No-reference image quality assessment using modified extreme learning machine classifier

In this paper, we present a machine learning approach to measure the visual quality of JPEG-coded images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity (HVS) factors such as edge amplitude, edge length, background activity and background luminance. Image quality assessment involves estimating the functional relationship between HVS features and subjective test scores. The quality of the compressed images are obtained without referring to their original images ('No Reference' metric). Here, the problem of quality estimation is transformed to a classification problem and solved using extreme learning machine (ELM) algorithm. In ELM, the input weights and the bias values are randomly chosen and the output weights are analytically calculated. The generalization performance of the ELM algorithm for classification problems with imbalance in the number of samples per quality class depends critically on the input weights and the bias values. Hence, we propose two schemes, namely the k-fold selection scheme (KS-ELM) and the real-coded genetic algorithm (RCGA-ELM) to select the input weights and the bias values such that the generalization performance of the classifier is a maximum. Results indicate that the proposed schemes significantly improve the performance of ELM classifier under imbalance condition for image quality assessment. The experimental results prove that the estimated visual quality of the proposed RCGA-ELM emulates the mean opinion score very well. The experimental results are compared with the existing JPEG no-reference image quality metric and full-reference structural similarity image quality metric.

ELISA: An Estimated Load Information Scheduling Algorithm for Distributed Computing Systems

In this paper, we present a decentralized dynamic load scheduling/balancing algorithm called ELISA (Estimated Load Information Scheduling Algorithm) for general purpose distributed computing systems. ELISA uses estimated state information based upon periodic exchange of exact state information between neighbouring nodes to perform load scheduling. The primary objective of the algorithm is to cut down on the communication and load transfer overheads by minimizing the frequency of status exchange and by restricting the load transfer and status exchange within the buddy set of a processor. It is shown that the resulting algorithm performs almost as well as a perfect information algorithm and is superior to other load balancing schemes based on the random sharing and Ni-Hwang algorithms. A sensitivity analysis to study the effect of various design parameters on the effectiveness of load balancing is also carried out. Finally, the algorithm's performance is tested on large dimensional hypercubes in the presence of time-varying load arrival process and is shown to perform well in comparison to other algorithms. This makes ELISA a viable and implementable load balancing algorithm for use in general purpose distributed computing systems.

Supersonic flutter of composite skin panels of repeated-sublaminate layup

In high-speed aerospace vehicles, supersonic flutter is a well-known phenomenon of dynamic instability to which external skin panels are prone. In theory, the instability stage is expressed by the 'flutter critical parameter' Q(crit), which is a function of the stiffness-, and dynamic pressure parameters. For a composite skin panel, Q(crit) can be maximised by lay-up optimisation. Repeated-sublaminate lay-up schemes possess good potential for economical lay-up optimisation because the corresponding effort is limited to a family of sublaminates of few layers only. When Q(crit) is obtained for all sublaminates of a family, and the sublaminates ranked accordingly, the resulting ranking reveals not only the optimum lay-up, but also the near-optimum lay-ups, which are useful design alternatives, and the inferior lay-ups which should be avoided. In this paper, we examine sublaminate-ranking characteristics for a composite panel prone to supersonic flutter. In particular, we consider a simple supported midplane-symmetrical rectangular panel of typical aspect ratio alpha and flow angle psi, and for four-layered sublaminates, obtain the Q(crit)-based rankings for a wide range of the number of repeats, r. From the rankings, we find that an optimum lay-up can exist for which the outermost layer is oriented wide of, rather than along, the flow. Furthermore, for many lay-ups other than the optimum and the inferior, we see that as r increases, Q(crit) undergoes significant change in the course of converging. To reconcile these findings, eigenvalue-coalescence characteristics are discussed in detail for specific cases.

Energy-Efficient Decentralized Cooperative Routing in Wireless Networks

Wireless adhoc networks transmit information from a source to a destination via multiple hops in order to save energy and, thus, increase the lifetime of battery-operated nodes. The energy savings can be especially significant in cooperative transmission schemes, where several nodes cooperate during one hop to forward the information to the next node along a route to the destination. Finding the best multi-hop transmission policy in such a network which determines nodes that are involved in each hop, is a very important problem, but also a very difficult one especially when the physical wireless channel behavior is to be accounted for and exploited. We model the above optimization problem for randomly fading channels as a decentralized control problem - the channel observations available at each node define the information structure, while the control policy is defined by the power and phase of the signal transmitted by each node. In particular, we consider the problem of computing an energy-optimal cooperative transmission scheme in a wireless network for two different channel fading models: (i) slow fading channels, where the channel gains of the links remain the same for a large number of transmissions, and (ii) fast fading channels, where the channel gains of the links change quickly from one transmission to another. For slow fading, we consider a factored class of policies (corresponding to local cooperation between nodes), and show that the computation of an optimal policy in this class is equivalent to a shortest path computation on an induced graph, whose edge costs can be computed in a decentralized manner using only locally available channel state information (CSI). For fast fading, both CSI acquisition and data transmission consume energy. Hence, we need to jointly optimize over both these; we cast this optimization problem as a large stochastic optimization problem. We then jointly optimize over a set of CSI functions of the local channel states, and a c- - orresponding factored class of control poli.

Implicit and multigrid procedures for steady-state computations with upwind algorithms

A computational study for the convergence acceleration of Euler and Navier-Stokes computations with upwind schemes has been conducted in a unified framework. It involves the flux-vector splitting algorithms due to Steger-Warming and Van Leer, the flux-difference splitting algorithms due to Roe and Osher and the hybrid algorithms, AUSM (Advection Upstream Splitting Method) and HUS (Hybrid Upwind Splitting). Implicit time integration with line Gauss-Seidel relaxation and multigrid are among the procedures which have been systematically investigated on an individual as well as cumulative basis. The upwind schemes have been tested in various implicit-explicit operator combinations such that the optimal among them can be determined based on extensive computations for two-dimensional flows in subsonic, transonic, supersonic and hypersonic flow regimes. In this study, the performance of these implicit time-integration procedures has been systematically compared with those corresponding to a multigrid accelerated explicit Runge-Kutta method. It has been demonstrated that a multigrid method employed in conjunction with an implicit time-integration scheme yields distinctly superior convergence as compared to those associated with either of the acceleration procedures provided that effective smoothers, which have been identified in this investigation, are prescribed in the implicit operator.

A pseudo-dynamical systems approach to a class of inverse problems in engineering

A pseudo-dynamical approach for a class of inverse problems involving static measurements is proposed and explored. Following linearization of the minimizing functional associated with the underlying optimization problem, the new strategy results in a system of linearized ordinary differential equations (ODEs) whose steady-state solutions yield the desired reconstruction. We consider some explicit and implicit schemes for integrating the ODEs and thus establish a deterministic reconstruction strategy without an explicit use of regularization. A stochastic reconstruction strategy is then developed making use of an ensemble Kalman filter wherein these ODEs serve as the measurement model. Finally, we assess the numerical efficacy of the developed tools against a few linear and nonlinear inverse problems of engineering interest.

Analysis Of Curved Laminated Beams Of Bimodulus Composite-Materials

Composite materials exhibiting different moduli in tension and in compression, commonly called as bimodular composites are being used in many engineering fields. A finite element analysis is carried out for small deflection static behavior of laminated curved beams of bi modulus materials for both solid and hollow circular cross-sections using an iterative procedure. The finite element has 16 d.o.f. and uses the displacement field in terms of first order Hermite in terpolation polynomials. The neutral surface, i.e. the locus of points having zero axial strain is found to vary drastically depending on the loading, lay up schemes and radius of curvature. As il lustrations, plots of the cross-sections of the ruled neutral-surface are presented for some of the investigated cases. Using this element a few problems of curved laminated beams of bimodulus materials are solved for both solid and hollow circular cross-sections.

Mesh-free approximations via the error reproducing kernel method and applications to nonlinear systems developing shocks

Error estimates for the error reproducing kernel method (ERKM) are provided. The ERKM is a mesh-free functional approximation scheme [A. Shaw, D. Roy, A NURBS-based error reproducing kernel method with applications in solid mechanics, Computational Mechanics (2006), to appear (available online)], wherein a targeted function and its derivatives are first approximated via non-uniform rational B-splines (NURBS) basis function. Errors in the NURBS approximation are then reproduced via a family of non-NURBS basis functions, constructed using a polynomial reproduction condition, and added to the NURBS approximation of the function obtained in the first step. In addition to the derivation of error estimates, convergence studies are undertaken for a couple of test boundary value problems with known exact solutions. The ERKM is next applied to a one-dimensional Burgers equation where, time evolution leads to a breakdown of the continuous solution and the appearance of a shock. Many available mesh-free schemes appear to be unable to capture this shock without numerical instability. However, given that any desired order of continuity is achievable through NURBS approximations, the ERKM can even accurately approximate functions with discontinuous derivatives. Moreover, due to the variation diminishing property of NURBS, it has advantages in representing sharp changes in gradients. This paper is focused on demonstrating this ability of ERKM via some numerical examples. Comparisons of some of the results with those via the standard form of the reproducing kernel particle method (RKPM) demonstrate the relative numerical advantages and accuracy of the ERKM.

Simple new PWM patterns for thyristor three-phase AC/DC convertors

Thyristor forced commutated AC/DC convertors are useful for improving the power factor and waveform of AC-side line current. These are controlled through pulse-width modulation schemes for best performance. However, the 3-phase versions impose restrictions on the PWM strategies that can be implemented for excellent harmonic rejection. This paper presents new PWM control strategies for the 3-phase converters and compares them along with the conventional 4-pulse PWM strategy for harmonic elimination. Finally, two new PWM strategies are shown to be the best, for which oscillograms are presented from actual implementation.

Collision avoidance between UAV clusters using swarm intelligence techniques

In this article, several basic swarming laws for Unmanned Aerial Vehicles (UAVs) are developed for both two-dimensional (2D) plane and three-dimensional (3D) space. Effects of these basic laws on the group behaviour of swarms of UAVs are studied. It is shown that when cohesion rule is applied an equilibrium condition is reached in which all the UAVs settle at the same altitude on a circle of constant radius. It is also proved analytically that this equilibrium condition is stable for all values of velocity and acceleration. A decentralised autonomous decision-making approach that achieves collision avoidance without any central authority is also proposed in this article. Algorithms are developed with the help of these swarming laws for two types of collision avoidance, Group-wise and Individual, in 2D plane and 3D space. Effect of various parameters are studied on both types of collision avoidance schemes through extensive simulations.

Comparison of Rectangular and Polar Quantizers in Digital Holography

Complex amplitude encoded in any digital hologram must undergo quantization, usually in either polar or rectangular format . In this paper these two schemes are compared under the constraints and conditions inherent in digital holography . For Fourier transform holograms when the spectrum is levelled through phase coding, the rectangular format is shown to be optimal . In the absence of phase coding, and also if the amplitude spectrum has a large dynamic range, the polar format may be preferable .

A global convergence criterion for discrete-time multivariable adaptive systems

The paper deals with the basic problem of adjusting a matrix gain in a discrete-time linear multivariable system. The object is to obtain a global convergence criterion, i.e. conditions under which a specified error signal asymptotically approaches zero and other signals in the system remain bounded for arbitrary initial conditions and for any bounded input to the system. It is shown that for a class of up-dating algorithms for the adjustable gain matrix, global convergence is crucially dependent on a transfer matrix G(z) which has a simple block diagram interpretation. When w(z)G(z) is strictly discrete positive real for a scalar w(z) such that w-1(z) is strictly proper with poles and zeros within the unit circle, an augmented error scheme is suggested and is proved to result in global convergence. The solution avoids feeding back a quadratic term as recommended in other schemes for single-input single-output systems.

Technicolor

The need for reexamination of the standard model of strong, weak, and electromagnetic interactions is discussed, especially with regard to 't Hooft's criterion of naturalness. It has been argued that theories with fundamental scalar fields tend to be unnatural at relatively low energies. There are two solutions to this problem: (i) a global supersymmetry, which ensures the absence of all the naturalness-violating effects associated with scalar fields, and (ii) composite structure of the scalar fields, which starts showing up at energy scales where unnatural effects would otherwise have appeared. With reference to the second solution, this article reviews the case for dynamical breaking of the gauge symmetry and the technicolor scheme for the composite Higgs boson. This new interaction, of the scaled-up quantum chromodynamic type, keeps the new set of fermions, the technifermions, together in the Higgs particles. It also provides masses for the electroweak gauge bosons W± and Z0 through technifermion condensate formation. In order to give masses to the ordinary fermions, a new interaction, the extended technicolor interaction, which would connect the ordinary fermions to the technifermions, is required. The extended technicolor group breaks down spontaneously to the technicolor group, possibly as a result of the "tumbling" mechanism, which is discussed here. In addition, the author presents schemes for the isospin breaking of mass matrices of ordinary quarks in the technicolor models. In generalized technicolor models with more than one doublet of technifermions or with more than one technicolor sector, we have additional low-lying degrees of freedom, the pseudo-Goldstone bosons. The pseudo-Goldstone bosons in the technicolor model of Dimopoulos are reviewed and their masses computed. In this context the vacuum alignment problem is also discussed. An effective Lagrangian is derived describing colorless low-lying degrees of freedom for models with two technicolor sectors in the combined limits of chiral symmetry and large number of colors and technicolors. Finally, the author discusses suppression of flavor-changing neutral currents in the extended technicolor models.

A Simple Multiple Pulsewidth Modulated AC Choppe

A simple multiple pulsewidth modulated (MPWM) ac chopper using power transistors for 3-ý power control is discussed. 120ý chopping period is used for main transistors so that the circuit can accommodate resistive and lagging or leading power factor loads. Only 1-ý sensing is used for 3-ý control. An alternate economical power and control schemes for 3-ý MPWM ac choppers suitable only for resistive loads is also suggested. The experimental results for 12 choppings per cycle are given.

An Adaptive Scheme for Learning the Probability Threshold in Pattern Recognition

The statistical minimum risk pattern recognition problem, when the classification costs are random variables of unknown statistics, is considered. Using medical diagnosis as a possible application, the problem of learning the optimal decision scheme is studied for a two-class twoaction case, as a first step. This reduces to the problem of learning the optimum threshold (for taking appropriate action) on the a posteriori probability of one class. A recursive procedure for updating an estimate of the threshold is proposed. The estimation procedure does not require the knowledge of actual class labels of the sample patterns in the design set. The adaptive scheme of using the present threshold estimate for taking action on the next sample is shown to converge, in probability, to the optimum. The results of a computer simulation study of three learning schemes demonstrate the theoretically predictable salient features of the adaptive scheme.