agents.