Algorithms for Fast Aggregated Convergecast in Sensor Networks

Fast and periodic collection of aggregated data is of considerable interest for mission-critical and continuous monitoring applications in sensor networks. In the many-to-one communication paradigm, referred to as convergecast, we focus on applications wherein data packets are aggregated at each hop en-route to the sink along a tree-based routing topology, and address the problem of minimizing the convergecast schedule length by utilizing multiple frequency channels. The primary hindrance in minimizing the schedule length is the presence of interfering links. We prove that it is NP-complete to determine whether all the interfering links in an arbitrary network can be removed using at most a constant number of frequencies. We give a sufficient condition on the number of frequencies for which all the interfering links can be removed, and propose a polynomial time algorithm that minimizes the schedule length in this case. We also prove that minimizing the schedule length for a given number of frequencies on an arbitrary network is NP-complete, and describe a greedy scheme that gives a constant factor approximation on unit disk graphs. When the routing tree is not given as an input to the problem, we prove that a constant factor approximation is still achievable for degree-bounded trees. Finally, we evaluate our algorithms through simulations and compare their performance under different network parameters

Reflectivity Parameter Extraction from RADAR Images Using Back Propagation Algorithm

Pattern recognition has been acknowledged as one of the promising research areas and it has drawn the awareness among many researchers since its existence at the beginning of the nineties. Multilayer Neural networks are used in pattern Recognition and classification based on the features derived from the input patterns. The Reflectivity information extracted from the Doppler Weather Radar (DWR) image helps in identifying the convective cloud type which has a strong relation to the precipitation rate. The reflectivity information is rooted in the DWR image with the help of colors and color bar is provided to distinguish among different reflectivity information. Artificial Neural network predicts the color based on the maximum likelihood estimation problem. This paper presents a best possible backpropagation algorithm for color identification in DWR images by comparing various backpropagation algorithms such as LevenbergMarquardt, Conjugate gradient, and Resilient back propagation etc.,. Pattern recognition using Neural networks presents better results compared to standard distance measures. It is observed that Levenberg-Marquardt backpropagation algorithm yields a regression value of 99% approximately and accuracy of 98

Electron-photon scattering mediated by localized plasmons: A quantitative analysis by eigen-response theory

We show that the scattering interaction between a high energy electron and a photon can be strongly enhanced by different types of localized plasmons in a non-trivial way. The scattering interaction is predicted by an eigen-response theory, numerically verified by finite-difference-time-domain simulation, and experimentally verified by cathodoluminescence spectroscopy. We find that the scattering interaction associated with dark plasmons can be as strong as that of bright plasmons. Such a strong interaction may offer new opportunities to improve single-plasmon detection and high-resolution characterization techniques for high quality plasmonic materials.Comment: 4 pages, 4 figures (excluding Supporting Information

On the use of phase of the Fourier transform for face recognition under variations in illumination

In this paper, we propose a representation of the face image based on the phase of the 2-D Fourier transform of the image to overcome the adverse effect of illumination. The phase of the Fourier transform preserves the locations of the edges of a given face image. The main problem in the use of the phase spectrum is the need for unwrapping of the phase. The problem of unwrapping is avoided by considering two functions of the phase spectrum rather than the phase directly. Each of these functions gives partial evidence of the given face image. The effect of noise is reduced by using the first few eigenvectors of the eigenanalysis on the two phase functions separately. Experimental results on combining the evidences from the two phase functions show that the proposed method provides an alternative representation of the face images for dealing with the issue of illumination in face recognition

SPECTROSCOPIC AND VOLUMETRIC TECHNIQUES FOR THE ESTIMATION OF IVABRADINE IMPURITY 3,3'-(PROPANE-1,3-DIYL)BIS(7,8-DIMETHOXY-1,3,4,5-TETRAHYDRO-2H-BENZO[D]AZEPIN-2-ONE)

Objective: Two simple and sensitive techniques - one spectrophotometric and one titrimetric- have been developed for the determination of 3,3'-(propane-1,3-diyl)bis(7,8-dimethoxy-1,3,4,5-tetrahydro-2H-benzo[d]azepin-2-one) commonly known as ivabradine impurity-9 (IVA-9). Methods: The spectrophotometric method is based on the oxidation of drug impurity by excess cerium (IV) sulphate in acidic medium and the subsequent reaction of the remaining Ce(IV) with a known amount of ferrous ammonium sulphate. The resultant ferric ion is then made to react with thiocyanate in acid medium to form a brown coloured complex which is analyzed spectrophotometrically against the reagent blank. In the volumetric method, the un-reacted Ce(IV) is titrated against standard ferrous ammonium sulphate to estimate the quantity of IVA-9. Results: The colored complex showed an absorption maximum at 479 nm when measured  spectrophotometrically. The stated methods are validated statistically using the International Council for Harmonization guidelines-ICH Q2(R1) for precision and accuracy. The method showed a linear response from 0.5 to 100µg/ml with a correlation coefficient of 0.9985 Conclusion : No estimation techniques have been reported to date for the determination of this molecule. The proposed techniques may be used for the routine quantification in its pure form and also in presence of its parent drug molecule Ivabradine

Simulation of Five Level Diode Clamped Multilevel Inverter

The power electronics device which converts DC power to AC power at required output voltage and frequency level is known as inverter. The voltage source inverters produce an output voltage or a current with levels either 0 or +ve or-ve V dc. They are known as two-level inverters. Multilevel inverter is to synthesize a near sinusoidal voltage from several levels of dc voltages. Multilevel inverter has advantage like minimum harmonic distortion. Multi-level inverters are emerging as the new breed of power converter options for high power applications. They typically synthesize the stair-case voltage waveform (from several dc sources) which has reduced harmonic content. Multi-level inverters have many attractive features, high voltage capability, reduced common mode voltages near sinusoidal outputs, low dv/dt, and smaller or even no output filter; sometimes no transformer is required at the input side, called the transformer-less solution, making them suitable for high power applications In this paper a 5-level Diode clamped multilevel inverter is developed by IGBTS using Simulink. Gating signals for these IGBTS have been generated by designing comparators. In order to maintain the different voltage levels at appropriate intervals, the conduction time intervals of IGBT have been maintained by controlling the pulse width of gating pulses[6] (by varying the reference signals magnitude of the comparator). The simulation results for 5-level and THD for the output have been identified by MATLAB/SIMULINK

Design and Analysis of Multilevel Inverter with Reduced Number of Switches using Multicarrier SPWM Techniques

Multi-level inverter has been widely accepted for high voltage applications. Their performance is highly superior to that of conventional two level inverter due to reduced harmonic distortion, lower electromagnetic interference and higher dc link voltages. Multi-level inverter (MLI) has some disadvantages such as increased number of components, complex pulse width modulation control method, and voltage-balancing problem. In order to increase the level of the output, the numbers of switches are increased and losses and complexity also increased. Hence to reduce these losses and complexity, a new topology is designed in this project i.e. Multi-level inverter (MLI) with reduced number of switches. A new inverter topology has been proposed which has superior features over conventional topologies in terms of the required power switches and isolated dc supplies, control requirements and reliability. In the mentioned topology, the switching operation is separated into high- and low-frequency parts. Design and simulation analysis of new 7 level inverter topology with multicarrier spwm techniques is presented in this project thesis using MATLAB/SIMULIN