PES News

This paper presents a new method for the generation of a reference voltage for a dynamic voltage restorer (DVR). These voltages, when injected in series with a distribution feeder by a voltage source inverter, can tightly regulate the voltage at the load terminal against imbalance or harmonics in the source side. It is stipulated that the DVR does not supply any real power in the steady state. The reference voltage generation scheme is validated through digital computer simulation studies.     

Screen‐printed biosensor for allergens

Allergen levels in indoor environments, leading to many diseases, eg asthma, rhinitis and conjunctivitis, affect a large and increasing fraction of the population. A quite effective and inexpensive method of a rough but very rapid overall assessment of total allergen level in the environment has been developed. The method involved estimation of protein in allergen extracts by screen‐printed electrodes using two different techniques. The biosensor comprised a rhodinised carbon working electrode, a silver/silver chloride reference electrode and a carbon counter electrode. In the first method the enzyme protease reacted with allergen protein to release amino acid, which produced hydrogen peroxide in the presence of amino acid oxidase. This was detected amperometrically. The second method used potassium bromide as electrolyte and the electrode was subjected to dual potential. Bromine, released due to electrolysis at higher potential, was consumed by the allergen protein at lower potential. In the first method, a unique technique was used to microencapsulate the enzyme protease and immobilise it on the surface of the electrode by in‐situ polymerisation to avoid contact with the amino acid oxidase. A total of seven allergens were tested and the results gave a good correlation with the standard protein measurement method. Environmental specimens from indoors, schools and workplaces can be evaluated for the aeroallergens produced by dust mites, animal hairs, cockroach debris, pollens, etc as a means of determining the exposure risk. Copyright © 2005 Society of Chemical Industry     

Detecting nondeterminacy in parallel programs

Methods and tools for detecting nondeterminacy in programs for shared-memory multiprocessors are discussed. The approach described divides the debugging chore into two phases. The first phase uses tools that automatically detect nondeterminacy to debug synchronization errors, assuming it is decided at the outset to make the parallel program determinate. At the end of this phase, it is known that the program is determinate, that timing differences will not affect results, and the debugging sessions are repeatable. In the second phase, an interactive break-point debugger is used to find arithmetic and logical errors. The proposed tools fall into two groups: those that statically analyze the source program and those that analyze an execution trace of the program     

Classification Based on Hybridization of Parametric and Nonparametric Classifiers

Parametric methods of classification assume specific parametric models for competing population densities (e.g., Gaussian population densities can lead to linear and quadratic discriminant analysis) and they work well when these model assumptions are valid. Violation in one or more of these parametric model assumptions often leads to a poor classifier. On the other hand, nonparametric classifiers (e.g., nearest-neighbor and kernel-based classifiers) are more flexible and free from parametric model assumptions. But, the statistical instability of these classifiers may lead to poor performance when we have small numbers of training sample observations. Nonparametric methods, however, do not use any parametric structure of population densities. Therefore, even when one has some additional information about population densities, that important information is not used to modify the nonparametric classification rule. This paper makes an attempt to overcome these limitations of parametric and nonparametric approaches and combines their strengths to develop some hybrid classification methods. We use some simulated examples and benchmark data sets to examine the performance of these hybrid discriminant analysis tools. Asymptotic results on their misclassification rates have been derived under appropriate regularity conditions.     

Surface modes of a sessile water drop: an optical tweezer based study

A high-precision method to study the dynamics of two-fluid interfaces using an optical tweezer and a phase-sensitive detection technique are described. The disturbances set up at the interface are studied by analyzing the motion of an optically trapped particle in the bulk of the fluid, i.e., away from the interface. The usefulness of the technique is demonstrated for the well-known problem of a horizontally vibrated sessile liquid drop. The vibrational modes of the liquid drop excited by sinusoidally vibrating the support in a horizontal plane appear as resonances in the motion of the trapped particle. The nature of the resonance is studied in detail by measuring the real part, the imaginary part, and the phase response of the motion of the particle as a function of the "effective" size of the liquid drop. Excellent quantitative agreement with the theoretically predicted values of the eigenfrequencies and damping of the surface modes is obtained.     

A mixture-of-experts framework for adaptive Kalman filtering

This paper proposes a modular and flexible approach to adaptive Kalman filtering using the framework of a mixture-of-experts regulated by a gating network. Each expert is a Kalman filter modeled with a different realization of the unknown system parameters such as process and measurement noise. The gating network performs on-line adaptation of the weights given to individual filter estimates based on performance. This scheme compares very favorably with the classical Magill filter bank, which is based on a Bayesian technique, in terms of: estimation accuracy; quicker response to changing environments; and numerical stability and computational demands. The proposed filter bank is further enhanced by periodically using a search algorithm in a feedback loop. Two search algorithms are considered. The first algorithm uses a recursive quadratic programming approach which extremizes a modified maximum likelihood function to update the parameters of the best performing filter in the bank. This particular approach to parameter adaptation allows a real-time implementation. The second algorithm uses a genetic algorithm to search for the parameter vector and is suited for post-processed data type applications. The workings and power of the overall filter bank and the suggested adaptation schemes are illustrated by a number of examples.     

Improved Multilevel Hysteresis Current Regulation and Capacitor Voltage Balancing Schemes for Flying Capacitor Multilevel Inverter

This paper focuses on the development of multilevel hysteresis current regulation strategies. Two such strategies have been discussed and some modifications in their control tasks have been proposed to achieve more reliable and improved performance. In general, the multiband concept has been used while making the proposals. The hysteresis band size considerations have also been presented by taking into account the desired and existing system conditions. The proposed modulation schemes have been applied to a five-level flying-capacitor inverter, whose operation under hysteresis current control mode is much less established. A new method of flying-capacitor voltage balancing is proposed which ensures balanced flying-capacitor voltages and, at the same time, maintains the desired current profile. It uses a time-based approach for controlling the capacitor voltages and achieves appreciable voltage spectrum under wide range of load power factor conditions. The performance of the proposed strategies is confirmed through both simulation and experimental investigations.     

A distributed algorithm for fault simulation of combinatorial and asynchronous sequential digital designs, utilizing circuit partitioning, on loosely-coupled parallel processors

Fault simulation constitutes an indispensable tool in ensuring the correctness and quality of manufactured digital designs. Traditional uniprocessor based algorithms for fault simulation have been observed to be agonizingly slow for today's large and complex digital designs. More recently, a few researchers introduce an approach, as evident in the literature, wherein the fault set is partitioned and the digital design fault simulated for each of the fault subset on separate processors of a parallel processor system. The approach is limited in that it continues to utilize the traditional uniprocessor-based algorithm and the performance results are not encouraging. This paper introduces, perhaps for the first time, a distributed algorithm that is capable of fault simulating both combinational and asynchronous sequential digital designs on parallel processors. An underlying assumption of the algorithm is that the digital design, under fault simulation, is partitioned by the user. In this approach, referred to as NODIFS in this paper, every component in the circuit is modeled as an asynchronous, concurrent, entity that is fault simulated as soon as appropriate signal transitions and fault lists are asserted at its input ports. The circuit partitioning is such that components of every partition are allocated to a unique processor of the parallel processor system. Consequently, a number of components may be concurrently fault simulated on multiple processors in NODIFS implying significant increase in throughput. This approach promises (i) very high throughput because of its ability, in principle, to utilize the maximal inherent parallelism, and (ii) scalability. The algorithm is novel in that the overall task of decision-making i.e., fault simulation of the circuit, is distributed into a number of natural, independent, and concurrent entities that execute asynchronously to utilize maximal parallelism. NODIFS's success is the result of the asynchronous distributed discrete-event simulation algorithm, YADDES, and a new approach to fault simulation. The notion of scalability implies that where the problem size increases, the algorithm continues to apply and, by increasing the number of computational engines proportionately, the performance of the algorithm will continue to increase. Furthermore, NODIFS is a natural choice for fault simulation of digital designs at the behavior-level — an eventual reality, wherein the ratio of the computational to communication load for the behavior models may approach a significantly large value. This paper also reports on an implementation of NODIFS on both the ARMSTRONG parallel processor system at Brown University and the performance results indicate significant increase in the speedup for a few representative example digital designs. It is stressed that the representative digital designs serve to support the mathematical validity of the algorithm along with the proof of correctness and not to demonstrate a high-performance, commercial, industrial-quality fault simulator.