Identification of spectral lines of elements using artificial neural networks

Artificial neural networks (ANNs) are relatively new computational tools that have found extensive utilization in solving many complex real-world problems. This paper describes how an ANN can be used to identify the spectral lines of elements. The spectral lines of Cadmium (Cd), Calcium (Ca), Iron (Fe), Lithium (Li), Mercury (Hg), Potassium (K) and Strontium (Sr) in the visible range are chosen for the investigation. One of the unique features of this technique is that it uses the whole spectrum in the visible range instead of individual spectral lines. The spectrum of a sample taken with a spectrometer contains both original peaks and spurious peaks. It is a tedious task to identify these peaks to determine the elements present in the sample. ANNs capability of retrieving original data from noisy spectrum is also explored in this paper. The importance of the need of sufficient data for training ANNs to get accurate results is also emphasized. Two networks are examined: one trained in all spectral lines and other with the persistent lines only. The network trained in all spectral lines is found to be superior in analyzing the spectrum even in a noisy environment.

Wideband Low-Distortion Sigma-Delta ADC for WLAN

This work presents a wideband low-distortion sigmadelta analog-to-digital converter (ADC) for Wireless Local Area Network (WLAN) standard. The proposed converter makes use of low-distortion swing suppression SDM architecture which is highly suitable for low oversampling ratios to attain high linearity over a wide bandwidth. The modulator employs a 2-2 cascaded sigma-delta modulator with feedforward path with a single-bit quantizer in the first stage and 4-bit in the second stage. The modulator is designed in TSMC 0.18um CMOS technology and operates at 1.8V supply voltage. Simulation results show that, a peak SNDR of 57dB and a spurious free dynamic range (SFDR) of 66dB is obtained for a 10MHz signal bandwidth, and an oversampling ratio of 8.

Hydrogeology and hydrochemistry of the aquifer systems of Kuttanad area, Kerala: Their role in understanding the evolution of groundwaters

This is an attempt to understand the important factors that control the occurrence, development and hydrochemical evolution of groundwater resources in sedimentary multi aquifer systems. The primary objective of this work is an integrated study of the hydrogeology and hydrochemistry with a view to elucidate the hydrochemical evolution of groundwater resources in the aquifer systems. The study is taken up in a typical coastal sedimentary aquifer system evolved under fluvio-marine environment in the coastal area of Kerala, known as the Kuttanad. The present study has been carried out to understand the aquifer systems, their inter relationships and evolution in the Kuttanad area of Kerala. The multi aquifer systems in the Kuttanad basin were formed from the sediments deposited under fluvio-marine and fluvial depositional environments and the marine transgressions and regressions in the geological past and palaeo climatic conditions influenced the hydrochemical environment in these aquifers. The evolution of groundwater and the hydrochemical processes involved in the formation of the present day water quality are elucidated from hydrochemical studies and the information derived from the aquifer geometry and hydraulic properties. Kuttanad area comprises of three types of aquifer systems namely phreatic aquifer underlain by Recent confined aquifer followed by Tertiary confined aquifers. These systems were formed by the deposition of sediments under fluvio-marine and fluvial environment. The study of the hydrochemical and hydraulic properties of the three aquifer systems proved that these three systems are separate entities. The phreatic aquifers in the area have low hydraulic gradients and high rejected recharge. The Recent confined aquifer has very poor hydraulic characteristics and recharge to this aquifer is very low. The Tertiary aquifer system is the most potential fresh water aquifer system in the area and the groundwater flow in the aquifer is converging towards the central part of the study area (Alleppey town) due to large scale pumping of water for water supply from this aquifer system. Mixing of waters and anthropogenic interferences are the dominant processes modifying the hydrochemistry in phreatic aquifers. Whereas, leaching of salts and cation exchange are the dominant processes modifying the hydrochemistry of groundwater in the confined aquifer system of Recent alluvium. Two significant chemical reactions modifying the hydrochemistry in the Recent aquifers are oxidation of iron in ferruginous clays which contributes hydrogen ions and the decomposition of organic matter in the aquifer system which consumes hydrogen ions. The hydrochemical environment is entirely different in the Tertiary aquifers as the groundwater in this aquifer system are palaeo waters evolved during various marine transgressions and regressions and these waters are being modified by processes of leaching of salts, cation exchange and chemical reactions under strong reducing environment. It is proved that the salinity observed in the groundwaters of Tertiary aquifers are not due to seawater mixing or intrusion, but due to dissolution of salts from the clay formations and ion exchange processes. Fluoride contamination in this aquifer system lacks a regional pattern and is more or less site specific in natureThe lowering of piezometric heads in the Tertiary aquifer system has developed as consequence of large scale pumping over a long period. Hence, puping from this aquifer system is to be regulated as a groundwater management strategy. Pumping from the Tertiary aquifers with high capacity pumps leads to well failures and mixing of saline water from the brackish zones. Such mixing zones are noticed from the hydrochemical studies. This is the major aquifer contamination in the Tertiary aquifer system which requires immediate attention. Usage of pumps above 10 HP capacities in wells taping Tertiary aquifers should be discouraged for sustainable development of these aquifers. The recharge areas need to be identified precisely for recharging the aquifer systems throughartificial means.

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.