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.
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
strategy using space vector modulations and a deadbeat algorithm in the stator flux reference frame. The lumped disturbances such as parameter variation and load disturbance of the system are estimated by a neuro-sliding mode approach based on model reference adaptive control (MRAC). An adaptive observer......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
Efficient adaptive fuzzy control scheme
Papp, Z.; Driessen, B.J.F.
1995-01-01
The paper presents an adaptive nonlinear (state-) feedback control structure, where the nonlinearities are implemented as smooth fuzzy mappings defined as rule sets. The fine tuning and adaption of the controller is realized by an indirect adaptive scheme, which modifies the parameters of the fuzzy
Yingmin Jia
2009-01-01
This paper mainly studies the model matching problem of multiple-output-delay systems in which the reference model is assigned to a diagonal transfer function matrix.A new model matching controller structure is first developed,and then,it is shown that the controller is feasible if and only if the sets of Diophantine equations have common solutions.The obtained controller allows a parametric representation,which shows that an adaptive scheme can be used to tolerate parameter variations in the plants.The resulting adaptive law can guarantee the global stability of the closed-loop systems and the convergence of the output error.
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.
Robustness of Model Reference Adaptive Schemes with Respect to Modeling Errors.
1982-10-01
regulation problem global stability properties are no longer guaranteed, but a region of attraction exists for exact adaptive regulation. In the case of... regulation problem and the tracking problem for the example (5.1) to (5.3). - a. Regulation: In the regulation problem expressions (5.8) to (5.10) become r(t...if y>0(1/u). 3Remark 5.2.2: As p- 0, domain D(p) becomes the whole space R , that is the adaptive regulation problem (5.15) to (5.18) is well posed
Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin
2014-03-01
In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method.
A new adaptive control scheme based on the interacting multiple model (IMM) estimation
Afshari, Hamed H.; Al-Ani, Dhafar; Habibi, Saeid [McMaster University, Hamilton (Canada)
2016-06-15
In this paper, an Interacting multiple model (IMM) adaptive estimation approach is incorporated to design an optimal adaptive control law for stabilizing an Unmanned vehicle. Due to variations of the forward velocity of the Unmanned vehicle, its aerodynamic derivatives are constantly changing. In order to stabilize the unmanned vehicle and achieve the control objectives for in-flight conditions, one seeks for an adaptive control strategy that can adjust itself to varying flight conditions. In this context, a bank of linear models is used to describe the vehicle dynamics in different operating modes. Each operating mode represents a particular dynamic with a different forward velocity. These models are then used within an IMM filter containing a bank of Kalman filters (KF) in a parallel operating mechanism. To regulate and stabilize the vehicle, a Linear quadratic regulator (LQR) law is designed and implemented for each mode. The IMM structure determines the particular mode based on the stored models and in-flight input-output measurements. The LQR controller also provides a set of controllers; each corresponds to a particular flight mode and minimizes the tracking error. Finally, the ultimate control law is obtained as a weighted summation of all individual controllers whereas weights are obtained using mode probabilities of each operating mode.
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.
Tsai, T. C.; Chen, J. P.; Dearden, C.
2014-12-01
The wide variety of ice crystal shapes and growth habits makes it a complicated issue in cloud models. This study developed the bulk ice adaptive habit parameterization based on the theoretical approach of Chen and Lamb (1994) and introduced a 6-class hydrometeors double-moment (mass and number) bulk microphysics scheme with gamma-type size distribution function. Both the proposed schemes have been implemented into the Weather Research and Forecasting model (WRF) model forming a new multi-moment bulk microphysics scheme. Two new moments of ice crystal shape and volume are included for tracking pristine ice's adaptive habit and apparent density. A closure technique is developed to solve the time evolution of the bulk moments. For the verification of the bulk ice habit parameterization, some parcel-type (zero-dimension) calculations were conducted and compared with binned numerical calculations. The results showed that: a flexible size spectrum is important in numerical accuracy, the ice shape can significantly enhance the diffusional growth, and it is important to consider the memory of growth habit (adaptive growth) under varying environmental conditions. Also, the derived results with the 3-moment method were much closer to the binned calculations. A field campaign of DIAMET was selected to simulate in the WRF model for real-case studies. The simulations were performed with the traditional spherical ice and the new adaptive shape schemes to evaluate the effect of crystal habits. Some main features of narrow rain band, as well as the embedded precipitation cells, in the cold front case were well captured by the model. Furthermore, the simulations produced a good agreement in the microphysics against the aircraft observations in ice particle number concentration, ice crystal aspect ratio, and deposition heating rate especially within the temperature region of ice secondary multiplication production.
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.
Rybynok, V O; Kyriacou, P A [City University, London (United Kingdom)
2007-10-15
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.
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.
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 actuator failure compensation and disturbance rejection scheme for spacecraft
Xuelian Yao; Gang Tao; Ruiyun Qi
2014-01-01
An adaptive actuator failure compensation scheme is proposed for attitude tracking control of spacecraft with unknown disturbances and uncertain actuator failures. A new feature of this adaptive control scheme is the adaptation of the failure pattern parameter estimates, as wel as the failure signal parameter es-timates, for direct adaptive actuator failure compensation. Based on an adaptive backstepping control design, the estimates of the disturbance parameters are used to solve the disturbance rejection problem. The unknown disturbances are compensated completely with the stability of the whole closed-loop system. The scheme is not only able to accommodate uncertain actuator failures, but also robust against unknown external disturbances. Simulation results verify the desired adaptive actuator failure compensation perfor-mance.
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 mobility management scheme in hierarchical mobile IPv6
Fang, Bo; Song, Junde
2004-04-01
Hierarchical mobile IPv6 makes the mobility management localized. Registration with HA is only needed while MN moving between MAP domains. This paper proposed an adaptive mobility management scheme based on the hierarchical mobile IPv6. The scheme focuses on the MN operation as well as MAP operation during the handoff. Adaptive MAP selection algorithm can be used to select a suitable MAP to register with once MN moves into a new subnet while MAP can thus adaptively changing his management domain. Furthermore, MAP can also adaptively changes its level in the hierarchical referring on the service load or other related information. Detailed handoff algorithm is also discussed in this paper.
Image Compression using Space Adaptive Lifting Scheme
Ramu Satyabama
2011-01-01
Full Text Available Problem statement: Digital images play an important role both in daily life applications as well as in areas of research and technology. Due to the increasing traffic caused by multimedia information and digitized form of representation of images; image compression has become a necessity. Approach: Wavelet transform has demonstrated excellent image compression performance. New algorithms based on Lifting style implementation of wavelet transforms have been presented in this study. Adaptively is introduced in lifting by choosing the prediction operator based on the local properties of the image. The prediction filters are chosen based on the edge detection and the relative local variance. In regions where the image is locally smooth, we use higher order predictors and near edges we reduce the order and thus the length of the predictor. Results: We have applied the adaptive prediction algorithms to test images. The original image is transformed using adaptive lifting based wavelet transform and it is compressed using Set Partitioning In Hierarchical Tree algorithm (SPIHT and the performance is compared with the popular 9/7 wavelet transform. The performance metric Peak Signal to Noise Ratio (PSNR for the reconstructed image is computed. Conclusion: The proposed adaptive algorithms give better performance than 9/7 wavelet, the most popular wavelet transforms. Lifting allows us to incorporate adaptivity and nonlinear operators into the transform. The proposed methods efficiently represent the edges and appear promising for image compression. The proposed adaptive methods reduce edge artifacts and ringing and give improved PSNR for edge dominated images.
Adaptive lifting scheme of wavelet transforms for image compression
Wu, Yu; Wang, Guoyin; Nie, Neng
2001-03-01
Aiming at the demand of adaptive wavelet transforms via lifting, a three-stage lifting scheme (predict-update-adapt) is proposed according to common two-stage lifting scheme (predict-update) in this paper. The second stage is updating stage. The third is adaptive predicting stage. Our scheme is an update-then-predict scheme that can detect jumps in image from the updated data and it needs not any more additional information. The first stage is the key in our scheme. It is the interim of updating. Its coefficient can be adjusted to adapt to data to achieve a better result. In the adaptive predicting stage, we use symmetric prediction filters in the smooth area of image, while asymmetric prediction filters at the edge of jumps to reduce predicting errors. We design these filters using spatial method directly. The inherent relationships between the coefficients of the first stage and the other stages are found and presented by equations. Thus, the design result is a class of filters with coefficient that are no longer invariant. Simulation result of image coding with our scheme is good.
An Improved Scalar Costa Scheme Based on Watson Perceptual Model
QI Kai-yue; CHEN Jian-bo; ZHOU Yi
2008-01-01
An improved scalar Costa scheme (SCS) was proposed by using improved Watson perceptual model to adaptively decide quantization step size and scaling factor. The improved scheme equals to embed hiding data based on an actual image. In order to withstand amplitude scaling attack, the Watson perceptual model was redefined, and the improved scheme using the new definition can insure quantization step size in decoder that is proportional to amplitude scaling attack factor. The performance of the improved scheme outperforms that of SCS with fixed quantization step size. The improved scheme combines information theory and visual model.
Block-based adaptive lifting schemes for multiband image compression
Masmoudi, Hela; Benazza-Benyahia, Amel; Pesquet, Jean-Christophe
2004-02-01
In this paper, we are interested in designing lifting schemes adapted to the statistics of the wavelet coefficients of multiband images for compression applications. More precisely, nonseparable vector lifting schemes are used in order to capture simultaneously the spatial and the spectral redundancies. The underlying operators are then computed in order to minimize the entropy of the resulting multiresolution representation. To this respect, we have developed a new iterative block-based classification algorithm. Simulation tests carried out on remotely sensed multispectral images indicate that a substantial gain in terms of bit-rate is achieved by the proposed adaptive coding method w.r.t the non-adaptive one.
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.
Chaos Synchronization in the Belousov-Zhabotinsky Chemical Reaction by Adaptive Control Scheme
LI,Yan-Ni(李艳妮); CHEN,Lan(陈兰); CAI,Zun-Sheng(蔡遵生); ZHAO,Xue-Zhuang(赵学庄)
2002-01-01
The adaptive synchronization scheme proposed by John and Amritkar was employed into the Belousov-Zhabotinsky (BZ) 4-variable-Montanator model system. By the parameter adjustment, chaos synchronization has been obtained. Through calculating thetransient time, the optimal combination of the stiffness constant and damping constant was obtained. Furthermore, the relationships among the transient time, conditional Lyapunov exponents, the stiffness constant and damping constant were discussed. Also, the BZ system with the adaptive synchronization scheme might be used for the communication purposes.
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.
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.
Adaptive Noise Reduction Scheme for Salt and Pepper
Gebreyohannes, Tina
2012-01-01
In this paper, a new adaptive noise reduction scheme for images corrupted by impulse noise is presented. The proposed scheme efficiently identifies and reduces salt and pepper noise. MAG (Mean Absolute Gradient) is used to identify pixels which are most likely corrupted by salt and pepper noise that are candidates for further median based noise reduction processing. Directional filtering is then applied after noise reduction to achieve a good tradeoff between detail preservation and noise removal. The proposed scheme can remove salt and pepper noise with noise density as high as 90% and produce better result in terms of qualitative and quantitative measures of images.
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...
An efficient class of WENO schemes with adaptive order
Balsara, Dinshaw S.; Garain, Sudip; Shu, Chi-Wang
2016-12-01
Finite difference WENO schemes have established themselves as very worthy performers for entire classes of applications that involve hyperbolic conservation laws. In this paper we report on two major advances that make finite difference WENO schemes more efficient. The first advance consists of realizing that WENO schemes require us to carry out stencil operations very efficiently. In this paper we show that the reconstructed polynomials for any one-dimensional stencil can be expressed most efficiently and economically in Legendre polynomials. By using Legendre basis, we show that the reconstruction polynomials and their corresponding smoothness indicators can be written very compactly. The smoothness indicators are written as a sum of perfect squares. Since this is a computationally expensive step, the efficiency of finite difference WENO schemes is enhanced by the innovation which is reported here. The second advance consists of realizing that one can make a non-linear hybridization between a large, centered, very high accuracy stencil and a lower order WENO scheme that is nevertheless very stable and capable of capturing physically meaningful extrema. This yields a class of adaptive order WENO schemes, which we call WENO-AO (for adaptive order). Thus we arrive at a WENO-AO(5,3) scheme that is at best fifth order accurate by virtue of its centered stencil with five zones and at worst third order accurate by virtue of being non-linearly hybridized with an r = 3 CWENO scheme. The process can be extended to arrive at a WENO-AO(7,3) scheme that is at best seventh order accurate by virtue of its centered stencil with seven zones and at worst third order accurate. We then recursively combine the above two schemes to arrive at a WENO-AO(7,5,3) scheme which can achieve seventh order accuracy when that is possible; graciously drop down to fifth order accuracy when that is the best one can do; and also operate stably with an r = 3 CWENO scheme when that is the only thing
Linewidth-tolerant adaptive equalization scheme for OQAM
Mao, Deng; Tang, Haoyuan; Lu, Jianing; Deng, Lei; Fu, Songnian; Feng, Yonghua; Liu, Deming
2017-06-01
A linewidth-tolerant adaptive equalization scheme is proposed for M-ary offset quadrature amplitude modulation (OQAM) signal at the presence of wide laser linewidth. Initially, we present a close-form mathematical expression of OQAM signal at the presence of phase noise and derive the condition to obtain the optimal tap value of adaptive equalizer. Our theoretical investigations proves that phase noise in OQAM signal may result in variation of optimal tap value of adaptive equalizer. Consequently, conventional digital signal processing (DSP) flow that separates adaptive equalization and carrier phase recovery (CPR) into two independent modules cannot apply to OQAM signal anymore. Then, we propose a linewidth-tolerant adaptive equalization scheme that incorporate both adaptive equalizer and CPR for m-ary OQAM signal. Taking the 16-OQAM into account, we comprehensively evaluate its performance to compensate residual chromatic dispersion (CD) and polarization mode dispersion (PMD) at the presence of wide laser linewidth. Simulation shows that our proposed adaptive equalization can effectively compensate residual CD that is below 400 ps/nm without performance penalty at the presence of wide laser linewidth. In particular, a tolerance of linewidth and symbol duration products of 1 ×10-4 is secured under conditions of CD=400 ps/nm and DGD=10 ps, given 1-dB required-OSNR penalty at BER=10-3.
An adaptive actuator failure compensation scheme for two linked 2WD mobile robots
Ma, Yajie; Al-Dujaili, Ayad; Cocquempot, Vincent; El Badaoui El Najjar, Maan
2017-01-01
This paper develops a new adaptive compensation control scheme for two linked mobile robots with actuator failurs. A configuration with two linked two-wheel drive (2WD) mobile robots is proposed, and the modelling of its kinematics and dynamics are given. An adaptive failure compensation scheme is developed to compensate actuator failures, consisting of a kinematic controller and a multi-design integration based dynamic controller. The kinematic controller is a virtual one, and based on which, multiple adaptive dynamic control signals are designed which covers all possible failure cases. By combing these dynamic control signals, the dynamic controller is designed, which ensures system stability and asymptotic tracking properties. Simulation results verify the effectiveness of the proposed adaptive failure compensation scheme.
Landis, Wayne G; Markiewicz, April J; Ayre, Kim K; Johns, Annie F; Harris, Meagan J; Stinson, Jonah M; Summers, Heather M
2017-01-01
Adaptive management has been presented as a method for the remediation, restoration, and protection of ecological systems. Recent reviews have found that the implementation of adaptive management has been unsuccessful in many instances. We present a modification of the model first formulated by Wyant and colleagues that puts ecological risk assessment into a central role in the adaptive management process. This construction has 3 overarching segments. Public engagement and governance determine the goals of society by identifying endpoints and specifying constraints such as costs. The research, engineering, risk assessment, and management section contains the decision loop estimating risk, evaluating options, specifying the monitoring program, and incorporating the data to re-evaluate risk. The 3rd component is the recognition that risk and public engagement can be altered by various externalities such as climate change, economics, technological developments, and population growth. We use the South River, Virginia, USA, study area and our previous research to illustrate each of these components. In our example, we use the Bayesian Network Relative Risk Model to estimate risks, evaluate remediation options, and provide lists of monitoring priorities. The research, engineering, risk assessment, and management loop also provides a structure in which data and the records of what worked and what did not, the learning process, can be stored. The learning process is a central part of adaptive management. We conclude that risk assessment can and should become an integral part of the adaptive management process. Integr Environ Assess Manag 2017;13:115-126. © 2016 SETAC.
A Model of Hierarchical Key Assignment Scheme
ZHANG Zhigang; ZHAO Jing; XU Maozhi
2006-01-01
A model of the hierarchical key assignment scheme is approached in this paper, which can be used with any cryptography algorithm. Besides, the optimal dynamic control property of a hierarchical key assignment scheme will be defined in this paper. Also, our scheme model will meet this property.
An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery
Xiangguang Leng
2016-08-01
Full Text Available 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.
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.
A NOVEL LINK ADAPTATION SCHEME TO ENHANCE PERFORMANCE OF IEEE 802.11G WIRELESS LAN
无
2006-01-01
A novel link adaptation scheme using linear Auto Regressive (AR) model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the low efficiency caused by time interval between the time when Received Signal Strength (RSS) is measured and the time when rate is selected. The best rate is selected based on data payload length, frame retry count and the estimated RSS, which is estimated from recorded RSSs. Simulation results show that the proposed scheme enhances mean throughput performance up to 7%, in saturation state,and up to 24% in finite load state compared with those non-estimation schemes, performance enhancements in average drop rate and average number of transmission attempts per data frame delivery also validate the effectiveness of the proposed scheme.
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.
2016-10-01
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.
An adaptive nonlocal means scheme for medical image denoising
Thaipanich, Tanaphol; Kuo, C.-C. Jay
2010-03-01
Medical images often consist of low-contrast objects corrupted by random noise arising in the image acquisition process. Thus, image denoising is one of the fundamental tasks required by medical imaging analysis. In this work, we investigate an adaptive denoising scheme based on the nonlocal (NL)-means algorithm for medical imaging applications. In contrast with the traditional NL-means algorithm, the proposed adaptive NL-means (ANL-means) denoising scheme has three unique features. First, it employs the singular value decomposition (SVD) method and the K-means clustering (K-means) technique for robust classification of blocks in noisy images. Second, the local window is adaptively adjusted to match the local property of a block. Finally, a rotated block matching algorithm is adopted for better similarity matching. Experimental results from both additive white Gaussian noise (AWGN) and Rician noise are given to demonstrate the superior performance of the proposed ANL denoising technique over various image denoising benchmarks in term of both PSNR and perceptual quality comparison.
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.
A RELIABILITY ENHANCED DENSITY ADAPTIVE DATA DISSEMINATION SCHEME FOR VANETS
Zhou Lianke; Cui Gang; Luo Danyan; Liu Hongwei
2011-01-01
In this paper,a reliability enhanced and density adaptive data disseminating scheme is proposed for Vehicular Ad hoc NETworks (VANETs).The distributed on demand inquiring and responding mechanism is employed to get nodes' connectivity information.The announcing-listening process is also designed to find the nodes with bigger additional degree to rebroadcast,by which the relaying node is selected freely from density's influence.Simultaneously,a reliability parameter is designed to choose redundant relays for each hop.According to the importance of the broadcast,the parameter is set by the source node properly.Simulation results show that the scheme has achieved good performances such as low forwarding ratio,short latency and low load.The broadcast coverage ratio is ensured against the influence of key link errors and relaying nodes failure by paying suitable additional communication.
Identification and adaptive control scheme using fuzzy parameterized linear filters
Papp, Z.
1998-01-01
A nonlinear fuzzy control structure enhanced with supervised learning and/or adaption is presented. Availability of at least a partial process model is assumed. Nonlinear process identification procedure is used to complete the partial model. Based on the identification model the system sensitivity
An adaptive interpolation scheme for molecular potential energy surfaces
Kowalewski, Markus; Larsson, Elisabeth; Heryudono, Alfa
2016-08-01
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 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.
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.
Modeling Students' Mathematics Using Steffe's Fraction Schemes
Norton, Anderson H.; McCloskey, Andrea V.
2008-01-01
Each year, more teachers learn about the successful intervention program known as Math Recovery (USMRC 2008; Wright 2003). The program uses Steffe's whole-number schemes to model, understand, and support children's development of whole-number reasoning. Readers are probably less familiar with Steffe's fraction schemes, which have proven similarly…
Investigating the scale-adaptivity of a shallow cumulus parameterization scheme with LES
Brast, Maren; Schemann, Vera; Neggers, Roel
2017-04-01
In this study we investigate the scale-adaptivity of a new parameterization scheme for shallow cumulus clouds in the gray zone. The Eddy-Diffusivity Multiple Mass-Flux (or ED(MF)n ) scheme is a bin-macrophysics scheme, in which subgrid transport is formulated in terms of discretized size densities. While scale-adaptivity in the ED-component is achieved using a pragmatic blending approach, the MF-component is filtered such that only the transport by plumes smaller than the grid size is maintained. For testing, ED(MF)n is implemented in a large-eddy simulation (LES) model, replacing the original subgrid-scheme for turbulent transport. LES thus plays the role of a non-hydrostatic testing ground, which can be run at different resolutions to study the behavior of the parameterization scheme in the boundary-layer gray zone. In this range convective cumulus clouds are partially resolved. We find that at high resolutions the clouds and the turbulent transport are predominantly resolved by the LES, and the transport represented by ED(MF)n is small. This partitioning changes towards coarser resolutions, with the representation of shallow cumulus clouds becoming exclusively carried by the ED(MF)n. The way the partitioning changes with grid-spacing matches the results of previous LES studies, suggesting some scale-adaptivity is captured. Sensitivity studies show that a scale-inadaptive ED component stays too active at high resolutions, and that the results are fairly insensitive to the number of transporting updrafts in the ED(MF)n scheme. Other assumptions in the scheme, such as the distribution of updrafts across sizes and the value of the area fraction covered by updrafts, are found to affect the location of the gray zone.
An Adaptive Estimation Scheme for Open-Circuit Voltage of Power Lithium-Ion Battery
Yun Zhang
2013-01-01
Full Text Available Open-circuit voltage (OCV is one of the most important parameters in determining state of charge (SoC of power battery. The direct measurement of it is costly and time consuming. This paper describes an adaptive scheme that can be used to derive OCV of the power battery. The scheme only uses the measurable input (terminal current and the measurable output (terminal voltage signals of the battery system and is simple enough to enable online implement. Firstly an equivalent circuit model is employed to describe the polarization characteristic and the dynamic behavior of the lithium-ion battery; the state-space representation of the electrical performance for the battery is obtained based on the equivalent circuit model. Then the implementation procedure of the adaptive scheme is given; also the asymptotic convergence of the observer error and the boundedness of all the parameter estimates are proven. Finally, experiments are carried out, and the effectiveness of the adaptive estimation scheme is validated by the experimental results.
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.
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 Variable Structure Control Scheme for Underactuated Mechanical Manipulators
Jung Hua Yang
2012-01-01
Full Text Available Mechanical arms have been widely used in the industry for many decades. They have played a dominant role in factory automation. However the control performance, or even system stability, would be deteriorated if some of the actuators fail during the operations. Hence, in this study, an adaptive variable structure scheme is presented to solve this problem. It is shown that, by applying the control mechanism proposed in this paper, the motion of robot systems can maintain asymptotical stability in case of actuators failure. The control algorithms as well as the convergence analysis are theoretically proved based on Lyapunov theory. In addition, to demonstrate the validity of the controller, a number of simulations as well as real-time experiments are also performed for Pendubot robot and Furuta robot systems. The results confirm the applicability of the proposed controller.
A SUBDIVISION SCHEME FOR VOLUMETRIC MODELS
GhulamMustafa; LiuXuefeng
2005-01-01
In this paper, a subdivision scheme which generalizes a surface scheme in previous papers to volume meshes is designed. The scheme exhibits significant control over shrink-age/size of volumetric models. It also has the ability to conveniently incorporate boundaries and creases into a smooth limit shape of models. The method presented here is much simpler and easier as compared to MacCracken and Joy's. This method makes no restrictions on the local topology of meshes. Particularly, it can be applied without any change to meshes of nonmanifold topology.
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.
A.M. Ibrahim
2016-09-01
Full Text Available This paper presents an adaptive protection coordination scheme for optimal coordination of DOCRs in interconnected power networks with the impact of DG, the used coordination technique is the Artificial Bee Colony (ABC. The scheme adapts to system changes; new relays settings are obtained as generation-level or system-topology changes. The developed adaptive scheme is applied on the IEEE 30-bus test system for both single- and multi-DG existence where results are shown and discussed.
HUANG Chih-wei; HWANG Jenq-neng
2006-01-01
With the rapid growth of wireless broadband technologies, such as WLAN and WiMAX, quality streaming video contents are available through portable devices anytime, anywhere. The layered multicast system using scalable video codecs has been proposed as an efficient architecture for video dissemination taking account of user and link diversities. However, in the wired/wireless combined best-effort based heterogeneous IP networks which provide more fluctuation in available bandwidth and end-to-end delay, the performance of streaming systems has been greatly degraded due to frequent packet loss, resulting from either wired congestion or wireless fading/shadowing. In this paper, we present a real-time embedded packet train probing scheme for estimating end-to-end available bandwidth so as to accomplish effective congestion and error control. This is facilitated by effective classification of packet loss sources, delay trend detection algorithm and flexible transmission rate of packets. Under the proper wireless channel modelling and estimation, our layered structure can allow appropriate subscription of video layers and adaptively insert necessary amount of forward error correction (FEC) packets so as to achieve QoS optimized system for scalable video multicasting.
Chaos Synchronization in the Belousov—Zhabotinsky Chemical Reaction by Adaptive Control Scheme
李艳妮; 陈兰; 等
2002-01-01
The adaptive synchronization sc heme proposed by John and Amritkar was employed into the Belousov-Zhabotinsky（BZ)4-varibale-Montanator model system.By the parameter adjustment,chaos synchroniztion has been obtained ,Through calculating the transient time,the optimal combination of the stiffness constant and damping constant was obtained .Furthermore,the relationships among the transient time,conditional Lyapunov exponents,the stiffiness constant and damping constant were discussed ,Also ,the BZ system with the adaptive synchronization scheme might be used for the communication purposes.
Adaptive codebook selection schemes for image classification in correlated channels
Hu, Chia Chang; Liu, Xiang Lian; Liu, Kuan-Fu
2015-09-01
The multiple-input multiple-output (MIMO) system with the use of transmit and receive antenna arrays achieves diversity and array gains via transmit beamforming. Due to the absence of full channel state information (CSI) at the transmitter, the transmit beamforming vector can be quantized at the receiver and sent back to the transmitter by a low-rate feedback channel, called limited feedback beamforming. One of the key roles of Vector Quantization (VQ) is how to generate a good codebook such that the distortion between the original image and the reconstructed image is the minimized. In this paper, a novel adaptive codebook selection scheme for image classification is proposed with taking both spatial and temporal correlation inherent in the channel into consideration. The new codebook selection algorithm is developed to select two codebooks from the discrete Fourier transform (DFT) codebook, the generalized Lloyd algorithm (GLA) codebook and the Grassmannian codebook to be combined and used as candidates of the original image and the reconstructed image for image transmission. The channel is estimated and divided into four regions based on the spatial and temporal correlation of the channel and an appropriate codebook is assigned to each region. The proposed method can efficiently reduce the required information of feedback under the spatially and temporally correlated channels, where each region is adaptively. Simulation results show that in the case of temporally and spatially correlated channels, the bit-error-rate (BER) performance can be improved substantially by the proposed algorithm compared to the one with only single codebook.
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.
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.
Adaptive Bit Loading Scheme with Semi-Blind Channel Estimation for OFDM Systems
LI Ying; SU Guang-chuan
2006-01-01
An adaptive bit loading and power-allocation scheme is proposed in order to augment the performance of the system based on orthogonal frequency division multiplexing (OFDM), which is based on the maximum power margin. Coinciding with the adaptive loading scheme, a semi-blind channel estimation algorithm using subspace decomposition method is proposed, which uses the information in the cyclic prefix. An initial channel state information is estimated by using the training sequences with the method of interpolation filtering. The proposed adaptive scheme is simulated on an OFDM wireless local area network(WLAN) system in a time-varying channel. The performance is compared to the constant loading scheme.
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.
2014-10-01
Number: SET 2015-0030 412 TW-PA-14481 Adaptive Modulation Schemes for OFDM and...SUBTITLE Adaptive Modulation Schemes for OFDM and SOQPSK Using Error Vector Magnitude (EVM) and Godard Dispersion 5a. CONTRACT NUMBER: W900KK-13-C...schemes of OFDM and SOQPSK? • Possible Approaches: • Find a common metric that applies for both OFDM and SOQPSK • Find the relationship between two
Group Buying Schemes : A Sustainable Business Model?
Köpp, Sebastian; Mukhachou, Aliaksei; Schwaninger, Markus
2013-01-01
Die Autoren gehen der Frage nach, ob "Group Buying Schemes" wie beispielsweise von den Unternehmen Groupon und Dein Deal angeboten, ein nachhaltiges Geschäftsmodell sind. Anhand der Fallstudie Groupon wird mit einem System Dynamics Modell festgestellt, dass das Geschäftsmodell geändert werden muss, wenn die Unternehmung auf Dauer lebensfähig sein soll. The authors examine if group buying schemes are a sustainable business model. By means of the Groupon case study and using a System Dynami...
ADAPTIVE LIFTING BASED IMAGE COMPRESSION SCHEME WITH PARTICLE SWARM OPTIMIZATION TECHNIQUE
Nishat kanvel
2010-09-01
Full Text Available 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.
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...... system were constructed and linearized. Controllers are implemented and tested on the manipulator. Pressure feedback was found to greatly improve system stability margins. Passive gain feedforward shows improved tracking performance for small changes in load pressure. For large changes in load pressure......, active gain feedforward shows a slightly improved performance. Computed-Torque Control shows better performance, but requires a well described system for best performance. A novel Adaptive Inverse Dynamics Controller was tested and the performance was found to be similar to that of Computed...
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.
A Modified Model Predictive Control Scheme
Xiao-Bing Hu; Wen-Hua Chen
2005-01-01
In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offline LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offline so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach.
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.
Yasui, Kotaro; Sakai, Kazuhiko; Kano, Takeshi; Owaki, Dai; Ishiguro, Akio
2017-01-01
Recently, myriapods have attracted the attention of engineers because mobile robots that mimic them potentially have the capability of producing highly stable, adaptive, and resilient behaviors. The major challenge here is to develop a control scheme that can coordinate their numerous legs in real time, and an autonomous decentralized control could be the key to solve this problem. Therefore, we focus on real centipedes and aim to design a decentralized control scheme for myriapod robots by drawing inspiration from behavioral experiments on centipede locomotion under unusual conditions. In the behavioral experiments, we observed the response to the removal of a part of the terrain and to amputation of several legs. Further, we determined that the ground reaction force is significant for generating rhythmic leg movements; the motion of each leg is likely affected by a sensory input from its neighboring legs. Thus, we constructed a two-dimensional model wherein a simple local reflexive mechanism was implemented in each leg. We performed simulations by using this model and demonstrated that the myriapod robot could move adaptively to changes in the environment and body properties. Our findings will shed new light on designing adaptive and resilient myriapod robots that can function under various circumstances. PMID:28152103
A Distributed and Adaptive Location Management Scheme for Hierarchical Mobility Management
无
2006-01-01
Hierarchical mobility management is sensitive to the failure of gateway mobility agents and prone to degrade performance on heavy loads. This paper proposes a distributed and adaptive location management scheme based on Hierarchical Mobile IPv6. This scheme can balance the loads of mobility anchor points and increase the robustness of the hierarchical structure to certain extents. In this scheme, the optimized IP paging scheme is adopted to reduce the paging signaling cost and improve the scalability of the hierarchical mobility management. We implement the distributed and adaptive location management scheme in a simulation platform and compare its performance with that of two other location management schemes. Our simulation results show that our scheme is capable of balancing the signaling and traffic loads of mobility ancher points, decreasing the average handover latency, and increasing the throughout of the visited networks.
Campa, Alessandro; Esposito, Giuseppe; Belli, Mauro
Cellular response to radiation is often modified by a previous delivery of a small "priming" dose: a smaller amount of damage, defined by the end point being investigated, is observed, and for this reason the effect is called adaptive response. An improved understanding of this effect is essential (as much as for the case of the bystander effect) for a reliable radiation risk assessment when low dose irradiations are involved. Experiments on adaptive response have shown that there are a number of factors that strongly influence the occurrence (and the level) of the adaptation. In particular, priming doses and dose rates have to fall in defined ranges; the same is true for the time interval between the delivery of the small priming dose and the irradiation with the main, larger, dose (called in this case challenging dose). Different hypotheses can be formulated on the main mechanism(s) determining the adaptive response: an increased efficiency of DNA repair, an increased level of antioxidant enzymes, an alteration of cell cycle progression, a chromatin conformation change. An experimental clearcut evidence going definitely in the direction of one of these explanations is not yet available. Modelling can be done at different levels. Simple models, relating the amount of damage, through elementary differential equations, to the dose and dose rate experienced by the cell, are relatively easy to handle, and they can be modified to account for the priming irradiation. However, this can hardly be of decisive help in the explanation of the mechanisms, since each parameter of these models often incorporates in an effective way several cellular processes related to the response to radiation. In this presentation we show our attempts to describe adaptive response with models that explicitly contain, as a dynamical variable, the inducible adaptive agent. At a price of a more difficult treatment, this approach is probably more prone to give support to the experimental studies
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.
Adapted Active Appearance Models
Renaud Séguier
2009-01-01
Full Text Available Active Appearance Models (AAMs are able to align efficiently known faces under duress, when face pose and illumination are controlled. We propose Adapted Active Appearance Models to align unknown faces in unknown poses and illuminations. Our proposal is based on the one hand on a specific transformation of the active model texture in an oriented map, which changes the AAM normalization process; on the other hand on the research made in a set of different precomputed models related to the most adapted AAM for an unknown face. Tests on public and private databases show the interest of our approach. It becomes possible to align unknown faces in real-time situations, in which light and pose are not controlled.
An Adaptive Scheme for Neighbor Discovery in Mobile Ad Hoc Networks
无
2007-01-01
The neighbor knowledge in mobile ad hoc networks is important information. However, the accuracy of neighbor knowledge is paid in terms of energy consumption. In traditional schemes for neighbor discovery, a mobile node uses fixed period to send HELLO messages to notify its existence. An adaptive scheme was proposed.The objective is that when mobile nodes are distributed sparsely or move slowly, fewer HELLO messages are needed to achieve reasonable accuracy, while in a mutable network where nodes are dense or move quickly, they can adaptively send more HELLO messages to ensure the accuracy. Simulation results show that the adaptive scheme achieves the objective and performs effectively.
Adaptive Digital Predistortion Schemes to Linearize RF Power Amplifiers with Memory Effects
ZHANG Peng; WU Si-liang; ZHANG Qin
2008-01-01
To compensate for nonlinear distortion introduced by RF power amplifiers (PAs) with memory effects, two correlated models, namely an extended memory polynomial (EMP) model and a memory lookup table (LUT) model, are proposed for predistorter design. Two adaptive digital predistortion (ADPD) schemes with indirect learning architecture are presented. One adopts the EMP model and the recursive least square (RLS) algorithm, and the other utilizes the memory LUT model and the least mean square (LMS) algorithm. Simulation results demonstrate that the EMP-based ADPD yields the best linearization performance in terms of suppressing spectral regrowth. It is also shown that the ADPD based on memory LUT makes optimum tradeoff between performance and computational complexity.
A Rate Adaptation Scheme According to Channel Conditions in Wireless LANs
Numoto, Daisuke; Inai, Hiroshi
Rate adaptation in wireless LANs is to select the most suitable transmission rate automatically according to channel condition. If the channel condition is good, a station can choose a higher transmission rate, otherwise, it should choose a lower but noise-resistant transmission rate. Since IEEE 802.11 does not specify any rate adaptation scheme, several schemes have been proposed. However those schemes provide low throughput or unfair transmission opportunities among stations especially when the number of stations increases. In this paper, we propose a rate adaptation scheme under which the transmission rate quickly closes and then stays around an optimum rate even in the presence of a large number of stations. Via simulation, our scheme provides higher throughput than existing ones and almost equal fairness.
ADAPTIVE FILTER FOR SYSTEM IDENTIFICATION USING QUANTIZATION SCHEMES
Nitesh Mudgal
2012-03-01
Full Text Available The Least Mean Square (LMS Algorithm finds its application in System identification due to its simplicity.Reduction of the complexity of Adaptive Finite Impulse Response(FIR filter had received attention in the area of adative filter. This paper proposes methods of system identification using adaptive filter which are based on a Quantised version of the LMS, namely the Clipped Least Mean Square (CLMS and Modified Clipped Least Mean Square( QX-LMS algorithms. In both Algorithms coefficients of the adaptive filter are adjusted automatically by an adaptive algorithm based on the input signals. This property makes the adaptive filter has an important application in system identification.the Quantized version of Least Mean Square Algorithm increases covergence property as compared to normal Least Mean Square Algorithm.
Evaluation of a Neural-Network-Based adaptive Beamforming Scheme with Magnitude-Only Constraints
Castaldi, G.; Galdi, V.; Gerini, G.
2009-01-01
In this paper, we present an adaptive beamforming scheme for smart antenna arrays in the presence of several desired and interfering signals, and additive white Gaussian noise. As compared with standard schemes, the proposed algorithm minimizes the noise and interference contributions, but enforces
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 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.
High order discretization schemes for stochastic volatility models
Jourdain, Benjamin
2009-01-01
In usual stochastic volatility models, the process driving the volatility of the asset price evolves according to an autonomous one-dimensional stochastic differential equation. We assume that the coefficients of this equation are smooth. Using It\\^o's formula, we get rid, in the asset price dynamics, of the stochastic integral with respect to the Brownian motion driving this SDE. Taking advantage of this structure, we propose - a scheme, based on the Milstein discretization of this SDE, with order one of weak trajectorial convergence for the asset price, - a scheme, based on the Ninomiya-Victoir discretization of this SDE, with order two of weak convergence for the asset price. We also propose a specific scheme with improved convergence properties when the volatility of the asset price is driven by an Orstein-Uhlenbeck process. We confirm the theoretical rates of convergence by numerical experiments and show that our schemes are well adapted to the multilevel Monte Carlo method introduced by Giles [2008a,b].
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.
Raul, Pramod R; Pagilla, Prabhakar R
2015-05-01
In this paper, two adaptive Proportional-Integral (PI) control schemes are designed and discussed for control of web tension in Roll-to-Roll (R2R) manufacturing systems. R2R systems are used to transport continuous materials (called webs) on rollers from the unwind roll to the rewind roll. Maintaining web tension at the desired value is critical to many R2R processes such as printing, coating, lamination, etc. Existing fixed gain PI tension control schemes currently used in industrial practice require extensive tuning and do not provide the desired performance for changing operating conditions and material properties. The first adaptive PI scheme utilizes the model reference approach where the controller gains are estimated based on matching of the actual closed-loop tension control systems with an appropriately chosen reference model. The second adaptive PI scheme utilizes the indirect adaptive control approach together with relay feedback technique to automatically initialize the adaptive PI gains. These adaptive tension control schemes can be implemented on any R2R manufacturing system. The key features of the two adaptive schemes is that their designs are simple for practicing engineers, easy to implement in real-time, and automate the tuning process. Extensive experiments are conducted on a large experimental R2R machine which mimics many features of an industrial R2R machine. These experiments include trials with two different polymer webs and a variety of operating conditions. Implementation guidelines are provided for both adaptive schemes. Experimental results comparing the two adaptive schemes and a fixed gain PI tension control scheme used in industrial practice are provided and discussed.
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.
A Practical Adaptive TuCM Scheme for Rayleigh Flat Fading Channels
伍守豪; 宋文涛
2004-01-01
A practical adaptive turbo coded modulation (TuCM) scheme was proposed and its adaptive method was described. With some hardware considerations, a suboptimal optimization algorithm that the number of fading regions is variable was put forward. Furthermore, the cutoff fade depth of power adaptation was modified to reduce the interruption probability. The results show that the proposed adaptive TuCM comes within 3 dB of Rayleigh fading channel capacity, and exhibits about 3 dB power gain relative to the conventional adaptive trellis-coded modulation (TCM), and is easy to realize by hardware.
Moment Preserving Adaptive Particle Weighting Scheme for PIC Simulations
2012-07-01
Analytical Solution for Density, n(x, t) Crank-Nicolson Particle Simulations C-N is Stable and Non -Dissipative for Re(λ)=0 φ x av T E = T+φ = const. JEAN...Reproduces 3-4 Orders of Magnitude Random Merge -> Thermalization 3000 First Point, 1500 First Cross Bi- Maxwellian Specifically Difficult Octree Merge...3000 First Point, 1500 First Cross Bi- Maxwellian Specifically Difficult Octree Merge Significantly Better Merge & Split Adapts Particle Count Despite
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.
A modified adaptive compensation scheme for nonlinear bandlimited satellite channels
Feng, Gang; Li, Le-Min; Wu, Shi-Qi
The authors propose a modified algorithm for an adaptive predistorter (APD) to compensate for the nonlinear distortion encountered in a satellite channel. They describe a recursive algorithm for an APD in rectangular coordinates and give the structure for implementation of the algorithm. A modified recursive algorithm which is called the sign algorithm and the structure for implementation are proposed. Computer simulation results show that the sign algorithm is effective for the compensation of nonlinear satellite channels. The modified algorithm is based on the rectangular representation of data symbols.
Estimation of Stator winding faults in induction motors using an adaptive observer scheme
Kallesøe, C. S.; Vadstrup, P.; Rasmussen, Henrik;
2004-01-01
This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit...... and an expression of the current in the short circuit. Moreover the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has happened in the motor. To be able to develop this observer, a model particular suitable for the chosen observer design, is also...... derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate inter-turn short circuit faults....
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.
ADER-WENO finite volume schemes with space-time adaptive mesh refinement
Dumbser, Michael; Zanotti, Olindo; Hidalgo, Arturo; Balsara, Dinshaw S.
2013-09-01
We present the first high order one-step ADER-WENO finite volume scheme with adaptive mesh refinement (AMR) in multiple space dimensions. High order spatial accuracy is obtained through a WENO reconstruction, while a high order one-step time discretization is achieved using a local space-time discontinuous Galerkin predictor method. Due to the one-step nature of the underlying scheme, the resulting algorithm is particularly well suited for an AMR strategy on space-time adaptive meshes, i.e. with time-accurate local time stepping. The AMR property has been implemented 'cell-by-cell', with a standard tree-type algorithm, while the scheme has been parallelized via the message passing interface (MPI) paradigm. The new scheme has been tested over a wide range of examples for nonlinear systems of hyperbolic conservation laws, including the classical Euler equations of compressible gas dynamics and the equations of magnetohydrodynamics (MHD). High order in space and time have been confirmed via a numerical convergence study and a detailed analysis of the computational speed-up with respect to highly refined uniform meshes is also presented. We also show test problems where the presented high order AMR scheme behaves clearly better than traditional second order AMR methods. The proposed scheme that combines for the first time high order ADER methods with space-time adaptive grids in two and three space dimensions is likely to become a useful tool in several fields of computational physics, applied mathematics and mechanics.
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.
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...
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.
Chen, Xianshun; Feng, Liang; Ong, Yew Soon
2012-07-01
In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.
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.
Multiple-Model Adaptive Switching Control for Uncertain Multivariable Systems
Baldi, Simone; Battistelli, Giorgio; Mari, Daniele; Mosca, Edoardo; Tesi, Pietro
2011-01-01
This paper addresses the problem of controlling an uncertain multi-input multi-output (MIMO) system by means of adaptive switching control schemes. In particular, the paper aims at extending the approach of multiple-model unfalsified adaptive switched control, so far restricted to single-input singl
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.
Adaptive Numerical Algorithms in Space Weather Modeling
Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.; Stout, Quentin F.; Glocer, Alex; Ma, Ying-Juan; Opher, Merav
2010-01-01
Space weather describes the various processes in the Sun-Earth system that present danger to human health and technology. The goal of space weather forecasting is to provide an opportunity to mitigate these negative effects. Physics-based space weather modeling is characterized by disparate temporal and spatial scales as well as by different physics in different domains. A multi-physics system can be modeled by a software framework comprising of several components. Each component corresponds to a physics domain, and each component is represented by one or more numerical models. The publicly available Space Weather Modeling Framework (SWMF) can execute and couple together several components distributed over a parallel machine in a flexible and efficient manner. The framework also allows resolving disparate spatial and temporal scales with independent spatial and temporal discretizations in the various models. Several of the computationally most expensive domains of the framework are modeled by the Block-Adaptive Tree Solar wind Roe Upwind Scheme (BATS-R-US) code that can solve various forms of the magnetohydrodynamics (MHD) equations, including Hall, semi-relativistic, multi-species and multi-fluid MHD, anisotropic pressure, radiative transport and heat conduction. Modeling disparate scales within BATS-R-US is achieved by a block-adaptive mesh both in Cartesian and generalized coordinates. Most recently we have created a new core for BATS-R-US: the Block-Adaptive Tree Library (BATL) that provides a general toolkit for creating, load balancing and message passing in a 1, 2 or 3 dimensional block-adaptive grid. We describe the algorithms of BATL and demonstrate its efficiency and scaling properties for various problems. BATS-R-US uses several time-integration schemes to address multiple time-scales: explicit time stepping with fixed or local time steps, partially steady-state evolution, point-implicit, semi-implicit, explicit/implicit, and fully implicit numerical
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...
Adaptive Test Schemes for Control of Paratuberculosis in Dairy Cows
Kirkeby, Carsten Thure; Græsbøll, Kaare; Nielsen, Søren Saxmose
2016-01-01
through a variety of test-strategies, but are challenged by the lack of perfect tests. Frequent testing increases the sensitivity but the costs of testing are a cause of concern for farmers. Here, we used a herd simulation model using milk ELISA tests to evaluate the epidemiological and economic...
What Drives Business Model Adaptation?
Saebi, Tina; Lien, Lasse B.; Foss, Nicolai Juul
2016-01-01
-rigidity as well as prospect theory to examine business model adaptation in response to external threats and opportunities. Additionally, drawing on the behavioural theory of the firm, we argue that the past strategic orientation of a firm creates path dependencies that influence the propensity of the firm...... to adapt its business model. We test our hypotheses on a sample of 1196 Norwegian companies, and find that firms are more likely to adapt their business model under conditions of perceived threats than opportunities, and that strategic orientation geared towards market development is more conducive......Business models change as managers not only innovate business models, but also engage in more mundane adaptation in response to external changes, such as changes in the level or composition of demand. However, little is known about what causes such business model adaptation. We employ threat...
Adaptive Test Schemes for Control of Paratuberculosis in Dairy Cows
Kirkeby, Carsten Thure; Græsbøll, Kaare; Nielsen, Søren Saxmose;
2016-01-01
Paratuberculosis is a chronic infection that in dairy cattle causes reduced milk yield, weight loss, and ultimately fatal diarrhea. Subclinical animals can excrete bacteria (Mycobacterium avium ssp. paratuberculosis, MAP) in feces and infect other animals. Farmers identify the infectious animals...... through a variety of test-strategies, but are challenged by the lack of perfect tests. Frequent testing increases the sensitivity but the costs of testing are a cause of concern for farmers. Here, we used a herd simulation model using milk ELISA tests to evaluate the epidemiological and economic...
A Self-adaptive Scope Allocation Scheme for Labeling Dynamic XML Documents
Shen, Y.; Feng, L.; Shen, T.; Wang, B.
2004-01-01
This paper proposes a self-adaptive scope allocation scheme for labeling dynamic XML documents. It is general, light-weight and can be built upon existing data retrieval mechanisms. Bayesian inference is used to compute the actual scope allocated for labeling a certain node based on both the prior i
Estimation of Stator Winding Faults in Induction Motors using an Adaptive Observer Scheme
Kallesøe, C. S.; Vadstrup, P.; Rasmussen, Henrik
2004-01-01
This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit a...
Block-Based Adaptive Vector Lifting Schemes for Multichannel Image Coding
Amel Benazza-Benyahia
2007-04-01
Full Text Available We are interested in lossless and progressive coding of multispectral images. To this respect, nonseparable vector lifting schemes are used in order to exploit simultaneously the spatial and the interchannel similarities. The involved operators are adapted to the image contents thanks to block-based procedures grounded on an entropy optimization criterion. A vector encoding technique derived from EZW allows us to further improve the efficiency of the proposed approach. Simulation tests performed on remote sensing images show that a significant gain in terms of bit rate is achieved by the resulting adaptive coding method with respect to the non-adaptive one.
Block-Based Adaptive Vector Lifting Schemes for Multichannel Image Coding
Pesquet Jean-Christophe
2007-01-01
Full Text Available We are interested in lossless and progressive coding of multispectral images. To this respect, nonseparable vector lifting schemes are used in order to exploit simultaneously the spatial and the interchannel similarities. The involved operators are adapted to the image contents thanks to block-based procedures grounded on an entropy optimization criterion. A vector encoding technique derived from EZW allows us to further improve the efficiency of the proposed approach. Simulation tests performed on remote sensing images show that a significant gain in terms of bit rate is achieved by the resulting adaptive coding method with respect to the non-adaptive one.
A stable interface element scheme for the p-adaptive lifting collocation penalty formulation
Cagnone, J. S.; Nadarajah, S. K.
2012-02-01
This paper presents a procedure for adaptive polynomial refinement in the context of the lifting collocation penalty (LCP) formulation. The LCP scheme is a high-order unstructured discretization method unifying the discontinuous Galerkin, spectral volume, and spectral difference schemes in single differential formulation. Due to the differential nature of the scheme, the treatment of inter-cell fluxes for spatially varying polynomial approximations is not straightforward. Specially designed elements are proposed to tackle non-conforming polynomial approximations. These elements are constructed such that a conforming interface between polynomial approximations of different degrees is recovered. The stability and conservation properties of the scheme are analyzed and various inviscid compressible flow calculations are performed to demonstrate the potential of the proposed approach.
Context-Adaptive Arithmetic Coding Scheme for Lossless Bit Rate Reduction of MPEG Surround in USAC
Yoon, Sungyong; Pang, Hee-Suk; Sung, Koeng-Mo
We propose a new coding scheme for lossless bit rate reduction of the MPEG Surround module in unified speech and audio coding (USAC). The proposed scheme is based on context-adaptive arithmetic coding for efficient bit stream composition of spatial parameters. Experiments show that it achieves the significant lossless bit reduction of 9.93% to 12.14% for spatial parameters and 8.64% to 8.96% for the overall MPEG Surround bit streams compared to the original scheme. The proposed scheme, which is not currently included in USAC, can be used for the improved coding efficiency of MPEG Surround in USAC, where the saved bits can be utilized by the other modules in USAC.
Adaptivity with near-orthogonality constraint for high compression rates in lifting scheme framework
Sliwa, Tadeusz; Voisin, Yvon; Diou, Alain
2004-01-01
Since few years, Lifting Scheme has proven its utility in compression field. It permits to easily create fast, reversible, separable or no, not necessarily linear, multiresolution analysis for sound, image, video or even 3D graphics. An interesting feature of lifting scheme is the ability to build adaptive transforms for compression, more easily than with other decompositions. Many works have already be done in this subject, especially in lossless or near-lossless compression framework : better compression than with usually used methods can be obtained. However, most of the techniques used in adaptive near-lossless compression can not be extended to higher lossy compression rates, even in the simplest cases. Indeed, this is due to the quantization error introduced before coding, which has not controlled propagation through inverse transform. Authors have put their interest to the classical Lifting Scheme, with linear convolution filters, but they studied criterions to maintain a high level of adaptivity and a good error propagation through inverse transform. This article aims to present relatively simple criterion to obtain filters able to build image and video compression with high compression rate, tested here with the Spiht coder. For this, upgrade and predict filters are simultaneously adapted thanks to a constrained least-square method. The constraint consists in a near-orthogonality inequality, letting sufficiently high level of adaptivity. Some compression results are given, illustrating relevance of this method, even with short filters.
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
Blonbou, Ruddy, E-mail: ruddy.blonbou@univ-ag.f [Geosciences and Energy Research Laboratory, Universite des Antilles et de la Guyane, Guadeloupe (France); Monjoly, Stephanie; Dorville, Jean-Francois [Geosciences and Energy Research Laboratory, Universite des Antilles et de la Guyane, Guadeloupe (France)
2011-06-15
Research highlights: {yields} We develop a real time algorithm for grid-connected wind energy storage management. {yields} The method aims to guarantee, with {+-}5% error margin, the power sent to the grid. {yields} Dynamic scheduling of energy storage is based on short-term energy prediction. {yields} 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.
Modeling and Simulation of Downlink Subcarrier Allocation Schemes in LTE
Popovska Avramova, Andrijana; Yan, Ying; Dittmann, Lars
2012-01-01
The efficient utilization of the air interface in the LTE standard is achieved through a combination of subcarrier allocation schemes, adaptive modulation and coding, and transmission power allotment. The scheduler in the base station has a major role in achieving the required QoS and the overall...
An adaptive semi-implicit scheme for simulations of unsteady viscous compressible flows
Steinthorsson, Erlendur; Modiano, David; Crutchfield, William Y.; Bell, John B.; Colella, Phillip
1995-11-01
A numerical scheme for simulation of unsteady, viscous, compressible flows is considered. The scheme employs an explicit discretization of the inviscid terms of the Navier-Stokes equations and an implicit discretization of the viscous terms. The discretization is second order accurate in both space and time. Under appropriate assumptions, the implicit system of equations can be decoupled into two linear systems of reduced rank. These are solved efficiently using a Gauss-Seidel method with multigrid convergence acceleration. When coupled with a solution-adaptive mesh refinement technique, the hybrid explicit-implicit scheme provides an effective methodology for accurate simulations of unsteady viscous flows. The methodology is demonstrated for both body-fitted structured grids and for rectangular (Cartesian) grids.
Universal adaptive self-stabilizing traversal scheme: random walk and reloading wave
Bernard, Thibault; Sohier, Devan
2011-01-01
In this paper, we investigate random walk based token circulation in dynamic environments subject to failures. We describe hypotheses on the dynamic environment that allow random walks to meet the important property that the token visits any node infinitely often. The randomness of this scheme allows it to work on any topology, and require no adaptation after a topological change, which is a desirable property for applications to dynamic systems. For random walks to be a traversal scheme and to answer the concurrence problem, one needs to guarantee that exactly one token circulates in the system. In the presence of transient failures, configurations with multiple tokens or with no token can occur. The meeting property of random walks solves the cases with multiple tokens. The reloading wave mechanism we propose, together with timeouts, allows to detect and solve cases with no token. This traversal scheme is self-stabilizing, and universal, meaning that it needs no assumption on the system topology. We describ...
An adaptive scaling and biasing scheme for OFDM-based visible light communication systems.
Wang, Zhaocheng; Wang, Qi; Chen, Sheng; Hanzo, Lajos
2014-05-19
Orthogonal frequency-division multiplexing (OFDM) has been widely used in visible light communication systems to achieve high-rate data transmission. Due to the nonlinear transfer characteristics of light emitting diodes (LEDs) and owing the high peak-to-average-power ratio of OFDM signals, the transmitted signal has to be scaled and biased before modulating the LEDs. In this contribution, an adaptive scaling and biasing scheme is proposed for OFDM-based visible light communication systems, which fully exploits the dynamic range of the LEDs and improves the achievable system performance. Specifically, the proposed scheme calculates near-optimal scaling and biasing factors for each specific OFDM symbol according to the distribution of the signals, which strikes an attractive trade-off between the effective signal power and the clipping-distortion power. Our simulation results demonstrate that the proposed scheme significantly improves the performance without changing the LED's emitted power, while maintaining the same receiver structure.
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.
Yavuz Ates
2016-05-01
Full Text Available The renewable energy-based distributed generation (DG implementation in power systems has been an active research area during the last few decades due to several environmental, economic and political factors. Although the integration of DG offers many advantages, several concerns, including protection schemes in systems with the possibility of bi-directional power flow, are raised. Thus, new protection schemes are strongly required in power systems with a significant presence of DG. In this study, an adaptive protection strategy for a distribution system with DG integration is proposed. The proposed strategy considers both grid-connected and islanded operating modes, while the adaptive operation of the protection is dynamically realized considering the availability of DG power production (related to faults or meteorological conditions in each time step. Besides, the modular structure and fast response of the proposed strategy is validated via simulations conducted on the IEEE 13-node test system.
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.
An Adaptive Video Coding Control Scheme for Real-Time MPEG Applications
Hsia Shih-Chang
2003-01-01
Full Text Available This paper proposes a new rate control scheme to increase the coding efficiency for MPEG systems. Instead of using a static group of picture (GOP structure, we present an adaptive GOP structure that uses more P- and B-frame coding, while the temporal correlation among the video frames maintains high. When there is a scene change, we immediately insert intramode coding to reduce the prediction error. Moreover, an enhanced prediction frame is used to improve the coding quality in the adaptive GOP. This rate control algorithm can both achieve better coding efficiency and solve the scene change problem. Even if the coding bit rate is over the predefined level, this coding scheme does not require re-encoding for real-time systems. Simulations demonstrate that our proposed algorithm can achieve better quality than TM5, and satisfactory reliability for detecting scene changes.
Some fundamental problems for an energy conserving adaptive resolution molecular dynamics scheme
Site, L. Delle
2007-01-01
Adaptive resolution molecular dynamics (MD) schemes allow for changing the number of degrees of freedom on the fly and preserve the free exchange of particles between regions of different resolution. There are two main alternatives on how to design the algorithm to switch resolution using auxiliary ''switching'' functions; force based and potential energy based approach. In this work we show that, in the framework of classical MD, the latter presents fundamental conceptual problems which make...
ADER-WENO Finite Volume Schemes with Space-Time Adaptive Mesh Refinement
Dumbser, Michael; Hidalgo, Arturo; Balsara, Dinshaw S
2012-01-01
We present the first high order one-step ADER-WENO finite volume scheme with Adaptive Mesh Refinement (AMR) in multiple space dimensions. High order spatial accuracy is obtained through a WENO reconstruction, while a high order one-step time discretization is achieved using a local space-time discontinuous Galerkin predictor method. Due to the one-step nature of the underlying scheme, the resulting algorithm is particularly well suited for an AMR strategy on space-time adaptive meshes, i.e.with time-accurate local time stepping. The AMR property has been implemented 'cell-by-cell', with a standard tree-type algorithm, while the scheme has been parallelized via the Message Passing Interface (MPI) paradigm. The new scheme has been tested over a wide range of examples for nonlinear systems of hyperbolic conservation laws, including the classical Euler equations of compressible gas dynamics and the equations of magnetohydrodynamics (MHD). High order in space and time have been confirmed via a numerical convergenc...
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.
An Adaptive Checkpointing Scheme for Peer-to-Peer Based Volunteer Computing Work Flows
Ni, Lei
2007-01-01
Volunteer Computing, sometimes called Public Resource Computing, is an emerging computational model that is very suitable for work-pooled parallel processing. As more complex grid applications make use of work flows in their design and deployment it is reasonable to consider the impact of work flow deployment over a Volunteer Computing infrastructure. In this case, the inter work flow I/O can lead to a significant increase in I/O demands at the work pool server. A possible solution is the use of a Peer-to- Peer based parallel computing architecture to off-load this I/O demand to the workers; where the workers can fulfill some aspects of work flow coordination and I/O checking, etc. However, achieving robustness in such a large scale system is a challenging hurdle towards the decentralized execution of work flows and general parallel processes. To increase robustness, we propose and show the merits of using an adaptive checkpoint scheme that efficiently checkpoints the status of the parallel processes accordin...
Tang, Suhua; Shirazi, Mehdad N.; Shagdar, Oyunchimeg; Suzuki, Ryutaro; Obana, Sadao
In Mobile Ad hoc Networks (MANET) geographic routing is characterized by local forwarding decision. Links with a long progress are preferred under the greedy forwarding rule. However in a real system long links tend to have a high packet loss rate due to multipath fading. A sub-optimal solution may separately exploit path diversity or rate adaptation. In this paper we study channel efficiency of multi-hop forwarding and try to jointly optimize rate adaptation and forwarder selection in geographic routing by the tradeoff between progress and instantaneous rate. We define a new metric-Bit Transfer Speed (BTS)-as the ratio of the progress made towards the destination to the equivalent time taken to transfer a payload bit. This metric takes overhead, rate and progress into account. Then we propose a packet forwarding scheme that Opportunistically exploits both long Progress and Adaptive Rate (OPAR) by a cross-layer design of routing and MAC. In OPAR each node selects for a packet the forwarder with the highest BTS. The forwarder changes as local topology (progress), packet size (overhead ratio) or channel state (data rate) varies. Simulation results show that compared with the normalized advance (NADV) [7] scheme and contention-based forwarding (CBF) [17] scheme, OPAR has lower packet loss and can effectively reduce channel occupation time by over 30% in the scenario with moderate mobility speeds.
Near-orthogonal and adaptive affine lifting scheme on vector-valued signals
Sliwa, Tadeusz; Voisin, Yvon; Diou, Alain
2004-02-01
Lifting Scheme is actually a widely used second generation multi-resolution technique in image and video processing field. It permits to easily create fast, reversible, separable or no, not necessarily linear, multi-resolution analysis for sound, image, video or even 3D graphics. An interesting feature of lifting scheme is the ability to build adaptive transforms, more easily than with other decompositions. Many works have already be done in this subject, especially in lossless or near-lossless compression framework where there is no orthogonal constraint. However, some applications as lossy compression or de-noising requires well conditioned transforms. Indeed, this is due to the use of shrinking or quantization which has not controlled propagation through inverse transform. Authors have recently presented a technique permitting to determine some lifting scheme filters in order to obtain a high level of adaptivity combined with near-orthogonal properties, useful for most of these applications. Naturly coming into the adaptive near orthogonal framework, the point of interest of this article is affine algebraic filters. Color images and video have especially been studied through point of view of compression. In this way, the treatment of the vector aspect of signal, not only by processing channels independently, becomes the focus point of the article.
Navaro Pierre
2011-11-01
Full Text Available A new scheme for discretizing the P1 model on unstructured polygonal meshes is proposed. This scheme is designed such that its limit in the diffusion regime is the MPFA-O scheme which is proved to be a consistent variant of the Breil-Maire diffusion scheme. Numerical tests compare this scheme with a derived GLACE scheme for the P1 system. Un nouveau schéma de discrétisation du modèle P1 sur maillage non structuré composé de polygones est proposé. Ce schéma est construit pour que sa limite en régime diffusion soit le schéma MPFA-O qu’on démontre être une variante consistante du schéma de diffusion de Breil-Maire. Ce schéma est comparé sur des cas tests avec un schéma dérivé du schéma GLACE pour le modèle P1.
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.
2016-08-01
With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m-bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m-bonacci sequences to detect eavesdropping. Meanwhile, we encode m-bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications.
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.
A Fuzzy Identity-Based Signature Scheme from Lattices in the Standard Model
Chunli Yang
2014-01-01
Full Text Available A fuzzy identity-based signature (FIBS scheme allows a user with identity ID to issue a signature that could be verified with identity ID' if and only if ID and ID' lie within a certain distance. To obtain an FIBS scheme that can resist known quantum attacks, we use the double-trapdoor technique from ABB10a for secret key extracting and the vanishing trapdoor technique from Boyen10 for message signing. In addition, in order to reflect the functionality of fuzziness, Shamir secret sharing scheme is also used in our construction. In this paper, we propose an FIBS scheme from lattices and prove that this new scheme achieves strong unforgeability under selective chosen-identity and adaptive chosen-message attacks (SU-sID-CMA in the standard model. To the best of our knowledge, our scheme is not only the first FIBS scheme from lattices without random oracles but also the first FIBS scheme that achieves strong unforgeability.
Development and evaluation of novel forecasting adaptive ensemble model
C.M. Anish
2016-09-01
Full Text Available This paper proposes a new ensemble based adaptive forecasting structure for efficient different interval days' ahead prediction of five different asset values (NAV. In this approach three individual adaptive structures such as adaptive moving average (AMA, adaptive auto regressive moving average (AARMA and feedback radial basis function network (FRBF are employed to first train with conventional LMS, conventional forward-backward LMS and corresponding learning algorithm of FRBF respectively. After successful validation of each model the output obtained by each individual model is optimally weighted using Genetic algorithm (GA as well as particle swarm optimization (PSO based techniques to produce the best possible different days ahead prediction accuracy. Finally the results of prediction obtained of the NAV values are compared with the results obtained by individual predictors as well as by other four existing ensemble schemes. It is in general demonstrated that in all cases the proposed forecasting scheme outperforms other competitive methods.
Adaptive cyber-attack modeling system
Gonsalves, Paul G.; Dougherty, Edward T.
2006-05-01
The pervasiveness of software and networked information systems is evident across a broad spectrum of business and government sectors. Such reliance provides an ample opportunity not only for the nefarious exploits of lone wolf computer hackers, but for more systematic software attacks from organized entities. Much effort and focus has been placed on preventing and ameliorating network and OS attacks, a concomitant emphasis is required to address protection of mission critical software. Typical software protection technique and methodology evaluation and verification and validation (V&V) involves the use of a team of subject matter experts (SMEs) to mimic potential attackers or hackers. This manpower intensive, time-consuming, and potentially cost-prohibitive approach is not amenable to performing the necessary multiple non-subjective analyses required to support quantifying software protection levels. To facilitate the evaluation and V&V of software protection solutions, we have designed and developed a prototype adaptive cyber attack modeling system. Our approach integrates an off-line mechanism for rapid construction of Bayesian belief network (BN) attack models with an on-line model instantiation, adaptation and knowledge acquisition scheme. Off-line model construction is supported via a knowledge elicitation approach for identifying key domain requirements and a process for translating these requirements into a library of BN-based cyber-attack models. On-line attack modeling and knowledge acquisition is supported via BN evidence propagation and model parameter learning.
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
A Trust-Based Adaptive Probability Marking and Storage Traceback Scheme for WSNs.
Liu, Anfeng; Liu, Xiao; Long, Jun
2016-03-30
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%.
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...
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.
Adaptive visual attention model
Hügli, Heinz; Bur, Alexandre
2009-01-01
Visual attention, defined as the ability of a biological or artificial vision system to rapidly detect potentially relevant parts of a visual scene, provides a general purpose solution for low level feature detection in a vision architecture. Well considered for its universal detection behaviour, the general model of visual attention is suited for any environment but inferior to dedicated feature detectors in more specific environments. The goal of the development presented in this paper is t...
DING XIU-HUAN; FU ZHI-GUO; ZHANG SHU-GONG
2009-01-01
This paper proposes an XTR version of the Kurosawa-Desmedt scheme. Our scheme is secure against adaptive choeen-ciphertext attack under the XTR version of the Decisional Diffie-Hellman assumption in the standard model. Comparing efficiency between the Kurosawa-Desmedt scheme and the proposed XTR-Kurosawa-Desmedt scheme, we find that the proposed scheme is more efficient than the Kurosawa-Desmedt scheme both in communication and computation without compromising security.
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.
Load-adaptive frequency reuse scheme for inter-cell interference coordination in relay networks
CHEN Mu-qiong; JI Hong; LI Xi
2010-01-01
Cellular relay networks adopting orthogonal frequency division multiple(OFDM)technology has been widely accepted for next generation wireless communication due to its advantage in enlarging coverage scale as well as improving data rate.In order to improve the performance of user equipments(UEs)near the cell edge,especially to avoid the interference from inter-cell and intra cell,an enhanced soft frequency reuse scheme is adopted in this paper to assure inter-cell interference coordination(ICIC).Compared with traditional frequency allocation work,the proposed scheme is interference-aware and load-adaptive,which dynamically assigns available frequency among UES under certain schedule method in variable traffic load condition and mitigates interference using information provided by interference indicator.It can improve signal-to-interference plus noise ratio(SINR)of the UE in each sub channel thus enable the system achieve better throughput and blocking probability performance.Simulation results prove that the proposed scheme may achieve desirable performance on throughput,blocking probability and spectral utilization in the sector under different traffic load compared with other schemes.
Spatial model of lifting scheme in wavelet transforms and image compression
Wu, Yu; Li, Gang; Wang, Guoyin
2002-03-01
Wavelet transforms via lifting scheme are called the second-generation wavelet transforms. However, in some lifting schemes the coefficients are transformed using mathematical method from the first-generation wavelets, so the filters with better performance using in lifting are limited. The spatial structures of lifting scheme are also simple. For example, the classical lifting scheme, predicting-updating, is two-stage, and most researchers simply adopt this structure. In addition, in most design results the lifting filters are not only hard to get and also fixed. In our former work, we had presented a new three-stage lifting scheme, predicting-updating-adapting, and the results of filter design are no more fixed. In this paper, we continue to research the spatial model of lifting scheme. A group of general multi-stage lifting schemes are achieved and designed. All lifting filters are designed in spatial domain and proper mathematical methods are selected. Our designed coefficients are flexible and can be adjusted according to different data. We give the mathematical design details in this paper. Finally, all designed model of lifting are used in image compression and satisfactory results are achieved.
A modified symplectic PRK scheme for seismic wave modeling
Liu, Shaolin; Yang, Dinghui; Ma, Jian
2017-02-01
A new scheme for the temporal discretization of the seismic wave equation is constructed based on symplectic geometric theory and a modified strategy. The ordinary differential equation in terms of time, which is obtained after spatial discretization via the spectral-element method, is transformed into a Hamiltonian system. A symplectic partitioned Runge-Kutta (PRK) scheme is used to solve the Hamiltonian system. A term related to the multiplication of the spatial discretization operator with the seismic wave velocity vector is added into the symplectic PRK scheme to create a modified symplectic PRK scheme. The symplectic coefficients of the new scheme are determined via Taylor series expansion. The positive coefficients of the scheme indicate that its long-term computational capability is more powerful than that of conventional symplectic schemes. An exhaustive theoretical analysis reveals that the new scheme is highly stable and has low numerical dispersion. The results of three numerical experiments demonstrate the high efficiency of this method for seismic wave modeling.
Generic-Model-Based Description Scheme for MPEG-7
Deng Juan; Tan Hut; Chen Xin-meng
2004-01-01
We propose a new description scheme for MPEG7-: Generic-model-based Description Scheme to describe contents of audio, video, text and other sorts of multimedia.It uses a generic model as the description frame, which provides a simple but useful object-based structure. The main components of the description scheme are generic model, objects and object fcatures. The proposed description scheme is illustrated and exemplified by Extensible Markup Language.It aims at clarity and flexibility to support MPEG-7 applications such as query and edit. We demonstrate its feasibility and efficiency by presenting applications: Digital Broadcasting and Edit System (DEBS) and Non-linear Edit System (NLES) that already used the generic structure or will greatly benefit from it.
Xu Xiaorong; Zhang Jianwu; Huang Aiping; Jiang Bin
2012-01-01
An Adaptive Measurement Scheme (AMS) is investigated with Compressed Sensing (CS)theory in Cognitive Wireless Sensor Network (C-WSN).Local sensing information is collected via energy detection with Analog-to-Information Converter (AIC) at massive cognitive sensors,and sparse representation is considered with the exploration of spatial temporal correlation structure of detected signals.Adaptive measurement matrix is designed in AMS,which is based on maximum energy subset selection.Energy subset is calculated with sparse transformation of sensing information,and maximum energy subset is selected as the row vector of adaptive measurement matrix.In addition,the measurement matrix is constructed by orthogonalization of those selected row vectors,which also satisfies the Restricted Isometry Property (RIP) in CS theory.Orthogonal Matching Pursuit (OMP) reconstruction algorithm is implemented at sink node to recover original information.Simulation results are performed with the comparison of Random Measurement Scheme (RMS).It is revealed that,signal reconstruction effect based on AMS is superior to conventional RMS Gaussian measurement.Moreover,AMS has better detection performance than RMS at lower compression rate region,and it is suitable for large-scale C-WSN wideband spectrum sensing.
Doulamis, A; Doulamis, N; Ntalianis, K; Kollias, S
2003-01-01
In this paper, an unsupervised video object (VO) segmentation and tracking algorithm is proposed based on an adaptable neural-network architecture. The proposed scheme comprises: 1) a VO tracking module and 2) an initial VO estimation module. Object tracking is handled as a classification problem and implemented through an adaptive network classifier, which provides better results compared to conventional motion-based tracking algorithms. Network adaptation is accomplished through an efficient and cost effective weight updating algorithm, providing a minimum degradation of the previous network knowledge and taking into account the current content conditions. A retraining set is constructed and used for this purpose based on initial VO estimation results. Two different scenarios are investigated. The first concerns extraction of human entities in video conferencing applications, while the second exploits depth information to identify generic VOs in stereoscopic video sequences. Human face/ body detection based on Gaussian distributions is accomplished in the first scenario, while segmentation fusion is obtained using color and depth information in the second scenario. A decision mechanism is also incorporated to detect time instances for weight updating. Experimental results and comparisons indicate the good performance of the proposed scheme even in sequences with complicated content (object bending, occlusion).
无
2005-01-01
Adaptive Delaunay triangulation is combined with the cell-centered upwinding algorithm to analyze inviscid high-speed compressible flow problems. The multidimensional dissipation scheme was developed and included in the upwinding algorithm for unstructured triangular meshes to improve the computed shock wave resolution. The solution accuracy is further improved by coupling an error estimation procedure to a remeshing algorithm that generates small elements in regions with large change of solution gradients, and at the same time, larger elements in other regions. The proposed scheme is further extended to achieve higher-order spatial and temporal solution accuracy. Efficiency of the combined procedure is evaluated by analyzing supersonic shocks and shock propagation behaviors for both the steady and unsteady high-speed compressible flows.
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...
Model reference, sliding mode adaptive control for flexible structures
Yurkovich, S.; Ozguner, U.; Al-Abbass, F.
1988-01-01
A decentralized model reference adaptive approach using a variable-structure sliding model control has been developed for the vibration suppression of large flexible structures. Local models are derived based upon the desired damping and response time in a model-following scheme, and variable structure controllers are then designed which employ colocated angular rate and position feedback. Numerical simulations have been performed using NASA's flexible grid experimental apparatus.
Analysis of Adaptive Control Scheme in IEEE 802.11 and IEEE 802.11e Wireless LANs
Lee, Bih-Hwang; Lai, Hui-Cheng
In order to achieve the prioritized quality of service (QoS) guarantee, the IEEE 802.11e EDCAF (the enhanced distributed channel access function) provides the distinguished services by configuring the different QoS parameters to different access categories (ACs). An admission control scheme is needed to maximize the utilization of wireless channel. Most of papers study throughput improvement by solving the complicated multidimensional Markov-chain model. In this paper, we introduce a back-off model to study the transmission probability of the different arbitration interframe space number (AIFSN) and the minimum contention window size (CWmin). We propose an adaptive control scheme (ACS) to dynamically update AIFSN and CWmin based on the periodical monitoring of current channel status and QoS requirements to achieve the specific service differentiation at access points (AP). This paper provides an effective tuning mechanism for improving QoS in WLAN. Analytical and simulation results show that the proposed scheme outperforms the basic EDCAF in terms of throughput and service differentiation especially at high collision rate.
Adaptive rate selection scheme for video transmission to resolve IEEE 802.11 performance anomaly
Tang, Guijin; Zhu, Xiuchang
2011-10-01
Multi-rate transmission may lead to performance anomaly in an IEEE 802.11 network. It will decrease the throughputs of all the higher rate stations. This paper proposes an adaptive rate selection scheme for video service when performance anomaly occurs. Considering that video has the characteristic of tolerance to packet loss, we actively drop several packets so as to select the rates as high as possible for transmitting packets. Experiment shows our algorithm can decrease the delay and jitter of video, and improve the system throughput as well.
Adapting Parcellation Schemes to Study Fetal Brain Connectivity in Serial Imaging Studies
Cheng, Xi; Wilm, Jakob; Seshamani, Sharmishtaa
2013-01-01
of the 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......A crucial step in studying brain connectivity is the definition of the Regions Of Interest (ROI's) which are considered as nodes of a network graph. These ROI's identified in structural imaging reflect consistent functional regions in the anatomies being compared. However in serial studies...
An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks
Wu, Guowei; Xia, Feng; Xu, Zichuan; 10.3390/s101109590
2010-01-01
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.
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.
Comparison of tropospheric chemistry schemes for use within global models
K. M. Emmerson
2008-11-01
Full Text Available Methane and ozone are two important climate gases with significant tropospheric chemistry. Within chemistry-climate and transport models this chemistry is simplified for computational expediency. We compare the state of the art Master Chemical Mechanism (MCM with six tropospheric chemistry schemes (CRI-reduced, GEOS-CHEM and a GEOS-CHEM adduct, MOZART, TOMCAT and CBM-IV that could be used within composition transport models. We test the schemes within a box model framework under conditions derived from a composition transport model and from field observations from a regional scale pollution event. We find that CRI-reduced provides much skill in simulating the full chemistry, yet with greatly reduced complexity. We find significant variations between the other chemical schemes, and reach the following conclusions. 1 The inclusion of a gas phase N_{2}O_{5}+H_{2}O reaction in some schemes and not others is a large source of uncertainty in the inorganic chemistry. 2 There are significant variations in the calculated concentration of PAN between the schemes, which will affect the long range transport of reactive nitrogen in global models. 3 The representation of isoprene chemistry differs hugely between the schemes, leading to significant uncertainties on the impact of isoprene on composition. 4 Night-time chemistry is badly represented with significant disagreements in the ratio of NO_{3} to NO_{x}. Resolving these four issues through further investigative laboratory studies will reduce the uncertainties within the chemical schemes of global tropospheric models.
Moist convection scheme in Model E2
Kim, Daehyun; Yao, Mao-Sung
2013-01-01
This documentation describes the version of the Del Genio - Yao cumulus parameterization used in the NASA Goddard Institute for Space Studies Model E2 GCM. This version was used for the official GISS submissions to the CMIP5 archive.
Adaptively Refined Euler and Navier-Stokes Solutions with a Cartesian-Cell Based Scheme
Coirier, William J.; Powell, Kenneth G.
1995-01-01
A Cartesian-cell based scheme with adaptive mesh refinement for solving the Euler and Navier-Stokes equations in two dimensions has been developed and tested. Grids about geometrically complicated bodies were generated automatically, by recursive subdivision of a single Cartesian cell encompassing the entire flow domain. Where the resulting cells intersect bodies, N-sided 'cut' cells were created using polygon-clipping algorithms. The grid was stored in a binary-tree data structure which provided a natural means of obtaining cell-to-cell connectivity and of carrying out solution-adaptive mesh refinement. The Euler and Navier-Stokes equations were solved on the resulting grids using an upwind, finite-volume formulation. The inviscid fluxes were found in an upwinded manner using a linear reconstruction of the cell primitives, providing the input states to an approximate Riemann solver. The viscous fluxes were formed using a Green-Gauss type of reconstruction upon a co-volume surrounding the cell interface. Data at the vertices of this co-volume were found in a linearly K-exact manner, which ensured linear K-exactness of the gradients. Adaptively-refined solutions for the inviscid flow about a four-element airfoil (test case 3) were compared to theory. Laminar, adaptively-refined solutions were compared to accepted computational, experimental and theoretical results.
The Nonlinear Sigma Model With Distributed Adaptive Mesh Refinement
Liebling, S L
2004-01-01
An adaptive mesh refinement (AMR) scheme is implemented in a distributed environment using Message Passing Interface (MPI) to find solutions to the nonlinear sigma model. Previous work studied behavior similar to black hole critical phenomena at the threshold for singularity formation in this flat space model. This work is a follow-up describing extensions to distribute the grid hierarchy and presenting tests showing the correctness of the model.
A novel OFDM transmission scheme with length-adaptive Cyclic Prefix
张朝阳; 赖利锋
2004-01-01
Conventional OFDM transmission system uses a fixed-length Cyclic Prefix to counteract Inter-Symbol Interferences (1SI) caused by channel delay spreading under wireless mobile environment. This may cause considerable performance deterioration when the CP length is less than the channel RMS delay spread, or may decrease the system power and spectrum efficiency when it is much larger. A novel Orthogonal Frequency Division Multiplexing (OFDM) transmission scheme is proposed in this paper to adapt the CP length to the variation of channel delay spread. AOFDM-VCPL utilizes the preamble or pilot sub-carriers of each OFDM packet to estimate the channel RMS delay spread; and then uses a criterion to calculate the CP length, which finally affects the OFDM transmitter. As illustrated in the simulation section, by deploying this scheme in a typical wireless environment, the system can transmit at data rate 11.5Mb/s higher than conventional non-adaptive system while gaining a 0.65dB power saving at the same BER performance.
A novel OFDM transmission scheme with length-adaptive Cyclic Prefix
张朝阳; 赖利峰
2004-01-01
Conventional OFDM transmission system uses a fixed-length Cyclic Prefix to counteract Inter-Symbol Interferences(ISI)caused by channel delay spreading under wireless mobile environment. This may cause considerable performance deterioration when the CP length is less than the channel RMS delay spread,or may decrease the system power and spectrum efficiency when it is much larger. A novel Orthogonal Frequency Division Multiplexing(OFDM)transmission scheme is proposed in this paper to adapt the CP length to the variation of channel delay spread. AOFDM-VCPL utilizes the preamble or pilot sub-carriers of each OFDM packet to estimate the channel RMS delay spread; and then uses a criterion to calculate the CP length,which finally affects the OFDM transmitter. As illustrated in the simulation section,by deploying this scheme in a typical wireless environment,the system can transmit at data rate 11.5 Mb/s higher than conventional non-adaptive system while gaining a 0.65 dB power saving at the same BER performance.
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.
Gil Gye-Tae
2010-01-01
Full Text Available We deal with a cost-based adaptive handover hysteresis scheme for the horizontal handover decision strategies, as one of the self-optimization techniques that can minimize the handover failure rate (HFR in the 3rd generation partnership project (3GPP long-term evolution (LTE system based on the network-controlled hard handover. Especially, for real-time operation, we propose an adaptive hysteresis scheme with a simplified cost function considering some dominant factors closely related to HFR performance such as the load difference between the target and serving cells, the velocity of user equipment (UE, and the service type. With the proposed scheme, a proper hysteresis value based on the dominant factors is easily obtained, so that the handover parameter optimization for minimizing the HFR can be effectively achieved. Simulation results show that the proposed scheme can support better HFR performance than the conventional schemes.
Accelerated failure time model under general biased sampling scheme.
Kim, Jane Paik; Sit, Tony; Ying, Zhiliang
2016-07-01
Right-censored time-to-event data are sometimes observed from a (sub)cohort of patients whose survival times can be subject to outcome-dependent sampling schemes. In this paper, we propose a unified estimation method for semiparametric accelerated failure time models under general biased estimating schemes. The proposed estimator of the regression covariates is developed upon a bias-offsetting weighting scheme and is proved to be consistent and asymptotically normally distributed. Large sample properties for the estimator are also derived. Using rank-based monotone estimating functions for the regression parameters, we find that the estimating equations can be easily solved via convex optimization. The methods are confirmed through simulations and illustrated by application to real datasets on various sampling schemes including length-bias sampling, the case-cohort design and its variants. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
The Numerical Scheme Development of a Simplified Frozen Soil Model
LI Qian; SUN Shufen; DAI Qiudan
2009-01-01
In almost all frozen soil models used currently,three variables of temperature,ice content and moisture content are used as prognostic variables and the rate term,accounting for the contribution of the phase change between water and ice,is shown explicitly in both the energy and mass balance equations.The models must be solved by a numerical method with an iterative process,and the rate term of the phase change needs to be pre-estimated at the beginning in each iteration step.Since the rate term of the phase change in the energy equation is closely related to the release or absorption of the great amount of fusion heat,a small error in the rate term estimation will introduce greater error in the energy balance,which will amplify the error in the temperature calculation and in turn,cause problems for the numerical solution convergence.In this work,in order to first reduce the trouble,the methodology of the variable transformation is applied to a simplified frozen soil model used currently,which leads to new frozen soil scheme used in this work.In the new scheme,the enthalpy and the total water equivalent are used as predictive variables in the governing equations to replace temperature,volumetric soil moisture and ice content used in many current models.By doing so,the rate terms of the phase change are not shown explicitly in both the mass and energy equations and its pre-estimation is avoided.Secondly,in order to solve this new scheme more functionally,the development of the numerical scheme to the new scheme is described and a numerical algorithm appropriate to the numerical scheme is developed.In order to evaluate the new scheme of the frozen soil model and its relevant algorithm,a series of model evaluations are conducted by comparing numerical results from the new model scheme with three observational data sets.The comparisons show that the results from the model are in good agreement with these data sets in both the change trend of variables and their
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.
Scheduling and adaptation of London's future water supply and demand schemes under uncertainty
Huskova, Ivana; Matrosov, Evgenii S.; Harou, Julien J.; Kasprzyk, Joseph R.; Reed, Patrick M.
2015-04-01
The changing needs of society and the uncertainty of future conditions complicate the planning of future water infrastructure and its operating policies. These systems must meet the multi-sector demands of a range of stakeholders whose objectives often conflict. Understanding these conflicts requires exploring many alternative plans to identify possible compromise solutions and important system trade-offs. The uncertainties associated with future conditions such as climate change and population growth challenge the decision making process. Ideally planners should consider portfolios of supply and demand management schemes represented as dynamic trajectories over time able to adapt to the changing environment whilst considering many system goals and plausible futures. Decisions can be scheduled and adapted over the planning period to minimize the present cost of portfolios while maintaining the supply-demand balance and ecosystem services as the future unfolds. Yet such plans are difficult to identify due to the large number of alternative plans to choose from, the uncertainty of future conditions and the computational complexity of such problems. Our study optimizes London's future water supply system investments as well as their scheduling and adaptation over time using many-objective scenario optimization, an efficient water resource system simulator, and visual analytics for exploring key system trade-offs. The solutions are compared to Pareto approximate portfolios obtained from previous work where the composition of infrastructure portfolios that did not change over the planning period. We explore how the visual analysis of solutions can aid decision making by investigating the implied performance trade-offs and how the individual schemes and their trajectories present in the Pareto approximate portfolios affect the system's behaviour. By doing so decision makers are given the opportunity to decide the balance between many system goals a posteriori as well as
Inflationary gravitational waves in collapse scheme models
Mariani, Mauro, E-mail: mariani@carina.fcaglp.unlp.edu.ar [Facultad de Ciencias Astronómicas y Geofísicas, Universidad Nacional de La Plata, Paseo del Bosque S/N, 1900 La Plata (Argentina); Bengochea, Gabriel R., E-mail: gabriel@iafe.uba.ar [Instituto de Astronomía y Física del Espacio (IAFE), UBA-CONICET, CC 67, Suc. 28, 1428 Buenos Aires (Argentina); León, Gabriel, E-mail: gleon@df.uba.ar [Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria – Pab. I, 1428 Buenos Aires (Argentina)
2016-01-10
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.
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.
Pathak, Harshavardhana S.; Shukla, Ratnesh K.
2016-08-01
A high-order adaptive finite-volume method is presented for simulating inviscid compressible flows on time-dependent redistributed grids. The method achieves dynamic adaptation through a combination of time-dependent mesh node clustering in regions characterized by strong solution gradients and an optimal selection of the order of accuracy and the associated reconstruction stencil in a conservative finite-volume framework. This combined approach maximizes spatial resolution in discontinuous regions that require low-order approximations for oscillation-free shock capturing. Over smooth regions, high-order discretization through finite-volume WENO schemes minimizes numerical dissipation and provides excellent resolution of intricate flow features. The method including the moving mesh equations and the compressible flow solver is formulated entirely on a transformed time-independent computational domain discretized using a simple uniform Cartesian mesh. Approximations for the metric terms that enforce discrete geometric conservation law while preserving the fourth-order accuracy of the two-point Gaussian quadrature rule are developed. Spurious Cartesian grid induced shock instabilities such as carbuncles that feature in a local one-dimensional contact capturing treatment along the cell face normals are effectively eliminated through upwind flux calculation using a rotated Hartex-Lax-van Leer contact resolving (HLLC) approximate Riemann solver for the Euler equations in generalized coordinates. Numerical experiments with the fifth and ninth-order WENO reconstructions at the two-point Gaussian quadrature nodes, over a range of challenging test cases, indicate that the redistributed mesh effectively adapts to the dynamic flow gradients thereby improving the solution accuracy substantially even when the initial starting mesh is non-adaptive. The high adaptivity combined with the fifth and especially the ninth-order WENO reconstruction allows remarkably sharp capture of
Action versus result-oriented schemes in a grassland agroecosystem: a dynamic modelling approach.
Sabatier, Rodolphe; Doyen, Luc; Tichit, Muriel
2012-01-01
Effects of agri-environment schemes (AES) on biodiversity remain controversial. While most AES are action-oriented, result-oriented and habitat-oriented schemes have recently been proposed as a solution to improve AES efficiency. The objective of this study was to compare action-oriented, habitat-oriented and result-oriented schemes in terms of ecological and productive performance as well as in terms of management flexibility. We developed a dynamic modelling approach based on the viable control framework to carry out a long term assessment of the three schemes in a grassland agroecosystem. The model explicitly links grazed grassland dynamics to bird population dynamics. It is applied to lapwing conservation in wet grasslands in France. We ran the model to assess the three AES scenarios. The model revealed the grazing strategies respecting ecological and productive constraints specific to each scheme. Grazing strategies were assessed by both their ecological and productive performance. The viable control approach made it possible to obtain the whole set of viable grazing strategies and therefore to quantify the management flexibility of the grassland agroecosystem. Our results showed that habitat and result-oriented scenarios led to much higher ecological performance than the action-oriented one. Differences in both ecological and productive performance between the habitat and result-oriented scenarios were limited. Flexibility of the grassland agroecosystem in the result-oriented scenario was much higher than in that of habitat-oriented scenario. Our model confirms the higher flexibility as well as the better ecological and productive performance of result-oriented schemes. A larger use of result-oriented schemes in conservation may also allow farmers to adapt their management to local conditions and to climatic variations.
Action versus result-oriented schemes in a grassland agroecosystem: a dynamic modelling approach.
Rodolphe Sabatier
Full Text Available Effects of agri-environment schemes (AES on biodiversity remain controversial. While most AES are action-oriented, result-oriented and habitat-oriented schemes have recently been proposed as a solution to improve AES efficiency. The objective of this study was to compare action-oriented, habitat-oriented and result-oriented schemes in terms of ecological and productive performance as well as in terms of management flexibility. We developed a dynamic modelling approach based on the viable control framework to carry out a long term assessment of the three schemes in a grassland agroecosystem. The model explicitly links grazed grassland dynamics to bird population dynamics. It is applied to lapwing conservation in wet grasslands in France. We ran the model to assess the three AES scenarios. The model revealed the grazing strategies respecting ecological and productive constraints specific to each scheme. Grazing strategies were assessed by both their ecological and productive performance. The viable control approach made it possible to obtain the whole set of viable grazing strategies and therefore to quantify the management flexibility of the grassland agroecosystem. Our results showed that habitat and result-oriented scenarios led to much higher ecological performance than the action-oriented one. Differences in both ecological and productive performance between the habitat and result-oriented scenarios were limited. Flexibility of the grassland agroecosystem in the result-oriented scenario was much higher than in that of habitat-oriented scenario. Our model confirms the higher flexibility as well as the better ecological and productive performance of result-oriented schemes. A larger use of result-oriented schemes in conservation may also allow farmers to adapt their management to local conditions and to climatic variations.
M. Louta
2014-01-01
Full Text Available WiMAX (Worldwide Interoperability for Microwave Access constitutes a candidate networking technology towards the 4G vision realization. By adopting the Orthogonal Frequency Division Multiple Access (OFDMA technique, the latest IEEE 802.16x amendments manage to provide QoS-aware access services with full mobility support. A number of interesting scheduling and mapping schemes have been proposed in research literature. However, they neglect a considerable asset of the OFDMA-based wireless systems: the dynamic adjustment of the downlink-to-uplink width ratio. In order to fully exploit the supported mobile WiMAX features, we design, develop, and evaluate a rigorous adaptive model, which inherits its main aspects from the reinforcement learning field. The model proposed endeavours to efficiently determine the downlink-to-uplinkwidth ratio, on a frame-by-frame basis, taking into account both the downlink and uplink traffic in the Base Station (BS. Extensive evaluation results indicate that the model proposed succeeds in providing quite accurate estimations, keeping the average error rate below 15% with respect to the optimal sub-frame configurations. Additionally, it presents improved performance compared to other learning methods (e.g., learning automata and notable improvements compared to static schemes that maintain a fixed predefined ratio in terms of service ratio and resource utilization.
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.
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.
A new simplified adaptive control scheme for multi-terminal HVDC transmission systems
Meah, Kala [Electrical and Computer Engineering, York College of Pennsylvania, York, PA 17405 (United States); Ula, A.H.M. Sadrul [Electrical and Computer Engineering, University of Wyoming, Laramie, WY 82071 (United States)
2010-05-15
This paper proposes a new control scheme for multi-terminal HVDC (MTDC) systems to improve the performance during the system transients such as AC line faults. The new method is called parallel multi-proportional-integral (MPI) control scheme. This new control scheme provides wide range of controller parameters and has the ability to response quickly. To evaluate the performance of the proposed control scheme, a four-terminal HVDC system is considered with the detailed modeling of converters, commutation transformers, source impedances, line parameters, and filters. Simulation results from various transient conditions are compared between the proposed controller, the fuzzy logic-based auto-tuning PI controller, and the conventional fixed-parameter PI controller. The SimPowerSystems and the fuzzy logic toolboxes in the MATLAB/SIMULINK software package are used to conduct the simulations. Simulation results show that the MPI controller has better performance than the conventional fixed-parameter PI controller and has very similar responses compared to the fuzzy logic-based auto-tuning PI controller without any added complexity in controller design procedure for a MTDC system. (author)
Design of signal-adapted multidimensional lifting scheme for lossy coding.
Gouze, Annabelle; Antonini, Marc; Barlaud, Michel; Macq, Benoît
2004-12-01
This paper proposes a new method for the design of lifting filters to compute a multidimensional nonseparable wavelet transform. Our approach is stated in the general case, and is illustrated for the 2-D separable and for the quincunx images. Results are shown for the JPEG2000 database and for satellite images acquired on a quincunx sampling grid. The design of efficient quincunx filters is a difficult challenge which has already been addressed for specific cases. Our approach enables the design of less expensive filters adapted to the signal statistics to enhance the compression efficiency in a more general case. It is based on a two-step lifting scheme and joins the lifting theory with Wiener's optimization. The prediction step is designed in order to minimize the variance of the signal, and the update step is designed in order to minimize a reconstruction error. Application for lossy compression shows the performances of the method.
Modelling of Substrate Noise and Mitigation Schemes for UWB Systems
Shen, Ming; Mikkelsen, Jan H.; Larsen, Torben
2012-01-01
The last chapter of this first part of the book, chapter seven, is devoted to Modeling of Substrate Noise and Mitigation Schemes for Ultrawideband (UWB) systems, and is written by Ming Shen, Jan H. Mikkelsen, and Torben Larsen from Aalborg University, Denmark. In highly integrated mixed-mode desi...
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.
Bridge aerodynamics and aeroelasticity: A comparison of modeling schemes
Wu, Teng; Kareem, Ahsan
2013-11-01
Accurate modeling of wind-induced loads on bridge decks is critical to ensure the functionality and survivability of long-span bridges. Over the last few decades, several schemes have emerged to model bridge behavior under winds from an aerodynamic/aeroelastic perspective. A majority of these schemes rely on the quasi-steady (QS) theory. This paper systematically compares and assesses the efficacy of five analytical models available in the literature with a new model presented herein. These models include: QS theory-based model, corrected QS theory-based model, linearized QS theory-based model, semi-empirical linear model, hybrid model, and the proposed modified hybrid model. The ability of these models to capture fluid memory and nonlinear effects either individually or collectively is examined. In addition, their ability to include the effects of turbulence in the approach flow on the bridge behavior is assessed. All models are compared in a consistent manner by utilizing the time domain approach. The underlying role of each model in capturing the physics of bridge behavior under winds is highlighted and the influence of incoming turbulence and its interaction with the bridge deck is examined. A discussion is included that focuses on a number of critical parameters pivotal to the effectiveness of corresponding models.
Runoff prediction using an integrated hybrid modelling scheme
Remesan, Renji; Shamim, Muhammad Ali; Han, Dawei; Mathew, Jimson
2009-06-01
SummaryRainfall runoff is a very complicated process due to its nonlinear and multidimensional dynamics, and hence difficult to model. There are several options for a modeller to consider, for example: the type of input data to be used, the length of model calibration (training) data and whether or not the input data be treated as signals with different frequency bands so that they can be modelled separately. This paper describes a new hybrid modelling scheme to answer the above mentioned questions. The proposed methodology is based on a hybrid model integrating wavelet transformation, a modelling engine (Artificial Neural Network) and the Gamma Test. First, the Gamma Test is used to decide the required input data dimensions and its length. Second, the wavelet transformation decomposes the input signals into different frequency bands. Finally, a modelling engine (ANN in this study) is used to model the decomposed signals separately. The proposed scheme was tested using the Brue catchment, Southwest England, as a case study and has produced very positive results. The hybrid model outperforms all other models tested. This study has a wider implication in the hydrological modelling field since its general framework could be applied to other model combinations (e.g., model engine could be Support Vector Machines, neuro-fuzzy systems, or even a conceptual model. The signal decomposition could be carried out by Fourier transformation).
Sotiropoulos, Vassilios; Kaznessis, Yiannis N
2008-01-07
Models involving stochastic differential equations (SDEs) play a prominent role in a wide range of applications where systems are not at the thermodynamic limit, for example, biological population dynamics. Therefore there is a need for numerical schemes that are capable of accurately and efficiently integrating systems of SDEs. In this work we introduce a variable size step algorithm and apply it to systems of stiff SDEs with multiple multiplicative noise. The algorithm is validated using a subclass of SDEs called chemical Langevin equations that appear in the description of dilute chemical kinetics models, with important applications mainly in biology. Three representative examples are used to test and report on the behavior of the proposed scheme. We demonstrate the advantages and disadvantages over fixed time step integration schemes of the proposed method, showing that the adaptive time step method is considerably more stable than fixed step methods with no excessive additional computational overhead.
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.
Adaptive Call Admission Control Based on Reward-Penalty Model in Wireless/Mobile Network
Jian-Hui Huang; De-Pei Qian; Sheng-Ling Wang
2007-01-01
A dynamic threshold-based Call Admission Control (CAC) scheme used in wireless/mobile network for multi- class services is proposed. In the scheme, each class's CAC thresholds are solved through establishing a reward-penalty model which strives to maximize network's revenue. In order to lower Handoff Dropping Probability (HDP), the scheme joints packet and connection levels Quality of Service constraints, designing a bandwidth degradation algorithm to accept handoff calls by degrading existing calls' bandwidth during network congestion. Analyses show that the CAC thresholds change adaptively with the average call arrival rate. The performance comparison shows that the proposed scheme outperforms the Mobile IP Reservation scheme.
An activation-recruitment scheme for use in muscle modeling.
Hawkins, D A; Hull, M L
1992-12-01
The derivation of a new activation-recruitment scheme and the results of a study designed to test its validity are presented. The activation scheme utilizes input data of processed surface EMG signals, muscle composition, muscle architecture, and experimentally determined activation coefficients. In the derivation, the relationship between muscle activation and muscle fiber recruitment was considered. In the experimental study, triceps muscle force was determined for isometric elbow extension tasks varying in intensity from 10 to 100% of a maximum voluntary contraction (MVC) using both a muscle model that incorporates the activation scheme, and inverse dynamics techniques. The forces calculated using the two methods were compared statistically. The modeled triceps force was not significantly different from the experimental results determined using inverse dynamics techniques for average activation levels greater than 25% of MVC, but was significantly different for activation levels less than 25% of MVC. These results lend support for use of the activation-recruitment scheme for moderate to large activation levels, and suggest that factors in addition to fiber recruitment play a role in force regulation at lower activation levels.
An Adaptive Control Scheme for Nonholonomic Mobile Robot with Parametric Uncertainty
Touati, F.; F. Mnif
2005-01-01
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 convergen...
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.
Load adaptive start-up scheme for synchronous boost DC-DC converter
Guoding, Dai; Wenliang, Xiu; Yuezhi, Liu; Yawei, Qi; Zuqi, Dong
2016-10-01
This paper presents a load adaptive soft-start scheme through which the inductor current of the synchronous boost DC-DC converter can trace the load current at the start-up stage. This scheme effectively eliminates the inrush-current and over-shoot voltage and improves the load capability of the converter. According to the output voltage, the start-up process is divided into three phases and at each phase the inductor current is limited to match the load. In the pre-charge phase, a step-increasing constant current gives a smooth rise of the output voltage which avoids inrush current and ensures the converter successfully starts up at different load situations. An additional ring oscillator operation phase enables the converter to start up as low as 1.4 V. When the converter enters into the system loop soft-start phase, an output voltage and inductor current detection methods make the transition of the phases smooth and the inductor current and output voltage rise steadily. Effective protection circuits such as short-circuit protection, current limit circuit and over-temperature protection circuit are designed to guarantee the safety and reliability of the chip during the start-up process. The proposed start-up circuit is implemented in a synchronous boost DC-DC converter based on TSMC 0.35 μm CMOS process with an input voltage range 1.4-4.2 V, and a steady output voltage 5 V, and the switching frequency is 1 MHz. Simulation results show that inrush current and overshoot voltage are suppressed with a load range from 0-2.1 A, and inductor current is as low as 259 mA when the output shorts to the ground.
Kipka, H.; Pfennig, B.; Fink, M.; Kralisch, S.; Krause, P.; Flügel, W.
2010-12-01
Fully spatially distributed hydrological modeling requires a topological linkage of single modeling entities (e.g. Hydrological Response Units - HRU) in order to reproduce relevant attenuation and translation processes within the stream but also during the transport of water in form of lateral surface or subsurface flow. Most often such linkage is considered by a one dimensional (1D) approach which links one modeling entity to only one receiver that follows in flow direction. The comparison with actual lateral water movement in catchments show that such a 1D routing scheme is often too simple which can lead to an overestimation of the runoff concentration along the 1D flow paths. On the other hand an underestimation of runoff in flow cascades that do not reside next to the main 1D flow paths can occur as the affected HRUs don’t receive realistic inflow from their source entities above. As a catchment-wide consequence the 1D routing scheme can result in a significant over- or underestimation of the contributing area for specific parts of a catchment which can have important implications on the spatial distribution of accompanying processes such as spatial variation of soil moisture, soil erosion or nutrient/contaminant transport. To address the problems outlined above a new approach has been developed that allows a multi-dimensional linkage of model entities in such a way that each entity can have various receivers to which the water is passed. This extended routing scheme was implemented in the hydrological, nutrient transport and erosion modeling system J2000-S-E and was used for the simulation of the hydrological processes of a number of meso-scaled catchments in Thuringia, Germany. This work will present the most important facts of the extended routing scheme, the simulation results along with the comparison of those obtained with the 1D linkage and will highlight the impacts on the hydrological process dynamics as well as on the HRU-based mass transport and
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.
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.
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.
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...
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
A Three-Dimensional Scale-adaptive Turbulent Kinetic Energy Model in ARW-WRF Model
Zhang, Xu; Bao, Jian-Wen; Chen, Baode
2017-04-01
A new three-dimensional (3D) turbulent kinetic energy (TKE) subgrid mixing model is developed to address the problem of simulating the convective boundary layer (CBL) across the terra incognita in the Advanced Research version of the Weather Research and Forecasting Model (ARW-WRF). The new model combines the horizontal and vertical subgrid turbulent mixing into a single energetically consistent framework, in contrast to the convectional one-dimensional (1D) planetary boundary layer (PBL) schemes. The transition between large-eddy simulation (LES) and mesoscale limit is accomplished in the new scale-adaptive model. A series of dry CBL and real-time simulations using the WRF model are carried out, in which the newly-developed, scale-adaptive, more general and energetically consistent TKE-based model is compared with the conventional 1D TKE-based PBL schemes for parameterizing vertical subgrid turbulent mixing against the WRF LES dataset and observations. The characteristics of the WRF-simulated results using the new and conventional schemes are compared. The importance of including the nonlocal component in the vertical buoyancy specification in the newly-developed general TKE-based scheme is illustrated. The improvements of the new scheme over convectional PBL schemes across the terra incognita can be seen in the partitioning of vertical flux profiles. Through comparing the results from the simulations against the WRF LES dataset and observations, we will show the feasibility of using the new scheme in the WRF model in the lieu of the conventional PBL parameterization schemes.
Hsuan-Yu Lin
2008-11-01
Full Text Available Adaptive reduced-rank (RR multistage matrix Wiener filtering (MMWF techniques, based on the minimum mean-square error (MMSE criterion, are proposed for direct-sequence (DS ultra-wideband (UWB communication systems. These RR-MMWF-based algorithms employ an adaptive fuzzy-inference determined filter stage. As a consequence, the proposed schemes achieve a substantial saving in complexity without compromising system performance and dynamic convergence/tracking capability. Additionally, the fuzzy-logic-controlled matrix conjugate gradient (MCG algorithm is developed for a robust and reduced-rank implementation of the full-rank MMWF. Simulations are conducted to illustrate the convergence/tracking superiority and to provide a comparative evaluation of the proposed algorithms with the MMWF-based schemes using other adaptive stage-selecting criteria.
An Adaptive Control Scheme for Nonholonomic Mobile Robot with Parametric Uncertainty
F. Mnif
2005-03-01
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.
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.
Accuracy tests of radiation schemes used in hot Jupiter Global Circulation Models
Amundsen, David Skålid; Tremblin, Pascal; Manners, James; Hayek, Wolfgang; Mayne, N J; Acreman, David M
2014-01-01
The treatment of radiation transport in global circulation models (GCMs) is crucial to correctly describe Earth and exoplanet atmospheric dynamics processes. The two-stream approximation and correlated-$k$ method are currently state-of-the-art approximations applied in both Earth and hot Jupiter GCM radiation schemes to facilitate rapid calculation of fluxes and heating rates. Their accuracy have been tested extensively for Earth-like conditions, but verification of the methods' applicability to hot Jupiter-like conditions is lacking in the literature. We are adapting the UK Met Office GCM, the Unified Model (UM), for the study of hot Jupiters, and present in this work the adaptation of the Edwards-Slingo radiation scheme based on the two-stream approximation and the correlated-$k$ method. We discuss the calculation of absorption coefficients from high temperature line lists and highlight the large uncertainty in the pressure-broadened line widths. We compare fluxes and heating rates obtained with our adapted...
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
Adaptively Security CP-ABE Scheme Supporting Attribute Revocation%适应性安全且支持属性撤销的CP-ABE方案
彭开锋; 张席
2015-01-01
现有支持属性间接撤销的CP-ABE方案存在撤销代价与安全性难以兼顾的问题，为此，借鉴属性间接撤销思想和双系统加密技术，提出一个适应性安全且支持属性撤销的CP-ABE方案，并基于3素数子群判定问题证明该方案的安全性。分析结果表明，与经典ABE属性撤销方案相比，该方案的效率较高，访问策略表达更为灵活。%In the existing CP-ABE schemes that supporting attribute indirect revocation,the cost of revocation and its security can not be taken into account in the model simultaneously. Based on the idea of attribute indirect revocation and the dual system encryption technique,this paper constructs an adaptively security CP-ABE scheme that supports attribute revocation,and proves the security of the scheme using the 3P-SDP. Analysis result shows that,compared with the ABE schemes proposed before,the proposed scheme is more flexible and efficient in the access policy and attribute revocation.
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.
CFD DPAL modeling for various schemes of flow configurations
Waichman, Karol; Barmashenko, Boris D.; Rosenwaks, Salman
2014-10-01
Comprehensive analysis of kinetic and fluid dynamic processes in flowing-gas diode pumped alkali lasers (DPALs) using two- and three-dimensional computational fluid dynamics (2D and 3D CFD) models is reported for Cs DPALs. The models take into account effects of temperature rise and losses of alkali atoms due to ionization. Various gas flow regimes and transverse and parallel flow-optics directions configurations are studied. Optimization of the Cs DPAL parameters, using 3D CFD modeling, shows that applying high flow velocity and narrowband pumping, maximum lasing power as high as 40 kW can be obtained at pump power of 80 kW for transverse flow configuration in a pumped volume of ~ 0.7 cm3. At high pump power the calculated laser power is higher for the transverse scheme than for the parallel scheme because of a more efficient heat convection from the beam volume in the transverse configuration. The CFD models are applied to experimental devices and the calculated results are in good agreement with the measurements.
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
Onsager reciprocity principle for kinetic models and kinetic schemes
Mahendra, Ajit Kumar
2013-01-01
Boltzmann equation requires some alternative simpler kinetic model like BGK to replace the collision term. Such a kinetic model which replaces the Boltzmann collision integral should preserve the basic properties and characteristics of the Boltzmann equation and comply with the requirements of non equilibrium thermodynamics. Most of the research in development of kinetic theory based methods have focused more on entropy conditions, stability and ignored the crucial aspect of non equilibrium thermodynamics. The paper presents a new kinetic model formulated based on the principles of non equilibrium thermodynamics. The new kinetic model yields correct transport coefficients and satisfies Onsager's reciprocity relationship. The present work also describes a novel kinetic particle method and gas kinetic scheme based on this linkage of non-equilibrium thermodynamics and kinetic theory. The work also presents derivation of kinetic theory based wall boundary condition which complies with the principles of non-equili...
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.
Accuracy tests of radiation schemes used in hot Jupiter global circulation models
Amundsen, David S.; Baraffe, Isabelle; Tremblin, Pascal; Manners, James; Hayek, Wolfgang; Mayne, Nathan J.; Acreman, David M.
2014-04-01
The treatment of radiation transport in global circulation models (GCMs) is crucial for correctly describing Earth and exoplanet atmospheric dynamics processes. The two-stream approximation and correlated-k method are currently state-of-the-art approximations applied in both Earth and hot Jupiter GCM radiation schemes to facilitate the rapid calculation of fluxes and heating rates. Their accuracy have been tested extensively for Earth-like conditions, but verification of the methods' applicability to hot Jupiter-like conditions is lacking in the literature. We are adapting the UK Met Office GCM, the Unified Model (UM), for the study of hot Jupiters, and present in this work the adaptation of the Edwards-Slingo radiation scheme based on the two-stream approximation and the correlated-k method. We discuss the calculation of absorption coefficients from high-temperature line lists and highlight the large uncertainty in the pressure-broadened line widths. We compare fluxes and heating rates obtained with our adapted scheme to more accurate discrete ordinate (DO) line-by-line (LbL) calculations ignoring scattering effects. We find that, in most cases, errors stay below 10% for both heating rates and fluxes using ~10 k-coefficients in each band and a diffusivity factor D = 1.66. The two-stream approximation and the correlated-k method both contribute non-negligibly to the total error. We also find that using band-averaged absorption coefficients, which have previously been used in radiative-hydrodynamical simulations of a hot Jupiter, may yield errors of ~100%, and should thus be used with caution.
On fractional order composite model reference adaptive control
Wei, Yiheng; Sun, Zhenyuan; Hu, Yangsheng; Wang, Yong
2016-08-01
This paper presents a novel composite model reference adaptive control approach for a class of fractional order linear systems with unknown constant parameters. The method is extended from the model reference adaptive control. The parameter estimation error of our method depends on both the tracking error and the prediction error, whereas the existing method only depends on the tracking error, which makes our method has better transient performance in the sense of generating smooth system output. By the aid of the continuous frequency distributed model, stability of the proposed approach is established in the Lyapunov sense. Furthermore, the convergence property of the model parameters estimation is presented, on the premise that the closed-loop control system is stable. Finally, numerical simulation examples are given to demonstrate the effectiveness of the proposed schemes.
A Muscle Synergy-inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis
Naji A Alibeji
2015-12-01
Full Text Available Abstract--- Abstract--- A hybrid neuroprosthesis that uses an electric motor-based wearable exoskeleton and functional electrical stimulation (FES has a promising potential to restore walking in persons with paraplegia. A hybrid actuation structure introduces effector redundancy, making its automatic control a challenging task because multiple muscles and additional electric motor need to be coordinated. Inspired by the muscle synergy principle, we designed a low dimensional controller to control multiple effectors: FES of multiple muscles and electric motors. The resulting control system may be less complex and easier to control. To obtain the muscle synergy-inspired low dimensional control, a subject-specific gait model was optimized to compute optimal control signals for the multiple effectors. The optimal control signals were then dimensionally reduced by using principal component analysis to extract synergies. Then, an adaptive feedforward controller with an update law for the synergy activation was designed. In addition, feedback control was used to provide stability and robustness to the control design. The adaptive-feedforward and feedback control structure makes the low dimensional controller more robust to disturbances and variations in the model parameters and may help to compensate for other time-varying phenomena (e.g., muscle fatigue. This is proven by using a Lyapunov stability analysis, which yielded semi-global uniformly ultimately bounded tracking. Computer simulations were performed to test the new controller on a 4 degree of freedom gait model.
Comparing Sediment Yield Predictions from Different Hydrologic Modeling Schemes
Dahl, T. A.; Kendall, A. D.; Hyndman, D. W.
2015-12-01
Sediment yield, or the delivery of sediment from the landscape to a river, is a difficult process to accurately model. It is primarily a function of hydrology and climate, but influenced by landcover and the underlying soils. These additional factors make it much more difficult to accurately model than water flow alone. It is not intuitive what impact different hydrologic modeling schemes may have on the prediction of sediment yield. Here, two implementations of the Modified Universal Soil Loss Equation (MUSLE) are compared to examine the effects of hydrologic model choice. Both the Soil and Water Assessment Tool (SWAT) and the Landscape Hydrology Model (LHM) utilize the MUSLE for calculating sediment yield. SWAT is a lumped parameter hydrologic model developed by the USDA, which is commonly used for predicting sediment yield. LHM is a fully distributed hydrologic model developed primarily for integrated surface and groundwater studies at the watershed to regional scale. SWAT and LHM models were developed and tested for two large, adjacent watersheds in the Great Lakes region; the Maumee River and the St. Joseph River. The models were run using a variety of single model and ensemble downscaled climate change scenarios from the Coupled Model Intercomparison Project 5 (CMIP5). The initial results of this comparison are discussed here.
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.
Thermal Error Modeling of a Machine Tool Using Data Mining Scheme
Wang, Kun-Chieh; Tseng, Pai-Chang
In this paper the knowledge discovery technique is used to build an effective and transparent mathematic thermal error model for machine tools. Our proposed thermal error modeling methodology (called KRL) integrates the schemes of K-means theory (KM), rough-set theory (RS), and linear regression model (LR). First, to explore the machine tool's thermal behavior, an integrated system is designed to simultaneously measure the temperature ascents at selected characteristic points and the thermal deformations at spindle nose under suitable real machining conditions. Second, the obtained data are classified by the KM method, further reduced by the RS scheme, and a linear thermal error model is established by the LR technique. To evaluate the performance of our proposed model, an adaptive neural fuzzy inference system (ANFIS) thermal error model is introduced for comparison. Finally, a verification experiment is carried out and results reveal that the proposed KRL model is effective in predicting thermal behavior in machine tools. Our proposed KRL model is transparent, easily understood by users, and can be easily programmed or modified for different machining conditions.
Modeling Phosphorous Losses from Seasonal Manure Application Schemes
Menzies, E.; Walter, M. T.
2015-12-01
Excess nutrient loading, especially nitrogen and phosphorus, to surface waters is a common and significant problem throughout the United States. While pollution remediation efforts are continuously improving, the most effective treatment remains to limit the source. Appropriate timing of fertilizer application to reduce nutrient losses is currently a hotly debated topic in the Northeastern United States; winter spreading of manure is under special scrutiny. We plan to evaluate the loss of phosphorous to surface waters from agricultural systems under varying seasonal fertilization schemes in an effort to determine the impacts of fertilizers applied throughout the year. The Cayuga Lake basin, located in the Finger Lakes region of New York State, is a watershed dominated by agriculture where a wide array of land management strategies can be found. The evaluation will be conducted on the Fall Creek Watershed, a large sub basin in the Cayuga Lake Watershed. The Fall Creek Watershed covers approximately 33,000 ha in central New York State with approximately 50% of this land being used for agriculture. We plan to use the Soil and Water Assessment Tool (SWAT) to model a number of seasonal fertilization regimes such as summer only spreading and year round spreading (including winter applications), as well as others. We will use the model to quantify the phosphorous load to surface waters from these different fertilization schemes and determine the impacts of manure applied at different times throughout the year. More detailed knowledge about how seasonal fertilization schemes impact phosphorous losses will provide more information to stakeholders concerning the impacts of agriculture on surface water quality. Our results will help farmers and extensionists make more informed decisions about appropriate timing of manure application for reduced phosphorous losses and surface water degradation as well as aid law makers in improving policy surrounding manure application.
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.
Tissue modeling schemes in low energy breast brachytherapy.
Afsharpour, Hossein; Landry, Guillaume; Reniers, Brigitte; Pignol, Jean-Philippe; Beaulieu, Luc; Verhaegen, Frank
2011-11-21
Breast tissue is heterogeneous and is mainly composed of glandular (G) and adipose (A) tissues. The proportion of G versus A varies considerably among the population. The absorbed dose distributions in accelerated partial breast irradiation therapy with low energy photon brachytherapy sources are very sensitive to tissue heterogeneities. Current clinical algorithms use the recommendations of the AAPM TG43 report which approximates the human tissues by unit density water. The aim of this study is to investigate various breast tissue modeling schemes for low energy brachytherapy. A special case of breast permanent seed implant is considered here. Six modeling schemes are considered. Uniform and non-uniform water breast (UWB and NUWB) consider the density but neglect the effect of the composition of tissues. The uniform and the non-uniform G/A breast (UGAB and NUGAB) as well the age-dependent breast (ADB) models consider the effect of the composition. The segmented breast tissue (SBT) method uses a density threshold to distinguish between G and A tissues. The PTV D(90) metric is used for the analysis and is based on the dose to water (D(90(w,m))). D(90(m,m)) is also reported for comparison to D(90(w,m)). The two-month post-implant D(90(w,m)) averaged over 38 patients is smaller in NUWB than in UWB by about 4.6% on average (ranging from 5% to 13%). Large average differences of G/A breast models with TG43 (17% and 26% in UGAB and NUGAB, respectively) show that the effect of the chemical composition dominates the effect of the density on dose distributions. D(90(w,m)) is 12% larger in SBT than in TG43 when averaged. These differences can be as low as 4% or as high as 20% when the individual patients are considered. The high sensitivity of dosimetry on the modeling scheme argues in favor of an agreement on a standard tissue modeling approach to be used in low energy breast brachytherapy. SBT appears to generate the most geometrically reliable breast tissue models in this
Experimental design schemes for learning Boolean network models
Atias, Nir; Gershenzon, Michal; Labazin, Katia; Sharan, Roded
2014-01-01
Motivation: A holy grail of biological research is a working model of the cell. Current modeling frameworks, especially in the protein–protein interaction domain, are mostly topological in nature, calling for stronger and more expressive network models. One promising alternative is logic-based or Boolean network modeling, which was successfully applied to model signaling regulatory circuits in human. Learning such models requires observing the system under a sufficient number of different conditions. To date, the amount of measured data is the main bottleneck in learning informative Boolean models, underscoring the need for efficient experimental design strategies. Results: We developed novel design approaches that greedily select an experiment to be performed so as to maximize the difference or the entropy in the results it induces with respect to current best-fit models. Unique to our maximum difference approach is the ability to account for all (possibly exponential number of) Boolean models displaying high fit to the available data. We applied both approaches to simulated and real data from the EFGR and IL1 signaling systems in human. We demonstrate the utility of the developed strategies in substantially improving on a random selection approach. Our design schemes highlight the redundancy in these datasets, leading up to 11-fold savings in the number of experiments to be performed. Availability and implementation: Source code will be made available upon acceptance of the manuscript. Contact: roded@post.tau.ac.il PMID:25161232
Adaptive finite difference for seismic wavefield modelling in acoustic media.
Yao, Gang; Wu, Di; Debens, Henry Alexander
2016-08-05
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.
Study on noise prediction model and control schemes for substation.
Chen, Chuanmin; Gao, Yang; Liu, Songtao
2014-01-01
With the government's emphasis on environmental issues of power transmission and transformation project, noise pollution has become a prominent problem now. The noise from the working transformer, reactor, and other electrical equipment in the substation will bring negative effect to the ambient environment. This paper focuses on using acoustic software for the simulation and calculation method to control substation noise. According to the characteristics of the substation noise and the techniques of noise reduction, a substation's acoustic field model was established with the SoundPLAN software to predict the scope of substation noise. On this basis, 4 reasonable noise control schemes were advanced to provide some helpful references for noise control during the new substation's design and construction process. And the feasibility and application effect of these control schemes can be verified by using the method of simulation modeling. The simulation results show that the substation always has the problem of excessive noise at boundary under the conventional measures. The excess noise can be efficiently reduced by taking the corresponding noise reduction methods.
A finite-volume scheme for a kidney nephron model
Seguin Nicolas
2012-04-01
Full Text Available We present a finite volume type scheme to solve a transport nephron model. The model consists in a system of transport equations with specific boundary conditions. The transport velocity is driven by another equation that can undergo sign changes during the transient regime. This is the main difficulty for the numerical resolution. The scheme we propose is based on an explicit resolution and is stable under a CFL condition which does not depend on the stiffness of source terms. Nous présentons un schéma numérique de type volume fini que l’on applique à un modèle de transport dans le néphron. Ce modèle consiste en un système d’équations de transport, avec des conditions aux bords spécifiques. La vitesse du transport est la solution d’un autre système d’équation et peut changer de signe au cours du régime transitoire. Ceci constitue la principale difficulté pour la résolution numérique. Le schéma proposé, basé sur une résolution explicite, est stable sous une condition CFL non restrictive.
Modeling of power control schemes in induction cooking devices
Beato, Alessio; Conti, Massimo; Turchetti, Claudio; Orcioni, Simone
2005-06-01
In recent years, with remarkable advancements of power semiconductor devices and electronic control systems, it becomes possible to apply the induction heating technique for domestic use. In order to achieve the supply power required by these devices, high-frequency resonant inverters are used: the force commutated, half-bridge series resonant converter is well suited for induction cooking since it offers an appropriate balance between complexity and performances. Power control is a key issue to attain efficient and reliable products. This paper describes and compares four power control schemes applied to the half-bridge series resonant inverter. The pulse frequency modulation is the most common control scheme: according to this strategy, the output power is regulated by varying the switching frequency of the inverter circuit. Other considered methods, originally developed for induction heating industrial applications, are: pulse amplitude modulation, asymmetrical duty cycle and pulse density modulation which are respectively based on variation of the amplitude of the input supply voltage, on variation of the duty cycle of the switching signals and on variation of the number of switching pulses. Each description is provided with a detailed mathematical analysis; an analytical model, built to simulate the circuit topology, is implemented in the Matlab environment in order to obtain the steady-state values and waveforms of currents and voltages. For purposes of this study, switches and all reactive components are modelled as ideal and the "heating-coil/pan" system is represented by an equivalent circuit made up of a series connected resistance and inductance.
An adaptive time integration scheme for blast loading on a saturated soil mass
Al-Khoury, R.; Weerheijm, J.; Dingerdis, K.; Sluys, L.J.
2011-01-01
This paper presents a time integration scheme capable of simulating blast loading of relatively high frequency on porous media, using coarse meshes. The scheme is based on the partition of unity finite element method. The discontinuity is imposed on the velocity field, while the displacement field i
A diversified portfolio model of adaptability.
Chandra, Siddharth; Leong, Frederick T L
2016-12-01
A new model of adaptability, the diversified portfolio model (DPM) of adaptability, is introduced. In the 1950s, Markowitz developed the financial portfolio model by demonstrating that investors could optimize the ratio of risk and return on their portfolios through risk diversification. The DPM integrates attractive features of a variety of models of adaptability, including Linville's self-complexity model, the risk and resilience model, and Bandura's social cognitive theory. The DPM draws on the concept of portfolio diversification, positing that diversified investment in multiple life experiences, life roles, and relationships promotes positive adaptation to life's challenges. The DPM provides a new integrative model of adaptability across the biopsychosocial levels of functioning. More importantly, the DPM addresses a gap in the literature by illuminating the antecedents of adaptive processes studied in a broad array of psychological models. The DPM is described in relation to the biopsychosocial model and propositions are offered regarding its utility in increasing adaptiveness. Recommendations for future research are also offered. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Dynamics Model Abstraction Scheme Using Radial Basis Functions
Silvia Tolu
2012-01-01
Full Text Available This paper presents a control model for object manipulation. Properties of objects and environmental conditions influence the motor control and learning. System dynamics depend on an unobserved external context, for example, work load of a robot manipulator. The dynamics of a robot arm change as it manipulates objects with different physical properties, for example, the mass, shape, or mass distribution. We address active sensing strategies to acquire object dynamical models with a radial basis function neural network (RBF. Experiments are done using a real robot’s arm, and trajectory data are gathered during various trials manipulating different objects. Biped robots do not have high force joint servos and the control system hardly compensates all the inertia variation of the adjacent joints and disturbance torque on dynamic gait control. In order to achieve smoother control and lead to more reliable sensorimotor complexes, we evaluate and compare a sparse velocity-driven versus a dense position-driven control scheme.
Unobtrusive user modeling for adaptive hypermedia
Holz, H.J.; Hofmann, K.; Reed, C.; Uchyigit, G.; Ma, M.Y.
2008-01-01
We propose a technique for user modeling in Adaptive Hypermedia (AH) that is unobtrusive at both the level of observable behavior and that of cognition. Unobtrusive user modeling is complementary to transparent user modeling. Unobtrusive user modeling induces user models appropriate for Educational
Qi, Shuanhu; Behringer, Hans; Schmid, Friederike
2013-01-01
We develop a multiscale hybrid scheme for simulations of soft condensed matter systems, which allows one to treat the system at the particle level in selected regions of space, and at the continuum level elsewhere. It is derived systematically from an underlying particle-based model by field theoretic methods. Particles in different representation regions can switch representations on the fly, controlled by a spatially varying tuning function. As a test case, the hybrid scheme is applied to s...
An interface capturing scheme for modeling atomization in compressible flows
Garrick, Daniel P.; Hagen, Wyatt A.; Regele, Jonathan D.
2017-09-01
The study of atomization in supersonic flow is critical to ensuring reliable ignition of scramjet combustors under startup conditions. Numerical methods incorporating surface tension effects have largely focused on the incompressible regime as most atomization applications occur at low Mach numbers. Simulating surface tension effects in compressible flow requires robust numerical methods that can handle discontinuities caused by both shocks and material interfaces with high density ratios. In this work, a shock and interface capturing scheme is developed that uses the Harten-Lax-van Leer-Contact (HLLC) Riemann solver while a Tangent of Hyperbola for INterface Capturing (THINC) interface reconstruction scheme retains the fluid immiscibility condition in the volume fraction and phasic densities in the context of the five equation model. The approach includes the effects of compressibility, surface tension, and molecular viscosity. One and two-dimensional benchmark problems demonstrate the desirable interface sharpening and conservation properties of the approach. Simulations of secondary atomization of a cylindrical water column after its interaction with a shockwave show good qualitative agreement with experimentally observed behavior. Three-dimensional examples of primary atomization of a liquid jet in a Mach 2 crossflow demonstrate the robustness of the method.
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.
[The model of adaptive primary image processing].
Dudkin, K N; Mironov, S V; Dudkin, A K; Chikhman, V N
1998-07-01
A computer model of adaptive segmentation of the 2D visual objects was developed. Primary image descriptions are realised via spatial frequency filters and feature detectors performing as self-organised mechanisms. Simulation of the control processes related to attention, lateral, frequency-selective and cross-orientation inhibition, determines the adaptive image processing.
Model evaluation of marine primary organic aerosol emission schemes
B. Gantt
2012-09-01
Full Text Available In this study, several marine primary organic aerosol (POA emission schemes have been evaluated using the GEOS-Chem chemical transport model in order to provide guidance for their implementation in air quality and climate models. These emission schemes, based on varying dependencies of chlorophyll a concentration ([chl a] and 10 m wind speed (U_{10}, have large differences in their magnitude, spatial distribution, and seasonality. Model comparison with weekly and monthly mean values of the organic aerosol mass concentration at two coastal sites shows that the source function exclusively related to [chl a] does a better job replicating surface observations. Sensitivity simulations in which the negative U_{10} and positive [chl a] dependence of the organic mass fraction of sea spray aerosol are enhanced show improved prediction of the seasonality of the marine POA concentrations. A top-down estimate of submicron marine POA emissions based on the parameterization that compares best to the observed weekly and monthly mean values of marine organic aerosol surface concentrations has a global average emission rate of 6.3 Tg yr^{−1}. Evaluation of existing marine POA source functions against a case study during which marine POA contributed the major fraction of submicron aerosol mass shows that none of the existing parameterizations are able to reproduce the hourly-averaged observations. Our calculations suggest that in order to capture episodic events and short-term variability in submicron marine POA concentration over the ocean, new source functions need to be developed that are grounded in the physical processes unique to the organic fraction of sea spray aerosol.
Spatial interpolation schemes of daily precipitation for hydrologic modeling
Hwang, Y.; Clark, M.; Rajagopalan, B.; Leavesley, G.
2012-01-01
Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.
Model evaluation of marine primary organic aerosol emission schemes
Gantt, B.; Johnson, M. S.; Meskhidze, N.; Sciare, J.; Ovadnevaite, J.; Ceburnis, D.; O'Dowd, C. D.
2012-09-01
In this study, several marine primary organic aerosol (POA) emission schemes have been evaluated using the GEOS-Chem chemical transport model in order to provide guidance for their implementation in air quality and climate models. These emission schemes, based on varying dependencies of chlorophyll a concentration ([chl a]) and 10 m wind speed (U10), have large differences in their magnitude, spatial distribution, and seasonality. Model comparison with weekly and monthly mean values of the organic aerosol mass concentration at two coastal sites shows that the source function exclusively related to [chl a] does a better job replicating surface observations. Sensitivity simulations in which the negative U10 and positive [chl a] dependence of the organic mass fraction of sea spray aerosol are enhanced show improved prediction of the seasonality of the marine POA concentrations. A top-down estimate of submicron marine POA emissions based on the parameterization that compares best to the observed weekly and monthly mean values of marine organic aerosol surface concentrations has a global average emission rate of 6.3 Tg yr-1. Evaluation of existing marine POA source functions against a case study during which marine POA contributed the major fraction of submicron aerosol mass shows that none of the existing parameterizations are able to reproduce the hourly-averaged observations. Our calculations suggest that in order to capture episodic events and short-term variability in submicron marine POA concentration over the ocean, new source functions need to be developed that are grounded in the physical processes unique to the organic fraction of sea spray aerosol.
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.
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.
An Adaptive Indexed Binary Search Tree for Efficient Homomorphic Coercion Resistant Voting Scheme
Vinodu George
2010-02-01
Full Text Available This paper presents a voting scheme that coalesces many of the advantageous features of an efficient e-votingscheme like receipt-freeness, uncoercibility and write-in ballot, without requiring untappable channels. Someof the previous schemes in the literature provide most of these features with a penalty of increased runningtime. The proposed scheme utilizes the advantages of a novel data structure known as “ Indexed binarysearch tree (IBST” for reducing the running time to linear order The self organizing nature of the datastructure ensures an efficient voting process. It also satisfies the desirable features of the existing write-in andcoercion resistant voting schemes, such as fair degree of efficiency and protection against any kind ofadversarial behavior with lowest running time.
Provisioning of adaptability to variable topologies for routing schemes in MANETs
Jiang, Shengming; Liu, Yaoda; Jiang, Yuming
2004-01-01
Frequent changes in network topologies caused by mobility in. mobile ad hoc networks (MANETs) impose great challenges to designing routing schemes for such networks. Various routing schemes each aiming at particular type of MANET (e.g., flat or clustered. MANETs) with different mobility degrees (e.......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...... across different types of MANETs. To handle this issue, a quantity that can predict the link status for a time period in the future with the consideration of mobility is required. In this paper, we discuss such a quantity and investigate how well this quantity can be used by the link caching scheme...
Triviality of $\\varphi^4$ theory in a finite volume scheme adapted to the broken phase
Siefert, Johannes
2014-01-01
We study the standard one-component $\\varphi^4$-theory in four dimensions. A renormalized coupling is defined in a finite size renormalization scheme which becomes the standard scheme of the broken phase for large volumes. Numerical simulations are reported using the worm algorithm in the limit of infinite bare coupling. The cutoff dependence of the renormalized coupling closely follows the perturbative Callan Symanzik equation and the triviality scenario is hence further supported.
Ushaq, Muhammad; Fang, Jiancheng
2013-10-01
Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be
Modeling Prioritized Hard Handoff Management Scheme for Wireless Mobile Networks
BISWAJIT BHOWMIK
2012-08-01
Full Text Available The channel associated with the current connection serviced by a base station is changed while a call is in progress. Usually, continuous service is achieved by supporting handoff from one cell to another. It is often initiated either by crossing a cell boundary or by deterioration in quality of the signal in the current channel. The existing call is then changed to a new base station. For the traffics which are non stationary at and are away from the servicing base station, the chances of a call to be handed off are increasing. In this paper we propose a scheme MH_2S to modeling and implementing a traffic model with handoff behavior for wireless mobile networks . The simulation model MH_2S with priority is developed to investigate the performance behavior of hard handoff strategy. Novelty of the proposed model MH_2S results that it can improve call blocking rate of handoff calls. In addition to this, measurement of blocking probabilities for both originating calls and handoff calls is another impressive achievement of the model.
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.
Grigory I. Shishkin
2008-01-01
A boundary value problem is considered for a singularly perturbed parabolic convection-diffusion equation; we construct a finite difference scheme on a priori (se-quentially) adapted meshes and study its convergence. The scheme on a priori adapted meshes is constructed using a majorant function for the singular component of the discrete solution, which allows us to find a priori a subdomain where the computed solution requires a further improvement. This subdomain is defined by the perturbation parameter ε, the step-size of a uniform mesh in x, and also by the required accuracy of the discrete solution and the prescribed number of refinement iterations K for im-proving the solution. To solve the discrete problems aimed at the improvement of the solution, we use uniform meshes on the subdomains. The error of the numerical so-lution depends weakly on the parameter ε. The scheme converges almost ε-uniformly, precisely, under the condition N-1 = o(ev), where N denotes the number of nodes in the spatial mesh, and the value v=v(K) can be chosen arbitrarily small for suitable K.
Adaptive
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.
Rudnick, H.; Palma, R.; Cura, E.; Silva, C. [Pontificia Univ. Catolica de Chile, Santiago (Chile). Dept. de Ingenieria Electrica
1996-08-01
A dynamic transmission planning methodology using a genetic algorithm is formulated for the purpose of determining an economically adapted electric transmission system in a deregulated open access environment. Transmission investment sensitivity information linked to short term marginal income is used. A computer program is developed and applied to obtain a long range adapted transmission grid for the Chilean electrical system. Two open access pricing methodologies are evaluated in a spot price framework, as applied to the adapted grid over the time horizon.
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.
Status adaptive routing with delayed rebroadcast scheme in AODV-based MANETs
LI Ting; TANG Rui-bo; JI Hong
2008-01-01
An efficient solution is proposed in this article to determine the best reliable route and to prolong the lifetime of the mobile Ad-hoc networks (MANETs). In the proposed solution, the route discovery process of the Ad-hoc on-demand distance vector routing protocol (AODV) has been modified using a novel delayed rebroadcast scheme. It combines the shortest route selection criterion of AODV with the real network status including the wireless link quality, the remaining power capacity, as well as the traffic load at each node. Simulation results show that the proposed scheme can significantly extend the network lifetime and provide fewer packet losses than the conventional AODV protocol.
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.
Gall, Heather E.; Jafvert, Chad T.; Jenkinson, Byron
2010-11-01
Automated sample collection for water quality research and evaluation generally is performed by simple time-paced or flow-weighted sampling protocols. However, samples collected on strict time-paced or flow-weighted schemes may not adequately capture all elements of storm event hydrographs (i.e., rise, peak, and recession). This can result in inadequate information for calculating chemical mass flux over storm events. In this research, an algorithm was developed to guide automated sampling of hydrographs based on storm-specific information. A key element of the new "hydrograph-specific sampling scheme" is the use of a hydrograph recession model for predicting the hydrograph recession curve, during which flow-paced intervals are calculated for scheduling the remaining samples. The algorithm was tested at a tile drained Midwest agricultural site where real-time flow data were processed by a programmable datalogger that in turn activated an automated sampler at the appropriate sampling times to collect a total of twenty samples during each storm event independent of the number of sequential hydrographs generated. The utility of the algorithm was successfully tested with hydrograph data collected at both a tile drain and agricultural ditch, suggesting the potential for general applicability of the method. This sampling methodology is flexible in that the logic can be adapted for use with any hydrograph recession model; however, in this case a power law equation proved to be the most practical model.
G. Santhosh Kumar
2014-01-01
Full Text Available In this paper, we propose a frame-work for the performance evaluation of frequency allocation schemes in 3G LTE OFDMA systems. We first develop an analytical model for collisions in an OFDMA system for an arbitrary number of users in the different cells. We then calculate the capacity of the system using a Markov model and taking into account the inter-cell interference and its impact on the adaptive modulation. We finally apply this model to compare three frequency allocation schemes, namely reuse 1, reuse 3, and a mix of reuse 1 and 3. Our results show that a mix of reuse 1 and 3 schemes outperforms a reuse 1 scheme in terms of better cell-edge performance, and outperforms also a reuse 3 scheme by achieving an higher cell throughput.
Numerical Modeling of Deep Mantle Convection: Advection and Diffusion Schemes for Marker Methods
Mulyukova, Elvira; Dabrowski, Marcin; Steinberger, Bernhard
2013-04-01
Thermal and chemical evolution of Earth's deep mantle can be studied by modeling vigorous convection in a chemically heterogeneous fluid. Numerical modeling of such a system poses several computational challenges. Dominance of heat advection over the diffusive heat transport, and a negligible amount of chemical diffusion results in sharp gradients of thermal and chemical fields. The exponential dependence of the viscosity of mantle materials on temperature also leads to high gradients of the velocity field. The accuracy of many numerical advection schemes degrades quickly with increasing gradient of the solution, while the computational effort, in terms of the scheme complexity and required resolution, grows. Additional numerical challenges arise due to a large range of length-scales characteristic of a thermochemical convection system with highly variable viscosity. To examplify, the thickness of the stem of a rising thermal plume may be a few percent of the mantle thickness. An even thinner filament of an anomalous material that is entrained by that plume may consitute less than a tenth of a percent of the mantle thickness. We have developed a two-dimensional FEM code to model thermochemical convection in a hollow cylinder domain, with a depth- and temperature-dependent viscosity representative of the mantle (Steinberger and Calderwood, 2006). We use marker-in-cell method for advection of chemical and thermal fields. The main advantage of perfoming advection using markers is absence of numerical diffusion during the advection step, as opposed to the more diffusive field-methods. However, in the common implementation of the marker-methods, the solution of the momentum and energy equations takes place on a computational grid, and nodes do not generally coincide with the positions of the markers. Transferring velocity-, temperature-, and chemistry- information between nodes and markers introduces errors inherent to inter- and extrapolation. In the numerical scheme
Site, Luigi Delle; Junghans, Christoph; Wang, Han
2014-01-01
We describe the adaptive resolution multiscale method AdResS. The conceptual evolution as well as the improvements of its technical efficiency are described step by step, with an explicit reference to current limitations and open problems.
Che, Y.; Li, R. X.; Han, C. X.; Wang, J.; Cui, S. G.; Deng, B.; Wei, X.
2012-08-01
This paper presents an adaptive lag synchronization based method for simultaneous identification of topology and parameters of uncertain general complex dynamical networks with and without time delays. Based on Lyapunov stability theorem and LaSalle's invariance principle, an adaptive controller is designed to realize lag synchronization between drive and response systems, meanwhile, identification criteria of network topology and system parameters are obtained. Numerical simulations illustrate the effectiveness of the proposed method.
Adaptive control model of water resources regulation in the Yellow River
WEI; Jiahua; WANG; Guangqian; WENG; Wenbin; CAI; Zhiguo; C
2004-01-01
According to the principle of procedure control and the characteristic of stochastic of inflow and water demands, this paper deals with the application of adaptive control to a water resources regulation system. The main control objective is to approach the vested target of water resources allocation by controlling the reservoir discharge and water demand. The adaptive control implemented is based on the linear quadratic control approach. Models of water balance, reservoir adjusted model and allocation model are used for the control purposes. The results show the performance of this adaptive scheme and its ability to control the water resources allocation process.
A new approach to adaptive data models
Ion LUNGU
2016-12-01
Full Text Available Over the last decade, there has been a substantial increase in the volume and complexity of data we collect, store and process. We are now aware of the increasing demand for real time data processing in every continuous business process that evolves within the organization. We witness a shift from a traditional static data approach to a more adaptive model approach. This article aims to extend understanding in the field of data models used in information systems by examining how an adaptive data model approach for managing business processes can help organizations accommodate on the fly and build dynamic capabilities to react in a dynamic environment.
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 the netw......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...... the network, the contribution share of faraway and close WTs in the LFC plan is same, whereas there may be sufficient spinning reserve available in the local WTs close to the event location. This paper employs the initial voltage drop at the moment of perturbation to assess the proximity to the failure point...
A self-adaptive image encryption scheme with half-pixel interchange permutation operation
Ye, Ruisong; Liu, Li; Liao, Minyu; Li, Yafang; Liao, Zikang
2017-01-01
A plain-image dependent image encryption scheme with half-pixel-level swapping permutation strategy is proposed. In the new permutation operation, a pixel-swapping operation between four higher bit-planes and four lower bit-planes is employed to replace the traditional confusion operation, which not only improves the conventional permutation efficiency within the plain-image, but also changes all the pixel gray values. The control parameters of generalized Arnold map applied for the permutation operation are related to the plain-image content and consequently can resist chosen-plaintext and known-plaintext attacks effectively. To enhance the security of the proposed image encryption, one multimodal skew tent map is applied to generate pseudo-random gray value sequence for diffusion operation. Simulations have been carried out thoroughly to demonstrate that the proposed image encryption scheme is highly secure thanks to its large key space and efficient permutation-diffusion operations.
A distributed adaptive multi-hop certification authority scheme for mobile Ad Hoc networks
Tan Xuezhi; Wu Shaochuan; Jia Shilou
2005-01-01
This paper theoretically analyzes a deficiency of the existing scheme, and proposes a distributed multi-hop certification authority scheme for mobile Ad Hoc networks. In our design, we distribute the certification authority functions through a threshold secret sharing mechanism, in which each node holds a secret share and multiple nodes jointly provide complete services. Certification authority is not limited in a local neighborhood but can be completed within multi-hop location. In addition, we replace broadcast by multicast to improve system performance and reduce communication overhead. This paper resolves some technical problems of ubiquitous certification authority services, and presents a wieldy multi-hop certification authority algorithm. Simulation results confirm the availability and effectiveness of our design.
Graphical Models and Computerized Adaptive Testing.
Mislevy, Robert J.; Almond, Russell G.
This paper synthesizes ideas from the fields of graphical modeling and education testing, particularly item response theory (IRT) applied to computerized adaptive testing (CAT). Graphical modeling can offer IRT a language for describing multifaceted skills and knowledge, and disentangling evidence from complex performances. IRT-CAT can offer…
Adaptive Duty-Cycling to Enhance Topology Control Schemes in Wireless Sensor Networks
Myungsu Cha; Mihui Kim; Dongsoo S. Kim; Hyunseung Choo
2014-01-01
To prolong the network lifetime, various scheduling approaches that schedule wireless devices of nodes to switch between active and sleep states have been studied. Topology control schemes are one of the scheduling approaches that can extend the network lifetime and reduce the additional communication delays at the same time. However, they do not guarantee that all nodes have the same lifetime. They reduce the network coverage and prevent seamless communications. This paper proposes an adapti...
Nonhydrostatic adaptive mesh dynamics for multiscale climate models (Invited)
Collins, W.; Johansen, H.; McCorquodale, P.; Colella, P.; Ullrich, P. A.
2013-12-01
Many of the atmospheric phenomena with the greatest potential impact in future warmer climates are inherently multiscale. Such meteorological systems include hurricanes and tropical cyclones, atmospheric rivers, and other types of hydrometeorological extremes. These phenomena are challenging to simulate in conventional climate models due to the relatively coarse uniform model resolutions relative to the native nonhydrostatic scales of the phenomonological dynamics. To enable studies of these systems with sufficient local resolution for the multiscale dynamics yet with sufficient speed for climate-change studies, we have adapted existing adaptive mesh dynamics for the DOE-NSF Community Atmosphere Model (CAM). In this talk, we present an adaptive, conservative finite volume approach for moist non-hydrostatic atmospheric dynamics. The approach is based on the compressible Euler equations on 3D thin spherical shells, where the radial direction is treated implicitly (using a fourth-order Runga-Kutta IMEX scheme) to eliminate time step constraints from vertical acoustic waves. Refinement is performed only in the horizontal directions. The spatial discretization is the equiangular cubed-sphere mapping, with a fourth-order accurate discretization to compute flux averages on faces. By using both space-and time-adaptive mesh refinement, the solver allocates computational effort only where greater accuracy is needed. The resulting method is demonstrated to be fourth-order accurate for model problems, and robust at solution discontinuities and stable for large aspect ratios. We present comparisons using a simplified physics package for dycore comparisons of moist physics. Hadley cell lifting an advected tracer into upper atmosphere, with horizontal adaptivity
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.
Hybrid Surface Mesh Adaptation for Climate Modeling
Ahmed Khamayseh; Valmor de Almeida; Glen Hansen
2008-01-01
Solution-driven mesh adaptation is becoming quite popular for spatial error control in the numerical simulation of complex computational physics applications, such as climate modeling. Typically, spatial adaptation is achieved by element subdivision (h adaptation) with a primary goal of resolving the local length scales of interest. A second, lesspopular method of spatial adaptivity is called "mesh motion" (r adaptation); the smooth repositioning of mesh node points aimed at resizing existing elements to capture the local length scales. This paper proposes an adaptation method based on a combination of both element subdivision and node point repositioning (rh adaptation). By combining these two methods using the notion of a mobility function, the proposed approach seeks to increase the flexibility and extensibility of mesh motion algorithms while providing a somewhat smoother transition between refined regions than is pro-duced by element subdivision alone. Further, in an attempt to support the requirements of a very general class of climate simulation applications, the proposed method is de-signed to accommodate unstructured, polygonal mesh topologies in addition to the most popular mesh types.
3 Lectures: "Lagrangian Models", "Numerical Transport Schemes", and "Chemical and Transport Models"
Douglass, A.
2005-01-01
The topics for the three lectures for the Canadian Summer School are Lagrangian Models, numerical transport schemes, and chemical and transport models. In the first lecture I will explain the basic components of the Lagrangian model (a trajectory code and a photochemical code), the difficulties in using such a model (initialization) and show some applications in interpretation of aircraft and satellite data. If time permits I will show some results concerning inverse modeling which is being used to evaluate sources of tropospheric pollutants. In the second lecture I will discuss one of the core components of any grid point model, the numerical transport scheme. I will explain the basics of shock capturing schemes, and performance criteria. I will include an example of the importance of horizontal resolution to polar processes. We have learned from NASA's global modeling initiative that horizontal resolution matters for predictions of the future evolution of the ozone hole. The numerical scheme will be evaluated using performance metrics based on satellite observations of long-lived tracers. The final lecture will discuss the evolution of chemical transport models over the last decade. Some of the problems with assimilated winds will be demonstrated, using satellite data to evaluate the simulations.
Schwing, Alan Michael
For computational fluid dynamics, the governing equations are solved on a discretized domain of nodes, faces, and cells. The quality of the grid or mesh can be a driving source for error in the results. While refinement studies can help guide the creation of a mesh, grid quality is largely determined by user expertise and understanding of the flow physics. Adaptive mesh refinement is a technique for enriching the mesh during a simulation based on metrics for error, impact on important parameters, or location of important flow features. This can offload from the user some of the difficult and ambiguous decisions necessary when discretizing the domain. This work explores the implementation of adaptive mesh refinement in an implicit, unstructured, finite-volume solver. Consideration is made for applying modern computational techniques in the presence of hanging nodes and refined cells. The approach is developed to be independent of the flow solver in order to provide a path for augmenting existing codes. It is designed to be applicable for unsteady simulations and refinement and coarsening of the grid does not impact the conservatism of the underlying numerics. The effect on high-order numerical fluxes of fourth- and sixth-order are explored. Provided the criteria for refinement is appropriately selected, solutions obtained using adapted meshes have no additional error when compared to results obtained on traditional, unadapted meshes. In order to leverage large-scale computational resources common today, the methods are parallelized using MPI. Parallel performance is considered for several test problems in order to assess scalability of both adapted and unadapted grids. Dynamic repartitioning of the mesh during refinement is crucial for load balancing an evolving grid. Development of the methods outlined here depend on a dual-memory approach that is described in detail. Validation of the solver developed here against a number of motivating problems shows favorable
THE APPLICATION OF TIDAL SIGNAL EXCLUSION SCHEME FROM INITIALIZATION IN A GENERAL CIRCULATION MODEL
杨学胜; 王军; 陈谊
2004-01-01
In this paper, some corrections was made to the assumption that the forcing is quasi-static, which is the basis of the nonlinear diabatic initialization scheme adopted by a global model T106L19. Thus the tidal signal is expressed and excluded from the initialization scheme. It shows that the new scheme captures the semi-diurnal pressure variation and is much closer to the uninitialized field. Compared with the standard initialization scheme, both the anomaly correlation coefficients and RMS of 500 hPa geopotential height simulated under the new scheme have improved significantly.
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.
On usage of CABARET scheme for tracer transport in INM ocean model
Diansky, Nikolay; Kostrykin, Sergey; Gusev, Anatoly; Salnikov, Nikolay
2010-06-01
The contemporary state of ocean numerical modelling sets some requirements for the numerical advection schemes used in ocean general circulation models (OGCMs). The most important requirements are conservation, monotonicity and numerical efficiency including good parallelization properties. Investigation of some advection schemes shows that one of the best schemes satisfying the criteria is CABARET scheme. 3D-modification of the CABARET scheme was used to develop a new transport module (for temperature and salinity) for the Institute of Numerical Mathematics ocean model (INMOM). Testing of this module on some common benchmarks shows a high accuracy in comparison with the second-order advection scheme used in the INMOM. This new module was incorporated in the INMOM and experiments with the modified model showed a better simulation of oceanic circulation than its previous version.
A novel data adaptive detection scheme for distributed fiber optic acoustic sensing
Ölçer, Íbrahim; Öncü, Ahmet
2016-05-01
We introduce a new approach for distributed fiber optic sensing based on adaptive processing of phase sensitive optical time domain reflectometry (Φ-OTDR) signals. Instead of conventional methods which utilizes frame averaging of detected signal traces, our adaptive algorithm senses a set of noise parameters to enhance the signal-to-noise ratio (SNR) for improved detection performance. This data set is called the secondary data set from which a weight vector for the detection of a signal is computed. The signal presence is sought in the primary data set. This adaptive technique can be used for vibration detection of health monitoring of various civil structures as well as any other dynamic monitoring requirements such as pipeline and perimeter security applications.
An Adaptive Identification and Control Scheme Using Radial Basis Function Networks
无
1999-01-01
In this paper, adaptive identification and control of nonlinear dynamical systems are investigated using radial basis function networks (RBF). Firstly, a novel approach to train the RBF is introduced, which employs an adaptive fuzzy generalized learning vector quantization (AFGLVQ) technique and recursive least squares algorithm with variable forgetting factor (VRLS). The AFGLVQ adjusts the centers of the RBF while the VRLS updates the connection weights of the network. The identification algorithm has the properties of rapid convergence and persistent adaptability that make it suitable for real-time control. Secondly, on the basis of the one-step ahead RBF predictor, the control law is optimized iteratively through a numerical stable Davidon's least squares-based (SDLS) minimization approach. Four nonlinear examples are simulated to demonstrate the effectiveness of the identification and control algorithms.
Switching Control System Based on Robust Model Reference Adaptive Control
HU Qiong; FEI Qing; MA Hongbin; WU Qinghe; GENG Qingbo
2016-01-01
For conventional adaptive control,time-varying parametric uncertainty and unmodeled dynamics are ticklish problems,which will lead to undesirable performance or even instability and nonrobust behavior,respectively.In this study,a class of discrete-time switched systems with unmodeled dynamics is taken into consideration.Moreover,nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper,and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance.For robustness against unmodeled dynamics and uncertainty,robust model reference aclaptive control (RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems.Meanwhile,two different switching laws are presented for switched systems and nonlinear systems,respectively.Thereby,the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems.Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes.Furthermore,as to the proposed scheme for nonlinear systems,its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.
Multi-loop adaptive internal model control based on a dynamic partial least squares model
Zhao ZHAO; Bin HU; Jun LIANG
2011-01-01
A multi-loop adaptive internal model control (IMC) strategy based on a dynamic partial least squares (PLS) framework is proposed to account for plant model errors caused by slow aging, drift in operational conditions, or environmental changes. Since PLS decomposition structure enables multi-loop controller design within latent spaces, a multivariable adaptive control scheme can be converted easily into several independent univariable control loops in the PLS space. In each latent subspace,once the model error exceeds a specific threshold, online adaptation rules are implemented separately to correct the plant model mismatch via a recursive least squares (RLS) algorithm. Because the IMC extracts the inverse of the minimum part of the internal model as its structure, the IMC controller is self-tuned by explicitly updating the parameters, which are parts of the internal model.Both parameter convergence and system stability are briefly analyzed, and proved to be effective. Finally, the proposed control scheme is tested and evaluated using a widely-used benchmark of a multi-input multi-output (MIMO) system with pure delay.
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.
Battistelli, Giorgio; Mosca, Edoardo; Tesi, Pietro
2011-01-01
In this paper, a multi-model unfalsified adaptive switching control scheme is proposed for controlling uncertain plants subject to time variations. In the adopted approach, the switching between the candidate controllers is orchestrated according to a hysteresis logic variant wherein the memory leng
A positive and entropy-satisfying finite volume scheme for the Baer-Nunziato model
Coquel, Frédéric; Hérard, Jean-Marc; Saleh, Khaled
2017-02-01
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 [16] for the isentropic Baer-Nunziato model and consequently inherits its main properties. To our knowledge, this is the only existing scheme for which the approximated phase fractions, phase densities and phase internal energies are proven to remain positive without any restrictive condition other than a classical fully computable CFL condition. For ideal gas and stiffened gas equations of state, real values of the phasic speeds of sound are also proven to be maintained by the numerical scheme. 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. This last property, which ensures the non-linear stability of the numerical method, is satisfied for any admissible equation of state. We provide a numerical study for the convergence of the approximate solutions towards some exact Riemann solutions. The numerical simulations show that the relaxation scheme compares well with two of the most popular existing schemes available for the Baer-Nunziato model, namely Schwendeman-Wahle-Kapila's Godunov-type scheme [39] and Tokareva-Toro's HLLC scheme [44]. The relaxation scheme also shows a higher precision and a lower computational cost (for comparable accuracy) than a standard numerical scheme used in the nuclear industry, namely Rusanov's scheme. Finally, we assess the good behavior of the scheme when approximating vanishing phase solutions.
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.
Numerical tests of efficiency of the retrospective time integration scheme in the self-memory model
GU Xiangqian; YOU Xingtian; ZHU He; CAO Hongxing
2004-01-01
A set of numerical tests was carried out to compare the retrospective time integral scheme in a self-memory model,whose dynamic kernel is the barotropical quasi-geostrophic model, with the ordinary centered difference scheme in the barotropical quasigeostrophic model. The Rossby-Haurwitz wave function was taken as the initial fields for both schemes. The results show that in comparison with the ordinary centered difference scheme, the retrospective time integral scheme reduces by 2 orders of magnitude the forecast error, and the forecast error increases very little with lengthening of the time-step. Therefore, the retrospective time integral scheme has advantages of improving the forecast accuracy, extending the predictable duration and reducing the computation amount.
Arturo Torres-González
2014-04-01
Full Text Available 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 inter-beacon measurements with different inter-beacon depth levels and at different rates. It also includes a supervision module that monitors the SLAM performance and dynamically selects the measurement gathering configuration balancing SLAM accuracy and resource consumption. The proposed scheme has been applied to an extended Kalman filter SLAM with auxiliary particle filters for beacon initialization (PF-EKF SLAM and validated with experiments performed in the CONET Integrated Testbed. It achieved lower map and robot errors (34% and 14%, respectively than traditional methods with a lower computational burden (16% and similar beacon energy consumption.
Torres-González, Arturo; Martinez-de Dios, Jose Ramiro; Ollero, Anibal
2014-04-25
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 inter-beacon measurements with different inter-beacon depth levels and at different rates. It also includes a supervision module that monitors the SLAM performance and dynamically selects the measurement gathering configuration balancing SLAM accuracy and resource consumption. The proposed scheme has been applied to an extended Kalman filter SLAM with auxiliary particle filters for beacon initialization (PF-EKF SLAM) and validated with experiments performed in the CONET Integrated Testbed. It achieved lower map and robot errors (34% and 14%, respectively) than traditional methods with a lower computational burden (16%) and similar beacon energy consumption.
Adaptive regression for modeling nonlinear relationships
Knafl, George J
2016-01-01
This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of outcome variables. Such nonlinear dependence is often not considered in applied research, yet nonlinear relationships are common and so need to be addressed. A standard linear analysis can produce misleading conclusions, while a nonlinear analysis can provide novel insights into data, not otherwise possible. A variety of examples of the benefits of modeling nonlinear relationships are presented throughout the book. Methods are covered using what are called fractional polynomials based on real-valued power transformations of primary predictor variables combined with model selection based on likelihood cross-validation. The book covers how to formulate and conduct such adaptive fractional polynomial modeling in the s...
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.
Adaptive Control of MEMS Gyroscope Based on T-S Fuzzy Model
Yunmei Fang
2015-01-01
Full Text Available A multi-input multioutput (MIMO Takagi-Sugeno (T-S fuzzy model is built on the basis of a nonlinear model of MEMS gyroscope. A reference model is adjusted so that a local linear state feedback controller could be designed for each T-S fuzzy submodel based on a parallel distributed compensation (PDC method. A parameter estimation scheme for updating the parameters of the T-S fuzzy models is designed and analyzed based on the Lyapunov theory. A new adaptive law can be selected to be the former adaptive law plus a nonnegative in variable to guarantee that the derivative of the Lyapunov function is smaller than zero. The controller output is implemented on the nonlinear model and T-S fuzzy model, respectively, for the purpose of comparison. Numerical simulations are investigated to verify the effectiveness of the proposed control scheme and the correctness of the T-S fuzzy model.
An explanatory model of underwater adaptation
Joaquín Colodro
Full Text Available The underwater environment is an extreme environment that requires a process of human adaptation with specific psychophysiological demands to ensure survival and productive activity. From the standpoint of existing models of intelligence, personality and performance, in this explanatory study we have analyzed the contribution of individual differences in explaining the adaptation of military personnel in a stressful environment. Structural equation analysis was employed to verify a model representing the direct effects of psychological variables on individual adaptation to an adverse environment, and we have been able to confirm, during basic military diving courses, the structural relationships among these variables and their ability to predict a third of the variance of a criterion that has been studied very little to date. In this way, we have confirmed in a sample of professionals (N = 575 the direct relationship of emotional adjustment, conscientiousness and general mental ability with underwater adaptation, as well as the inverse relationship of emotional reactivity. These constructs are the psychological basis for working under water, contributing to an improved adaptation to this environment and promoting risk prevention and safety in diving activities.
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
Error estimation and adaptive chemical transport modeling
Malte Braack
2014-09-01
Full Text Available We present a numerical method to use several chemical transport models of increasing accuracy and complexity in an adaptive way. In largest parts of the domain, a simplified chemical model may be used, whereas in certain regions a more complex model is needed for accuracy reasons. A mathematically derived error estimator measures the modeling error and provides information where to use more accurate models. The error is measured in terms of output functionals. Therefore, one has to consider adjoint problems which carry sensitivity information. This concept is demonstrated by means of ozone formation and pollution emission.
Modeling 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 concepts
In Chapters 1 and 2 an overview of the problem formulation
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
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
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.
Modeling and Simulation of Handover Scheme in Integrated EPON-WiMAX Networks
Yan, Ying; Dittmann, Lars
2011-01-01
by enhancing the traditional MPCP signaling protocol, which cooperatively collects mobility information from the front-end wireless network and makes centralized bandwidth allocation decisions in the backhaul optical network. The integrated network architecture and the joint handover scheme are simulated using......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...... OPNET modeler. Results show validation of the protocol, i.e., integrated handover scheme gains better network performances....
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.
Model Based Adaptive Piecewise Linear Controller for Complicated Control Systems
Tain-Sou Tsay
2014-01-01
Full Text Available A model based adaptive piecewise linear control scheme for industry processes with specifications on peak overshoots and rise times is proposed. It is a gain stabilized control technique. Large gain is used for large tracking error to get fast response. Small gain is used between large and small tracking error for good performance. Large gain is used again for small tracking error to cope with large disturbance. Parameters of the three-segment piecewise linear controller are found by an automatic regulating time series which is function of output characteristics of the plant and reference model. The time series will be converged to steady values after the time response of the considered system matching that of the reference model. The proposed control scheme is applied to four numerical examples which have been compensated by PID controllers. Parameters of PID controllers are found by optimization method. It gives an almost command independent response and gives significant improvements for response time and performance.
Adaptive Covariance Estimation with model selection
Biscay, Rolando; Loubes, Jean-Michel
2012-01-01
We provide in this paper a fully adaptive penalized procedure to select a covariance among a collection of models observing i.i.d replications of the process at fixed observation points. For this we generalize previous results of Bigot and al. and propose to use a data driven penalty to obtain an oracle inequality for the estimator. We prove that this method is an extension to the matricial regression model of the work by Baraud.
A second-order characteristic line scheme for solving a juvenile-adult model of amphibians.
Deng, Keng; Wang, Yi
2015-01-01
In this paper, we develop a second-order characteristic line scheme for a nonlinear hierarchical juvenile-adult population model of amphibians. The idea of the scheme is not to follow the characteristics from the initial data, but for each time step to find the origins of the grid nodes at the previous time level. Numerical examples are presented to demonstrate the accuracy of the scheme and its capability to handle solutions with singularity.
Gillibrand, P. A.; Herzfeld, M.
2016-05-01
We present a flux-form semi-Lagrangian (FFSL) advection scheme designed for offline scalar transport simulation with coastal ocean models using curvilinear horizontal coordinates. The scheme conserves mass, overcoming problems of mass conservation typically experienced with offline transport models, and permits long time steps (relative to the Courant number) to be used by the offline model. These attributes make the method attractive for offline simulation of tracers in biogeochemical or sediment transport models using archived flow fields from hydrodynamic models. We describe the FFSL scheme, and test it on two idealised domains and one real domain, the Great Barrier Reef in Australia. For comparison, we also include simulations using a traditional semi-Lagrangian advection scheme for the offline simulations. We compare tracer distributions predicted by the offline FFSL transport scheme with those predicted by the original hydrodynamic model, assess the conservation of mass in all cases and contrast the computational efficiency of the schemes. We find that the FFSL scheme produced very good agreement with the distributions of tracer predicted by the hydrodynamic model, and conserved mass with an error of a fraction of one percent. In terms of computational speed, the FFSL scheme was comparable with the semi-Lagrangian method and an order of magnitude faster than the full hydrodynamic model, even when the latter ran in parallel on multiple cores. The FFSL scheme presented here therefore offers a viable mass-conserving and computationally-efficient alternative to traditional semi-Lagrangian schemes for offline scalar transport simulation in coastal models.
ART-GAS: An Adaptive and Real-Time GTS Allocation Scheme for IEEE 802.15.4
Xia, Feng; Cao, Yang; Xue, Lei
2012-01-01
IEEE 802.15.4 supports a Guaranteed Time Slot (GTS) allocation mechanism for time-critical and delay-sensitive data transmissions in Wireless Personal Area Networks (WPANs). However, the inflexible first-come-first-served GTS allocation policy and the passive deallocation mechanism significantly reduce network efficiency. In this paper, we propose an Adaptive and Real-Time GTS Allocation Scheme (ART-GAS) to provide differentiated services for devices with different priorities, which guarantees data transmissions for time-sensitive and high-traffic devices. The bandwidth utilization in IEEE 802.15.4-based PAN is improved. Simulation results show that our ART-GAS algorithm significantly outperforms the existing GTS mechanism specified in IEEE 802.15.4.
A fast and efficient adaptive threshold rate control scheme for remote sensing images.
Chen, Xiao; Xu, Xiaoqing
2012-01-01
The JPEG2000 image compression standard is ideal for processing remote sensing images. However, its algorithm is complex and it requires large amounts of memory, making it difficult to adapt to the limited transmission and storage resources necessary for remote sensing images. In the present study, an improved rate control algorithm for remote sensing images is proposed. The required coded blocks are sorted downward according to their numbers of bit planes prior to entropy coding. An adaptive threshold computed from the combination of the minimum number of bit planes, along with the minimum rate-distortion slope and the compression ratio, is used to truncate passes of each code block during Tier-1 encoding. This routine avoids the encoding of all code passes and improves the coding efficiency. The simulation results show that the computational cost and working buffer memory size of the proposed algorithm reach only 18.13 and 7.81%, respectively, of the same parameters in the postcompression rate distortion algorithm, while the peak signal-to-noise ratio across the images remains almost the same. The proposed algorithm not only greatly reduces the code complexity and buffer requirements but also maintains the image quality.
Adapting virtual camera behaviour through player modelling
Burelli, Paolo; Yannakakis, Georgios N.
2015-01-01
Research in virtual camera control has focused primarily on finding methods to allow designers to place cameras effectively and efficiently in dynamic and unpredictable environments, and to generate complex and dynamic plans for cinematography in virtual environments. In this article, we propose...... a novel approach to virtual camera control, which builds upon camera control and player modelling to provide the user with an adaptive point-of-view. To achieve this goal, we propose a methodology to model the player’s preferences on virtual camera movements and we employ the resulting models to tailor...... the viewpoint movements to the player type and her game-play style. Ultimately, the methodology is applied to a 3D platform game and is evaluated through a controlled experiment; the results suggest that the resulting adaptive cinematographic experience is favoured by some player types and it can generate...
Ning Li; Chunsheng Weng
2011-01-01
@@ A modified adaptive algebraic reconstruction technique (MAART) with an auto-adjustment relaxation parameter and smoothness regularization is developed to reveal the tomographic reconstruction of H2O distribution in combustion from incomplete projections.Determinations of relaxation parameter and regularization factor are discussed with regard to the consideration of improvement in reconstruction and reduction of computational burden.A two-wavelength scheme from tunable diode laser absorption measurement, 7444.36 and 7185.59 cm-1, is used to simplify the nonlinear solution problem for obtaining the tomographic distributions of concentration and temperature simultaneously.Results of calculations demonstrate that MAART can perform the reconstruction results more efficiently with little complex modification and much lower iterations as compared with the traditional algebraic reconstruction technique (ART) or simultaneous iterative reconstruction technique (SIRT) methods.The stability of the algorithm is studied by reconstruction from projections with random noise at different levels to demonstrate the dependence of reconstruction results on precise line-of-sight measurements.%A modified adaptive algebraic reconstruction technique (MAART) with an auto-adjustment relaxation parameter and smoothness regularization is developed to reveal the tomographic reconstruction of H2O distribution in combustion from incomplete projections. Determinations of relaxation parameter and regularization factor are discussed with regard to the consideration of improvement in reconstruction and reduction of computational burden. A two-wavelength scheme from tunable diode laser absorption measurement, 7444.36 and 7185.59 cm-1, is used to simplify the nonlinear solution problem for obtaining the tomographic distributions of concentration and temperature simultaneously. Results of calculations demonstrate that MAART can perform the reconstruction results more efficiently with little complex
Decentralized model reference adaptive sliding mode control based on fuzzy model
Gu Haijun; Zhang Tianping; Shen Qikun
2006-01-01
A new design scheme of decentralized model reference adaptive sliding mode controller for a class of MIMO nonlinear systems with the high-order interconnections is proposed. The design is based on the universal approximation capability of the Takagi - Seguno (T-S) fuzzy systems. Motivated by the principle of certainty equivalentcontrol, a decentralized adaptive controller is designed to achieve the tracking objective without computation of the T-S fuzz ymodel. The approach does not require the upper bound of the uncertainty term to be known through some adaptive estimation. By theoretical analysis, the closed-loop fuzzy control system is proven to be globally stable in the sense that all signalsinvolved are bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.
An Adaptive Medium Access Parameter Prediction Scheme for IEEE 802.11 Real-Time Applications
Estefanía Coronado
2017-01-01
Full Text Available Multimedia communications have experienced an unprecedented growth due mainly to the increase in the content quality and the emergence of smart devices. The demand for these contents is tending towards wireless technologies. However, these transmissions are quite sensitive to network delays. Therefore, ensuring an optimum QoS level becomes of great importance. The IEEE 802.11e amendment was released to address the lack of QoS capabilities in the original IEEE 802.11 standard. Accordingly, the Enhanced Distributed Channel Access (EDCA function was introduced, allowing it to differentiate traffic streams through a group of Medium Access Control (MAC parameters. Although EDCA recommends a default configuration for these parameters, it has been proved that it is not optimum in many scenarios. In this work a dynamic prediction scheme for these parameters is presented. This approach ensures an appropriate traffic differentiation while maintaining compatibility with the stations without QoS support. As the APs are the only devices that use this algorithm, no changes are required to current network cards. The results show improvements in both voice and video transmissions, as well as in the QoS level of the network that the proposal achieves with regard to EDCA.
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.
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 linked...... countries should opt to support stationary fuel cells, we find that in Denmark it would be promising to apply the net metering based support scheme for households with an electricity consumption exceeding the electricity production from the fuel cell. In France and Portugal the most promising support scheme...
Yang, Xiaofeng; Han, Daozhi
2017-02-01
In this paper, we develop a series of linear, unconditionally energy stable numerical schemes for solving the classical phase field crystal model. The temporal discretizations are based on the first order Euler method, the second order backward differentiation formulas (BDF2) and the second order Crank-Nicolson method, respectively. The schemes lead to linear elliptic equations to be solved at each time step, and the induced linear systems are symmetric positive definite. We prove that all three schemes are unconditionally energy stable rigorously. Various classical numerical experiments in 2D and 3D are performed to validate the accuracy and efficiency of the proposed schemes.
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.
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.
Adaptive evolution on a continuous lattice model
Claudino, Elder S.; Lyra, M. L.; Gleria, Iram; Campos, Paulo R. A.
2013-03-01
In the current work, we investigate the evolutionary dynamics of a spatially structured population model defined on a continuous lattice. In the model, individuals disperse at a constant rate v and competition is local and delimited by the competition radius R. Due to dispersal, the neighborhood size (number of individuals competing for reproduction) fluctuates over time. Here we address how these new variables affect the adaptive process. While the fixation probabilities of beneficial mutations are roughly the same as in a panmitic population for small fitness effects s, a dependence on v and R becomes more evident for large s. These quantities also strongly influence fixation times, but their dependencies on s are well approximated by s-1/2, which means that the speed of the genetic wave front is proportional to s. Most important is the observation that the model exhibits a dual behavior displaying a power-law growth for the fixation rate and speed of adaptation with the beneficial mutation rate, as observed in other spatially structured population models, while simultaneously showing a nonsaturating behavior for the speed of adaptation with the population size N, as in homogeneous populations.
Zeeshan Ahmad; Meng Jun
2015-01-01
DEA is a nonparametric method used in operation researches and economics fields for the evaluation of the production frontier. It has distinct intrinsic which is worth coping with assessment problems with multiple inputs in particular with multiple outputs. This paper usedDεC2R model of DEA to assess the comparative efficiency of the multiple schemes of agricultural industrial structure, at the end we chose the most favorable also known as "OPTIMAL" scheme. In addition to this, using some functional insights from DEA model non optimal schemes or less optimal schemes had also been improved to some extent. Assessment and selection of optimal schemes of agricultural industrial structure using DEA model gave a greater and better insight of agricultural industrial structure and was the first of such researches in Pakistan.
A Markov Chain Model for the Analysis of Round-Robin Scheduling Scheme
Shukla, D; Singhai, Rahul; Agarwal, R K
2010-01-01
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
Adaptive stabilization of continuous-time systems through a controllable modified estimation model
M. de la Sen
2004-01-01
Full Text Available This paper presents an indirect adaptive control scheme of continuous-time systems. The estimated plant model is controllable and then the adaptive scheme is free from singularities. Such singularities are avoided through a modification of the estimated plant parameter vector so that its associated Sylvester matrix is guaranteed to be nonsingular. That property is achieved by ensuring that the absolute value of its determinant does not lie below a positive threshold. An alternative modification scheme based on the achievement of a modifieddiagonally dominant Sylvester matrix of the parameter estimates is also proposed. This diagonal dominance is achieved through estimates modification as a way to guarantee the controllability of the modified estimated model when a controllability measure of the estimation model without modification fails. In both schemes, the use of an explicit hysteresis switching function for the modification of the estimates is not required to ensure the controllability of the modified estimated model. Both schemes ensure that chattering due to switches associated with the modification is not present.
Adaptive load balancing scheme in ad hoc networks%Ad hoc网络中一种自适应的负载均衡机制
袁玉华; 陈惠民; 贾旻
2007-01-01
An adaptive load balancing scheme is proposed to balance the load in ad hoc networks.The new scheme can be applied in most on-demand routing protocols resulting in significant performance improvement.The proposed scheme is applied to the ad hoc on-demand distance vector(AODV)routing protocol.Simulation results show that the network load is balanced on the whole,and performance in packet loss rate,routing overhead and average end-to-end delay is also improved.
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 ...
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
Model-Free Adaptive Heating Process Control
Ivana LUKÁČOVÁ; Piteľ, Ján
2009-01-01
The aim of this paper is to analyze the dynamic behaviour of a Model-Free Adaptive (MFA) heating process control. The MFA controller is designed as three layer neural network with proportional element. The method of backward propagation of errors was used for neural network training. Visualization and training of the artificial neural network was executed by Netlab in Matlab environment. Simulation of the MFA heating process control with outdoor temperature compensation has proved better resu...
Fully Adaptive Radar Modeling and Simulation Development
2017-04-01
Organization (NATO) Sensors Electronics Technology (SET)-227 Panel on Cognitive Radar. The FAR M&S architecture developed in Phase I allows for...Air Force’s previously developed radar M&S tools. This report is organized as follows. In Chapter 3, we provide an overview of the FAR framework...AFRL-RY-WP-TR-2017-0074 FULLY ADAPTIVE RADAR MODELING AND SIMULATION DEVELOPMENT Kristine L. Bell and Anthony Kellems Metron, Inc
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.
Xiong, Linping; Zhang, Lulu; Tang, Weidong; Ma, Yuqin
2012-01-01
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.
Adaptive Control and Synchronization of the Shallow Water Model
P. Sangapate
2012-01-01
Full Text Available The shallow water model is one of the important models in dynamical systems. This paper investigates the adaptive chaos control and synchronization of the shallow water model. First, adaptive control laws are designed to stabilize the shallow water model. Then adaptive control laws are derived to chaos synchronization of the shallow water model. The sufficient conditions for the adaptive control and synchronization have been analyzed theoretically, and the results are proved using a Barbalat's Lemma.
A Model for Climate Change Adaptation
Pasqualini, D.; Keating, G. N.
2009-12-01
Climate models predict serious impacts on the western U.S. in the next few decades, including increased temperatures and reduced precipitation. In combination, these changes are linked to profound impacts on fundamental systems, such as water and energy supplies, agriculture, population stability, and the economy. Global and national imperatives for climate change mitigation and adaptation are made actionable at the state level, for instance through greenhouse gas (GHG) emission regulations and incentives for renewable energy sources. However, adaptation occurs at the local level, where energy and water usage can be understood relative to local patterns of agriculture, industry, and culture. In response to the greenhouse gas emission reductions required by California’s Assembly Bill 32 (2006), Sonoma County has committed to sharp emissions reductions across several sectors, including water, energy, and transportation. To assist Sonoma County develop a renewable energy (RE) portfolio to achieve this goal we have developed an integrated assessment model, CLEAR (CLimate-Energy Assessment for Resiliency) model. Building on Sonoma County’s existing baseline studies of energy use, carbon emissions and potential RE sources, the CLEAR model simulates the complex interactions among technology deployment, economics and social behavior. This model enables assessment of these and other components with specific analysis of their coupling and feedbacks because, due to the complex nature of the problem, the interrelated sectors cannot be studied independently. The goal is an approach to climate change mitigation and adaptation that is replicable for use by other interested communities. The model user interfaces helps stakeholders and policymakers understand options for technology implementation.
An Efficient Code-Based Threshold Ring Signature Scheme with a Leader-Participant Model
Guomin Zhou
2017-01-01
Full Text Available Digital signature schemes with additional properties have broad applications, such as in protecting the identity of signers allowing a signer to anonymously sign a message in a group of signers (also known as a ring. While these number-theoretic problems are still secure at the time of this research, the situation could change with advances in quantum computing. There is a pressing need to design PKC schemes that are secure against quantum attacks. In this paper, we propose a novel code-based threshold ring signature scheme with a leader-participant model. A leader is appointed, who chooses some shared parameters for other signers to participate in the signing process. This leader-participant model enhances the performance because every participant including the leader could execute the decoding algorithm (as a part of signing process upon receiving the shared parameters from the leader. The time complexity of our scheme is close to Courtois et al.’s (2001 scheme. The latter is often used as a basis to construct other types of code-based signature schemes. Moreover, as a threshold ring signature scheme, our scheme is as efficient as the normal code-based ring signature.
Efficient hierarchical identity based encryption scheme in the standard model over lattices
Feng-he WANG; Chun-xiao WANG; Zhen-hua LIU
2016-01-01
Using lattice basis delegation in a fi xed dimension, we propose an efficient lattice-based hierarchical identity based encryption (HIBE) scheme in the standard model whose public key size is only (dm2+mn) log q bits and whose message-ciphertext expansion factor is only log q, where d is the maximum hierarchical depth and (n,m,q) are public parameters. In our construction, a novel public key assignment rule is used to averagely assign one random and public matrix to two identity bits, which implies that d random public matrices are enough to build the proposed HIBE scheme in the standard model, compared with the case in which 2d such public matrices are needed in the scheme proposed at Crypto 2010 whose public key size is (2dm2+mn+m) log q. To reduce the message-ciphertext expansion factor of the proposed scheme to log q, the encryption algorithm of this scheme is built based on Gentry’s encryption scheme, by which m2 bits of plaintext are encrypted into m2 log q bits of ciphertext by a one time encryption operation. Hence, the presented scheme has some advantages with respect to not only the public key size but also the message-ciphertext expansion factor. Based on the hardness of the learning with errors problem, we demonstrate that the scheme is secure under selective identity and chosen plaintext attacks.
Income distribution: An adaptive heterogeneous model
da Silva, L. C.; de Figueirêdo, P. H.
2014-02-01
In this communication an adaptive process is introduced into a many-agent model for closed economic system in order to establish general features of income distribution. In this new version agents are able to modify their exchange parameter ωi of resources through an adaptive process. The conclusions indicate that assuming an instantaneous learning behavior of all agents a Γ-distribution for income is reproduced while a frozen behavior establishes a Pareto’s distribution for income with an exponent ν=0.94±0.02. A third case occurs when a heterogeneous “inertia” behavior is introduced leading us to a Γ-distribution at the low income regime and a power-law decay for the large income values with an exponent ν=2.05±0.05. This method enables investigation of the resources flux in the economic environment and produces also bounding values for the Gini index comparable with data evidences.
A benchmark study of numerical schemes for one-dimensional arterial blood flow modelling.
Boileau, Etienne; Nithiarasu, Perumal; Blanco, Pablo J; Müller, Lucas O; Fossan, Fredrik Eikeland; Hellevik, Leif Rune; Donders, Wouter P; Huberts, Wouter; Willemet, Marie; Alastruey, Jordi
2015-10-01
Haemodynamical simulations using one-dimensional (1D) computational models exhibit many of the features of the systemic circulation under normal and diseased conditions. Recent interest in verifying 1D numerical schemes has led to the development of alternative experimental setups and the use of three-dimensional numerical models to acquire data not easily measured in vivo. In most studies to date, only one particular 1D scheme is tested. In this paper, we present a systematic comparison of six commonly used numerical schemes for 1D blood flow modelling: discontinuous Galerkin, locally conservative Galerkin, Galerkin least-squares finite element method, finite volume method, finite difference MacCormack method and a simplified trapezium rule method. Comparisons are made in a series of six benchmark test cases with an increasing degree of complexity. The accuracy of the numerical schemes is assessed by comparison with theoretical results, three-dimensional numerical data in compatible domains with distensible walls or experimental data in a network of silicone tubes. Results show a good agreement among all numerical schemes and their ability to capture the main features of pressure, flow and area waveforms in large arteries. All the information used in this study, including the input data for all benchmark cases, experimental data where available and numerical solutions for each scheme, is made publicly available online, providing a comprehensive reference data set to support the development of 1D models and numerical schemes.
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
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
On the Security of Provably Secure Multi-Receiver ID-Based Signcryption Scheme
Tan, Chik-How
Recently, Duan and Cao proposed an multi-receiver identity-based signcryption scheme. They showed that their scheme is secure against adaptive chosen ciphertext attacks in the random oracle model. In this paper, we show that their scheme is in fact not secure against adaptive chosen ciphertext attacks under their defined security model.
Prudhomme, Serge
2015-01-07
The need for surrogate models and adaptive methods can be best appreciated if one is interested in parameter estimation using a Bayesian calibration procedure for validation purposes. We extend here our latest work on error decomposition and adaptive refinement for response surfaces to the development of surrogate models that can be substituted for the full models to estimate the parameters of Reynolds-averaged Navier-Stokes models. The error estimates and adaptive schemes are driven here by a quantity of interest and are thus based on the approximation of an adjoint problem. We will focus in particular to the accurate estimation of evidences to facilitate model selection. The methodology will be illustrated on the Spalart-Allmaras RANS model for turbulence simulation.
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.
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)
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)
An optimal adaptive time-stepping scheme for solving reaction-diffusion-chemotaxis systems.
Chiu, Chichia; Yu, Jui-Ling
2007-04-01
Reaction-diffusion-chemotaxis systems have proven to be fairly accurate mathematical models for many pattern formation problems in chemistry and biology. These systems are important for computer simulations of patterns, parameter estimations as well as analysis of the biological systems. To solve reaction-diffusion-chemotaxis systems, efficient and reliable numerical algorithms are essential for pattern generations. In this paper, a general reaction-diffusion-chemotaxis system is considered for specific numerical issues of pattern simulations. We propose a fully explicit discretization combined with a variable optimal time step strategy for solving the reaction-diffusion-chemotaxis system. Theorems about stability and convergence of the algorithm are given to show that the algorithm is highly stable and efficient. Numerical experiment results on a model problem are given for comparison with other numerical methods. Simulations on two real biological experiments will also be shown.
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.
Analyses of models for promotion schemes and ownership arrangements
Hansen, Lise-Lotte Pade; Schröder, Sascha Thorsten; Münster, Marie
2011-01-01
Micro-Combined Heat and Power systems may contribute to changing the energy system at the residential level. Being a part of a distributed generation system, the stationary fuel cells constitute a promising element in a potentially sustainable and environmentally friendly energy system. Fuel cell...... 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...... to the political stage, where the necessary support schemes have to be in place in combination with guarantees that the political objectives for the future energy system does not change dramatically. One of the main challenges of the fuel cell technology is the efficiency while others are the cost as well...
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.
Adaptive Lattice Boltzmann Model for Compressible Flows
无
2000-01-01
A new lattice Boltzmann model for compressible flows is presented. The main difference from the standard lattice Boltzmann model is that the particle velocities are no longer constant, but vary with the mean velocity and internal energy. The adaptive nature of the particle velocities permits the mean flow to have a high Mach number. The introduction of a particle potential energy makes the model suitable for a perfect gas with arbitrary specific heat ratio. The Navier-Stokes (N-S) equations are derived by the Chapman-Enskog method from the BGK Boltzmann equation. Two kinds of simulations have been carried out on the hexagonal lattice to test the proposed model. One is the Sod shock-tube simulation. The other is a strong shock of Mach number 5.09 diffracting around a corner.
On adaptive refinements in discrete probabilistic fracture models
J. Eliáš
2017-01-01
Full Text Available The possibility to adaptively change discretization density is a well acknowledged and used feature of many continuum models. It is employed to save computational time and increase solution accuracy. Recently, adaptivity has been introduced also for discrete particle models. This contribution applies adaptive technique in probabilistic discrete modelling where material properties are varying in space according to a random field. The random field discretization is adaptively refined hand in hand with the model geometry.
Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain.
Banks, R F; Baldasano, J M
2016-12-01
Here we analyze the impact of four planetary boundary-layer (PBL) parametrization schemes from the Weather Research and Forecasting (WRF) numerical weather prediction model on simulations of meteorological variables and predicted pollutant concentrations from an air quality forecast system (AQFS). The current setup of the Spanish operational AQFS, CALIOPE, is composed of the WRF-ARW V3.5.1 meteorological model tied to the Yonsei University (YSU) PBL scheme, HERMES v2 emissions model, CMAQ V5.0.2 chemical transport model, and dust outputs from BSC-DREAM8bv2. We test the performance of the YSU scheme against the Assymetric Convective Model Version 2 (ACM2), Mellor-Yamada-Janjic (MYJ), and Bougeault-Lacarrère (BouLac) schemes. The one-day diagnostic case study is selected to represent the most frequent synoptic condition in the northeast Iberian Peninsula during spring 2015; regional recirculations. It is shown that the ACM2 PBL scheme performs well with daytime PBL height, as validated against estimates retrieved using a micro-pulse lidar system (mean bias=-0.11km). In turn, the BouLac scheme showed WRF-simulated air and dew point temperature closer to METAR surface meteorological observations. Results are more ambiguous when simulated pollutant concentrations from CMAQ are validated against network urban, suburban, and rural background stations. The ACM2 scheme showed the lowest mean bias (-0.96μgm(-3)) with respect to surface ozone at urban stations, while the YSU scheme performed best with simulated nitrogen dioxide (-6.48μgm(-3)). The poorest results were with simulated particulate matter, with similar results found with all schemes tested. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Synaptic dynamics: linear model and adaptation algorithm.
Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W
2014-08-01
In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and
Model Driven Mutation Applied to Adaptative Systems Testing
Bartel, Alexandre; Munoz, Freddy; Klein, Jacques; Mouelhi, Tejeddine; Traon, Yves Le
2012-01-01
Dynamically Adaptive Systems modify their behav- ior and structure in response to changes in their surrounding environment and according to an adaptation logic. Critical sys- tems increasingly incorporate dynamic adaptation capabilities; examples include disaster relief and space exploration systems. In this paper, we focus on mutation testing of the adaptation logic. We propose a fault model for adaptation logics that classifies faults into environmental completeness and adaptation correct- ness. Since there are several adaptation logic languages relying on the same underlying concepts, the fault model is expressed independently from specific adaptation languages. Taking benefit from model-driven engineering technology, we express these common concepts in a metamodel and define the operational semantics of mutation operators at this level. Mutation is applied on model elements and model transformations are used to propagate these changes to a given adaptation policy in the chosen formalism. Preliminary resul...
Verification and comparison of four numerical schemes for a 1D viscoelastic blood flow model
Wang, Xiaofei; Lagrée, Pierre-Yves
2013-01-01
In this paper, we present four numerical schemes for a 1D viscoelastic blood flow model. In the case with a small nonlinearity (small amplitude of wave), asymptotic analysis predicts several behaviours of the wave: propagation in a uniform tube, attenuation of the amplitude due to the skin friction, diffusion due to the viscosity of the wall, and reflection and transmission at a branching point. These predictions are compared very favorably with all of the numerical solutions. The schemes are also tested in case with a larger nonlinearity. Finally, we apply all of the schemes on a relatively realistic arterial system with 55 arteries. The schemes are compared in four aspects: the spatial and temporal convergence speed, the ability to capture shock phenomena, the computation speed and the complexity of the implementation. The suitable conditions for the application of the various schemes are discussed.
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.
A Backward Unlinkable Secret Handshake Scheme with Revocation Support in the Standard Model
Yamin Wen
2015-10-01
Full Text Available Secret handshake schemes have been proposed to achieve private mutual authentications, which allow the members of a certain organization to anonymously authenticate each other without exposing their affiliations. In this paper, a backward unlinkable secret handshake scheme with revocation support (BU-RSH is constructed. For a full-fledged secret handshake scheme, it is indispensable to furnish it with practical functionality, such as unlinkability, revocation and traceability. The revocation is achieved in the BU-RSH scheme, as well as the unlinkability and the traceability. Moreover, the anonymity of revoked members is improved, so that the past transcripts of revoked members remain private, i.e., backward unlinkability. In particular, the BU-RSH scheme is provably secure in the standard model by assuming the intractability of the `-hidden strong Diffie-Hellman problem and the subgroup decision problem.
A theoretical extraction scheme of transport information based on exclusion models
Chen Hua; Du Lei; Qu Cheng-Li; Li Wei-Hua; He Liang; Chen Wen-Hao; Sun Peng
2010-01-01
In order to explore how to extract more transport information from current fluctuation, a theoretical extraction scheme is presented in a single barrier structure based on exclusion models, which include counter-flows model and tunnel model. The first four cumulants of these two exclusion models are computed in a single barrier structure, and their characteristics are obtained. A scheme with the help of the first three cumulants is devised to check a transport process to follow the counter-flows model, the tunnel model or neither of them. Time series generated by Monte Carlo techniques is adopted to validate the abstraction procedure, and the result is reasonable.
Application of model reference adaptive control to a flexible remote manipulator arm
Meldrum, D. R.; Balas, M. J.
1986-01-01
An exact modal state-space representation is derived in detail for a single-link, flexible remote manipulator with a noncollocated sensor and actuator. A direct model following adaptive controller is designed to control the torque at the pinned end of the arm so as to command the free end to track a prescribed sinusoidal motion. Conditions that must be satisfied in order for the controller to work are stated. Simulation results to date are discussed along with the potential of the model following adaptive control scheme in robotics and space environments.
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.
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.
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.
Burgalat, J.; Rannou, P.; Cours, T.; Rivière, E. D.
2014-03-01
Microphysical models describe the way aerosols and clouds behave in the atmosphere. Two approaches are generally used to model these processes. While the first approach discretizes processes and aerosols size distributions on a radius grid (bin scheme), the second uses bulk parameters of the size distribution law (its mathematical moments) to represent the evolution of the particle population (moment scheme). However, with the latter approach, one needs to have an a priori knowledge of the size distributions. Moments scheme for Cloud microphysics modeling have been used and enhanced since decades for climate studies of the Earth. Most of the tools are based on Log-Normal law which are suitable for Earth, Mars or Venus. On Titan, due to the fractal structure of the aerosols, the size distributions do not follow a log-normal law. Then using a moment scheme in that case implies to define the description of the size distribution and to review the equations that are widely published in the literature. Our objective is to enable the use of a fully described microphysical model using a moment scheme within a Titan's Global Climate Model. As a first step in this direction, we present here a moment scheme dedicated to clouds microphysics adapted for Titan's atmosphere conditions. We perform comparisons between the two kinds of schemes (bin and moments) using an annual and a diurnal cycle, to check the validity of our moment description. The various forcing produce a time-variable cloud layer in relation with the temperature cycle. We compare the column opacities and the temperature for the two schemes, for each cycles. We also compare more detailed quantities as the opacity distribution of the cloud events at different periods of these cycles. Results show that differences between the two approaches have a small impact on the temperature (less than 1 K) and range between 1% and 10% for haze and clouds opacities. Both models behave in similar way when forced by an annual and
LI Yu-hong; ZHOU Zheng
2005-01-01
A rate adaptive multi-band ultra-wideband (UWB) system based on the quadrature fractal modulation (QFM)scheme was proposed. Exploring the use of homogeneous signals as modulating waveforms in UWB system, the signal within each 528MHz sub-band was divided into 8 different frequency bandwidths using wavelets transform and these data sequences to be transmitted were embedded into homogeneous waveforms. It is found that the use of homogeneous signals in such UWB system is quite feasible, leadings to a novel multi-rate diversity strategy. Within each 528MHz sub-band, the UWB-QFM system can provide much higher data rates than that of the UWB orthogonal frequency division multiplexing (OFDM) system. Simulation results also show that the bit error rate (BER) performance of the UWB-QFM system achieves a greatly improvement over existing UWB-OFDM system. Due to the fractal properties of the homogeneous signals, these data sequences to be transmitted can be recovered using arbitrarily short receiver signal.
Transfer Scheme Evaluation Model for a Transportation Hub based on Vectorial Angle Cosine
Li-Ya Yao
2014-07-01
Full Text Available As the most important node in public transport network, efficiency of a transport hub determines the entire efficiency of the whole transport network. In order to put forward effective transfer schemes, a comprehensive evaluation index system of urban transport hubs’ transfer efficiency was built, evaluation indexes were quantified, and an evaluation model of a multi-objective decision hub transfer scheme was established based on vectorial angle cosine. Qualitative and quantitative analysis on factors affecting transfer efficiency is conducted, which discusses the passenger satisfaction, transfer coordination, transfer efficiency, smoothness, economy, etc. Thus, a new solution to transfer scheme utilization was proposed.
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.
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.
Adaptation dynamics of the quasispecies model
Jain, Kavita
2009-02-01
We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.
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.
Biohybrid Control of General Linear Systems Using the Adaptive Filter Model of Cerebellum.
Wilson, Emma D; Assaf, Tareq; Pearson, Martin J; Rossiter, Jonathan M; Dean, Paul; Anderson, Sean R; Porrill, John
2015-01-01
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 cancelation of reafferent noise. It has also been successfully applied to problems in robotics, such as adaptive camera stabilization and sensor noise cancelation. 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 stabilizes 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.
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.
European upper mantle tomography: adaptively parameterized models
Schäfer, J.; Boschi, L.
2009-04-01
We have devised a new algorithm for upper-mantle surface-wave tomography based on adaptive parameterization: i.e. the size of each parameterization pixel depends on the local density of seismic data coverage. The advantage in using this kind of parameterization is that a high resolution can be achieved in regions with dense data coverage while a lower (and cheaper) resolution is kept in regions with low coverage. This way, parameterization is everywhere optimal, both in terms of its computational cost, and of model resolution. This is especially important for data sets with inhomogenous data coverage, as it is usually the case for global seismic databases. The data set we use has an especially good coverage around Switzerland and over central Europe. We focus on periods from 35s to 150s. The final goal of the project is to determine a new model of seismic velocities for the upper mantle underlying Europe and the Mediterranean Basin, of resolution higher than what is currently found in the literature. Our inversions involve regularization via norm and roughness minimization, and this in turn requires that discrete norm and roughness operators associated with our adaptive grid be precisely defined. The discretization of the roughness damping operator in the case of adaptive parameterizations is not as trivial as it is for the uniform ones; important complications arise from the significant lateral variations in the size of pixels. We chose to first define the roughness operator in a spherical harmonic framework, and subsequently translate it to discrete pixels via a linear transformation. Since the smallest pixels we allow in our parameterization have a size of 0.625 °, the spherical-harmonic roughness operator has to be defined up to harmonic degree 899, corresponding to 810.000 harmonic coefficients. This results in considerable computational costs: we conduct the harmonic-pixel transformations on a small Beowulf cluster. We validate our implementation of adaptive
Convergence of discrete duality finite volume schemes for the cardiac bidomain model
Andreianov, Boris; Karlsen, Kenneth H; Pierre, Charles
2010-01-01
We prove convergence of discrete duality finite volume (DDFV) schemes on distorted meshes for a class of simplified macroscopic bidomain models of the electrical activity in the heart. Both time-implicit and linearised time-implicit schemes are treated. A short description is given of the 3D DDFV meshes and of some of the associated discrete calculus tools. Several numerical tests are presented.
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.
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.
Ping Wang; Chaohe Yang; Xuemin Tian; Dexian Huang
2014-01-01
The performance of data-driven models relies heavily on the amount and quality of training samples, so it might deteriorate significantly in the regions where samples are scarce. The objective of this paper is to develop an on-line SVR model updating strategy to track the change in the process characteristics efficiently with affordable computational burden. This is achieved by adding a new sample that violates the Karush-Kuhn-Tucker condi-tions of the existing SVR model and by deleting the old sample that has the maximum distance with respect to the newly added sample in feature space. The benefits offered by such an updating strategy are exploited to develop an adaptive model-based control scheme, where model updating and control task perform alternately. The effectiveness of the adaptive controller is demonstrated by simulation study on a continuous stirred tank reactor. The results reveal that the adaptive MPC scheme outperforms its non-adaptive counterpart for large-magnitude set point changes and variations in process parameters.
Comparison of tropospheric gas-phase chemistry schemes for use within global models
K. M. Emmerson
2009-03-01
Full Text Available Methane and ozone are two important climate gases with significant tropospheric chemistry. Within chemistry-climate and transport models this chemistry is simplified for computational expediency. We compare the state of the art Master Chemical Mechanism (MCM with six tropospheric chemistry schemes (CRI-reduced, GEOS-CHEM and a GEOS-CHEM adduct, MOZART-2, TOMCAT and CBM-IV that could be used within composition transport models. We test the schemes within a box model framework under conditions derived from a composition transport model and from field observations from a regional scale pollution event. We find that CRI-reduced provides much skill in simulating the full chemistry, yet with greatly reduced complexity. We find significant variations between the other chemical schemes, and reach the following conclusions. 1 The inclusion of a gas phase N_{2}O_{5}+H_{2}O reaction in one scheme and not others is a large source of uncertainty in the inorganic chemistry. 2 There are significant variations in the calculated concentration of PAN between the schemes, which will affect the long range transport of reactive nitrogen in global models. 3 The representation of isoprene chemistry differs hugely between the schemes, leading to significant uncertainties on the impact of isoprene on composition. 4 Differences are found in NO_{3} concentrations in the nighttime chemistry. Resolving these four issues through further investigative laboratory studies will reduce the uncertainties within the chemical schemes of global tropospheric models.
A model and regularization scheme for ultrasonic beamforming clutter reduction.
Byram, Brett; Dei, Kazuyuki; Tierney, Jaime; Dumont, Douglas
2015-11-01
Acoustic clutter produced by off-axis and multipath scattering is known to cause image degradation, and in some cases these sources may be the prime determinants of in vivo image quality. We have previously shown some success addressing these sources of image degradation by modeling the aperture domain signal from different sources of clutter, and then decomposing aperture domain data using the modeled sources. Our previous model had some shortcomings including model mismatch and failure to recover B-Mode speckle statistics. These shortcomings are addressed here by developing a better model and by using a general regularization approach appropriate for the model and data. We present results with L1 (lasso), L2 (ridge), and L1/L2 combined (elastic-net) regularization methods. We call our new method aperture domain model image reconstruction (ADMIRE). Our results demonstrate that ADMIRE with L1 regularization, or weighted toward L1 in the case of elastic-net regularization, have improved image quality. L1 by itself works well, but additional improvements are seen with elastic-net regularization over the pure L1 constraint. On in vivo example cases, L1 regularization showed mean contrast improvements of 4.6 and 6.8 dB on fundamental and harmonic images, respectively. Elastic net regularization (α = 0.9) showed mean contrast improvements of 17.8 dB on fundamental images and 11.8 dB on harmonic images. We also demonstrate that in uncluttered Field II simulations the decluttering algorithm produces the same contrast, contrast-tonoise ratio, and speckle SNR as normal B-mode imaging, demonstrating that ADMIRE preserves typical image features.
Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks
Hagen, Espen; Dahmen, David; Stavrinou, Maria L
2016-01-01
and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...... on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network...... model for a ∼1 mm(2) patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its...
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.
Development of Non-staggered, semi-implicit ICE numerical scheme for a two-fluid, three-field model
Jeong, Jae Jun; Yoon, H. Y.; Bae, S. W
2007-11-15
A pilot code for one-dimensional, transient, two-fluid, three-field model has been developed. In this code, the semi-implicit ICE numerical scheme has been adapted to a 'non-staggered' grid. Using several conceptual problems, the numerical scheme has been verified. The results of the verifications are summarized below: - It was confirmed that the basic pilot code can simulate various flow conditions (such as single-phase liquid flow, two-phase mixture flow, and single-phase vapor flow) and transitions of the flow conditions. A mist flow was not simulated, but it seems that the basic pilot code can simulate mist flow conditions. - The mass and energy conservation was confirmed for single-phase liquid and single-phase vapor flows. - It was confirmed that the inlet pressure and velocity boundary conditions work properly. - It was confirmed that, for single- and two-phase flows, the velocity and temperature of non-existing phase are calculated as intended. The non-staggered, semi-implicit ICE numerical scheme, which has been developed in this study, will be a starting point of a new code development that adopts an unstructured finite volume method.
A seawater desalination scheme for global hydrological models
Hanasaki, Naota; Yoshikawa, Sayaka; Kakinuma, Kaoru; Kanae, Shinjiro
2016-10-01
Seawater desalination is a practical technology for providing fresh water to coastal arid regions. Indeed, the use of desalination is rapidly increasing due to growing water demand in these areas and decreases in production costs due to technological advances. In this study, we developed a model to estimate the areas where seawater desalination is likely to be used as a major water source and the likely volume of production. The model was designed to be incorporated into global hydrological models (GHMs) that explicitly include human water usage. The model requires spatially detailed information on climate, income levels, and industrial and municipal water use, which represent standard input/output data in GHMs. The model was applied to a specific historical year (2005) and showed fairly good reproduction of the present geographical distribution and national production of desalinated water in the world. The model was applied globally to two periods in the future (2011-2040 and 2041-2070) under three distinct socioeconomic conditions, i.e., SSP (shared socioeconomic pathway) 1, SSP2, and SSP3. The results indicate that the usage of seawater desalination will have expanded considerably in geographical extent, and that production will have increased by 1.4-2.1-fold in 2011-2040 compared to the present (from 2.8 × 109 m3 yr-1 in 2005 to 4.0-6.0 × 109 m3 yr-1), and 6.7-17.3-fold in 2041-2070 (from 18.7 to 48.6 × 109 m3 yr-1). The estimated global costs for production for each period are USD 1.1-10.6 × 109 (0.002-0.019 % of the total global GDP), USD 1.6-22.8 × 109 (0.001-0.020 %), and USD 7.5-183.9 × 109 (0.002-0.100 %), respectively. The large spreads in these projections are primarily attributable to variations within the socioeconomic scenarios.
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.
Feedback control scheme of traffic jams based on the coupled map car-following model
Zhou, Tong; Sun, Di-Hua; Zhao, Min; Li, Hua-Min
2013-09-01
Based on the pioneering work of Konishi et al. [Phys. Rev. E (1999) 60 4000], a new feedback control scheme is presented to suppress traffic jams based on the coupled map car-following model under the open boundary condition. The effect of the safe headway on the traffic system is considered. According to the control theory, the condition under which traffic jams can be suppressed is analyzed. The results are compared with the previous results concerning congestion control. The simulations show that the suppression performance of our scheme on traffic jams is better than those of the previous schemes, although all the schemes can suppress traffic jams. The simulation results are consistent with theoretical analyses.
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.
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.
Dislocation climb models from atomistic scheme to dislocation dynamics
Niu, Xiaohua; Luo, Tao; Lu, Jianfeng; Xiang, Yang
2017-02-01
We develop a mesoscopic dislocation dynamics model for vacancy-assisted dislocation climb by upscalings from a stochastic model on the atomistic scale. Our models incorporate microscopic mechanisms of (i) bulk diffusion of vacancies, (ii) vacancy exchange dynamics between bulk and dislocation core, (iii) vacancy pipe diffusion along the dislocation core, and (iv) vacancy attachment-detachment kinetics at jogs leading to the motion of jogs. Our mesoscopic model consists of the vacancy bulk diffusion equation and a dislocation climb velocity formula. The effects of these microscopic mechanisms are incorporated by a Robin boundary condition near the dislocations for the bulk diffusion equation and a new contribution in the dislocation climb velocity due to vacancy pipe diffusion driven by the stress variation along the dislocation. Our climb formulation is able to quantitatively describe the translation of prismatic loops at low temperatures when the bulk diffusion is negligible. Using this new formulation, we derive analytical formulas for the climb velocity of a straight edge dislocation and a prismatic circular loop. Our dislocation climb formulation can be implemented in dislocation dynamics simulations to incorporate all the above four microscopic mechanisms of dislocation climb.
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.
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.
Milan, M.; Schüttemeyer, D.; Venema, V.; Simmer, C.
2009-04-01
We implemented a PI (Physical Initialization) method in the non hydrostatic limited-area model COSMO (version 4.2) of the DWD (German Meteorological Service). The goal is the improvement of quantitative rain nowcasting with a high resolution NWP model. Input radar data is a DWD product: the national radar composite for 16 radars with a spatial resolution of one kilometer and a time resolution of 5 minutes. The conversion from reflectivity to rain rate is already made by DWD. This data is interpolated on the LM grid ( 2.8 × 2.8 km resolution) in order to calculate the analysed precipitation rate which depends on the observed precipitation and the model precipitation. The PIB (Physical Initialization Bonn) takes as input the radar based precipitation product and a cloud top height field retrieved from satellite observations, in our case we are using the SAFNWC products generated from Meteosat Second Generation data by DWD. During the assimilation window PIB adjusts the vertical wind, humidity, cloud water and cloud ice in order to force the model state towards the measurements. The most distinctive feature of the algorithm is the adjustment of the vertical wind profile in the framework of a simple precipitation scheme. The PIB assumes that the rain rate is proportional to the vertical humidity flux at cloud base and the vertical wind is adapted according to the conversion efficiency of saturated water vapor into rain water at the cloud base. This parameter is dynamically adjusted by the comparison between the model precipitation and the radar precipitation. The model is tested in convective cases over Germany, an identical twin experiment is used in order to demonstrate the consistency of PIB with the physics of the NWP model. In the tests which we have already performed this method has improved the forecast of the precipitation patterns, as well as the dynamics of the events. These improvements are found both during the assimilation window and for the first hours
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 flo
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.
Ranganathan, Panneerselvam; Gu, Sai
2016-08-01
The present work concerns with CFD modelling of biomass fast pyrolysis in a fluidised bed reactor. Initially, a study was conducted to understand the hydrodynamics of the fluidised bed reactor by investigating the particle density and size, and gas velocity effect. With the basic understanding of hydrodynamics, the study was further extended to investigate the different kinetic schemes for biomass fast pyrolysis process. The Eulerian-Eulerian approach was used to model the complex multiphase flows in the reactor. The yield of the products from the simulation was compared with the experimental data. A good comparison was obtained between the literature results and CFD simulation. It is also found that CFD prediction with the advanced kinetic scheme is better when compared to other schemes. With the confidence obtained from the CFD models, a parametric study was carried out to study the effect of biomass particle type and size and temperature on the yield of the products.
Resident space object tracking using an interacting multiple model mixing scheme
Lam, Quang M.
2014-06-01
A multiple model estimation scheme is proposed to enhance the robustness of a resident space object (RSO) tracker subject to its maneuverability uncertainties (unplanned or unknown jet firing activities) and other system variations. The concept is based on the Interacting Multiple Model (IMM) estimation scheme. Within the IMM framework, two Extended Kalman Filter (EKF) models: (i) a 6 State (Position and Velocity of a constant orbiting RSO) EKF and (ii) a 9 state (Position, Velocity, and Acceleration of a maneuvering RSO) EKF are designed and implemented to achieve RSO maneuvering detection and enhanced tracking accuracy. The IMM estimation scheme is capable of providing enhanced state vector estimation accuracy and consistent prediction of the RSO maneuvering status, thus offering an attractive design feature for future Space Situational Awareness (SSA) missions. The design concept is illustrated using the Matlab/Based Simulation testing environment.
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
A dynamic neutral fluid model for the PIC scheme
Wu, Alan; Lieberman, Michael; Verboncoeur, John
2010-11-01
Fluid diffusion is an important aspect of plasma simulation. A new dynamic model is implemented using the continuity and boundary equations in OOPD1, an object oriented one-dimensional particle-in-cell code developed at UC Berkeley. The model is described and compared with analytical methods given in [1]. A boundary absorption parameter can be adjusted from ideal absorption to ideal reflection. Simulations exhibit good agreement with analytic time dependent solutions for the two ideal cases, as well as steady state solutions for mixed cases. For the next step, fluid sources and sinks due to particle-particle or particle-fluid collisions within the simulation volume and to surface reactions resulting in emission or absorption of fluid species will be implemented. The resulting dynamic interaction between particle and fluid species will be an improvement to the static fluid in the existing code. As the final step in the development, diffusion for multiple fluid species will be implemented. [4pt] [1] M.A. Lieberman and A.J. Lichtenberg, Principles of Plasma Discharges and Materials Processing, 2nd Ed, Wiley, 2005.
On the modelling of compressible inviscid flow problems using AUSM schemes
Hajžman M.
2007-11-01
Full Text Available During last decades, upwind schemes have become a popular method in the field of computational fluid dynamics. Although they are only first order accurate, AUSM (Advection Upstream Splitting Method schemes proved to be well suited for modelling of compressible flows due to their robustness and ability of capturing shock discontinuities. In this paper, we review the composition of the AUSM flux-vector splitting scheme and its improved version noted AUSM+, proposed by Liou, for the solution of the Euler equations. Mach number splitting functions operating with values from adjacent cells are used to determine numerical convective fluxes and pressure splitting is used for the evaluation of numerical pressure fluxes. Both versions of the AUSM scheme are applied for solving some test problems such as one-dimensional shock tube problem and three dimensional GAMM channel. Features of the schemes are discussed in comparison with some explicit central schemes of the first order accuracy (Lax-Friedrichs and of the second order accuracy (MacCormack.
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; Shian-Jiann LIN; 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.
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
Tan, Maxine; Aghaei, Faranak; Wang, Yunzhi; Zheng, Bin
2017-01-01
The purpose of this study is to evaluate a new method to improve performance of computer-aided detection (CAD) schemes of screening mammograms with two approaches. In the first approach, we developed a new case based CAD scheme using a set of optimally selected global mammographic density, texture, spiculation, and structural similarity features computed from all four full-field digital mammography images of the craniocaudal (CC) and mediolateral oblique (MLO) views by using a modified fast and accurate sequential floating forward selection feature selection algorithm. Selected features were then applied to a ‘scoring fusion’ artificial neural network classification scheme to produce a final case based risk score. In the second approach, we combined the case based risk score with the conventional lesion based scores of a conventional lesion based CAD scheme using a new adaptive cueing method that is integrated with the case based risk scores. We evaluated our methods using a ten-fold cross-validation scheme on 924 cases (476 cancer and 448 recalled or negative), whereby each case had all four images from the CC and MLO views. The area under the receiver operating characteristic curve was AUC = 0.793 ± 0.015 and the odds ratio monotonically increased from 1 to 37.21 as CAD-generated case based detection scores increased. Using the new adaptive cueing method, the region based and case based sensitivities of the conventional CAD scheme at a false positive rate of 0.71 per image increased by 2.4% and 0.8%, respectively. The study demonstrated that supplementary information can be derived by computing global mammographic density image features to improve CAD-cueing performance on the suspicious mammographic lesions.
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 simulatio...... site. This study strongly indicates that the hybrid model may be used as an engineering tool to predict shoreline response following the implementation of a nourishment project....
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.
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.
SOLVING FRACTIONAL-ORDER COMPETITIVE LOTKA-VOLTERRA MODEL BY NSFD SCHEMES
S.ZIBAEI
2016-12-01
Full Text Available In this paper, we introduce fractional-order into a model competitive Lotka- Volterra prey-predator system. We will discuss the stability analysis of this fractional system. The non-standard nite difference (NSFD scheme is implemented to study the dynamic behaviors in the fractional-order Lotka-Volterra system. Proposed non-standard numerical scheme is compared with the forward Euler and fourth order Runge-Kutta methods. Numerical results show that the NSFD approach is easy and accurate for implementing when applied to fractional-order Lotka-Volterra model.
S. Kim
2013-08-01
Full Text Available The IEEE 802.11e EDCA (Enhanced Distributed Channel Access is able to provide QoS (Quality of Service by adjusting the transmission opportunities (TXOPs, which control the period to access the medium. The EDCA has a fairness problem among competing stations, which support multimedia applications with different delay bounds. In this paper, we propose a simple and effective scheme for alleviating the fairness problem. The proposed scheme dynamically allocates the TXOP value based on the delay bounds of the data packets in a queue and the traffic load of network. Performance of the proposed scheme is investigated by simulation. Our results show that compared to conventional scheme, the proposed scheme significantly improves network performance, and achieves a high degree of fairness among stations with different multimedia applications.
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.
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 th
Image Denoising via Bandwise Adaptive Modeling and Regularization Exploiting Nonlocal Similarity.
Xiong, Ruiqin; Liu, Hangfan; Zhang, Xinfeng; Zhang, Jian; Ma, Siwei; Wu, Feng; Gao, Wen
2016-09-27
This paper proposes a new image denoising algorithm based on adaptive signal modeling and regularization. It improves the quality of images by regularizing each image patch using bandwise distribution modeling in transform domain. Instead of using a global model for all the patches in an image, it employs content-dependent adaptive models to address the non-stationarity of image signals and also the diversity among different transform bands. The distribution model is adaptively estimated for each patch individually. It varies from one patch location to another and also varies for different bands. In particular, we consider the estimated distribution to have non-zero expectation. To estimate the expectation and variance parameters for every band of a particular patch, we exploit the nonlocal correlation in image to collect a set of highly similar patches as the data samples to form the distribution. Irrelevant patches are excluded so that such adaptively-learned model is more accurate than a global one. The image is ultimately restored via bandwise adaptive soft-thresholding, based on a Laplacian approximation of the distribution of similar-patch group transform coefficients. Experimental results demonstrate that the proposed scheme outperforms several state-of-the-art denoising methods in both the objective and the perceptual qualities.
Huang, Bo; Chen, Dehui; Li, Xingliang; Li, Chao
2014-05-01
The Global/Regional Assimilation and PrEdiction System (GRAPES) is the new-generation numerical weather prediction (NWP) system developed by the China Meteorological Administration. It is a fully compressible non-hydrostatical global/regional unified model that uses a traditional semi-Lagrangian advection scheme with cubic Lagrangian interpolation (referred to as the SL_CL scheme). The SL_CL scheme has been used in many operational NWP models, but there are still some deficiencies, such as the damping effects due to the interpolation and the relatively low accuracy. Based on Reich's semi-Lagrangian advection scheme (referred to as the R2007 scheme), the Re_R2007 scheme that uses the low- and high-order B-spline function for interpolation at the departure point, is developed in this paper. One- and two-dimensional idealized tests in the rectangular coordinate system with uniform grid cells were conducted to compare the Re_R2007 scheme and the SL_CL scheme. The numerical results showed that: (1) the damping effects were remarkably reduced with the Re_R2007 scheme; and (2) the normalized errors of the Re_R2007 scheme were about 7.5 and 3 times smaller than those of the SL_CL scheme in one- and two-dimensional tests, respectively, indicating the higher accuracy of the Re_R2007 scheme. Furthermore, two solid-body rotation tests were conducted in the latitude-longitude spherical coordinate system with nonuniform grid cells, which also verified the Re_R2007 scheme's advantages. Finally, in comparison with other global advection schemes, the Re_R2007 scheme was competitive in terms of accuracy and flow independence. An encouraging possibility for the application of the Re_R2007 scheme to the GRAPES model is provided.
A theoretical adaptive model of thermal comfort - Adaptive Predicted Mean Vote (aPMV)
Yao, Runming [School of Construction Management and Engineering, The University of Reading (United Kingdom); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Li, Baizhan [Key Laboratory of the Three Gorges Reservoir Region' s Eco-Environment (Ministry of Education), Chongqing University (China); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Liu, Jing [School of Construction Management and Engineering, The University of Reading (United Kingdom)
2009-10-15
This paper presents in detail a theoretical adaptive model of thermal comfort based on the ''Black Box'' theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient ({lambda}) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results. (author)
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.
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.; Mohr, Karen I.; Skofronick-Jackson, Gail M.; Peters-Lidard, Christa D.
2016-01-01
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.
Change in Farm Production Structure Within Different CAP Schemes – an LP Modelling Approach
Jaka ŽGAJNAR
2008-01-01
Full Text Available After accession to European Union in 2004 direct payments became veryimportant income source also for farmers in Slovenia. But agricultural policy inplace at accession changed significantly in year 2007 as result of CAP reformimplementation. The objective of this study was to evaluate decision makingimpacts of direct payments scheme implemented with the reform: regional or morelikely hybrid scheme. The change in farm production structure was simulated withmodel, applying gross margin maximisation, based on static linear programmingapproach. The model has been developed in a spreadsheet framework in MS Excelplatform. A hypothetical farm has been chosen to analyse different scenarios andspecializations. Focus of the analysis was on cattle sector, since it is expected thatdecoupling is going to have significant influence on its optimal productionstructure. The reason is high level of direct payments that could in pre-reformscheme rise up to 70 % of total gross margin. Model results confirm that the reformshould have unfavourable impacts on cattle farms with intensive productionpractice. The results show that hybrid scheme has minor negative impacts in allcattle specializations, while regional scheme would be better option for sheepspecialized farm. Analysis has also shown growing importance of CAP pillar IIpayments, among them particularly agri-environmental measures. In all threeschemes budgetary payments enable farmers to improve financial results and inboth reform schemes they alleviate economic impacts of the CAP reform.
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.
Yan, Huiping; Qian, Yun; Lin, Guang; Leung, Lai-Yung R.; Yang, Ben; Fu, Q.
2014-03-25
Convective parameterizations used in weather and climate models all display sensitivity to model resolution and variable skill in different climatic regimes. Although parameters in convective schemes can be calibrated using observations to reduce model errors, it is not clear if the optimal parameters calibrated based on regional data can robustly improve model skill across different model resolutions and climatic regimes. In this study, this issue is investigated using a regional modeling framework based on the Weather Research and Forecasting (WRF) model. To quantify the response and sensitivity of model performance to model parameters, we identified five key input parameters and specified their ranges in the Kain-Fritsch (KF) convection scheme in WRF and calibrated them across different spatial resolutions, climatic regimes, and radiation schemes using observed precipitation data. Results show that the optimal values for the five input parameters in the KF scheme are close and model sensitivity and error exhibit similar dependence on the input parameters for all experiments conducted in this study despite differences in the precipitation climatology. We found that the model overall performances in simulating precipitation are more sensitive to the coefficients of downdraft (Pd) and entrainment (Pe) mass flux and starting height of downdraft (Ph). However, we found that rainfall biases, which are probably more related to structural errors, still exist over some regions in the simulation even with the optimal parameters, suggesting further studies are needed to identify the sources of uncertainties and reduce the model biases or structural errors associated with missed or misrepresented physical processes and/or potential problems with the modeling framework.
Model and algorithm of optimizing alternate traffic restriction scheme in urban traffic network
徐光明; 史峰; 刘冰; 黄合来
2014-01-01
An optimization model and its solution algorithm for alternate traffic restriction (ATR) schemes were introduced in terms of both the restriction districts and the proportion of restricted automobiles. A bi-level programming model was proposed to model the ATR scheme optimization problem by aiming at consumer surplus maximization and overload flow minimization at the upper-level model. At the lower-level model, elastic demand, mode choice and multi-class user equilibrium assignment were synthetically optimized. A genetic algorithm involving prolonging codes was constructed, demonstrating high computing efficiency in that it dynamically includes newly-appearing overload links in the codes so as to reduce the subsequent searching range. Moreover, practical processing approaches were suggested, which may improve the operability of the model-based solutions.
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.
Validation of a RANS transition model using a high-order weighted compact nonlinear scheme
Tu, GuoHua; Deng, XiaoGang; Mao, MeiLiang
2013-04-01
A modified transition model is given based on the shear stress transport (SST) turbulence model and an intermittency transport equation. The energy gradient term in the original model is replaced by flow strain rate to saving computational costs. The model employs local variables only, and then it can be conveniently implemented in modern computational fluid dynamics codes. The fifth-order weighted compact nonlinear scheme and the fourth-order staggered scheme are applied to discrete the governing equations for the purpose of minimizing discretization errors, so as to mitigate the confusion between numerical errors and transition model errors. The high-order package is compared with a second-order TVD method on simulating the transitional flow of a flat plate. Numerical results indicate that the high-order package give better grid convergence property than that of the second-order method. Validation of the transition model is performed for transitional flows ranging from low speed to hypersonic speed.
Identity-based Signcryption Scheme for Multiple PKG in Standard Model%标准模型中基于身份的多PKG签密方案
冀会芳; 韩文报; 刘连东
2011-01-01
在随机预言模型中,现有的基于身份签密的多私钥生成器(PKG)方案都是可证明安全的.基于此,提出在标准模型中基于身份的多PKG签密方案,并证明其安全性.在DBDH假设下,方案的机密性满足在适应性选择密文攻击时,密文不可区分.在CDH假设下,方案的不可伪造性满足在适应性选择消息攻击时,签名存在性不可伪造.和已有方案相比,该方案在签密阶段效率较高.%Several identity-based signcryption schemes for multiple Private Key Generator(PKG) are proved security in random oracle model, a new identity-based signcryption scheme for multiple PKG is proposed with security proof in standard model. The confidentiality against adaptive chosen ciphertext attack is obtained under DBDH assumption, and the unforgeability against adaptive chosen message attack is derived under the CDH assumption. Compared with the existing schemes, the new scheme's signcryption phase is more efficient.
抗污染攻击的自适应网络编码传输机制%Adaptive secure network coding scheme against pollution attacks
何明; 邓罡; 王宏; 龚正虎
2013-01-01
The problem of pullution attacks was focused on and ASNC (adaptive secure network coding) scheme was proposed, which is an adaptive security scheme against pollution attacks in network coding systems. The proposed scheme allows participating nodes to detect polluted packets based on time and space properties of network coding. It is an innovative security scheme which can dynamically adjust the authentication strategy of participating nodes according to the security situation. In addition, ASNC scheme provides an efficient packet authentication without requiring the ex-istence of any extra secure channels. Security analysis and simulation of the scheme were also presented and the results demonstrate the practicality and efficiency of the ASNC scheme.%研究了网络编码中的污染攻击问题，提出了一种抗污染攻击的自适应网络编码传输机制ASNC (adaptive secure network coding)。在编码数据分组的传输过程中，该机制利用网络编码的时间和空间特性有效控制污染数据分组的传播。同时，ASNC机制创新性地促使网络编码系统动态调整安全策略，自适应于当前网络安全态势。此外，为了达到更好的实用性，ASNC机制有效利用网络编码的编码空间特性，不需要额外的安全数据通道和数据分组加密操作。ASNC机制的安全分析和仿真结果表明，其能够有效抵抗污染攻击，与不具有自适应能力的机制相比具有更好的安全效率。
Chern, J.; Tao, W.; Lang, S. E.; Matsui, T.
2012-12-01
The accurate representation of clouds and cloud processes in atmospheric general circulation models (GCMs) with relatively coarse resolution (~100 km) has been a long-standing challenge. With the rapid advancement in computational technology, new breed of GCMs that are capable of explicitly resolving clouds have been developed. Though still computationally very expensive, global cloud-resolving models (GCRMs) with horizontal resolutions of 3.5 to 14 km are already being run in an exploratory manner. Another less computationally demanding approach is the multi-scale modeling framework (MMF) that replaces conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM. The Goddard MMF is based on the coupling of the Goddard Cumulus Ensemble (GCE), a CRM model, and the GEOS global model. In recent years a few new and improved microphysical schemes are developed and implemented to the GCE based on observations from field campaigns. It is important to evaluating these microphysical schemes for global applications such as the MMFs and GCRMs. Two-year (2007-2008) MMF sensitivity experiments have been carried out with different cloud microphysical schemes. The model simulated mean and variability of surface precipitation, cloud types, cloud properties such as cloud amount, hydrometeors vertical profiles, and cloud water contents, etc. in different geographic locations and climate regimes are evaluated against TRMM, CloudSat and CALIPSO satellite observations. The Goddard MMF has also been coupled with the Goddard Satellite Data Simulation Unit (G-SDSU), a system with multi-satellite, multi-sensor, and multi-spectrum satellite simulators. The statistics of MMF simulated radiances and backscattering can be directly compared with satellite observations to evaluate the performance of different cloud microphysical schemes. We will assess the strengths and/or deficiencies in of these microphysics schemes and provide guidance on how to improve
Adaptive update using visual models for lifting-based motion-compensated temporal filtering
Li, Song; Xiong, H. K.; Wu, Feng; Chen, Hong
2005-03-01
Motion compensated temporal filtering is a useful framework for fully scalable video compression schemes. However, when supposed motion models cannot represent a real motion perfectly, both the temporal high and the temporal low frequency sub-bands may contain artificial edges, which possibly lead to a decreased coding efficiency, and ghost artifacts appear in the reconstructed video sequence at lower bit rates or in case of temporal scaling. We propose a new technique that is based on utilizing visual models to mitigate ghosting artifacts in the temporal low frequency sub-bands. Specifically, we propose content adaptive update schemes where visual models are used to determine image dependent upper bounds on information to be updated. Experimental results show that the proposed algorithm can significantly improve subjective visual quality of the low-pass temporal frames and at the same time, coding performance can catch or exceed the classical update steps.
Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model
Markowitz, Jared; Krishnaswamy, Pavitra; Eilenberg, Michael F.; Endo, Ken; Barnhart, Chris; Herr, Hugh
2011-01-01
Control schemes for powered ankle–foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle–tendon model that produces estimates of the activation, force, length and velocity of the major muscles spanning the ankle to derive local feedback loops that may be critical in the control of those muscles during walking. This purely reflexive approach ignores sources of non-reflexive neural drive and does not necessarily reflect the biological control scheme, yet can still closely reproduce the muscle dynamics estimated from biological data. The resulting neuromuscular model was applied to control a powered ankle–foot prosthesis and tested by an amputee walking at three speeds. The controller produced speed-adaptive behaviour; net ankle work increased with walking speed, highlighting the benefits of applying neuromuscular principles in the control of adaptive prosthetic limbs. PMID:21502131
A Big Data Driven Adaptive Routing Service Customization Scheme%大数据驱动的自适应路由服务定制机制
卜超; 王兴伟; 李福亮; 黄敏
2016-01-01
随着多种多样新型网络应用的涌现，传统的路由配置模式越来越难以适应用户多样化的数据通信需求。因此，需要依据用户对不同类型应用差异化的通信需求，在数据分组的传输路径上配置合适的路由功能，自适应地合成满足分组传输特性的路由服务，改善用户体验。根据由大数据带来的数据间关联关系新范式，文中试图从大量的应用通信流状态数据中，分析和获取用户体验与路由服务各属性之间的依赖关系，促进高效地实现路由服务的定制化。鉴于此，文中提出了大数据驱动的自适应路由服务定制机制（Big data driven Adaptive Routing service Customization scheme，BARC），以网内大量流状态数据为驱动，建立了用户需求属性模型，挖掘用户体验对路由需求的依赖关系，获得候选路由功能集合；考虑商业化运营模式下用户和网络服务提供商之间的利益关系，提出了双方利益共赢的博弈策略，获得符合双方利益的最佳路由服务定制化方案。仿真实现和性能评价表明，文中提出的大数据驱动的自适应路由服务定制机制是可行和有效的。%With various kinds of new network applications emerged,it is more and more difficult to satisfy their diversified data communication requirements by using the traditional routing configuration model.It is necessary to provision appropriate routing functions on the communication paths based on the users’specific communication demands on different types of applications,and compose routing services adaptively to satisfy their packet transmission characteristics with user experience improved.Inspired by the new paradigm of data correlation brought by the big data, in this paper the dependencies between user experience and routing service properties are analyzed and exploited to help customize routing services efficiently,and a Big data driven Adaptive Routing
Hyun, Jaeyub; Kook, Junghwan; Wang, Semyung
2015-01-01
and basis vectors for use according to the target system. The proposed model reduction scheme is applied to the numerical simulation of the simple mass-damping-spring system and the acoustic metamaterial systems (i.e., acoustic lens and acoustic cloaking device) for the first time. Through these numerical...
Doulamis, A D; Doulamis, N D; Kollias, S D
2003-01-01
Multimedia services and especially digital video is expected to be the major traffic component transmitted over communication networks [such as internet protocol (IP)-based networks]. For this reason, traffic characterization and modeling of such services are required for an efficient network operation. The generated models can be used as traffic rate predictors, during the network operation phase (online traffic modeling), or as video generators for estimating the network resources, during the network design phase (offline traffic modeling). In this paper, an adaptable neural-network architecture is proposed covering both cases. The scheme is based on an efficient recursive weight estimation algorithm, which adapts the network response to current conditions. In particular, the algorithm updates the network weights so that 1) the network output, after the adaptation, is approximately equal to current bit rates (current traffic statistics) and 2) a minimal degradation over the obtained network knowledge is provided. It can be shown that the proposed adaptable neural-network architecture simulates a recursive nonlinear autoregressive model (RNAR) similar to the notation used in the linear case. The algorithm presents low computational complexity and high efficiency in tracking traffic rates in contrast to conventional retraining schemes. Furthermore, for the problem of offline traffic modeling, a novel correlation mechanism is proposed for capturing the burstness of the actual MPEG video traffic. The performance of the model is evaluated using several real-life MPEG coded video sources of long duration and compared with other linear/nonlinear techniques used for both cases. The results indicate that the proposed adaptable neural-network architecture presents better performance than other examined techniques.
Modeling of processes of an adaptive business management
Karev Dmitry Vladimirovich; Karev Vladimir Petrovich
2011-01-01
On the basis of the analysis of systems of adaptive management board business proposed the original version of the real system of adaptive management, the basis of which used dynamic recursive model cash flow forecast and real data. Proposed definitions and the simulation of scales and intervals of model time in the control system, as well as the thresholds observations and conditions of changing (correction) of the administrative decisions. The process of adaptive management is illustrated o...
Aerosol model selection and uncertainty modelling by adaptive MCMC technique
M. Laine
2008-12-01
Full Text Available We present a new technique for model selection problem in atmospheric remote sensing. The technique is based on Monte Carlo sampling and it allows model selection, calculation of model posterior probabilities and model averaging in Bayesian way.
The algorithm developed here is called Adaptive Automatic Reversible Jump Markov chain Monte Carlo method (AARJ. It uses Markov chain Monte Carlo (MCMC technique and its extension called Reversible Jump MCMC. Both of these techniques have been used extensively in statistical parameter estimation problems in wide area of applications since late 1990's. The novel feature in our algorithm is the fact that it is fully automatic and easy to use.
We show how the AARJ algorithm can be implemented and used for model selection and averaging, and to directly incorporate the model uncertainty. We demonstrate the technique by applying it to the statistical inversion problem of gas profile retrieval of GOMOS instrument on board the ENVISAT satellite. Four simple models are used simultaneously to describe the dependence of the aerosol cross-sections on wavelength. During the AARJ estimation all the models are used and we obtain a probability distribution characterizing how probable each model is. By using model averaging, the uncertainty related to selecting the aerosol model can be taken into account in assessing the uncertainty of the estimates.
Ulrich, Steve
This work addresses the direct adaptive trajectory tracking control problem associated with lightweight space robotic manipulators that exhibit elastic vibrations in their joints, and which are subject to parametric uncertainties and modeling errors. Unlike existing adaptive control methodologies, the proposed flexible-joint control techniques do not require identification of unknown parameters, or mathematical models of the system to be controlled. The direct adaptive controllers developed in this work are based on the model reference adaptive control approach, and manage modeling errors and parametric uncertainties by time-varying the controller gains using new adaptation mechanisms, thereby reducing the errors between an ideal model and the actual robot system. More specifically, new decentralized adaptation mechanisms derived from the simple adaptive control technique and fuzzy logic control theory are considered in this work. Numerical simulations compare the performance of the adaptive controllers with a nonadaptive and a conventional model-based controller, in the context of 12.6 m xx 12.6 m square trajectory tracking. To validate the robustness of the controllers to modeling errors, a new dynamics formulation that includes several nonlinear effects usually neglected in flexible-joint dynamics models is proposed. Results obtained with the adaptive methodologies demonstrate an increased robustness to both uncertainties in joint stiffness coefficients and dynamics modeling errors, as well as highly improved tracking performance compared with the nonadaptive and model-based strategies. Finally, this work considers the partial state feedback problem related to flexible-joint space robotic manipulators equipped only with sensors that provide noisy measurements of motor positions and velocities. An extended Kalman filter-based estimation strategy is developed to estimate all state variables in real-time. The state estimation filter is combined with an adaptive
Li, Wenkai; Guo, Weidong; Xue, Yongkang; Fu, Congbin; Qiu, Bo
2016-10-01
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
Prediction of Rolling Force Using AN Adaptive Neural Network Model during Cold Rolling of Thin Strip
Xie, H. B.; Jiang, Z. Y.; Tieu, A. K.; Liu, X. H.; Wang, G. D.
Customers for cold rolled strip products expect the good flatness and surface finish, consistent metallurgical properties and accurate strip thickness. These requirements demand accurate prediction model for rolling parameters. This paper presents a set-up optimization system developed to predict the rolling force during cold strip rolling. As the rolling force has the very nonlinear and time-varying characteristics, conventional methods with simple mathematical models and a coarse learning scheme are not sufficient to achieve a good prediction for rolling force. In this work, all the factors that influence the rolling force are analyzed. A hybrid mathematical roll force model and an adaptive neural network have been improved by adjusting the adaptive learning algorithm. A good agreement between the calculated results and measured values verifies that the approach is applicable in the prediction of rolling force during cold rolling of thin strips, and the developed model is efficient and stable.
An Enhanced Informed Watermarking Scheme Using the Posterior Hidden Markov Model
Chuntao Wang
2014-01-01
Full Text Available Designing a practical watermarking scheme with high robustness, feasible imperceptibility, and large capacity remains one of the most important research topics in robust watermarking. This paper presents a posterior hidden Markov model (HMM- based informed image watermarking scheme, which well enhances the practicability of the prior-HMM-based informed watermarking with favorable robustness, imperceptibility, and capacity. To make the encoder and decoder use the (nearly identical posterior HMM, each cover image at the encoder and each received image at the decoder are attacked with JPEG compression at an equivalently small quality factor (QF. The attacked images are then employed to estimate HMM parameter sets for both the encoder and decoder, respectively. Numerical simulations show that a small QF of 5 is an optimum setting for practical use. Based on this posterior HMM, we develop an enhanced posterior-HMM-based informed watermarking scheme. Extensive experimental simulations show that the proposed scheme is comparable to its prior counterpart in which the HMM is estimated with the original image, but it avoids the transmission of the prior HMM from the encoder to the decoder. This thus well enhances the practical application of HMM-based informed watermarking systems. Also, it is demonstrated that the proposed scheme has the robustness comparable to the state-of-the-art with significantly reduced computation time.
An enhanced informed watermarking scheme using the posterior hidden Markov model.
Wang, Chuntao
2014-01-01
Designing a practical watermarking scheme with high robustness, feasible imperceptibility, and large capacity remains one of the most important research topics in robust watermarking. This paper presents a posterior hidden Markov model (HMM-) based informed image watermarking scheme, which well enhances the practicability of the prior-HMM-based informed watermarking with favorable robustness, imperceptibility, and capacity. To make the encoder and decoder use the (nearly) identical posterior HMM, each cover image at the encoder and each received image at the decoder are attacked with JPEG compression at an equivalently small quality factor (QF). The attacked images are then employed to estimate HMM parameter sets for both the encoder and decoder, respectively. Numerical simulations show that a small QF of 5 is an optimum setting for practical use. Based on this posterior HMM, we develop an enhanced posterior-HMM-based informed watermarking scheme. Extensive experimental simulations show that the proposed scheme is comparable to its prior counterpart in which the HMM is estimated with the original image, but it avoids the transmission of the prior HMM from the encoder to the decoder. This thus well enhances the practical application of HMM-based informed watermarking systems. Also, it is demonstrated that the proposed scheme has the robustness comparable to the state-of-the-art with significantly reduced computation time.
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.
Adaptable Authentication Model: Exploring Security with Weaker Attacker Models
Ahmed, Naveed; Jensen, Christian D.
2011-01-01
suffer because of the identified vulnerabilities. Therefore, we may need to analyze a protocol for weaker notions of security. In this paper, we present a security model that supports such weaker notions. In this model, the overall goals of an authentication protocol are broken into a finer granularity......; for each fine level authentication goal, we determine the “least strongest-attacker” for which the authentication goal can be satisfied. We demonstrate that this model can be used to reason about the security of supposedly insecure protocols. Such adaptability is particularly useful in those applications......Most methods for protocol analysis classify protocols as “broken” if they are vulnerable to attacks from a strong attacker, e.g., assuming the Dolev-Yao attacker model. In many cases, however, exploitation of existing vulnerabilities may not be practical and, moreover, not all applications may...
LIMIT THEOREMS AND OPTIMAL DESIGN WITH ADAPTIVE URN MODELS
CHEN Guijing; ZHU Chunhua; WANG Yao-hung
2005-01-01
In this paper we study urn model, using some available estimates of successes probabilities, and adding particle parameter, we establish adaptive models. We obtain some strong convergence theorems, rates of convergence, asymptotic normality of components in the urn, and estimates. With these asymptotical results, we show that the adaptive designs given in this paper are asymptotically optimal designs.
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.
A general scheme for training and optimization of the Grenander deformable template model
Fisker, Rune; Schultz, Nette; Duta, N.
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 filter interpretation of the likelihood model....
Korpusik, Adam
2017-02-01
We present a nonstandard finite difference scheme for a basic model of cellular immune response to viral infection. The main advantage of this approach is that it preserves the essential qualitative features of the original continuous model (non-negativity and boundedness of the solution, equilibria and their stability conditions), while being easy to implement. All of the qualitative features are preserved independently of the chosen step-size. Numerical simulations of our approach and comparison with other conventional simulation methods are presented.
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...
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.
Stasser
1999-10-01
The basic elements of social decision scheme (SDS) theory are individual preferences, group preference compositions (distinguishable distributions), patterns of group influence (decision schemes, social combination rules), and collective responses (group decisions, judgments, solutions, and the like). The theory provides a framework for addressing two fundamental questions in the study of group performance: How are individual resources combined to yield a group response (the individual-into-group problem)? What are the implications of empirical observations under one set of circumstances for other conditions where data do not exist (the sparse data problem)? Several prescriptions for how to conduct fruitful group research are contained in the SDS tradition: make precise theoretical statements, provide strong and competitive tests of theories, and interpret empirical findings in the context of robust process models. Copyright 1999 Academic Press.
A Model-Free Scheme for Meme Ranking in Social Media.
He, Saike; Zheng, Xiaolong; Zeng, Daniel
2016-01-01
The prevalence of social media has greatly catalyzed the dissemination and proliferation of online memes (e.g., ideas, topics, melodies, tags, etc.). However, this information abundance is exceeding the capability of online users to consume it. Ranking memes based on their popularities could promote online advertisement and content distribution. Despite such importance, few existing work can solve this problem well. They are either daunted by unpractical assumptions or incapability of characterizing dynamic information. As such, in this paper, we elaborate a model-free scheme to rank online memes in the context of social media. This scheme is capable to characterize the nonlinear interactions of online users, which mark the process of meme diffusion. Empirical studies on two large-scale, real-world datasets (one in English and one in Chinese) demonstrate the effectiveness and robustness of the proposed scheme. In addition, due to its fine-grained modeling of user dynamics, this ranking scheme can also be utilized to explain meme popularity through the lens of social influence.
Chang-bae Moon
2011-01-01
Full Text Available Although there have been many researches on mobile robot localization, it is still difficult to obtain reliable localization performance in a human co-existing real environment. Reliability of localization is highly dependent upon developer's experiences because uncertainty is caused by a variety of reasons. We have developed a range sensor based integrated localization scheme for various indoor service robots. Through the experience, we found out that there are several significant experimental issues. In this paper, we provide useful solutions for following questions which are frequently faced with in practical applications: 1 How to design an observation likelihood model? 2 How to detect the localization failure? 3 How to recover from the localization failure? We present design guidelines of observation likelihood model. Localization failure detection and recovery schemes are presented by focusing on abrupt wheel slippage. Experiments were carried out in a typical office building environment. The proposed scheme to identify the localizer status is useful in practical environments. Moreover, the semi-global localization is a computationally efficient recovery scheme from localization failure. The results of experiments and analysis clearly present the usefulness of proposed solutions.
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.
Validation of sub-grid-scale mixing schemes using CFCs in a global ocean model
Robitaille, Daniel Y.; Weaver, Andrew J.
Three sub-grid-scale mixing parameterizations (lateral/vertical; isopycnal; Gent and McWilliams, 1990) are used in a global ocean model in an attempt to determine which yields the best ocean climate. Observed CFC-11 distributions, in both the North and South Atlantic, are used in evaluating the model results. While the isopycnal mixing scheme does improve the deep ocean potential temperature and salinity distributions, when compared to results from the traditional lateral/vertical mixing scheme, the CFC-11 distribution is worse in the upper ocean due to too much mixing. The Gent and McWilliams (1990) parameterization significantly improves the CFC-11 distributions when compared to both of the other schemes. The main improvement comes from a reduction of CFC uptake in the southern ocean where the ‘bolus’ transport cancels the mean advection of tracers and hence causes the Deacon Cell to disappear. These results suggest that the asymmetric response found in CO2-increase experiments, whereby the climate over the southern ocean does not warm as much as in the northern hemisphere, may be due to the particular mixing schemes used.
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.
La Malfa, Giampaolo; Lassi, Stefano; Bertelli, Marco; Albertini, Giorgio; Dosen, Anton
2009-01-01
The importance of emotional aspects in developing cognitive and social abilities has already been underlined by many authors even if there is no unanimous agreement on the factors constituting adaptive abilities, nor is there any on the way to measure them or on the relation between adaptive ability and cognitive level. The purposes of this study…
La Malfa, Giampaolo; Lassi, Stefano; Bertelli, Marco; Albertini, Giorgio; Dosen, Anton
2009-01-01
The importance of emotional aspects in developing cognitive and social abilities has already been underlined by many authors even if there is no unanimous agreement on the factors constituting adaptive abilities, nor is there any on the way to measure them or on the relation between adaptive ability and cognitive level. The purposes of this study…
Primdahl, Jørgen; Vesterager, Jens Peter; Finn, John A; Vlahos, George; Kristensen, Lone; Vejre, Henrik
2010-06-01
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 evaluation of AES. Impact models identify and establish the causal relationships between policy objectives and policy outcomes. We review and discuss the role of impact models at different stages in the AES policy process, and present results from a survey of impact models underlying 60 agri-environmental schemes in seven EU member states. We distinguished among three categories of impact models (quantitative, qualitative or common sense), depending on the degree of evidence in the formal scheme description, additional documents, or key person interviews. The categories of impact models used mainly 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 those concerned with biodiversity or landscape. Schemes explicitly targeted either on particular parts of individual farms or specific areas tended to be based more on quantitative impact models compared to whole-farm schemes and broad, horizontal schemes. We conclude that increased and better use of impact models has significant potential to improve efficiency and effectiveness of AES. (c) 2009 Elsevier Ltd. All rights reserved.
Rigatos, Gerasimos
2016-12-01
It is shown that the model of the hypothalamic-pituitary-adrenal gland axis is a differentially flat one and this permits to transform it to the so-called linear canonical form. For the new description of the system's dynamics the transformed control inputs contain unknown terms which depend on the system's parameters. To identify these terms an adaptive fuzzy approximator is used in the control loop. Thus an adaptive fuzzy control scheme is implemented in which the unknown or unmodeled system dynamics is approximated by neurofuzzy networks and next this information is used by a feedback controller that makes the state variables (CRH - corticotropin releasing hormone, adenocortocotropic hormone - ACTH, cortisol) of the hypothalamic-pituitary-adrenal gland axis model converge to the desirable levels (setpoints). This adaptive control scheme is exclusively implemented with the use of output feedback, while the state vector elements which are not directly measured are estimated with the use of a state observer that operates in the control loop. The learning rate of the adaptive fuzzy system is suitably computed from Lyapunov analysis, so as to assure that both the learning procedure for the unknown system's parameters, the dynamics of the observer and the dynamics of the control loop will remain stable. The performed Lyapunov stability analysis depends on two Riccati equations, one associated with the feedback controller and one associated with the state observer. Finally, it is proven that for the control scheme that comprises the feedback controller, the state observer and the neurofuzzy approximator, an H-infinity tracking performance can be succeeded.
Chen, Haizhou; Wang, Jiaxu; Li, Junyang; Tang, Baoping
2017-03-01
This paper presents a new scheme for rolling bearing fault diagnosis using texture features extracted from the time-frequency representations (TFRs) of the signal. To derive the proposed texture features, firstly adaptive optimal kernel time frequency representation (AOK-TFR) is applied to extract TFRs of the signal which essentially describe the energy distribution characteristics of the signal over time and frequency domain. Since the AOK-TFR uses the signal-dependent radially Gaussian kernel that adapts over time, it can exactly track the minor variations in the signal and provide an excellent time-frequency concentration in noisy environment. Simulation experiments are furthermore performed in comparison with common time-frequency analysis methods under different noisy conditions. Secondly, the uniform local binary pattern (uLBP), which is a computationally simple and noise-resistant texture analysis method, is used to calculate the histograms from the TFRs to characterize rolling bearing fault information. Finally, the obtained histogram feature vectors are input into the multi-SVM classifier for pattern recognition. We validate the effectiveness of the proposed scheme by several experiments, and comparative results demonstrate that the new fault diagnosis technique performs better than most state-of-the-art techniques, and yet we find that the proposed algorithm possess the adaptivity and noise resistance qualities that could be very useful in real industrial applications.
Simulation of hailstorm event using Mesoscale Model MM5 with modified cloud microphysics scheme
P. Chatterjee
2008-11-01
Full Text Available Mesoscale model MM5 (Version 3.5 with some modifications in the cloud microphysics scheme of Schultz (1995, has been used to simulate two hailstorm events over Gangetic Plain of West Bengal, India. While the first event occurred on 12 March 2003 and the hails covered four districts of the state of West Bengal, India, the second hailstorm event struck Srinikatan (22.65° N, 87.7° E on 10 April 2006 at 11:32 UT and it lasted for 2–3 min. Both these events can be simulated, if the same modifications are introduced in the cloud microphysics scheme of Schultz. However, the original scheme of Schultz cannot simulate any hail.
The results of simulation were compared with the necessary products of Doppler Weather Radar (DWR located at Kolkata (22.57° N, 88.35° E. Model products like reflectivity, graupel and horizontal wind are compared with the corresponding products of DWR. The pattern of hail development bears good similarity between model output and observation from DWR, if necessary modifications are introduced in the model. The model output of 24 h accumulated rain from 03:00 UT to next day 03:00 UT has also been compared with the corresponding product of the satellite TRMM.
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.
Tsuji, Takuya; Yokomine, Takehiko; Shimizu, Akihiko
2002-11-01
We have been engaged in the development of multi-scale adaptive simulation technique for incompressible turbulent flow. This is designed as that important scale components in the flow field are detected automatically by lifting wavelet and solved selectively. In conventional incompressible scheme, it is very common to solve Poisson equation of pressure to meet the divergence free constraints of incompressible flow. It may be not impossible to solve the Poisson eq. in the adaptive way, but this is very troublesome because it requires generation of control volume at each time step. We gave an eye on weakly compressible model proposed by Bao(2001). This model was derived from zero Mach limit asymptotic analysis of compressible Navier-Stokes eq. and does not need to solve the Poisson eq. at all. But it is relatively new and it requires demonstration study before the combination with the adaptation by wavelet. In present study, 2-D and 3-D Backstep flow were selected as test problems and applicability to turbulent flow is verified in detail. Besides, combination of adaptation by wavelet with weakly compressible model towards the adaptive turbulence simulation is discussed.
Development and basic evaluation of a prognostic aerosol scheme in the CNRM Climate Model
Michou, M.; Nabat, P.; Saint-Martin, D.
2014-09-01
We have implemented a prognostic aerosol scheme in the CNRM-GAME/CERFACS climate model, based upon the GEMS/MACC aerosol module of the ECMWF operational forecast model. This scheme describes the physical evolution of the five main types of aerosols, namely black carbon, organic matter, sulfate, desert dust and sea-salt. In this work, we describe the specificities of our implementation, for instance, taking into consideration a different dust scheme or boosting biomass burning emissions by a factor of 2, as well as the evaluation performed on simulation outputs. The simulations consist of 2004 conditions and transient runs over the 1993-2012 period, and are either free-running or nudged towards the ERA-Interim Reanalysis. Evaluation data sets include several satellite instrument AOD products (i.e., MODIS Aqua classic and Deep-Blue products, MISR and CALIOP products), as well as ground-based AERONET data and the derived AERONET climatology, MAC-v1. The internal variability of the model has little impact on the seasonal climatology of the AODs of the various aerosols, and the characteristics of a nudged simulation reflect those of a free-running simulation. In contrast, the impact of the new dust scheme is large, with modelled dust AODs from simulations with the new dust scheme close to observations. Overall patterns and seasonal cycles of the total AOD are well depicted with, however, a systematic low bias over oceans. The comparison to the fractional MAC-v1 AOD climatology shows disagreements mostly over continents, while that to AERONET sites outlines the capability of the model to reproduce monthly climatologies under very diverse dominant aerosol types. Here again, underestimation of the total AOD appears in several cases, linked sometimes to insufficient efficiency of the aerosol transport away from the aerosol sources. Analysis of monthly time series at 166 AERONET sites shows, in general, correlation coefficients higher than 0.5 and lower model variance than
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.
Histogram Equalization to Model Adaptation for Robust Speech Recognition
Hoirin Kim
2010-01-01
Full Text Available We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization algorithm on a single utterance basis. For more robust speech recognition in the heavily noisy conditions, trained acoustic covariance models are efficiently adapted by the signal-to-noise ratio-dependent linear interpolation between trained covariance models and utterance-level sample covariance models. Speech recognition experiments on both the digit-based Aurora2 task and the large vocabulary-based task showed that the proposed model adaptation approach provides significant performance improvements compared to the baseline speech recognizer trained on the clean speech data.
Overshooting dynamics in a model adaptive radiation
Meyer, J.R.; Schoustra, S.E.; LaChapelle, J.; Kassen, R.K.
2011-01-01
The history of life is punctuated by repeated periods of unusually rapid evolutionary diversification called adaptive radiation. The dynamics of diversity during a radiation reflect an overshooting pattern with an initial phase of exponential-like increase followed by a slower decline. Much
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.
Amundsen, David S.; Mayne, Nathan J.; Baraffe, Isabelle; Manners, James; Tremblin, Pascal; Drummond, Benjamin; Smith, Chris; Acreman, David M.; Homeier, Derek
2016-10-01
To study the complexity of hot Jupiter atmospheres revealed by observations of increasing quality, we have adapted the UK Met Office Global Circulation Model (GCM), the Unified Model (UM), to these exoplanets. The UM solves the full 3D Navier-Stokes equations with a height-varying gravity, avoiding the simplifications used in most GCMs currently applied to exoplanets. In this work we present the coupling of the UM dynamical core to an accurate radiation scheme based on the two-stream approximation and correlated-k method with state-of-the-art opacities from ExoMol. Our first application of this model is devoted to the extensively studied hot Jupiter HD 209458b. We have derived synthetic emission spectra and phase curves, and compare them to both previous models also based on state-of-the-art radiative transfer, and to observations. We find a reasonable agreement between observations and both our days side emission and hot spot offset, however, our night side emissions is too large. Overall our results are qualitatively similar to those found by Showman et al. (2009, ApJ, 699, 564) with the SPARC/MITgcm, however, we note several quantitative differences: Our simulations show significant variation in the position of the hottest part of the atmosphere with pressure, as expected from simple timescale arguments, and in contrast to the "vertical coherency" found by Showman et al. (2009). We also see significant quantitative differences in calculated synthetic observations. Our comparisons strengthen the need for detailed intercomparisons of dynamical cores, radiation schemes and post-processing tools to understand these differences. This effort is necessary in order to make robust conclusions about these atmospheres based on GCM results.
Modeling and Analysis of DIPPM: A New Modulation Scheme for Visible Light Communications
Sana Ullah Jan
2015-01-01
Full Text Available Visible Light Communication (VLC uses an Intensity-Modulation and Direct-Detection (IM/DD scheme to transmit data. However, the light source used in VLC systems is continuously switched on and off quickly, resulting in flickering. In addition, recent illumination systems include dimming support to allow users to dim the light sources to the desired level. Therefore, the modulation scheme for data transmission in VLC system must include flicker mitigation and dimming control capabilities. In this paper, the authors propose a Double Inverse Pulse Position Modulation (DIPPM scheme that minimizes flickering and supports a high level of dimming for the illumination sources in VLC systems. To form DIPPM, some changes are made in the symbol structure of the IPPM scheme, and a detailed explanation and mathematical model of DIPPM are given in this paper. Furthermore, both analytical and simulation results for the error performance of 2-DIPPM are compared with the performance of VPPM. Also, the communication performance of DIPPM is analyzed in terms of the normalized required power.
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.
ADAPTIVE LEARNING OF HIDDEN MARKOV MODELS FOR EMOTIONAL SPEECH
A. V. Tkachenia
2014-01-01
Full Text Available An on-line unsupervised algorithm for estimating the hidden Markov models (HMM parame-ters is presented. The problem of hidden Markov models adaptation to emotional speech is solved. To increase the reliability of estimated HMM parameters, a mechanism of forgetting and updating is proposed. A functional block diagram of the hidden Markov models adaptation algorithm is also provided with obtained results, which improve the efficiency of emotional speech recognition.
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.
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.
Chalupecký, Vladimír
2011-01-01
We propose a semi-discrete finite difference multiscale scheme for a concrete corrosion model consisting of a system of two-scale reaction-diffusion equations coupled with an ode. We prove energy and regularity estimates and use them to get the necessary compactness of the approximation estimates. Finally, we illustrate numerically the behavior of the two-scale finite difference approximation of the weak solution.
Modelling medical care usage under medical insurance scheme for urban non-working residents.
Xiong, Linping; Tian, Wenhua; Tang, Weidong
2013-06-01
This research investigates and evaluates China's urban medical care usage for non-working residents using microsimulation techniques. It focuses on modelling medical services usage and simulating medical expenses on hospitalization treatments as well as clinic services for serious illness in an urban area for the period of 2008-2010. A static microsimulation model was created to project the impact of the medical insurance scheme. Four kinds of achievements have been made. For three different scenarios, the model predicted the hospitalization services costs and payments, as well as the balance of the social pool fund and the medical burden on families.
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.
A survey of Strong Convergent Schemes for the Simulation of ...
PROF. OLIVER OSUAGWA
2014-12-01
Dec 1, 2014 ... scheme as well as the error between the analytic result and the numerical approximation. The error appeared ... financial mathematics and economics to model the .... is a standard m-dimensional Wiener process adapted to ...
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.
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.
Comparison of renormalization group schemes for sine-Gordon type models
Nandori, I; Sailer, K; Trombettoni, A
2009-01-01
We consider the scheme-dependence of the renormalization group (RG) flow obtained in the local potential approximation for two-dimensional periodic, sine-Gordon type field-theoric models with possible inclusion of explicit mass terms. For sine-Gordon type models showing up a Kosterlitz-Thouless-Berezinskii type phase transition the Wegner-Houghton, the Polchinski, the functional Callan-Symanzik and the effective average action RG methods give qualitatively the same result and the critical frequency (temperature) can be obtained scheme-independently from the RG equations linearized around the Gaussian fixed point. For the massive sine-Gordon model which undergoes an Ising type phase transition, the Wegner-Houghton, the functional Callan-Symanzik and the effective average action RG methods provide the same scheme-independent phase structure and value for the critical ratio, in agreement with the results of lattice methods. It is also shown that RG equations linearized around the Gaussian fixed point produce sch...
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.
M. Schraner
2008-10-01
Full Text Available We describe version 2.0 of the chemistry-climate model (CCM SOCOL. The new version includes fundamental changes of the transport scheme such as transporting all chemical species of the model individually and applying a family-based correction scheme for mass conservation for species of the nitrogen, chlorine and bromine groups, a revised transport scheme for ozone, furthermore more detailed halogen reaction and deposition schemes, and a new cirrus parameterisation in the tropical tropopause region. By means of these changes the model manages to overcome or considerably reduce deficiencies recently identified in SOCOL version 1.1 within the CCM Validation activity of SPARC (CCMVal. In particular, as a consequence of these changes, regional mass loss or accumulation artificially caused by the semi-Lagrangian transport scheme can be significantly reduced, leading to much more realistic distributions of the modelled chemical species, most notably of the halogens and ozone.
A multi-modal prostate segmentation scheme by combining spectral clustering and active shape models
Toth, Robert; Tiwari, Pallavi; Rosen, Mark; Kalyanpur, Arjun; Pungavkar, Sona; Madabhushi, Anant
2008-03-01
Segmentation of the prostate boundary on clinical images is useful in a large number of applications including calculating prostate volume during biopsy, tumor estimation, and treatment planning. Manual segmentation of the prostate boundary is, however, time consuming and subject to inter- and intra-reader variability. Magnetic Resonance (MR) imaging (MRI) and MR Spectroscopy (MRS) have recently emerged as promising modalities for detection of prostate cancer in vivo. In this paper we present a novel scheme for accurate and automated prostate segmentation on in vivo 1.5 Tesla multi-modal MRI studies. The segmentation algorithm comprises two steps: (1) A hierarchical unsupervised spectral clustering scheme using MRS data to isolate the region of interest (ROI) corresponding to the prostate, and (2) an Active Shape Model (ASM) segmentation scheme where the ASM is initialized within the ROI obtained in the previous step. The hierarchical MRS clustering scheme in step 1 identifies spectra corresponding to locations within the prostate in an iterative fashion by discriminating between potential prostate and non-prostate spectra in a lower dimensional embedding space. The spatial locations of the prostate spectra so identified are used as the initial ROI for the ASM. The ASM is trained by identifying user-selected landmarks on the prostate boundary on T2 MRI images. Boundary points on the prostate are identified using mutual information (MI) as opposed to the traditional Mahalanobis distance, and the trained ASM is deformed to fit the boundary points so identified. Cross validation on 150 prostate MRI slices yields an average segmentation sensitivity, specificity, overlap, and positive predictive value of 89, 86, 83, and 93% respectively. We demonstrate that the accurate initialization of the ASM via the spectral clustering scheme is necessary for automated boundary extraction. Our method is fully automated, robust to system parameters, and computationally efficient.
Hou, Chieh; Ateshian, Gerard A
2016-01-01
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.
Daniel Holdaway
2015-09-01
Full Text Available 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 non-linear 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.
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.
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.
Tapas Pandit
2016-08-01
Full Text Available Attribute-Based Signcryption (ABSC is a natural extension of Attribute-Based Encryption (ABE and Attribute-Based Signature (ABS, where one can have the message confidentiality and authenticity together. Since the signer privacy is captured in security of ABS, it is quite natural to expect that the signer privacy will also be preserved in ABSC. In this paper, first we propose an ABSC scheme which is weak existential unforgeable and IND-CCA secure in adaptive-predicates models and, achieves signer privacy. Then, by applying strongly unforgeable one-time signature (OTS, the above scheme is lifted to an ABSC scheme to attain strong existential unforgeability in adaptive-predicates model. Both the ABSC schemes are constructed on common setup, i.e the public parameters and key are same for both the encryption and signature modules. Our first construction is in the flavor of CtE&S paradigm, except one extra component that will be computed using both signature components and ciphertext components. The second proposed construction follows a new paradigm (extension of CtE&S , we call it “Commit then Encrypt and Sign then Sign” (CtE&S . The last signature is generated using a strong OTS scheme. Since, the non-repudiation is achieved by CtE&S paradigm, our systems also achieve the same.
A coupled model tree genetic algorithm scheme for flow and water quality predictions in watersheds
Preis, Ami; Ostfeld, Avi
2008-02-01
SummaryThe rapid advance in information processing systems along with the increasing data availability have directed research towards the development of intelligent systems that evolve models of natural phenomena automatically. This is the discipline of data driven modeling which is the study of algorithms that improve automatically through experience. Applications of data driven modeling range from data mining schemes that discover general rules in large data sets, to information filtering systems that automatically learn users' interests. This study presents a data driven modeling algorithm for flow and water quality load predictions in watersheds. The methodology is comprised of a coupled model tree-genetic algorithm scheme. The model tree predicts flow and water quality constituents while the genetic algorithm is employed for calibrating the model tree parameters. The methodology is demonstrated through base runs and sensitivity analysis for daily flow and water quality load predictions on a watershed in northern Israel. The method produced close fits in most cases, but was limited in estimating the peak flows and water quality loads.
A new multi-tracer transport scheme for the dynamical core of NCAR's Community Atmosphere Model
Erath, C.
2012-04-01
The integration of a conservative semi-Lagrangian multi-tracer transport scheme (CSLAM) in NCAR's High-Order Method Modeling Environment (HOMME) is considered here. HOMME is a highly scalable atmospheric modeling framework, and its current horizontal discretization relies on spectral element (SE) and/or discontinuous Galerkin (DG) methods on the cubed-sphere. It is one dynamical core of NCAR's Community Atmosphere Model (CAM). The main advantage of CSLAM is that the upstream cell (trajectories) information and computation of weights of integrals can be reused for each additional tracer. This makes CSLAM particularly interesting for global atmospheric modeling with growing number of tracers, e.g. more than 100 tracers for the chemistry version of CAM. An algorithm specifically designed for multiple processors and on the cubed-sphere grid for CSLAM in HOMME is a challenging task. HOMME is running on an element ansatz on the six cube faces. Inside these elements we create an Eulerian finite volume grid of equiangular gnomonic type, which represents the arrival grid in the scheme. But CSLAM relies on backward trajectories, which entails a departure grid. That means departure and arrival grid don't necessary have to be on the same element and certainly not on the same cube face. Also the reconstruction for higher order modeling needs a patch of tracer values which extend the element. Here we consider a third order reconstruction method. Therefore, we introduce a halo for the tracer values in the cell centers of a cube-element. The size of this halo depends on the Courant number (CFL condition) and the reconstruction type. Note that for a third order scheme and CFL number communication can be limited to one per time step. This data structure allows us to consider an element with its halo as one task where we have to be extra carful for elements which share a cube edge due to projection and orientation reasons. We stress that the reconstruction coefficients for elements
Modeling adaptation of carbon use efficiency in microbial communities
Steven D Allison
2014-10-01
Full Text Available In new microbial-biogeochemical models, microbial carbon use efficiency (CUE is often assumed to decline with increasing temperature. Under this assumption, soil carbon losses under warming are small because microbial biomass declines. Yet there is also empirical evidence that CUE may adapt (i.e. become less sensitive to warming, thereby mitigating negative effects on microbial biomass. To analyze potential mechanisms of CUE adaptation, I used two theoretical models to implement a tradeoff between microbial uptake rate and CUE. This rate-yield tradeoff is based on thermodynamic principles and suggests that microbes with greater investment in resource acquisition should have lower CUE. Microbial communities or individuals could adapt to warming by reducing investment in enzymes and uptake machinery. Consistent with this idea, a simple analytical model predicted that adaptation can offset 50% of the warming-induced decline in CUE. To assess the ecosystem implications of the rate-yield tradeoff, I quantified CUE adaptation in a spatially-structured simulation model with 100 microbial taxa and 12 soil carbon substrates. This model predicted much lower CUE adaptation, likely due to additional physiological and ecological constraints on microbes. In particular, specific resource acquisition traits are needed to maintain stoichiometric balance, and taxa with high CUE and low enzyme investment rely on low-yield, high-enzyme neighbors to catalyze substrate degradation. In contrast to published microbial models, simulations with greater CUE adaptation also showed greater carbon storage under warming. This pattern occurred because microbial communities with stronger CUE adaptation produced fewer degradative enzymes, despite increases in biomass. Thus the rate-yield tradeoff prevents CUE adaptation from driving ecosystem carbon loss under climate warming.
Fukuda, Ryoichi; Ehara, Masahiro
2014-10-01
Solvent effects on electronic excitation spectra are considerable in many situations; therefore, we propose an efficient and reliable computational scheme that is based on the symmetry-adapted cluster-configuration interaction (SAC-CI) method and the polarizable continuum model (PCM) for describing electronic excitations in solution. The new scheme combines the recently proposed first-order PCM SAC-CI method with the PTE (perturbation theory at the energy level) PCM SAC scheme. This is essentially equivalent to the usual SAC and SAC-CI computations with using the PCM Hartree-Fock orbital and integrals, except for the additional correction terms that represent solute-solvent interactions. The test calculations demonstrate that the present method is a very good approximation of the more costly iterative PCM SAC-CI method for excitation energies of closed-shell molecules in their equilibrium geometry. This method provides very accurate values of electric dipole moments but is insufficient for describing the charge-transfer (CT) indices in polar solvent. The present method accurately reproduces the absorption spectra and their solvatochromism of push-pull type 2,2'-bithiophene molecules. Significant solvent and substituent effects on these molecules are intuitively visualized using the CT indices. The present method is the simplest and theoretically consistent extension of SAC-CI method for including PCM environment, and therefore, it is useful for theoretical and computational spectroscopy.
Kinetic modeling and fitting software for interconnected reaction schemes: VisKin.
Zhang, Xuan; Andrews, Jared N; Pedersen, Steen E
2007-02-15
Reaction kinetics for complex, highly interconnected kinetic schemes are modeled using analytical solutions to a system of ordinary differential equations. The algorithm employs standard linear algebra methods that are implemented using MatLab functions in a Visual Basic interface. A graphical user interface for simple entry of reaction schemes facilitates comparison of a variety of reaction schemes. To ensure microscopic balance, graph theory algorithms are used to determine violations of thermodynamic cycle constraints. Analytical solutions based on linear differential equations result in fast comparisons of first order kinetic rates and amplitudes as a function of changing ligand concentrations. For analysis of higher order kinetics, we also implemented a solution using numerical integration. To determine rate constants from experimental data, fitting algorithms that adjust rate constants to fit the model to imported data were implemented using the Levenberg-Marquardt algorithm or using Broyden-Fletcher-Goldfarb-Shanno methods. We have included the ability to carry out global fitting of data sets obtained at varying ligand concentrations. These tools are combined in a single package, which we have dubbed VisKin, to guide and analyze kinetic experiments. The software is available online for use on PCs.
Distortion Modeling and Error Robust Coding Scheme for H.26L Video
CHENChuan; YUSongyu; CHENGLianji
2004-01-01
Transmission of hybrid-coded video including motion compensation and spatial prediction over error prone channel results in the well-known problem of error propagation because of the drift in reference frames between encoder and decoder. The prediction loop propa-gates errors and causes substantial degradation in video quality. Especially in H.26L video, both intra and inter prediction strategies are used to improve compression efficiency, however, they make error propagation more serious. This work proposes distortion models for H.26L video to optimally estimate the overall distortion of decoder frame reconstruction due to quantization, error propagation, and error concealment. Based on these statistical distortion models, our error robust coding scheme only integrates the distinct distortion between intra and inter macroblocks into a rate-distortlon based framework to select suitable coding mode for each macroblock, and so,the cost in computation complexity is modest. Simulations under typical 3GPP/3GPP2 channel and Internet channel conditions have shown that our proposed scheme achieves much better performance than those currently used in H.26L. The error propagation estimation and effect at high fractural pixel-level prediction have also been tested. All the results have demonstrated that our proposed scheme achieves a good balance between compression efficiency and error robustness for H.26L video, at the cost of modest additional complexity.
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.
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...
Computational quantum chemistry and adaptive ligand modeling in mechanistic QSAR.
De Benedetti, Pier G; Fanelli, Francesca
2010-10-01
Drugs are adaptive molecules. They realize this peculiarity by generating different ensembles of prototropic forms and conformers that depend on the environment. Among the impressive amount of available computational drug discovery technologies, quantitative structure-activity relationship approaches that rely on computational quantum chemistry descriptors are the most appropriate to model adaptive drugs. Indeed, computational quantum chemistry descriptors are able to account for the variation of the intramolecular interactions of the training compounds, which reflect their adaptive intermolecular interaction propensities. This enables the development of causative, interpretive and reasonably predictive quantitative structure-activity relationship models, and, hence, sound chemical information finalized to drug design and discovery.
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
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.
Hasegawa, Takemitsu; Hibino, Susumu; Hosoda, Yohsuke; Ninomiya, Ichizo
2007-08-01
An improvement is made to an automatic quadrature due to Ninomiya (J. Inf. Process. 3:162?170, 1980) of adaptive type based on the Newton?Cotes rule by incorporating a doubly-adaptive algorithm due to Favati, Lotti and Romani (ACM Trans. Math. Softw. 17:207?217, 1991; ACM Trans. Math. Softw. 17:218?232, 1991). We compare the present method in performance with some others by using various test problems including Kahaner?s ones (Computation of numerical quadrature formulas. In: Rice, J.R. (ed.) Mathematical Software, 229?259. Academic, Orlando, FL, 1971).
An adaptation model for trabecular bone at different mechanical levels
Lv Linwei
2010-07-01
Full Text Available Abstract Background Bone has the ability to adapt to mechanical usage or other biophysical stimuli in terms of its mass and architecture, indicating that a certain mechanism exists for monitoring mechanical usage and controlling the bone's adaptation behaviors. There are four zones describing different bone adaptation behaviors: the disuse, adaptation, overload, and pathologic overload zones. In different zones, the changes of bone mass, as calculated by the difference between the amount of bone formed and what is resorbed, should be different. Methods An adaptation model for the trabecular bone at different mechanical levels was presented in this study based on a number of experimental observations and numerical algorithms in the literature. In the proposed model, the amount of bone formation and the probability of bone remodeling activation were proposed in accordance with the mechanical levels. Seven numerical simulation cases under different mechanical conditions were analyzed as examples by incorporating the adaptation model presented in this paper with the finite element method. Results The proposed bone adaptation model describes the well-known bone adaptation behaviors in different zones. The bone mass and architecture of the bone tissue within the adaptation zone almost remained unchanged. Although the probability of osteoclastic activation is enhanced in the overload zone, the potential of osteoblasts to form bones compensate for the osteoclastic resorption, eventually strengthening the bones. In the disuse zone, the disuse-mode remodeling removes bone tissue in disuse zone. Conclusions The study seeks to provide better understanding of the relationships between bone morphology and the mechanical, as well as biological environments. Furthermore, this paper provides a computational model and methodology for the numerical simulation of changes of bone structural morphology that are caused by changes of mechanical and biological
Turing patterns in a reaction-diffusion model with the Degn-Harrison reaction scheme
Li, Shanbing; Wu, Jianhua; Dong, Yaying
2015-09-01
In this paper, we consider a reaction-diffusion model with Degn-Harrison reaction scheme. Some fundamental analytic properties of nonconstant positive solutions are first investigated. We next study the stability of constant steady-state solution to both ODE and PDE models. Our result also indicates that if either the size of the reactor or the effective diffusion rate is large enough, then the system does not admit nonconstant positive solutions. Finally, we establish the global structure of steady-state bifurcations from simple eigenvalues by bifurcation theory and the local structure of the steady-state bifurcations from double eigenvalues by the techniques of space decomposition and implicit function theorem.
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.
Comparison of Aircraft Models and Integration Schemes for Interval Management in the TRACON
Neogi, Natasha; Hagen, George E.; Herencia-Zapana, Heber
2012-01-01
Reusable models of common elements for communication, computation, decision and control in air traffic management are necessary in order to enable simulation, analysis and assurance of emergent properties, such as safety and stability, for a given operational concept. Uncertainties due to faults, such as dropped messages, along with non-linearities and sensor noise are an integral part of these models, and impact emergent system behavior. Flight control algorithms designed using a linearized version of the flight mechanics will exhibit error due to model uncertainty, and may not be stable outside a neighborhood of the given point of linearization. Moreover, the communication mechanism by which the sensed state of an aircraft is fed back to a flight control system (such as an ADS-B message) impacts the overall system behavior; both due to sensor noise as well as dropped messages (vacant samples). Additionally simulation of the flight controller system can exhibit further numerical instability, due to selection of the integration scheme and approximations made in the flight dynamics. We examine the theoretical and numerical stability of a speed controller under the Euler and Runge-Kutta schemes of integration, for the Maintain phase for a Mid-Term (2035-2045) Interval Management (IM) Operational Concept for descent and landing operations. We model uncertainties in communication due to missed ADS-B messages by vacant samples in the integration schemes, and compare the emergent behavior of the system, in terms of stability, via the boundedness of the final system state. Any bound on the errors incurred by these uncertainties will play an essential part in a composable assurance argument required for real-time, flight-deck guidance and control systems,. Thus, we believe that the creation of reusable models, which possess property guarantees, such as safety and stability, is an innovative and essential requirement to assessing the emergent properties of novel airspace
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.
Axisymmetric modeling of cometary mass loading on an adaptively refined grid: MHD results
Gombosi, Tamas I.; Powell, Kenneth G.; De Zeeuw, Darren L.
1994-01-01
The first results of an axisymmetric magnetohydrodynamic (MHD) model of the interaction of an expanding cometary atmosphere with the solar wind are presented. The model assumes that far upstream the plasma flow lines are parallel to the magnetic field vector. The effects of mass loading and ion-neutral friction are taken into account by the governing equations, whcih are solved on an adaptively refined unstructured grid using a Monotone Upstream Centered Schemes for Conservative Laws (MUSCL)-type numerical technique. The combination of the adaptive refinement with the MUSCL-scheme allows the entire cometary atmosphere to be modeled, while still resolving both the shock and the near nucleus of the comet. The main findingsare the following: (1) A shock is formed approximately = 0.45 Mkm upstream of the comet (its location is controlled by the sonic and Alfvenic Mach numbers of the ambient solar wind flow and by the cometary mass addition rate). (2) A contact surface is formed approximately = 5,600 km upstream of the nucleus separating an outward expanding cometary ionosphere from the nearly stagnating solar wind flow. The location of the contact surface is controlled by the upstream flow conditions, the mass loading rate and the ion-neutral drag. The contact surface is also the boundary of the diamagnetic cavity. (3) A closed inner shock terminates the supersonic expansion of the cometary ionosphere. This inner shock is closer to the nucleus on dayside than on the nightside.
A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model
Mizzi, A. P.
2011-12-01
A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model Arthur P. Mizzi National Center for Atmospheric Research Boulder, CO 80307 303-497-8987 mizzi@ucar.edu Recently, there has been increased interest in hybrid variational data assimilation due to its ability to improve numerical weather forecast accuracy by incorporating ensemble error information into the data assimilation process (Buehner, 2010a, b; Wang 2010). In this paper, we introduce a GSI/ETKF regional hybrid (Mizzi, 2011). The GSI/ETKF regional hybrid uses a modified version of NOAA/EMC's GSI global hybrid (Wang, 2010) for the ensemble mean analysis and an ETKF (Bishop, et. al., 2001) to update the ensemble perturbations. We tested the GSI/ETKF regional hybrid by applying it to cycling experiments with WRF/ARW on a coarse-resolution domain covering the continental United States (CONUS) that: (i) compared different ETKF schemes, and (ii) reduced and held the number of ETKF observations constant. The results from those experiments showed that: (i) the ETKF scheme requiring the least amount of inflation provided the lowest 12-hr forecast RMSEs (ii) holding the number of ETKF observations constant removed the oscillation in the posterior ETKF ensemble spread noted by Bowler et al., (2008), and (iii) reducing the number of ETKF observations lowered the 12-hr forecast RMSEs. Presently, we are extending this work to a comparison of the GSI/ETKF regional hybrid with a GSI/LETKF regional hybrid based on the LETKF of Ott, et. al., (2004) and a GSI/EnKF regional hybrid based on the DART EnKF (Anderson et. al., 2009). Generally, the GSI/LETKF and GSI/EnKF schemes require less ensemble spread inflation compared to the GSI/ETKF scheme. Consequently, we expect the GSI/LETKF and GSI/EnKF schemes to provide lower 12-hr forecast RMSEs compared to the GSI/ETKF results. Our preliminary results are consistent with that supposition.
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…
Nisar, Ubaid Ahmed; Ashraf, Waqas; Qamar, Shamsul
In this article, one and two-dimensional hydrodynamical models of semiconductor devices are numerically investigated. The models treat the propagation of electrons in a semiconductor device as the flow of a charged compressible fluid. It plays an important role in predicting the behavior of electron flow in semiconductor devices. Mathematically, the governing equations form a convection-diffusion type system with a right hand side describing the relaxation effects and interaction with a self consistent electric field. The proposed numerical scheme is a splitting scheme based on the kinetic flux-vector splitting (KFVS) method for the hyperbolic step, and a semi-implicit Runge-Kutta method for the relaxation step. The KFVS method is based on the direct splitting of macroscopic flux functions of the system on the cell interfaces. The second order accuracy of the scheme is achieved by using MUSCL-type initial reconstruction and Runge-Kutta time stepping method. Several case studies are considered. For validation, the results of current scheme are compared with those obtained from the splitting scheme based on the NT central scheme. The effects of various parameters such as low field mobility, device length, lattice temperature and voltage are analyzed. The accuracy, efficiency and simplicity of the proposed KFVS scheme validates its generic applicability to the given model equations. A two dimensional simulation is also performed by KFVS method for a MESFET device, producing results in good agreement with those obtained by NT-central scheme.
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.
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.
A mixed finite element scheme for viscoelastic flows with XPP model
Xianhong Han; Xikui Li
2008-01-01
A mixed finite element formulation for viscoe-lastic flows is derived in this paper, in which the FIC (finite incremental calculus) pressure stabilization process and the DEVSS (discrete elastic viscous stress splitting) method using the Crank-Nicolson-based split are introduced within a general framework of the iterative version of the fractio-nal step algorithm. The SU (streamline-upwind) method is particularly chosen to tackle the convective terms in constitu-tive equations of viscoelastic flows. Thanks to the proposed scheme the finite elements with equal low-order interpola-tion approximations for stress-velocity-pressure variables can be successfully used even for viscoelastic flows with high Weissenberg numbers. The XPP (extended Pom-Pom) consti-tutive model for describing viscoelastic behaviors is particu-larly integrated into the proposed scheme. The numerical results for the 4:1 sudden contraction flow problem demons-trate prominent stability, accuracy and convergence rate of the proposed scheme in both pressure and stress distributions over the flow domain within a wide range of the Weissenberg number, particularly the capability in reproducing the results, which can be used to explain the "die swell" phenomenon observed in the polymer injection molding process.
Liu, Zhe; Lin, Lei; Xie, Lian; Gao, Huiwang
2016-10-01
To improve the efficiency of the terrain-following σ-coordinate non-hydrostatic ocean model, a partially implicit finite difference (PIFD) scheme is proposed. By using explicit terms instead of implicit terms to discretize the parts of the vertical dynamic pressure gradient derived from the σ-coordinate transformation, the coefficient matrix of the discrete Poisson equation that the dynamic pressure satisfies can be simplified from 15 diagonals to 7 diagonals. The PIFD scheme is shown to run stably when it is applied to simulate five benchmark cases, namely, a standing wave in a basin, a surface solitary wave, a lock-exchange problem, a periodic wave over a bar and a tidally induced internal wave. Compared with the conventional fully implicit finite difference (FIFD) scheme, the PIFD scheme produces simulation results of equivalent accuracy at only 40-60% of the computational cost. The PIFD scheme demonstrates strong applicability and can be easily implemented in σ-coordinate ocean models.
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.
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.
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.)