Robust vector quantization for noisy channels

The paper briefly discusses techniques for making vector quantizers more tolerant to tranmsission errors. Two algorithms are presented for obtaining an efficient binary word assignment to the vector quantizer codewords without increasing the transmission rate. It is shown that about 4.5 dB gain over random assignment can be achieved with these algorithms. It is also proposed to reduce the effects of error propagation in vector-predictive quantizers by appropriately constraining the response of the predictive loop. The constrained system is shown to have about 4 dB of SNR gain over an unconstrained system in a noisy channel, with a small loss of clean-channel performance

Measurement of Dust Optical Properties in Coalsack

We have used FUSE and Voyager observations of dust scattered starlight in the neighborhood of the Coalsack Nebula to derive the optical constants of the dust grains. The albedo is consistent with a value of $0.28 \pm 0.04$ and the phase function asymmetry factor with a value of $0.61 \pm 0.07$ throughout the spectral range from 900 -- 1200 \AA, in agreement with previous determinations as well as theoretical predictions. We have now observed two regions (Ophiuchus and Coalsack) with intense diffuse background radiation and in both cases have found that the emission is due to light from nearby hot stars scattered by a relatively thin foreground cloud, with negligible contribution from the background molecular cloud.Comment: Total 19 pages, Figures 9, Accepted for publication in Astrophysical Journa

Efficient Data Averaging for Spin Noise Spectroscopy in Semiconductors

Spin noise spectroscopy (SNS) is the perfect tool to investigate electron spin dynamics in semiconductors at thermal equilibrium. We simulate SNS measurements and show that ultrafast digitizers with low bit depth enable sensitive, high bandwidth SNS in the presence of strong optical background shot noise. The simulations reveal that optimized input load at the digitizer is crucial for efficient spin noise detection while the bit depth influences the sensitivity rather weakly

GALEX Observations of Diffuse UV Radiation at High Spatial Resolution from the Sandage Nebulosity

Using the GALEX ultraviolet imagers we have observed a region of nebulosity first identified as starlight scattered by interstellar dust by Sandage (1976). Apart from airglow and zodiacal emission, we have found a diffuse UV background of between 500 and 800 \phunit in both the \galex FUV (1350 -- 1750 \AA) and NUV (1750 -- 2850 \AA). Of this emission, up to 250 \phunit is due to \htwo fluorescent emission in the FUV band; the remainder is consistent with scattering from interstellar dust. We have estimated the optical constants to be $a = 0.3; g = 0.7$ in the FUV and $a = 0.5; g = 0.7$ in the NUV, implying highly forward scattering grains, plus an extragalactic contribution of as much as 150 \phunit. These are the highest spatial resolution observations of the diffuse UV background to date and show an intrinsic scatter beyond that expected from instrumental noise alone. Further modeling is required to understand the nature of this scatter and its implications for the ISM.Comment: Total 20 pages, Figures 9, Accepted for publication in Astrophysical Journa

On the benefits of defining vicinal distributions in latent space

The vicinal risk minimization (VRM) principle is an empirical risk minimization (ERM) variant that replaces Dirac masses with vicinal functions. There is strong numerical and theoretical evidence showing that VRM outperforms ERM in terms of generalization if appropriate vicinal functions are chosen. Mixup Training (MT), a popular choice of vicinal distribution, improves the generalization performance of models by introducing globally linear behavior in between training examples. Apart from generalization, recent works have shown that mixup trained models are relatively robust to input perturbations/corruptions and at the same time are calibrated better than their non-mixup counterparts. In this work, we investigate the benefits of defining these vicinal distributions like mixup in latent space of generative models rather than in input space itself. We propose a new approach - \textit{VarMixup (Variational Mixup)} - to better sample mixup images by using the latent manifold underlying the data. Our empirical studies on CIFAR-10, CIFAR-100, and Tiny-ImageNet demonstrate that models trained by performing mixup in the latent manifold learned by VAEs are inherently more robust to various input corruptions/perturbations, are significantly better calibrated, and exhibit more local-linear loss landscapes.Comment: Accepted at Elsevier Pattern Recognition Letters (2021), Best Paper Award at CVPR 2021 Workshop on Adversarial Machine Learning in Real-World Computer Vision (AML-CV), Also accepted at ICLR 2021 Workshops on Robust-Reliable Machine Learning (Oral) and Generalization beyond the training distribution (Abstract

New Directions in Subband Coding

Two very different subband coders are described. The first is a modified dynamic bit-allocation-subband coder (D-SBC) designed for variable rate coding situations and easily adaptable to noisy channel environments. It can operate at rates as low as 12 kb/s and still give good quality speech. The second coder is a 16-kb/s waveform coder, based on a combination of subband coding and vector quantization (VQ-SBC). The key feature of this coder is its short coding delay, which makes it suitable for real-time communication networks. The speech quality of both coders has been enhanced by adaptive postfiltering. The coders have been implemented on a single AT&T DSP32 signal processo

Evaluation of inbred lines derived from commercial hybrids and their utilization in developing high yielding field corn (Zea mays L.) hybrids

Genetic enhancement and identification of genetically broad-based inbred lines for the development of new hybrids is the pre-requisite for the heterosis breeding. Newly derived 118 inbred lines were evaluated for their morpho-physiological characters in order to identify best suitable male and female parental lines. Total 10 best inbred lines were selected after thorough evaluation of 16 stable inbred lines, identified from the pool of 118 inbred lines. These inbred lines were crossed in line × tester manner, considering three inbred lines as male andrest as female, based on the Specific Combining Ability and General Combining Ability. Hybrids thus obtained were evaluated in two diverse agroclimatic situations and best heterotic hybrids were selected based on their standard heterosis and rank obtained in Duncan's Multiple Range Test analysis. Single location ANOVA for inbred lines and combined ANOVA for hybrids showed that selected inbreds and hybrids were significantly differing from each other. Since, there exists a Genotype × Environment interaction among hybrids, PCA also taken into consideration for giving weight as classification variable for the hybrids. Further, multi-location evaluation of these hybrids is proposed to identify stable hybrids suitable for large scale commercialization

Ectopic production of human placental lactogen by human breast tumors

Serum samples from 72 patients with established carcinoma of the breast were investigated for ectopic presence of hPL. Further, the relationship of ectopically-secreted hPL and hCG-β in breast cancer was investigated. Ten of 72 patients examined had detectable hPL and 12 had detectable hCG-β, at 1-2 ng/ml serum sensitivity of the assay. The presence of hPL in serum of breast cancer patients was found to be independent of that of hCG-β. Sera of 13 patients with cystic mastitis, five with fibroadenoma, two with acute inflamation of breast, 20 normal women (non-pregnant) and 20 normal men did not show any detectable serum hPL or hCG-β at the above mentioned sensitivity of the assay. Since these hormones were not detectable in normal men, normal non-pregnant women, and in patients having other pathological conditions of breast, the possible use of them as markers in cancer is expected