An Incremental Adaptive Quantizer: A Novel Quantization Scheme

Adaptive quantizers for PCM and DPCM coding of speech have been of great interest, and several excellent quantization strategies have evolved [1], [2]. In this paper we propose another algorithm for the step-size change in a quantizer. In the present strategy the quantizer is always a linear one except for the fact that the step size can be changed by a fixed amount at each sampling instant. This fixed value is also the minimum allowed step size. Hence, we have the name incremental adaptive quantizer. The quantizer has been simulated on a computer and its performance has been compared with that of Jayant's adaptive quantizer (JAQ), both in PCM and DPCM coders. The figure of merit used in the comparison is the signal-to-noise ratio (SNR) with a correlated sequence as the input. The preliminary results indicate that the new design can perform very well. However, it has the drawback of not being able to respond to very fast changes in the input. It can be easily realized in an integrated form using ROM's.     

Evaluation of the Mean Error-Free Interval of a Noisy Data Channel

This correspondence presents expressions for the Mean Error-Free Interval in a packet-oriented data transmission system. In particular, the case of transmission through a random-error channel is studied, with some results also given for more general noisy channels.     

Thermo-elastic properties of dense YSZ and porous Ni-ZrO2 monolithic and isotropic materials

Attempts are made to correlate the structure and properties of dense and porous Yittria Stabilized Zirconia to establish optimal thermo-elastic properties for better performance at elevated temperatures. Temperature and compositional dependence of isotropic elastic bulk properties (Young's modulus, Poisson's ratio and Shear and Bulk moduli) are determined using the stiffness constants reported in the literature. Anisotropy of Yittria Stabilized Zirconia increases with composition of Yittria dosage in Zirconia. Optimal composition of 12 mole% Yittria stabilized Zirconia is slightly better than 8 mole% Yittria Stabilized Zirconia based on the improved thermo-elastic properties for better performance at higher temperature (RT-400°C). However 15.5 mole% YSZ seems to be more suitable from the view point of thermo-elastic performance at elevated temperatures (500–800°C). Polycrystalline properties predicted are within 5% error limits of the experimental values for Young's modulus of 12 mole% Yittria Stabilized Zirconia. Numerical prediction of Young's modulus of 12 mole% YSZ for 〈100〉 orientation is 362 GPa as compared to experimental value of 370 GPa reported in literature.     

Mechanical,dynamic mechanical properties and thermal stability of fluorocarbon elastomer–liquid crystalline polymer blends

Blends of fluorocarbon elastomer (FKM) and liquid crystalline polymer (LCP) have been prepared by the melt mixing technique. Processing studies indicated the increase in viscosity with the addition of LCP. The tensile strength, tear strength, and modulus of the elastomer are greatly improved by the addition of the LCP. Dynamic mechanical analysis (DMA) results showed that the shift in the glass transition temperature (T_g) of the elastomer with the addition of LCP and the storage modulus of the blends increased above the T_g of FKM, whereas decreases below the T_g of the elastomer were seen with up to 20 wt% LCP; this suggests that the LCP acts as an effective reinforcing agent above the T_g of FKM. From the thermogravimetric analysis (TGA) and differential thermogravimetry (DTG), we found that the thermal stability of the elastomer enhances by blending with the LCP. The weight loss and the weight loss rate of the FKM decrease enormously with the addition of LCP. From the X‐ray diffraction (XRD) study, it has been observed that the LCP acts as a nucleating agent by increasing the crystallinity of the blend. The failure mechanism of the blends was studied using a scanning electron microscope (SEM). It suggested that the failure occurred in the blends; mainly due to the pull out of the fibrils from the matrix phase and due to lower interfacial adhesion between the LCP phase and the elastomer. POLYM. COMPOS. 26:306–315, 2005. © 2005 Society of Plastics Engineers     

Learning from data streams for automation and orchestration of 6G industrial IoT: toward a semantic communication framework

Neural Computing and Applications - Established methods of communication are based mainly on Shannon’s theory of information, which purposefully overlooks semantic elements of communication....     

CSCNN: Cost-Sensitive Convolutional Neural Network for Encrypted Traffic Classification

Neural Processing Letters - By the rapid development of the Internet and online applications, traffic classification not only has changed to an interesting topic in the field of computer networks...     

Trans-ungual delivery of itraconazole hydrochloride by iontophoresis

Itraconazole (ITR) is a potent antifungal drug. However, poor aqueous solubility limits its permeation ability across the human nail plate. Therefore, in this project, ITR was converted to hydrochloride salt (ITR-HCl) to improve its solubility and to render it amenable to iontophoresis. ITR-HCl was characterized by spectroscopic methods and antifungal efficacy was evaluated in comparison to the base. In vitro and ex vivo transport studies (passive and iontophoresis) were carried out across the porcine hoof membrane and excised human cadaver toe using two different protocols; continuous delivery of drug for 24?h and pulsed delivery of drug for 3 days (8?h/day). The antifungal efficacy of ITR-HCL was comparable to ITR. Iontophoresis was found to be more effective than passive mode of delivery of ITR-HCL. In both iontophoresis as well as passive mode of delivery, the pulsed protocol resulted in more ungual and trans-ungual delivery of drug than continuous protocol. ITR-HCL could be delivered into and across the nail plate by iontophoresis. Human cadaver toe appears to be a good model to investigate the ungual delivery of drugs.     

Investigation of the performance of several chemical additives on inhibition of asphaltene precipitation

The inhibition effects of several chemical additives on asphaltene precipitation were investigated by the microscopic method. The additives consist of a synthesized deep eutectic solvent (SDES), a commercial inhibitor, and three surfactants, namely lauric acid, octyl phenol, and dodecyl amine. The results showed the octyl phenol with 500 mg/L concentration is similar to commercial inhibitor and later SDES had the maximum effects on delaying the asphaltene precipitation onset point. The mean particle size of asphaltene using octyl phenol, SDES, lauric acid, and dodecyl amine decreased about 55%, 41%, 24%, and 18%, respectively, compared to the oil sample without any chemical additives.     

Predicting the velocity distribution of Rushton turbine impeller in mixing of polymeric liquids using fuzzy neural network models

Velocity profiles are helpful for the confident design of mixing tanks and chemical reactors in mixing processes. A fuzzy model and an artificial neural network have been presented for accurate prediction of velocity distribution of Rushton turbine impeller (RTI) for the mixing of polymeric liquids in the lower transition region: 35<Re′<1800. Local tangential and radial velocities were predicted along the discharge plane of the impeller. Experimental data were used for training, validation, and testing the neuromorphic models. The presented models are very accurate and reliable in predicting the velocity profiles over wide ranges of polymer concentrations and rotational speed. Comparison of the suggested fuzzy model and the empirical correlations shows that the proposed model outperforms the other alternatives both in accuracy and generality. The results show that the proposed neuromorphic models can successfully be used for prediction of velocity distribution in agitated tanks for viscoelastic polymeric fluids.