DIB - A Novel Optimized VANET Traffic Management Using a Deep Neural Network

The advancement of the Internet of Things (IoT) establishes the development of the Internet of Vehicles (IoV) and Intelligent Transportation Systems (ITS).  An integral part of ITS is the vehicular ad hoc network (VANET) with smart vehicles (SV).   In this research, a dynamic method of traffic regulation in VANET is presented using Deep Neural Networks (DNN) and Bat Algorithms (BA). With a reduced average delay, the former (DNN) is utilized to guide vehicles across very crowded routes to increase efficiency. In order to examine the traffic congestion status between network nodes, BA is integrated with the IoT and moved over VANETs. Experiments were conducted to test the effectiveness of the proposed method with various parameters such as average latency, packet delivery ratio (PDR) and throughput and the performance were compared with different machine learning (ML) algorithms.  The simulation outputs proved that the proposed technique supports real-time traffic circumstances with less energy usage and delay than existing methods

Design and Implementation of Intelligent Traffic-Management System for Smart Cities using Roaming Agent and Deep Neural Network (RAD2N)

In metropolitan areas, the exponential growth in quantity of vehicles has instigated gridlock, pollution, and delays in the transportation of freight. IoT is the modern revolution which pushes the world towards intelligent management systems and automated procedures. This makes a significant contribution to automation and intelligent societies. Traffic regulation and effective congestion management assist conserve many priceless resources. In order to recognize, collect and send data, autonomous vehicles are furnished with IoT powered Intelligent Traffic Management System (ITMS) having a set of sensors.  Moreover, machine learning (ML) algorithms can also be employed to enhance the transportation system.  Traffic jams, delays, and a high death rate are the results of the problems that the current transport management systems face.  In this paper, an active traffic control for VANET is proposed which merges Roaming Agents (RA) with deep neural networks (DNN). The effectiveness of the DNN with RA (RAD2N) routing method in VANETs is evaluated experimentally and compared with the traditional ML and other DL routing algorithms. Several traffic congestion indicators, including delay, packet delivery ratio (PDR) and throughput are used to validate RAD2N. The outcomes demonstrate that the proposed approach delivers lower latency and energy consumption

Natural plant resources in anti-cancer therapy-A review

Cancer is one of the most common devastating disease affecting millions of people peryear. Cancer has been estimated as the second leading cause of death in humans. So therehas been an intense search on various biological sources to develop a novel anti-cancer drugto combat this disease. Plants have proved to be an important natural source of anti-cancertherapy for several years. About 30 plant derived compounds have been isolated so far andare currently under clinical trials. These anti-cancer compounds have been found to beclinically active against various types of cancer cells. Further research in this area may leadto better treatment of cancer

Determining the sign of Δ31\Delta_{31} at long baseline neutrino experiments

Recently it is advocated that high intensity and low energy $(E_\nu \sim 2 GeV)$ neutrino beams should be built to probe the $(13)$ mixing angle $\phi$ to a level of a few parts in $10^4$. Experiments using such beams will have better signal to background ratio in searches for $\nu_\mu \to \nu_e$ oscillations. We propose that such experiments can also determine the sign of $\Delta_{31}$ even if the beam consists of {\it neutrinos} only. By measuring the $\nu_\mu \to \nu_e$ transitions in two different energy ranges, the effects due to propagation of neutrinos through earth's crust can be isolated and the sign of $\Delta_{31}$ can be determined. If the sensitivity of an experiment to $\phi$ is $\epsilon$, then the same experiment is automatically sensitive to matter effects and the sign of $\Delta_{31}$ for values of $\phi \geq 2 \epsilon$.Comment: Title changed and paper rewritten. 4 pages, 1 figure, revte

Topologically-Protected Qubits from a Possible Non-Abelian Fractional Quantum Hall State

The Pfaffian state is an attractive candidate for the observed quantized Hall plateau at Landau level filling fraction $\nu=5/2$. This is particularly intriguing because this state has unusual topological properties, including quasiparticle excitations with non-Abelian braiding statistics. In order to determine the nature of the $\nu=5/2$ state, one must measure the quasiparticle braiding statistics. Here, we propose an experiment which can simultaneously determine the braiding statistics of quasiparticle excitations and, if they prove to be non-Abelian, produce a topologically-protected qubit on which a logical NOT operation is performed by quasiparticle braiding. Using the measured excitation gap at $\nu=5/2$, we estimate the error rate to be $10^{-30}$ or lower

Assessment of nitrogen utilization from urea applied in rubber seedling nursery using 15N tracer technique

Nitrogen uptake from urea applied to rubber seedlings in the nursery was evaluated using 15N tracer methodology, in micro-plots established in the field. Effect of varying rates of N on growth, and the relative contribution of soil N and fertilizer N towards total N uptake were studied. Influence of rate of N application on growth of seedlings was observed up to three months, and after six months, growth of plants was comparable for all the four N levels. The efficiency of N absorption by the plant, expressed as percentage N utilization ranged from 13.62 per cent at 125 kg N ha-1 to 5.84 per cent at 500 kg N ha-1. The 15N balance sheet averaged over the four levels of N shows that about 9.27 per cent of applied N was taken up by rubber seedlings, about 8.78 per cent remained in 0-60 cm depth of soil and about 81.95 per cent was unaccounted N

ANALYITCAL METHOD DEVELOPMENT AND VALIDATION OF A REVERSED-PHASE HIGHPERFORMANCE LIQUID CHROMATOGRAPHY FOR THE DETERMINATION OF MODAFINIL IN BULK AND PHARMACEUTICAL DOSAGE FORMS

Objective: To development and validation of a reversed-phase high-performance liquid chromatography (RP-HPLC) for the determination of modafinil in bulk and pharmaceutical dosage forms.Methods: A simple, precise, rapid, and accurate RP-HPLC method was developed for the estimation of modafinil in bulk and pharmaceutical dosageforms. Xterra RP 18 (250 mm × 4.6 mm, 5 μ particle size) with a mobile phase consisting of methanol:water 70:30 V/V was used. The flow rate1.0 ml/min and the effluents were monitored at 260 nm. The retention time and recovery time was 12 minutes. The detector response was linear inthe concentration of 10-50 μg/ml. The respective linear regression equation being Y=452.1x+65237. The limit of detection and limit of quantificationwere 4.547 and 1.377 mcg, respectively. The method was validated by determining its accuracy, precision, and system suitability.Result: The objective of the present work is to develop simple, precise, and reliable HPLC method for the analysis of modafinil in bulk andpharmaceutical dosage forms. This is achieved using the most commonly employed Xterra RP 18 (250 mm × 4.6 mm, 5 μ particle size) columndetection at 260 nm. The present method was validated according to ICH guidelines.Conclusion: In this study, a simple, fast and reliable HPLC method was developed and validated for the determination of modafinil in pharmaceuticalformulations.Keywords: Modafinil, Reversed-phase high-performance liquid chromatography, Estimation, ICH guidelines, Tablets

Genome scanning for identification of resistance gene analogs (RGAs) in a highly durable blast resistance rice (Oryza sativa L.) cultivar, Moroberekan

Disease resistance in plants is a desirable economic trait. Many disease resistance genes from various plants have been cloned so far. The gene products of some of these can be distinguished by the presence of an N terminal nucleotide binding site and a C-terminal stretch of leucine-rich repeats. Oligonucleotides already designed from sequence motifs conserved between resistance N genes of tobacco and RPS2 of Arabidopsis thaliana were used as PCR primers (AS1/S2) to scan the rice blast disease resistant moroberekan genomic DNA. The primer pairs RL, CL and tobacco N gene which were used based on leucine-rich repeat regions of genes RPS2 in Arabidopsis, Cf9 of tomato against Cladosporium fulvum and N gene of tobacco confers resistance to the viral pathogen, tobacco mosaic virus respectively. The fragment amplified by the primer AS1/S2 was cloned and sequenced. The PCR products for the other three primers were sequenced directly. Homology search of the resultant nucleotide sequences and deduced amino acid sequences with the reported sequences available in public data bases of NCBI BLASTn and PSI blast indicated the presence of resistance protein-like gene in BRGA-1(blast resistant gene analogue-1), putative retro-elements and putative retro-transposons proteins in BRGA-2, mitochondrial DNA in BRGA-3 and NBS-LRR type resistance protein and NB-ARC domain containing expressed protein of Oryza sativa in BRGA-4.Key words: Disease resistance, Magnaporthe grisea, leucine-rich repeats (LRR), Nucleotide-binding site (NBS), retrotransposon, rice blast disease, Oryza sativa L

Outsourced Analysis of Encrypted Graphs in the Cloud with Privacy Protection

Huge diagrams have unique properties for organizations and research, such as client linkages in informal organizations and customer evaluation lattices in social channels. They necessitate a lot of financial assets to maintain because they are large and frequently continue to expand. Owners of large diagrams may need to use cloud resources due to the extensive arrangement of open cloud resources to increase capacity and computation flexibility. However, the cloud's accountability and protection of schematics have become a significant issue. In this study, we consider calculations for security savings for essential graph examination practices: schematic extraterrestrial examination for outsourcing graphs in the cloud server. We create the security-protecting variants of the two proposed Eigen decay computations. They are using two cryptographic algorithms: additional substance homomorphic encryption (ASHE) strategies and some degree homomorphic encryption (SDHE) methods. Inadequate networks also feature a distinctively confidential info adaptation convention to allow the trade-off between secrecy and data sparseness. Both dense and sparse structures are investigated. According to test results, calculations with sparse encoding can drastically reduce information. SDHE-based strategies have reduced computing time, while ASHE-based methods have reduced stockpiling expenses

Universality of scaling and multiscaling in turbulent symmetric binary fluids

We elucidate the universal scaling and multiscaling properties of the nonequilibrium steady states (NESS) in a driven symmetric binary fluid (SBF) mixture in its homogeneous miscible phase in three dimensions (3d). We show, for the first time, via Direct Numerical Simulations (DNS) that structure functions of the velocity and the concentration gradient exhibit multiscaling in 3d and extended self-similarity (ESS). We also find that, in contrast to the well-known passive scalar turbulence problem, structure functions of the concentration show simple scaling. We propose a new shell model for SBF turbulence which preserve all the invariances in the ideal limit of the SBF equations and which reduces to a well-known shell model for fluid turbulence in the zero concentration field limit. We show that the shell model has the same scaling properties as the 3d SBF equations. Our combined results from our DNS of the SBF equations and shell-model studies consistently bring out the multiscaling of the velocity and concentration gradient fields and simple scaling of the concentration field.Comment: 8 pages, 10 figures, published in Phys. Rev.