A minimum entropy based switched adaptive predictor for lossless compression of images

The gradient adjusted predictor (GAP) uses seven fixed slope quantization bins and a predictor is associated with each bin, for prediction of pixels. The slope bin boundary in the same appears to be fixed without employing a criterion function. This paper presents a technique for slope classification that results in slope bins which are optimum for a given set of images. It also presents two techniques that find predictors which are statistically optimal for each of the slope bins. Slope classification and the predictors associated with the slope bins are obtained off-line. To find a representative predictor for a bin, a set of least-squares (LS) based predictors are obtained for all the pixels belonging to that bin. A predictor, from the set of predictors, that results in the minimum prediction error energy is chosen to represent the bin. Alternatively, the predictor is chosen, from the same set, based on minimum entropy as the criterion. Simulation results, of the proposed method have shown a significant improvement in the compression performance as compared to the GAP. Computational complexity of the proposed method , excluding the training process, is of the same order as that of GAP.     

Simplified method of sizing and life cycle cost assessment of building integrated photovoltaic system

This paper presents methodology to evaluate size and cost of PV power system components. The simplified mathematical expressions are given for sizing of PV system components. The PV array size is determined based on daily electrical load (kWh/day) and number of sunshine hours on optimally tilted surface specific to the country. Based on life cycle cost (LCC) analysis, capital cost (US$/kW_P) and unit cost of electricity (US$/kWh) were determined for PV systems such as stand-alone PV (SAPV) and building integrated PV (BIPV). The mitigation of CO₂ emission, carbon credit and energy payback time (EPBT) of PV system are presented in this paper. Effect of carbon credit on the economics of PV system showed reduction in unit cost of electricity by 17-19% and 21-25% for SAPV and BIPV systems, respectively. This methodology was illustrated using actual case study on 2.32 kW_P PV system located in New Delhi (India).     

Advection transport model of vortex enhanced heat transfer

The present investigation is an analysis to predict the kinematic behavior of a Lagrangian fluid particle and the associated enhancement in advection heat transfer in vortex dominated channel flows. The vortex systems considered are two and four parallel vortex filaments in different configurations, subjected to external translation and pulsation. Such vortex systems are typical of the kind generated by the vortex generators mounted on channel walls of fin-tube and fin-plate heat exchangers. The method of analysis is efficient in predicting the intensity of mixing in the flow field and provides a quantitative estimate of advection heat transfer due to different configurations of the vortex systems. The predictions are primarily based on an analytical approach and hence offer quantification of advection requiring reduced computational cost as compared to the actual numerical solutions of the flow and temperature fields.     

An Algebraic Technique for Reliability Evaluation

An algebraic technique is proposed to obtain a simplified reliability expression of a general system. A success expression which directly gives the reliability expression, is formed and simplified by the procedure. The technique is equally efficient for simple and complex systems; yields computationally efficient reliability expressions; is routine (no decision making); yields an expression having a minimum number of product terms; and is easier than many existing techniques.     

Heat transfer in a viscoelastic boundary layer flow through a porous medium

This paper examines the viscoelastic fluid flow and heat transfer characteristics in a saturated porous medium over an impermeable stretching surface with frictional heating and internal heat generation or absorption. The heat transfer analysis has been carried out for two different heating processes, namely (i) with prescribed surface temperature (PST-case) and (ii) prescribed surface heat flux (PHF-case). The governing equations for the boundary layer flow problem result similar solutions. For the specified five boundary conditions, it is not possible to solve directly the resulting sixth-order nonlinear ordinary differential equation. For the present incompressible boundary layer flow problem with constant physical parameters, the momentum equation is decoupled from the energy equation. Two closed–form solutions for the momentum equation are obtained and identified the realistic solution of the physical problem. Exact solution for the velocity field and the skin-friction are obtained. Also, the solution for the temperature and the heat transfer characteristics are obtained in terms of Kummers function. Asymptotic results for the temperature function for large Prandtl numbers are presented. The work due to deformation in the energy equation, which is essential and escaped from the attention of researchers while formulating the visco-elastic boundary layer flow problems, is considered. Drastic variation in the values of heat transfer coefficient is observed when the work due to deformation is ignored.The authors would like to thank the reviewers for their valuable comments/ suggestions to improve the clarity of the paper.     

Characterizing Confluence by Rewrite Closure and Right Ground Term Rewrite Systems

Just as saturation under an appropriate superposition calculus leads to a convergent presentation of a given equational theory, saturation under a suitable chaining calculus gives, what we call, a rewrite closure. We present a theorem that characterizes confluence of (possibly nonterminating) term rewrite systems that admit a rewrite closure presentation, in terms of local confluence of a related terminating term rewrite system and joinability inclusion between these two rewrite systems. Using constraints to avoid variable chaining, we obtain a finite and computable rewrite closure presentation for right ground systems. This gives an alternate method to decide the reachability and joinability properties for right ground systems. The characterization of confluence, combined with the rewrite closure presentation, is used to obtain a decision procedure for confluence of right ground systems (this problem has been open for quite some time [8]), and a simple decision procedure for the unification problem of confluent right ground systems (result recently obtained in [17). An EXPTIME-hardness result is also proved for reachability and confluence of right ground systems.Research of the first author was supported in part by the Spanish CICYT project MAVERISH ref.TIC2001-2476-C03-01.Research of the second author was supported in part by NSF grant CCR-ITR-0326540. Research of the third author was supported in part by NSF grants CCR-0306475 and DUE-0313880.     

Patching Processor Design Errors with Programmable Hardware

Equipping processors with programmable hardware to patch design errors lets manufacturers release regular hardware patches, avoiding costly chip recalls and potentially speeding time to market. For each error detected, the manufacturer creates a fingerprint, which the customer uses to program the hardware. The hardware watches for error conditions; when they arise, it takes action to avoid the error. Overall, our scheme enables an exciting new environment where hardware design errors can be handled as easily as system software bugs, by applying a patch to the hardware     

Hybrid Verification of Protocol Bridges

It's usually necessary to apply formal verification on very small modules or else be content with bounded proofs on realistically large modules. But there is no denying that despite its capacity problems, formal verification has its strengths and utility and is a complementary technique to simulation. Used judiciously, simulation and formal techniques can complement each other's strengths, thereby balancing their respective weaknesses. There are different ways to combine these two techniques. In this article, we present two case studies of the application of one such technique: the hybrid verification of a serial protocol. We chose this example because of serial protocols' added complexity compared to parallel protocols. Both case studies involve the same serial protocol (I²C) but demonstrate different aspects of its verification. Selection of the same protocol in both case studies also demonstrates the tremendous value of reuse in formal verification.     

Synthesis of Stabilizing Antiwindup Controllers Using Piecewise Quadratic Lyapunov Functions

We consider the problem of antiwindup controller synthesis based on the general antiwindup framework presented in Kothare (Automatica, vol. 30, no. 12, pp. 1869-1883, 1994) applicable to linear time-invariant systems (LTI) subject to a saturating actuator. Our synthesis approach takes advantage of the fact that the antiwindup system is a piecewise affine system and thus, we can utilize piecewise quadratic Lyapunov function theory Johansson and Rantzer (IEEE Trans. Autom. Control, vol. 43, no. 4, pp. 555-559, Apr. 1998), Rantzer and Johansson (IEEE Trans. Autom. Control, vol. 45, no. 4, pp. 629-637, Apr. 2000), and Johansson (Proc. 14th World Congr., Beijing, China, 1999, pp. 521-5260) to determine a stabilizing antiwindup control law. The synthesis problem is expressed in terms of bilinear matrix inequalities (BMIs) and is solved using an iterative approach as well as using commercial software. The performance of the system is optimized by minimizing an upper bound on the induced gain of the system. The proposed approach is demonstrated using examples.     

Improved Decision Neural Network (IDNN) based consensus method to solve a multi-objective group decision making problem

Multi-criterion frameworks involving several subjective and quantitative factors that allow the complexity of Group Decision Making (GDM) to get worsen, especially for those problems which are having strategic dimensions. Recently, integration of multi-attribute utility theory (MAUT) and feed-forward neural network have been studied with a view to facilitate the automation of GDM. In this paper Improved Decision Neural Network (IDNN) based methodology has been developed to solve the multi-criterion decision problem in GDM. Reductions in the training data set, exploitation of indirect methods like multiplicative preference relation during the training process, and reduced number of iterations to map the MAUF are the advantages of this novel methodology. In this research, a soft consensus based group decision making methodology under linguistic assessments have been adopted for consensus forming among the groups.