On the magnetic and dielectric properties of nickel–neoprene nanocomposites

Nickel nanocomposites were prepared by incorporating nickel nanoparticles in a neoprene matrix according to a specific recipe for various loadings of nickel particles. The dielectric properties of these composites were evaluated for different frequencies ranging from 100 kHz to 8MHz at different temperatures from 30 ◦C to 120 ◦C. The dielectric permittivity increases with increase of nickel concentration. Increase in temperature enhances the permittivity initially, till 40 ◦C and thereafter the permittivity decreases. The dielectric loss exhibits relaxation peaks and the peaks shift to lower frequencies with increase in volume fraction of the nickel nanoparticles in the matrix. The evaluation of magnetic and dielectric properties of these composites suggests that the dielectric permittivity can be tailored by an appropriate loading of the filler using semi-empirical equations and the magnetic properties vary according to simple mixture equations

Creation and Annihilation of Fluxons in ac‐driven Semi-annular Josephson Junction

A new geometry (semiannular) for Josephson junction has been proposed and theoretical studies have shown that the new geometry is useful for electronic applications [1, 2]. In this work we study the voltage‐current response of the junction with a periodic modulation. The fluxon experiences an oscillating potential in the presence of the ac‐bias which increases the depinning current value. We show that in a system with periodic boundary conditions, average progressive motion of fluxon commences after the amplitude of the ac drive exceeds a certain threshold value. The analytic studies are justified by simulating the equation using finite‐difference method. We observe creation and annihilation of fluxons in semiannular Josephson junction with an ac‐bias in the presence of an external magnetic field.

A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

Significance Of Product Type And Brand In The Purchasing Behaviour Of Cattle Feeds: An Empirical Study In Kerala

Cattle feed industry is a major segment of animal feed industry. This industry is gradually evolving into an organized sector and the feed manufactures are increasingly using modern and sophisticated methods that seek to incorporate best global practices. This industry has got high potential for growth in India, given the fact that the country is the world’s leading producer of milk and its production is expected to grow at a compounded annual growth rate of 4 per cent. Besides, the concept of branded cattle feed as a packaged commodity is fast gaining popularity in rural India. There can be a positive change in the demand for cattle feed because of factors like (i) shrinkage of open land for cattle grazing, urbanization and resultant shortage of conventionally used cattle feeds, and (ii) introduction of high yield cattle requires specialized feeds. Earlier research studies done by the present authors have revealed the significant growth prospects of the branded cattle feed industry, the feed consumption pattern and the relatively high share of branded feeds, feed consumption pattern based on product types (like, pellet and mash), composition of cattle feed market and the relatively large shares of Kerala Feeds Ltd. (KFL) and Kerala Solvent Extractions Ltd. (KSE) brands, the major factors influencing the purchasing decisions etc. As a continuation of the earlier studies, this study makes a closer look into the significance of product types in the buyer behavior, level of awareness about the brand and its implications on purchasing decisions, and the brandshifting behavior and its determinants

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

FEM based Virtual Prototyping and Design of Third Harmonic Excitation System for Low Voltage Brushless Alternators

Salient pole brushless alternators coupled to IC engines are extensively used as stand-by power supply units for meeting in- dustrial power demands. Design of such generators demands high power to weight ratio, high e ciency and low cost per KVA out- put. Moreover, the performance characteristics of such machines like voltage regulation and short circuit ratio (SCR) are critical when these machines are put into parallel operation and alterna- tors for critical applications like defence and aerospace demand very low harmonic content in the output voltage. While designing such alternators, accurate prediction of machine characteristics, including total harmonic distortion (THD) is essential to mini- mize development cost and time. Total harmonic distortion in the output voltage of alternators should be as low as possible especially when powering very sophis- ticated and critical applications. The output voltage waveform of a practical AC generator is replica of the space distribution of the ux density in the air gap and several factors such as shape of the rotor pole face, core saturation, slotting and style of coil disposition make the realization of a sinusoidal air gap ux wave impossible. These ux harmonics introduce undesirable e ects on the alternator performance like high neutral current due to triplen harmonics, voltage distortion, noise, vibration, excessive heating and also extra losses resulting in poor e ciency, which in turn necessitate de-rating of the machine especially when connected to non-linear loads. As an important control unit of brushless alternator, the excitation system and its dynamic performance has a direct impact on alternator's stability and reliability. The thesis explores design and implementation of an excitation i system utilizing third harmonic ux in the air gap of brushless al- ternators, using an additional auxiliary winding, wound for 1=3rd pole pitch, embedded into the stator slots and electrically iso- lated from the main winding. In the third harmonic excitation system, the combined e ect of two auxiliary windings, one with 2=3rd pitch and another third harmonic winding with 1=3rd pitch, are used to ensure good voltage regulation without an electronic automatic voltage regulator (AVR) and also reduces the total harmonic content in the output voltage, cost e ectively. The design of the third harmonic winding by analytic methods demands accurate calculation of third harmonic ux density in the air gap of the machine. However, precise estimation of the amplitude of third harmonic ux in the air gap of a machine by conventional design procedures is di cult due to complex geome- try of the machine and non-linear characteristics of the magnetic materials. As such, prediction of the eld parameters by conven- tional design methods is unreliable and hence virtual prototyping of the machine is done to enable accurate design of the third har- monic excitation system. In the design and development cycle of electrical machines, it is recognized that the use of analytical and experimental methods followed by expensive and in exible prototyping is time consum- ing and no longer cost e ective. Due to advancements in com- putational capabilities over recent years, nite element method (FEM) based virtual prototyping has become an attractive al- ternative to well established semi-analytical and empirical design methods as well as to the still popular trial and error approach followed by the costly and time consuming prototyping. Hence, by virtually prototyping the alternator using FEM, the important performance characteristics of the machine are predicted. Design of third harmonic excitation system is done with the help of results obtained from virtual prototype of the machine. Third harmonic excitation (THE) system is implemented in a 45 KVA ii experimental machine and experiments are conducted to validate the simulation results. Simulation and experimental results show that by utilizing third harmonic ux in the air gap of the ma- chine for excitation purposes during loaded conditions, triplen harmonic content in the output phase voltage is signi cantly re- duced. The prototype machine with third harmonic excitation system designed and developed based on FEM analysis proved to be economical due to its simplicity and has the added advan- tage of reduced harmonics in the output phase voltage.