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.

Geochemistry of transition, non-transition and rare-earth elements in the surficial sediments of continental shelf of Kerala and an annex to the Cochin estuarine system

The metals present in the surface sediments have high demand on a global perspective, and the main reservoir of these elements is believed to be the ocean floor. A lot of studies on metals are going on throughout the world for its quantification and exploitation. Even though, some preliminary attempts have been made in selected areas for the quantitative study of metals in the western continental shelf of India, no comprehensive work has been reported so far. The importance of this study also lies on the fact that there has not been a proper evaluation of the impact of the Great Tsunami of 2004 on the coastal areas of the south India. In View of this, an attempt has been made to address the seasonal distribution, behavior and mechanisms which control the deposition of metals in the sediments of the western continental shelf and Cochin Estuary, an annex to this coastal marine region.Surface sediment samples were collected seasonally from two subenvironemnts of southwest coast of India, (continental shelf of Kerala and Cochin estuarine system), to estimate the seasonal distribution and geochemical behavior of non-transition, transition, rare-earth elements, Th and U. Bottom water samples were also taken from each station, and analysed for temperature, salinity and dissolved oxygen, hence the response of redox sensitive elements to oxygen minimum zone can be addressed. In addition, other sedimentary parameters such as sand, silt, clay fractions, CaCO3 and organic carbon content were also estimated to evaluate the control factors on level of metals present in the sediment. The study used different environmental data analysis techniques to evaluate the distribution and behavior of elements during different seasons. This includes environmental parameters such as elemental normalisation, enrichment factor, element excess, cerium and europium anomalies and authigenic uranium.