A simple low-cost electrical switching analyzer for I-V characterization of switching samples and devices

The phenomena of nonlinear I-V behavior and electrical switching find extensive applications in power control, information storage, oscillators, etc. The study of I-V characteristics and switching parameters is necessary for the proper application of switching materials and devices. In the present work, a simple low-cost electrical switching analyzer has been developed for the measurement of the electrical characteristics of switching materials and devices. The system developed consists of a microcontroller-based excitation source and a high-speed data acquisition system. The design details of the excitation source, its interface with the high-speed data acquisition system and personal computer, and the details of the application software developed for automated measurements are described. Typical I-V characteristics and switching curves obtained with the system developed are also presented to illustrate the capability of the instrument developed.

A low-cost lead-acid battery with high specific-energy

Lightweight grids for lead-acid battery grids have been prepared from acrylonitrile. butadiene styrene (ABS) copolymer followed by coating with lead. Subsequently, the grids have been electrochemically coated with a conductive and corrosion-resistant layer of polyaniline. These grids are about 75% lighter than those employed in conventional lead-acid batteries. Commercial-grade 6V/3.5 Ah (C-20-rate) lead-acid batteries have been assembled and characterized employing positive and negative plates constituting these grids. The specific energy of such a lead-acid battery is about 50 Wh/kg. The batteries can withstand fast charge-discharge duty cycles.

Development of a low-cost portable colorimeter for the estimation of fluoride in drinking water

People in many countries are affected by fluorosis owing to the high levels of fluoride in drinking water. An inexpensive method for estimating the concentration of the fluoride ion in drinking water would be helpful in identifying safe sources of water and also in monitoring the performance of defluoridation techniques. For this purpose, a simple, inexpensive, and portable colorimeter has been developed in the present work. It is used in conjunction with the SPADNS method, which shows a color change in the visible region on addition of water containing fluoride to a reagent solution. Groundwater samples were collected from different parts of the state of Karnataka, India and analysed for fluoride. The results obtained using the colorimeter and the double beam spectrophotometer agreed fairly well. The costs of the colorimeter and of the chemicals required per test were about Rs. 250 (US$ 5) and Rs. 2.5 (US$ 0.05), respectively. In addition, the cost of the chemicals required for constructing the calibration curve was about Rs. 15 (US$ 0.3). (C) 2010 Elsevier B.V. All rights reserved.

Noise minimization in RC-active filters using generalized impedance converters

A procedure has been given for minimizing the total output noise of a Generalized Impedance Converter (GIC), subject to constraints dictated by signal handling capability of the Operational Amplifiers and ease of microcircuit fabrication. The noise reduction is achieved only by the adjustment of RC elements of the GIC, and the total output noise after optimization in the example cited is close to the theoretical lower limit. The output noise of a higher-order filter can be reduced by RC-optimizing the individual GIC's of the active realization. Experimental results on a 20–24 kHz channel bank band-pass filter demonstrate the effectiveness of the above procedure.

Risk minimization in water quality control problems of a river system

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte-Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga-Bhadra river system in southern India, with a steady state BOD-DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality. (c) 2005 Elsevier Ltd. All rights reserved.

On Minimization of Test Application Time for RAS

Conventional Random access scan (RAS) for testing has lower test application time, low power dissipation, and low test data volume compared to standard serial scan chain based design In this paper, we present two cluster based techniques, namely, Serial Input Random Access Scan and Variable Word Length Random Access Scan to reduce test application time even further by exploiting the parallelism among the clusters and performing write operations on multiple bits Experimental results on benchmarks circuits show on an average 2-3 times speed up in test write time and average 60% reduction in write test data volume

Synthesis of Cost-Optimal Shell-and-Tube Heat Exchangers

Synthesis of cost-optimal shell-and-tube heat exchangers is a difficult task since it involves a large number of parameters. An attempt is made in this article to simplify the process of choosing the parameter values that will minimize the cost of any heat exchanger satisfying a given heat duty and a particular set of constraints. The simplification is based on decoupling of the geometric and the thermal aspects of the problem. The concept of curves for cost-optimal design is introduced and is shown to simplify the synthesis process for shell-and-tube heat exchangers.

Design options reduce exchanger cost

Heat exchanger design is a complex task involving the selection of a large number of interdependent design parameters. There are no established general techniques for optimizing the design, though a few earlier attempts provide computer software based on gradient methods, case study methods, etc. The authors felt that it would be useful to determine the nature of the optimal and near-optimal feasible designs to devise an optimization technique. Therefore, in this article they have obtained a large number of feasible designs of shell and tube heat exchangers, intended to perform a given heat duty, by an exhaustive search method. They have studied how their capital and operating costs varied. The study reveals several interesting aspects of the dependence of capital and total costs on various design parameters. The authors considered a typical shell and tube heat exchanger used in an oil refinery. Its heat duty, inlet temperature and other details are given.

Discrete-Time Controlled Markov Processes with Average Cost Criterion: A Survey

This work is a survey of the average cost control problem for discrete-time Markov processes. The authors have attempted to put together a comprehensive account of the considerable research on this problem over the past three decades. The exposition ranges from finite to Borel state and action spaces and includes a variety of methodologies to find and characterize optimal policies. The authors have included a brief historical perspective of the research efforts in this area and have compiled a substantial yet not exhaustive bibliography. The authors have also identified several important questions that are still open to investigation.

Spectroscopic and electrical properties of SiO2 films prepared by simple and cost effective sol-gel process

Amorphous SiO2 thin films were prepared on glass and silicon substrates by cost effective sol-gel method. Tetra ethyl ortho silicate (TEOS) was used as the precursor material, ethanol as solvent and concentrated HCl as a catalyst. The films were characterized at different annealing temperatures. The optical transmittance was slightly increased with increase of annealing temperature. The refractive index was found to be 1.484 at 550 nm. The formation of SiO2 film was analyzed from FT-IR spectra. The MOS capacitors were designed using silicon (1 0 0) substrates. The current-voltage (I-V), capacitance-voltage (C-V) and dissipation-voltage (D-V) measurements were taken for all the annealed films deposited on Si (1 0 0). The variation of current density, resistivity and dielectric constant of SiO2 films with different annealing temperatures was investigated and discussed for its usage in applications like MOS capacitor. The results revealed the decrease of dielectric constant and increase of resistivity of SiO2 films with increasing annealing temperature. (C) 2010 Elsevier B.V. All rights reserved.

Speedup Macroblock Mode Decision in H.264/SVC Encoding Using Cost-Sensitive Learning

In this paper we present a novel macroblock mode decision algorithm to speedup H.264/SVC Intra frame encoding. We replace the complex mode-decision calculations by a classifier which has been trained specifically to minimize the reduction in RD performance. This results in a significant speedup in encoding. The results show that machine learning has a great potential and can reduce the complexity substantially with negligible impact on quality. The results show that the proposed method reduces encoding time to about 70% in base layer and up to 50% in enhancement layer of the reference implementation with a negligible loss in quality.

An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes

We develop in this article the first actor-critic reinforcement learning algorithm with function approximation for a problem of control under multiple inequality constraints. We consider the infinite horizon discounted cost framework in which both the objective and the constraint functions are suitable expected policy-dependent discounted sums of certain sample path functions. We apply the Lagrange multiplier method to handle the inequality constraints. Our algorithm makes use of multi-timescale stochastic approximation and incorporates a temporal difference (TD) critic and an actor that makes a gradient search in the space of policy parameters using efficient simultaneous perturbation stochastic approximation (SPSA) gradient estimates. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal policy. (C) 2010 Elsevier B.V. All rights reserved.

Test Application Time Minimization for RAS using Basis Optimization of Column Decoder

Random Access Scan, which addresses individual flip-flops in a design using a memory array like row and column decoder architecture, has recently attracted widespread attention, due to its potential for lower test application time, test data volume and test power dissipation when compared to traditional Serial Scan. This is because typically only a very limited number of random ``care'' bits in a test response need be modified to create the next test vector. Unlike traditional scan, most flip-flops need not be updated. Test application efficiency can be further improved by organizing the access by word instead of by bit. In this paper we present a new decoder structure that takes advantage of basis vectors and linear algebra to further significantly optimize test application in RAS by performing the write operations on multiple bits consecutively. Simulations performed on benchmark circuits show an average of 2-3 times speed up in test write time compared to conventional RAS.

Lossless and lossy image compression using Boolean function minimization

A novel approach for lossless as well as lossy compression of monochrome images using Boolean minimization is proposed. The image is split into bit planes. Each bit plane is divided into windows or blocks of variable size. Each block is transformed into a Boolean switching function in cubical form, treating the pixel values as output of the function. Compression is performed by minimizing these switching functions using ESPRESSO, a cube based two level function minimizer. The minimized cubes are encoded using a code set which satisfies the prefix property. Our technique of lossless compression involves linear prediction as a preprocessing step and has compression ratio comparable to that of JPEG lossless compression technique. Our lossy compression technique involves reducing the number of bit planes as a preprocessing step which incurs minimal loss in the information of the image. The bit planes that remain after preprocessing are compressed using our lossless compression technique based on Boolean minimization. Qualitatively one cannot visually distinguish between the original image and the lossy image and the value of mean square error is kept low. For mean square error value close to that of JPEG lossy compression technique, our method gives better compression ratio. The compression scheme is relatively slower while the decompression time is comparable to that of JPEG.

Optimal control of arrivals to queues with delayed queue length information

We consider discrete-time versions of two classical problems in the optimal control of admission to a queueing system: i) optimal routing of arrivals to two parallel queues and ii) optimal acceptance/rejection of arrivals to a single queue. We extend the formulation of these problems to permit a k step delay in the observation of the queue lengths by the controller. For geometric inter-arrival times and geometric service times the problems are formulated as controlled Markov chains with expected total discounted cost as the minimization objective. For problem i) we show that when k = 1, the optimal policy is to allocate an arrival to the queue with the smaller expected queue length (JSEQ: Join the Shortest Expected Queue). We also show that for this problem, for k greater than or equal to 2, JSEQ is not optimal. For problem ii) we show that when k = 1, the optimal policy is a threshold policy. There are, however, two thresholds m(0) greater than or equal to m(1) > 0, such that mo is used when the previous action was to reject, and mi is used when the previous action was to accept.