Coded Index Modulation for Non-DC-Biased OFDM in Multiple LED Visible Light Communication

Use of multiple light emitting diodes (LED) is an attractive way to increase spectral efficiency in visible light communications (VLC). A non-DC-biased OFDM (NDC OFDM) scheme that uses two LEDs has been proposed in the literature recently. NDC OFDM has been shown to perform better than other OFDM schemes for VLC like DC-biased OFDM (DCO OFDM) and asymmetrically clipped OFDM (ACO OFDM) in multiple LEDs settings. In this paper, we propose an efficient multiple LED OFDM scheme for VLC which uses {\em coded index modulation}. The proposed scheme uses two transmitter blocks, each having a pair of LEDs. Within each block, NDC OFDM signaling is done. The selection of which block is activated in a signaling interval is decided by information bits (i.e., index bits). In order to improve the reliability of the index bits at the receiver (which is critical because of high channel correlation in multiple LEDs settings), we propose to use coding on the index bits alone. We call the proposed scheme as CI-NDC OFDM (coded index NDC OFDM) scheme. Simulation results show that, for the same spectral efficiency, CI-NDC OFDM that uses LDPC coding on the index bits performs better than NDC OFDM

Generalized Spatial Modulation in Indoor Wireless Visible Light Communication

In this paper, we investigate the performance of generalized spatial modulation (GSM) in indoor wireless visible light communication (VLC) systems. GSM uses $N_t$ light emitting diodes (LED), but activates only $N_a$ of them at a given time. Spatial modulation and spatial multiplexing are special cases of GSM with $N_{a}=1$ and $N_{a}=N_t$, respectively. We first derive an analytical upper bound on the bit error rate (BER) for maximum likelihood (ML) detection of GSM in VLC systems. Analysis and simulation results show that the derived upper bound is very tight at medium to high signal-to-noise ratios (SNR). The channel gains and channel correlations influence the GSM performance such that the best BER is achieved at an optimum LED spacing. Also, for a fixed transmission efficiency, the performance of GSM in VLC improves as the half-power semi-angle of the LEDs is decreased. We then compare the performance of GSM in VLC systems with those of other MIMO schemes such as spatial multiplexing (SMP), space shift keying (SSK), generalized space shift keying (GSSK), and spatial modulation (SM). Analysis and simulation results show that GSM in VLC outperforms the other considered MIMO schemes at moderate to high SNRs; for example, for 8 bits per channel use, GSM outperforms SMP and GSSK by about 21 dB, and SM by about 10 dB at $10^{-4}$ BER

Design and Evolution of Deep Convolutional Neural Networks in Image Classification – A Review

Convolutional Neural Network(CNN) is a well-known computer vision approach successfully applied for various classification and recognition problems. It has an outstanding power to identify patterns in 1D and 2D data. Though invented in 80's, it became hugely successful after LeCun's work on digit identification. Several CNN based models have been developed to record splendid performance on ImageNet and other databases. Ability of the CNN in learning complex features at different hierarchy from the data had made it the most successful among deep learning algorithms. Innovative architectural designs and hyperaparameter optimization have greatly improved the efficiency of CNN in pattern recognition. This review majorly focuses on the evolution and history of CNN models. Landmark CNN architectures are discussed with their categorization depending on various parameters. In addition, this also explores the architectural details of different layers, activation function, optimizers and other hyperparameters used by CNN. Review concludes by shedding the light on the applications and observations to be considered while designing the network

Design and Evolution of Deep Convolutional Neural Networks in Image Classification – A Review

Convolutional Neural Network(CNN) is a well-known computer vision approach successfully applied for various classification and recognition problems. It has an outstanding power to identify patterns in 1D and 2D data. Though invented in 80's, it became hugely successful after LeCun's work on digit identification. Several CNN based models have been developed to record splendid performance on ImageNet and other databases. Ability of the CNN in learning complex features at different hierarchy from the data had made it the most successful among deep learning algorithms. Innovative architectural designs and hyperaparameter optimization have greatly improved the efficiency of CNN in pattern recognition. This review majorly focuses on the evolution and history of CNN models. Landmark CNN architectures are discussed with their categorization depending on various parameters. In addition, this also explores the architectural details of different layers, activation function, optimizers and other hyperparameters used by CNN. Review concludes by shedding the light on the applications and observations to be considered while designing the network

A model for interacting instabilities and texture dynamics of patterns

A simple model to study interacting instabilities and textures of resulting patterns for thermal convection is presented. The model consisting of twelve-mode dynamical system derived for periodic square lattice describes convective patterns in the form of stripes and patchwork quilt. The interaction between stationary zig-zag stripes and standing patchwork quilt pattern leads to spatiotemporal patterns of twisted patchwork quilt. Textures of these patterns, which depend strongly on Prandtl number, are investigated numerically using the model. The model also shows an interesting possibility of a multicritical point, where stability boundaries of four different structures meet.Comment: 4 pages including 4 figures, page width revise

Initial Virologic Response and HIV Drug Resistance Among HIV-Infected Individuals Initiating First-line Antiretroviral Therapy at 2 Clinics in Chennai and Mumbai, India

Human immunodeficiency virus drug resistance (HIVDR) in cohorts of patients initiating antiretroviral therapy (ART) at clinics in Chennai and Mumbai, India, was assessed following World Health Organization (WHO) guidelines. Twelve months after ART initiation, 75% and 64.6% of participants at the Chennai and Mumbai clinics, respectively, achieved viral load suppression of <1000 copies/mL (HIVDR prevention). HIVDR at initiation of ART (P <.05) and 12-month CD4 cell counts <200 cells/μL (P <.05) were associated with HIVDR at 12 months. HIVDR prevention exceeded WHO guidelines (≥70%) at the Chennai clinic but was below the target in Mumbai due to high rates of loss to follow-up. Findings highlight the need for defaulter tracing and scale-up of routine viral load testing to identify patients failing first-line AR

Quasiperiodic waves at the onset of zero Prandtl number convection with rotation

We show the possibility of quasiperiodic waves at the onset of thermal convection in a thin horizontal layer of slowly rotating zero-Prandtl number Boussinesq fluid confined between stress-free conducting boundaries. Two independent frequencies emerge due to an interaction between a stationary instability and a self-tuned wavy instability in presence of coriolis force, if Taylor number is raised above a critical value. Constructing a dynamical system for the hydrodynamical problem, the competition between the interacting instabilities is analyzed. The forward bifurcation from the conductive state is self-tuned.Comment: 9 pages of text (LaTex), 5 figures (Jpeg format

Genetic Control of Susceptibility to Infection with Candida albicans in Mice

Candida albicans is an opportunistic pathogen that causes acute disseminated infections in immunocompromised hosts, representing an important cause of morbidity and mortality in these patients. To study the genetic control of susceptibility to disseminated C. albicans in mice, we phenotyped a group of 23 phylogenetically distant inbred strains for susceptibility to infection as measured by extent of fungal replication in the kidney 48 hours following infection. Susceptibility was strongly associated with the loss-of-function mutant complement component 5 (C5/Hc) allele, which is known to be inherited by approximately 40% of inbred strains. Our survey identified 2 discordant strains, AKR/J (C5-deficient, resistant) and SM/J (C5-sufficient, susceptible), suggesting that additional genetic effects may control response to systemic candidiasis in these strains. Haplotype association mapping in the 23 strains using high density SNP maps revealed several putative loci regulating the extent of C. albicans replication, amongst which the most significant were C5 (P value = 2.43×10−11) and a novel effect on distal chromosome 11 (P value = 7.63×10−9). Compared to other C5-deficient strains, infected AKR/J strain displays a reduced fungal burden in the brain, heart and kidney, and increased survival, concomitant with uniquely high levels of serum IFNγ. C5-independent genetic effects were further investigated by linkage analysis in an [A/JxAKR/J]F2 cross (n = 158) where the mutant Hc allele is fixed. These studies identified a chromosome 11 locus (Carg4, Candida albicans resistance gene 4; LOD = 4.59), and a chromosome 8 locus (Carg3; LOD = 3.95), both initially detected by haplotype association mapping. Alleles at both loci were inherited in a co-dominant manner. Our results verify the important effect of C5-deficiency in inbred mouse strains, and further identify two novel loci, Carg3 and Carg4, which regulate resistance to C. albicans infection in a C5-independent manner