Lenient Execution and Concurrent Execution of Re-entrant Routines: Efficient Implementation in Data Flow Systems

Implementation details of efficient schemes for lenient execution and concurrent execution of re-entrant routines in a data flow model have been discussed in this paper. The proposed schemes require no extra hardware support and utilise the existing hardware resources such as the Matching Unit and Memory Network Interface, effectively to achieve the above mentioned goals.

Performance Analysis of User Selected Subband Channel Quality Indicator Feedback Scheme of LTE

Frequency-domain scheduling and rate adaptation have helped next generation orthogonal frequency division multiple access (OFDMA) based wireless cellular systems such as Long Term Evolution (LTE) achieve significantly higher spectral efficiencies. To overcome the severe uplink feedback bandwidth constraints, LTE uses several techniques to reduce the feedback required by a frequency-domain scheduler about the channel state information of all subcarriers of all users. In this paper, we analyze the throughput achieved by the User Selected Subband feedback scheme of LTE. In it, a user feeds back only the indices of the best M subbands and a single 4-bit estimate of the average rate achievable over all selected M subbands. In addition, we compare the performance with the subband-level feedback scheme of LTE, and highlight the role of the scheduler by comparing the performances of the unfair greedy scheduler and the proportional fair (PF) scheduler. Our analysis sheds several insights into the working of the feedback reduction techniques used in LTE.

Composite material and piezoelectric coefficient uncertainty effects on structural health monitoring using feedback control gains as damage indicators

This article addresses uncertainty effect on the health monitoring of a smart structure using control gain shifts as damage indicators. A finite element model of the smart composite plate with surface-bonded piezoelectric sensors and actuators is formulated using first-order shear deformation theory and a matrix crack model is integrated into the finite element model. A constant gain velocity/position feedback control algorithm is used to provide active damping to the structure. Numerical results show that the response of the structure is changed due to matrix cracks and this change can be compensated by actively tuning the feedback controller. This change in control gain can be used as a damage indicator for structural health monitoring. Monte Carlo simulation is conducted to study the effect of material uncertainty on the damage indicator by considering composite material properties and piezoelectric coefficients as independent random variables. It is found that the change in position feedback control gain is a robust damage indicator.

A Flat Concurrent Prolog compiler for PARAM

We describe a compiler for the Flat Concurrent Prolog language on a message passing multiprocessor architecture. This compiler permits symbolic and declarative programming in the syntax of Guarded Horn Rules, The implementation has been verified and tested on the 64-node PARAM parallel computer developed by C-DAC (Centre for the Development of Advanced Computing, India), Flat Concurrent Prolog (FCP) is a logic programming language designed for concurrent programming and parallel execution, It is a process oriented language, which embodies dataflow synchronization and guarded-command as its basic control mechanisms. An identical algorithm is executed on every processor in the network, We assume regular network topologies like mesh, ring, etc, Each node has a local memory, The algorithm comprises of two important parts: reduction and communication, The most difficult task is to integrate the solutions of problems that arise in the implementation in a coherent and efficient manner. We have tested the efficacy of the compiler on various benchmark problems of the ICOT project that have been reported in the recent book by Evan Tick, These problems include Quicksort, 8-queens, and Prime Number Generation, The results of the preliminary tests are favourable, We are currently examining issues like indexing and load balancing to further optimize our compiler.

Nonlinear dynamics and chaotic motions in feedback-controlled two- and three-degree-of-freedom robots

The dynamics of a feedback-controlled rigid robot is most commonly described by a set of nonlinear ordinary differential equations. In this paper we analyze these equations, representing the feedback-controlled motion of two- and three-degrees-of-freedom rigid robots with revolute (R) and prismatic (P) joints in the absence of compliance, friction, and potential energy, for the possibility of chaotic motions. We first study the unforced or inertial motions of the robots, and show that when the Gaussian or Riemannian curvature of the configuration space of a robot is negative, the robot equations can exhibit chaos. If the curvature is zero or positive, then the robot equations cannot exhibit chaos. We show that among the two-degrees-of-freedom robots, the PP and the PR robot have zero Gaussian curvature while the RP and RR robots have negative Gaussian curvatures. For the three-degrees-of-freedom robots, we analyze the two well-known RRP and RRR configurations of the Stanford arm and the PUMA manipulator respectively, and derive the conditions for negative curvature and possible chaotic motions. The criteria of negative curvature cannot be used for the forced or feedback-controlled motions. For the forced motion, we resort to the well-known numerical techniques and compute chaos maps, Poincare maps, and bifurcation diagrams. Numerical results are presented for the two-degrees-of-freedom RP and RR robots, and we show that these robot equations can exhibit chaos for low controller gains and for large underestimated models. From the bifurcation diagrams, the route to chaos appears to be through period doubling.

Role of feedback in mammalian vision: a new hypothesis and a computational model

This paper presents a novel hypothesis on the function of massive feedback pathways in mammalian visual systems. We propose that the cortical feature detectors compete not for the right to represent the output at a point, but for exclusive rights to abstract and represent part of the underlying input. Feedback can do this very naturally. A computational model that implements the above idea for the problem of line detection is presented and based on that we suggest a functional role for the thalamo-cortical loop during perception of lines. We show that the model successfully tackles the so called Cross problem. Based on some recent experimental results, we discuss the biological plausibility of our model. We also comment on the relevance of our hypothesis (on the role of feedback) to general sensory information processing and recognition. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

The requirements for Ca2+, protein phosphorylation and concurrent protein synthesis for zeatin signaling of acidic chitinase transcript accumulation in Cucumis sativus L

We have previously reported that both Ca2+ and staurosporine-sensitive protein kinase(s) are involved in the cytokinin zeatin induction of cucumber chitinase activity and its protein content (Barwe et al. 2001). To further characterize signal transduction events involved in this cytokinin induction of chitinase gene expression, Northern hybridizations of total RNAs prepared from excised, dark-grown cucumber cotyledons treated with cytokinins and/or various agonists and antagonists of signal transduction components, were carried out using a cucumber acidic chitinase (CACHT) cDNA probe (Metraux et al. 1989). CACHT mRNA increased by approximately 5- to 6-fold in response to exogenous zeatin (Z), zeatin riboside (ZR), and benzyladenine (BA) treatment, but failed to accumulate in response to kinetin (K). Among the cytokinins tested, Z was most effective. The Z-induced accumulation of CACHT mRNA was inhibited by a plasma membrane Ca2+ channel blocker verapamil. Treatment of cotyledons with exogenous CaCl2 and calcium ionophore A23187 in the presence and absence of cytokinin enhanced CACHT mRNA accumulation. These two observations suggest the participation of extracellular calcium in signaling Z-induction. Furthermore, the presence of staurosporine (an inhibitor of protein kinase) in Z treatment reduced CACHT mRNA, suggesting the involvement of phosphorylation of one or more cellular proteins. In addition, we provide evidence that the Z-induction of CACHT mRNA is blocked by protein synthesis inhibitor cycloheximide treatment. Taken together, these results suggest that Ca2+ influx from extracellular space, protein phosphorylation, and concurrent protein synthesis events participate in cytokinin signaling during Z-induced CACHT transcript accumulation.

Haptic Feedback for Injecting Biological Cells using Miniature Compliant Mechanisms

We present a real-time haptics-aided injection technique for biological cells using miniature compliant mechanisms. Our system consists of a haptic robot operated by a human hand, an XYZ stage for micro-positioning, a camera for image capture, and a polydimethylsiloxane (PDMS) miniature compliant device that serves the dual purpose of an injecting tool and a force-sensor. In contrast to existing haptics-based micromanipulation techniques where an external force sensor is used, we use visually captured displacements of the compliant mechanism to compute the applied and reaction forces. The human hand can feel the magnified manipulation force through the haptic device in real-time while the motion of the human hand is replicated on the mechanism side. The images are captured using a camera at the rate of 30 frames per second for extracting the displacement data. This is used to compute the forces at the rate of 30 Hz. The force computed in this manner is sent at the rate of 1000 Hz to ensure stable haptic interaction. The haptic cell-manipulation system was tested by injecting into a zebrafish egg cell after validating the technique at a size larger than that of the cell.

Tracking analysis of an LMS decision feedback equalizer for a wireless channel

We consider a time varying wireless fading channel, equalized by an LMS Decision Feedback equalizer (DFE). We study how well this equalizer tracks the optimal MMSEDFE (Wiener) equalizer. We model the channel by an Autoregressive (AR) process. Then the LMS equalizer and the AR process are jointly approximated by the solution of a system of ODEs (ordinary differential equations). Using these ODEs, we show via some examples that the LMS equalizer moves close to the instantaneous Wiener filter after initial transience. We also compare the LMS equalizer with the instantaneous optimal DFE (the commonly used Wiener filter) designed assuming perfect previous decisions and computed using perfect channel estimate (we will call it as IDFE). We show that the LMS equalizer outperforms the IDFE almost all the time after initial transience.

LMS versus Wiener filter for a decision feedback equalizer

In this paper we study an LMS-DFE. We use the ODE framework to show that the LMS-DFE attractors are close to the true DFE Wiener filter (designed considering the decision errors) at high SNR. Therefore, via LMS one can obtain a computationally efficient way to obtain the true DFE Wiener filter under high SNR. We also provide examples to show that the DFE filter so obtained can significantly outperform the usual DFE Wiener filter (designed assuming perfect decisions) at all practical SNRs. In fact, the performance improvement is very significant even at high SNRs (up to 50%), where the popular Wiener filter designed with perfect decisions, is believed to be closer to the optimal one.

Swarm intelligence algorithms for integrated optimization of piezoelectric actuator and sensor placement and feedback gains

Swarm intelligence algorithms are applied for optimal control of flexible smart structures bonded with piezoelectric actuators and sensors. The optimal locations of actuators/sensors and feedback gain are obtained by maximizing the energy dissipated by the feedback control system. We provide a mathematical proof that this system is uncontrollable if the actuators and sensors are placed at the nodal points of the mode shapes. The optimal locations of actuators/sensors and feedback gain represent a constrained non-linear optimization problem. This problem is converted to an unconstrained optimization problem by using penalty functions. Two swarm intelligence algorithms, namely, Artificial bee colony (ABC) and glowworm swarm optimization (GSO) algorithms, are considered to obtain the optimal solution. In earlier published research, a cantilever beam with one and two collocated actuator(s)/sensor(s) was considered and the numerical results were obtained by using genetic algorithm and gradient based optimization methods. We consider the same problem and present the results obtained by using the swarm intelligence algorithms ABC and GSO. An extension of this cantilever beam problem with five collocated actuators/sensors is considered and the numerical results obtained by using the ABC and GSO algorithms are presented. The effect of increasing the number of design variables (locations of actuators and sensors and gain) on the optimization process is investigated. It is shown that the ABC and GSO algorithms are robust and are good choices for the optimization of smart structures.