Particle tracking techniques for electrokinetic microchannel flows

We have applied particle tracking techniques to obtain spatially resolved velocity measurements in electrokinetic flow devices. Both micrometer-resolution particle image velocimetry (micro-PMV) and particle tracking velocimetry (PTV) techniques have been used to quantify and study flow phenomena in electrokinetic systems applicable to microfluidic bioanalytical devices. To make the flow measurements quantitative, we performed a series of seed particle calibration experiments. First, we measure the electroosmotic wall mobility of a borosilicate rectangular capillary (40 by 400 microm) using current monitoring. In addition to this wall mobility characterization, we apply PTV to determine the electrophoretic mobilities of more than 1,000 fluorescent microsphere particles in aqueous buffer solutions. Particles from this calibrated particle/ buffer mixture are then introduced into two electrokinetic flow systems for particle tracking flow experiments. In these experiments, we use micro-PIV, together with an electric field prediction, to obtain electroosmotic flow bulk fluid velocity measurements. The first example flow system is a microchannel intersection where we demonstrate a detailed documentation of the similitude between the electrical fields and the velocity fields in an electrokinetic system with uniform zeta potential, zeta. In the second system, we apply micro-PIV to a microchannel system with nonuniform zeta. The latter experiment provides a simultaneous measurement of two distinct wall mobilities within the microchannel.     

A middleware‐transparent approach to developing distributed applications

An innovative middleware‐transparent approach to developing distributed applications is presented. The approach uses an aspect‐oriented software development technique to separate an application's middleware‐independent functionality from its middleware‐specific functionality. Application elements that are specific to the middleware are localized in aspects that can be seamlessly integrated into middleware‐independent application designs. The middleware‐transparent approach is used to decouple business functionality from middleware‐specific functionality. The decoupling allows developers to change middleware application elements without significantly modifying business functionality. Middleware technologies such as Java Remote Method Invocation (RMI), Jini, Simple Object Access Protocol (SOAP) remote procedure call (RPC) and .Net are used as examples to illustrate the approach. Copyright © 2005 John Wiley & Sons, Ltd.     

Modeling resonance tests for electrostrictive ceramics

The electromechanical coupling coefficient represents a useful figure-of-merit for comparing the quality of different electroactive materials. However, the coupling coefficient for an electrostrictive ceramic is not a unique material parameter, because it depends strongly on the applied DC bias field, AC field amplitude and frequency, and stress. These dependencies make direct comparison between electrostrictors and piezoelectrics somewhat ambiguous. In this paper, we developed a pair of coupling parameters for electrostrictors that were strictly material constants and completely characterized the material's electromechanical quality. We proposed relatively simple, inexpensive resonance testing to measure these new parameters from the electrical admittance of a vibrating electrostrictive rod. The electromechanical coupling coefficient for a specific loading condition is computed from these parameters, allowing direct comparison between electrostrictive and piezoelectric materials.     

Selective flocculation of iron oxide-kaolin mixtures using a modified polyacrylamide flocculant

High molecular weight polyacrylamides were synthesized and successfully modified to contain up to 8·3% hydroxamate functional groups. The selective flocculation tests carried out on 1:1 iron oxide/kaolin mixtures using parent polyacrylamide, polyacrylic acid and the modified polyacrylamide, confirm the possibility of enhancing selectivity through introduction of iron chelating functional groups in commercially available polymers. Starting with a feed grade of 35% iron, 92% recovery with acceptable grade of 60% iron has been achieved using the modified polyacrylamide. NCL communication No. 4415     

Variability of mesopause temperature derived from two independent methods using meteor radar and its comparison with SABER and EOS MLS and a collocated multi-wavelength dayglow photometer over an equatorial station,Thumba (8.5° N, 76.5° E)

Two independent methods for deriving mesopause temperature using meteor radar installed at an equatorial station, Thumba (8.5° N, 76.5° E), are discussed in this article. This meteor radar-derived mesopause temperature is then compared with two different types of spaceborne measurement, namely (i) Sounding the Atmosphere using Broadband Emission Radiometry (SABER) and (ii) the Earth Observing System Microwave Limb Sounder (EOS MLS), and a collocated multi-wavelength dayglow photometer (DGPM). The meteor radar-derived temperature is in fairly good agreement with all the three measurement techniques, with an uncertainty of ±10°. This study focuses on a detailed evaluation and inter-comparison of mesopause temperature derived from different measurement techniques. An attempt is also made to compare the suitability of these observations to study planetary waves and other oscillation activities in the mesospheric region.     

Bi-directional LSTM based channel estimation in 5G massive MIMO OFDM systems over TDL-C model with Rayleigh fading distribution

In this work, a deep learning (DL)-based massive multiple-input multiple-output (mMIMO) orthogonal frequency division multiplexing (OFDM) system is investigated over the tapped delay line type C (TDL-C) model with a Rayleigh fading distribution at frequencies ranging from 0.5 to 100 GHz. The proposed bi-directional long short-term memory (Bi-LSTM) channel state information (CSI) estimator uses online learning during training and offline learning during the practical implementation phase. The design of the estimator takes into account situations in which prior knowledge of channel statistics is limited and targets excellent performance, even with limited pilot symbols (PS). Three separate loss functions (mean square logarithmic error [MSLE], Huber, and Kullback–Leibler Distance [KLD]) are assessed in three classification layers. The symbol error rate (SER) and outage probability performance of the proposed estimator are evaluated using a number of optimization techniques, such as stochastic gradient descent (SGD), momentum, and the adaptive gradient (AdaGrad) algorithm. The Bi-LSTM-based CSI estimator is trained considering a specific number of PS. It can be readily seen that by incorporating a cyclic prefix (CP), the system becomes more resilient to channel impairments, resulting in a lower SER. Simulations show that the SGD optimization approach and Huber loss function-trained Bi-LSTM-based CSI estimator have the lowest SER and very high estimation accuracy. By using deep neural networks (DNNs), the Bi-LSTM method for CSI estimation achieves a superior channel capacity (in bps/Hz) at 10 dB than long short-term memory (LSTM) and other conventional CSI estimators, such as minimum mean square error (MMSE) and least squares (LS). The simulation results validate the analytical results in the study.     

A Measurement‐Based Approach for Designing Fixed‐Order Controllers for Unknown Closed‐Loop Architecture

This paper presents a new technique to design fixed‐structure controllers for linear unknown systems using a set of measurements. In model‐based approaches, the measured data are used to identify a model of the plant for which a suitable controller can be designed. Due to the fact that real processes cannot be described perfectly by mathematical models, designing controllers using such models to guarantee some desired closed‐loop performance is a challenging task. Hence, a possible alternative to model‐based methods is to directly utilize the measured data in the design process. We propose an approach to designing structured controllers using a set of closed‐loop frequency‐domain data. The principle of such an approach is based on computing the parameters of a fixed‐order controller for which the closed‐loop frequency response fits a desired frequency response that describes some desired performance indices. This problem is formulated as an error minimization problem, which can be solved to find suitable values of the controller parameters. The main feature of the proposed control methodology is that it can be applied to stable and unstable plants. Additionally, the design process depends on a pre‐selected controller structure, which allows for the selection of low‐order controllers. An application of the proposed method to a DC servomotor system is presented to experimentally validate and demonstrate its efficacy.     

An evolutionary lion optimization algorithm‐based image compression technique for biomedical applications

Recently, medical image compression becomes essential to effectively handle large amounts of medical data for storage and communication purposes. Vector quantization (VQ) is a popular image compression technique, and the commonly used VQ model is Linde–Buzo–Gray (LBG) that constructs a local optimal codebook to compress images. The codebook construction was considered as an optimization problem, and a bioinspired algorithm was employed to solve it. This article proposed a VQ codebook construction approach called the L2‐LBG method utilizing the Lion optimization algorithm (LOA) and Lempel Ziv Markov chain Algorithm (LZMA). Once LOA constructed the codebook, LZMA was applied to compress the index table and further increase the compression performance of the LOA. A set of experimentation has been carried out using the benchmark medical images, and a comparative analysis was conducted with Cuckoo Search‐based LBG (CS‐LBG), Firefly‐based LBG (FF‐LBG) and JPEG2000. The compression efficiency of the presented model was validated in terms of compression ratio (CR), compression factor (CF), bit rate, and peak signal to noise ratio (PSNR). The proposed L2‐LBG method obtained a higher CR of 0.3425375 and PSNR value of 52.62459 compared to CS‐LBG, FA‐LBG, and JPEG2000 methods. The experimental values revealed that the L2‐LBG process yielded effective compression performance with a better‐quality reconstructed image.     

A Nakagami-N-gamma Model for Shadowed Fading Channels

Wireless channels are subject to short term fading and shadowing. Such shadowed fading channels are described using a Nakagami-lognormal process, with the Nakagami-m (short term fading) and lognormal distributions (shadowing). This approach does not result in a closed form solution for the density function of the signal-to-noise ratio (SNR) making wireless systems analysis difficult. It was suggested that a gamma or an inverse Gaussian distribution can be used in place of the lognormal distribution providing an analytical framework. The match of these two distributions to the lognormal was less than ideal. Invoking shadowing as multiplicative process, the distribution of the product of N gamma variables is proposed in place of the lognormal pdf resulting in the Nakagami-N-gamma model. It is shown that this model leads to simple solutions to the density and distribution functions as well as error rates for coherent phase shift keying modems. The outage probabilities and error rates based on the Nakagami-lognormal (NL) and Nakagami-N-gamma (NNG) models were compared. Results showed excellent match at levels of shadowing generally observed in wireless systems. While values of N as low as 3 was sufficient for low values of m and weak to moderate shadowing, values of N in the range of 7–9 provided better match for higher levels of shadowing and higher values of m. By varying N, it is also possible to get the NNG pdf to move closer to the NL pdf making the new model an ideal one for the shadowed fading channels with its flexibility and availability of analytical expressions.