Time reversal acoustic communication receivers: DSP implementation and fast channel estimation

A communication system is implemented on digital signal processors (DSPs) for the underwater acoustic environment. The implemented receiver uses time reversal multi-channel combining followed by a single-channel decision feedback equalizer. Periodic channel estimation is employed to track the channel fluctuations. These techniques are used to mitigate time-varying inter-symbol interference, which is the main challenge in the underwater acoustic channel at operating frequencies greater than 10 kHz. Various optimization tasks are performed to reduce the receiver computational complexity. A fast implementation of the matching pursuit algorithm is tested on the DSP platform. Its performance, in terms of accuracy and run-time, is compared with that of the basic matching pursuit algorithm. Experimental results of the transmission and demodulation of binary phase-shift keying signals at three different symbol rates were obtained in the local Delaware Bay. The low bit error rates demonstrate the effectiveness of our implementation.     

Combining GPS carrier phase and Doppler observations for precise velocity determination

The truncation error and propagation error are analyzed for velocity determination through differential GPS carrier phase observations,and an approach for the choice of the best number of points for the central difference method is developed.In order to overcome the disadvantages of existing GPS velocity determination methods,a new velocity determination algorithm is presented,based on combining carrier phase and Doppler observations.The basic idea is that two types of observation are combined by adding the...     

Comparison of two-dimensional integration methods for shape reconstruction from gradient data

As a requisite and key step in some gradient-based measurement techniques, the reconstruction of the shape, more generally the scalar potential, from the measured gradient data has been studied for many years. In this work, three types of two-dimensional integration methods are compared under various conditions. The merits and drawbacks of each integration method are consequently revealed to provide suggestions in selection of a proper integration method for a particular application.     

RP-HPLC-DAD method for the determination of phenylepherine,paracetamol, caffeine and chlorpheniramine in bulk and marketed formulation

A simple, specific and accurate isocratic RP-HPLC-DAD method was developed for the simultaneous determination of phenylephrine, paracetamol, caffeine and chlorpheniramine in bulk and tablet dosage form. The four contents are present in variable concentrations and have variable chromatographic behavior making the process of analysis very difficult. For present studies a reversed-phase C-18 column (150 mm × 4.5 mm i.d., particle size 5 μm) with mobile phase consisting of acetonitrile, methanol and 10 Mm phosphate buffer 16:22:62 (v/v) (pH of buffer 2.5 ± 0.02, adjusted with ortho phosphoric acid) was used. The flow rate was 1.0 ml/min and eluents were monitored at 280 nm. The mean retention times of phenylephrine, paracetamol, caffeine and chlorpheniramine were found to be 1.8, 3.1, 5.2 and 10.9 min, respectively. The method was validated in terms of linearity, range, specificity, accuracy, precision and robustness. The proposed method was successfully applied to the estimation of phenylephrine, paracetamol, caffeine and chlorpheniramine in combined tablet dosage form.     

过渡态理论在化学体系中的2个应用实例*

在大学本科一二年级的物理化学教学中,化学动力学章节的学习涉及到对不同时间尺度的认识。本文利用过渡态理论得到的速率常数表达公式,以乙烷分子碳/碳单键旋转和水分子氢键交换的动力学过程为例,对这2个应用实例的动力学过程所发生的时间尺度做出估算。这些时间尺度的估算对于学生理解不同动力学过程的物理图像至关重要,同时也有助于加强学生对重要公式的理解并能够将这些公式在化学体系中灵活运用。     

Fabrication and Characterization of Zinc Oxide Nanowire Based Two-electrode Capacitive Biosensors on Flexible Substrates for Estimating Glucose Content in a Sample

The present work deals with fabrication and characterization of the zinc oxide (ZnO) nanowire based novel two-electrode capacitive biosensors on flexible Polyethylene terephthalate (PET) substrates for accurate estimation of glucose by analyzing the fundamental dielectric nature of the relevant sample. The morphology and crystalline quality of grown nanowires are analyzed by using field-emission scanning electron microscope (FESEM) and X-ray diffractometer (XRD), respectively. Current and capacitance values of the device have been studied for ten different glucose concentrations relevant to the physiological standards. The analytical performance of the devices in terms of enzyme activity, reliability and flexibility has also been evaluated.     

ECM and SAGE based joint estimation of timing and frequency offset for DMIMO–OFDM system

Distributed multiple-input multiple-output (DMIMO) technology is a key enabler of coverage extension and enhancement of link reliability in wireless networks through distributed spatial diversity. DMIMO employs classic relay channels in between the source and the destination to opportunistically form a virtual antenna array (VAA) for emulating cooperative diversity. Use of multiple antennas at the relays further increases capacity and reliability of the relay–destination channel through multiplexing and diversity of MIMO antennas respectively. In such network, the signal received at the destination is characterized by multiple timing offsets (MTO) due to different propagation delay and multiple carrier frequency offsets (MCFO) due to independent oscillators of the relays. Hence, synchronization becomes a crucial issue in DMIMO in order to realize the distributed coherence. In this paper, we address joint estimation of MCFO and MTO in DMIMO orthogonal frequency division multiplexing (OFDM) with MIMO configuration at the relays for estimate-and-forward (EF) relaying protocol. Two iterative algorithms, based on expectation conditional maximization (ECM) and space alternating generalized expectation–maximization (SAGE) are proposed for joint estimation in presence of inter carrier interference (ICI). The robustness of both the estimators to ICI is evaluated by mathematical analysis and supported by extensive simulations. The performance of the proposed estimators is assessed in terms of mean square error (MSE) and bit error rate (BER). The theoretical Cramer–Rao lower bound (CRLB) of estimator error variance is also derived.     

Optimal estimation of the diffusion coefficient from non-averaged and averaged noisy magnitude data

The magnitude operation changes the signal distribution in MRI images from Gaussian to Rician. This introduces a bias that must be taken into account when estimating the apparent diffusion coefficient. Several estimators are known in the literature. In the present paper, two novel schemes are proposed. Both are based on simple least squares fitting of the measured signal, either to the median (MD) or to the maximum probability (MP) value of the Probability Density Function (PDF). Fitting to the mean (MN) or a high signal-to-noise ratio approximation to the mean (HS) is also possible. Special attention is paid to the case of averaged magnitude images. The PDF, which cannot be expressed in closed form, is analyzed numerically. A scheme for performing maximum likelihood (ML) estimation from averaged magnitude images is proposed. The performance of several estimators is evaluated by Monte Carlo (MC) simulations. We focus on typical clinical situations, where the number of acquisitions is limited. For non-averaged data the optimal choice is found to be MP or HS, whereas uncorrected schemes and the power image (PI) method should be avoided. For averaged data MD and ML perform equally well, whereas uncorrected schemes and HS are inadequate. MD provides easier implementation and higher computational efficiency than ML. Unbiased estimation of the diffusion coefficient allows high resolution diffusion tensor imaging (DTI) and may therefore help solving the problem of crossing fibers encountered in white matter tractography.     

Improved Kinetic Rate Constants for Nylon 6, Nylon 6,6, and Nylon 6/6,6 Copolymer

Nylon 6 and 6,6 literature data are collected over a wide range of water concentrations and temperatures (0 ≤ [W]₀ ≤ 40.8 wt%, 200 ≤ T ≤300 °C) and used to fit parameters in an updated batch reactor model. The resulting copolymerization model uses side reactions to account for the complex influence of water on kinetics and reaction equilibria. The proposed parameter estimates result in a significant improvement in the fit to the data, corresponding to a 73% reduction in the weighted‐least‐squares objective function compared to when the parameters of Arai et al. are used. Copolymerization simulations are conducted at industrially relevant conditions, shedding light on the complex influence of water and on the potential to include waste nylon 6 cyclic dimer in the feedstock. The model and parameter estimates will be helpful in future models of nylon 6/6,6 copolymerization in continuous reactor systems.