An optimal weighted-average congestion based pricing scheme for enhanced QoS

Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes under a single service class and multiple queues, and present a multi-layered pricing scheme. We propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. The pricing policy used depends on a weighted average queue length at each node. This helps in reducing frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using our scheme over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our approach exhibits a throughput improvement in the range of 34 to 69 percent in all cases studied (over all routes) over the above scheme.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

Anomalous behavior of hydrodynamic modes in the two dimensional shear flow of a granular material

The growth rates of the hydrodynamic modes in the homogeneous sheared state of a granular material are determined by solving the Boltzmann equation. The steady velocity distribution is considered to be the product of the Maxwell Boltzmann distribution and a Hermite polynomial expansion in the velocity components; this form is inserted into them Boltzmann equation and solved to obtain the coeificients of the terms in the expansion. The solution is obtained using an expansion in the parameter epsilon =(1 - e)(1/2), and terms correct to epsilon(4) are retained to obtain an approximate solution; the error due to the neglect of higher terms is estimated at about 5% for e = 0.7. A small perturbation is placed on the distribution function in the form of a Hermite polynomial expansion for the velocity variations and a Fourier expansion in the spatial coordinates: this is inserted into the Boltzmann equation and the growth rate of the Fourier modes is determined. It is found that in the hydrodynamic limit, the growth rates of the hydrodynamic modes in the flow direction have unusual characteristics. The growth rate of the momentum diffusion mode is positive, indicating that density variations are unstable in the limit k--> 0, and the growth rate increases proportional to kslash} k kslash}(2/3) in the limit k --> 0 (in contrast to the k(2) increase in elastic systems), where k is the wave vector in the flow direction. The real and imaginary parts of the growth rate corresponding to the propagating also increase proportional to kslash k kslash(2/3) (in contrast to the k(2) and k increase in elastic systems). The energy mode is damped due to inelastic collisions between particles. The scaling of the growth rates of the hydrodynamic modes with the wave vector I in the gradient direction is similar to that in elastic systems. (C) 2000 Elsevier Science B.V. All rights reserved.

Robust multivariable controllers for a tublar ammonia reactor

The specific objective of this paper is to develop multivariable controllers that would achieve asymptotic regulation in the presence of parameter variations and disturbance inputs for a tubular reactor used in ammonia synthesis. A ninth order state space model with three control inputs and two disturbance inputs is generated from the nonlinear distributed model using linearization and lumping approximations. Using this model, an approach for control system design is developed keeping in view the imperfections of the model and the measurability of the state variables. Specifically, the design of feedforward and robust integral controllers using state and output feedback is considered. Also, the design of robust multiloop proportional integral controllers is presented. Finally the performance of these controllers is evaluated through simulation.

Optimization of an ammonia reactor using regression analysis

This paper presents an optimization algorithm for an ammonia reactor based on a regression model relating the yield to several parameters, control inputs and disturbances. This model is derived from the data generated by hybrid simulation of the steady-state equations describing the reactor behaviour. The simplicity of the optimization program along with its ability to take into account constraints on flow variables make it best suited in supervisory control applications.

A delta13C record of late Quaternary climate change from tropical peats in southern India

STABLE-ISOTOPE ratios of carbon in soils or lake sediments1-3 and of oxygen and hydrogen in peats4,5 have been found to reflect past moisture variations and hence to provide valuable palaeoclimate records. Previous applications of the technique to peat have been restricted to temperate regions, largely because tropical climate variations are less pronounced, making them harder to resolve. Here we present a deltaC-13 record spanning the past 20 kyr from peats in the Nilgiri hills, southern India. Because the site is at high altitude (>2,000 m above sea level), it is possible to resolve a clear climate signal. We observe the key climate shifts that are already known to have occurred during the last glacial maximum (18 kyr ago) and the subsequent deglaciation. In addition, we observe an arid phase from 6 to 3.5 kyr ago, and a short, wet phase about 600 years ago. The latter appears to correspond to the Mediaeval Warm Period, which previously was believed to be confined to Europe and North America6,7. Our results therefore suggest that this event may have extended over the entire Northern Hemisphere.

Critical earthquake input power spectral density function models for engineering structures

The problem of determining optimal power spectral density models for earthquake excitation which satisfy constraints on total average power, zero crossing rate and which produce the highest response variance in a given linear system is considered. The solution to this problem is obtained using linear programming methods. The resulting solutions are shown to display a highly deterministic structure and, therefore, fail to capture the stochastic nature of the input. A modification to the definition of critical excitation is proposed which takes into account the entropy rate as a measure of uncertainty in the earthquake loads. The resulting problem is solved using calculus of variations and also within linear programming framework. Illustrative examples on specifying seismic inputs for a nuclear power plant and a tall earth dam are considered and the resulting solutions are shown to be realistic.

Systematic crystallographic investigation of hydrogen-bonded networks involving monohydrogen tartrate-amine complexes: Potential materials for nonlinear optics

Crystal structures of six binary salts involving aromatic amines as cations and hydrogen tartrates as anions are presented. The materials are 2,6-xylidinium-L-monohydrogen tartrate monohydrate, C12H18O6.5N, P22(1)2(1), a = 7.283(2) Angstrom, b = 17.030(2) Angstrom, c = 22.196(2) Angstrom, Z = 8; 2,6-xylidinium-D-dibenzoyl monohydrogen tartrate, C26H25O8N, P2(1), a = 7.906(1) Angstrom, b = 24.757(1) Angstrom, c = 13.166(1) Angstrom, beta = 105.01(1)degrees, Z = 4; 2,3-xylidinium-D-dibenzoyl monohydrogen tartrate monohydrate, C26H26O8.5N, P2(1), a = 7.837(1) Angstrom, b = 24.488(1) Angstrom, c = 13.763(1) Angstrom, beta = 105.69(1)degrees, Z = 4; 2-toluidinium-D-dibenzoyl monohydrogen tartrate, C25H23O8N, P2(1)2(1)2(1), a = 13.553(2) Angstrom, b = 15.869(3) Angstrom, c = 22.123(2) Angstrom, Z = 8; 3-toluidinium-D-dibenzoyl monohydrogen tartrate (1:1), C25H23O8N, P1, a = 7.916(3) Angstrom, b = 11.467(6) Angstrom, c = 14.203(8) Angstrom, alpha = 96.44(4)degrees, beta = 98.20(5)degrees, = 110.55(5)degrees, Z = 2; 3-toluidinium-D-dibenzoyl tartrate dihydrate (1:2), C32H36O10N, P1, a = 7.828(3) Angstrom, b = 8.233(1) Angstrom, c = 24.888(8) Angstrom, alpha = 93.98 degrees, beta = 94.58(3)degrees, = 89.99(2)degrees, Z = 2. An analysis of the hydrogen-bonding schemes in terms of crystal packing, stoichiometric variations, and substitutional variations in these materials provides insights to design hydrogen-bonded networks directed toward the engineering of crystalline nonlinear optical materials.

Robustness Study of a Dynamic Inversion Control Law for a High Performance Aircraft

In the design of °ight control system modeling uncertainties in the form of param-eter variations is one of the major problems. It is even more critical for high performance aircrafts,since such aircrafts are purposefully designed unstable to enhance their performance (especially ma-neuverability). Hence the °ight control system needs to be quite e®ective in both assuring accurate tracking of pilot commands, while simultaneously assuring overall stability of the aircraft. In addi-tion, the control system must also be su±ciently robust to cater for possible parameter variations and inaccuracies . The primary aim of this paper is to carry out a robustness study of a dynamic inversion based nonlinear control design for a high performance aircraft, which has been developed recently [1].

An optimal weighted-average congestion based pricing scheme for enhanced QoS, , LNCS 4882, 2007

Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes under a single service class and multiple queues, and present a multi-layered pricing scheme. We propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. The pricing policy used depends on a weighted average queue length at each node. This helps in reducing frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using our scheme over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our approach exhibits a throughput improvement in the range of 34 to 69 percent in all cases studied (over all routes) over the above scheme.

A Simple Charge Model for Symmetric Double-Gate MOSFETs Adapted to Gate-Oxide-Thickness Asymmetry

Surface-potential-based compact charge models for symmetric double-gate metal-oxide-semiconductor field-effect transistors (SDG-MOSFETs) are based on the fundamental assumption of having equal oxide thicknesses for both gates. However, for practical devices, there will always be some amount of asymmetry between the gate oxide thicknesses due to process variations and uncertainties, which can affect device performance significantly. In this paper, we propose a simple surface-potential-based charge model, which is applicable for tied double-gate MOSFETs having same gate work function but could have any difference in gate oxide thickness. The proposed model utilizes the unique so-far-unexplored quasi-linear relationship between the surface potentials along the channel. In this model, the terminal charges could be computed by basic arithmetic operations from the surface potentials and applied biases, and thus, it could be implemented in any circuit simulator very easily and extendable to short-channel devices. We also propose a simple physics-based perturbation technique by which the surface potentials of an asymmetric device could be obtained just by solving the input voltage equation of SDG devices for small asymmetry cases. The proposed model, which shows excellent agreement with numerical and TCAD simulations, is implemented in a professional circuit simulator through the Verilog-A interface and demonstrated for a 101-stage ring oscillator simulation. It is also shown that the proposed model preserves the source/drain symmetry, which is essential for RF circuit design.

Optimal multi-layered congestion based pricing schemes for enhanced QoS

Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes with multiple queues and multiple grades of service. We present a closed-loop multi-layered pricing scheme and propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. This is different from most adaptive pricing schemes in the literature that do not obtain a closed-loop state dependent pricing policy. The method that we propose finds optimal price levels that are functions of the queue lengths at individual queues. Further, we also propose a variant of the above scheme that assigns prices to incoming packets at each node according to a weighted average queue length at that node. This is done to reduce frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using both of our schemes over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our first scheme exhibits a throughput improvement in the range of 67-82% among all routes over the above scheme. (C) 2011 Elsevier B.V. All rights reserved.

Local Structural Differences in Homologous Proteins: Specificities in Different SCOP Classes

The constant increase in the number of solved protein structures is of great help in understanding the basic principles behind protein folding and evolution. 3-D structural knowledge is valuable in designing and developing methods for comparison, modelling and prediction of protein structures. These approaches for structure analysis can be directly implicated in studying protein function and for drug design. The backbone of a protein structure favours certain local conformations which include alpha-helices, beta-strands and turns. Libraries of limited number of local conformations (Structural Alphabets) were developed in the past to obtain a useful categorization of backbone conformation. Protein Block (PB) is one such Structural Alphabet that gave a reasonable structure approximation of 0.42 angstrom. In this study, we use PB description of local structures to analyse conformations that are preferred sites for structural variations and insertions, among group of related folds. This knowledge can be utilized in improving tools for structure comparison that work by analysing local structure similarities. Conformational differences between homologous proteins are known to occur often in the regions comprising turns and loops. Interestingly, these differences are found to have specific preferences depending upon the structural classes of proteins. Such class-specific preferences are mainly seen in the all-beta class with changes involving short helical conformations and hairpin turns. A test carried out on a benchmark dataset also indicates that the use of knowledge on the class specific variations can improve the performance of a PB based structure comparison approach. The preference for the indel sites also seem to be confined to a few backbone conformations involving beta-turns and helix C-caps. These are mainly associated with short loops joining the regular secondary structures that mediate a reversal in the chain direction. Rare beta-turns of type I' and II' are also identified as preferred sites for insertions.

Dynamics of the North American continent

The forces that cause deformation of western North America have been debated for decades. Recent studies, primarily based on analysis of crustal stresses in the western United States, have suggested that the deformation of the region is mainly controlled by gravitational potential energy (GPE) variations and boundary loads, with basal tractions due to mantle flow playing a relatively minor role. We address these issues by modelling the deviatoric stress field over western North America from a 3-D finite element mantle circulation model with lateral viscosity variations. Our approach takes into account the contribution from both topography and shallow lithosphere structure (GPE) as well as that from deeper mantle flow in one single model, as opposed to separate lithosphere and circulation models, as has been done so far. In addition to predicting the deviatoric stresses we also jointly fit the constraints of geoid, dynamic topography and plate motion both globally and over North America, in order to ensure that the forces that arise in our models are dynamically consistent. We examine the sensitivity of the dynamic models to different lateral viscosity variations. We find that circulation models that include upper mantle slabs yield a better fit to observed plate velocities. Our results indicate that a model of GPE variations coupled with mantle convection gives the best fit to the observational constraints. We argue that although GPE variations control a large part of the deformation of the western United States, deeper mantle tractions also play a significant role. The average deviatoric stress magnitudes in the western United States range 30-40 MPa. The cratonic region exhibits higher coupling to mantle flow than the rest of the continent. We find that a relatively strong San Andreas fault gives a better fit to the observational constraints, especially that of plate velocity in western North America.