OFFLINE AND ONLINE SOLID PHASE EXTRACTION/PRECONCENTRATION OF INORGANICS

Solid phase extraction (SPE) is a powerful technique for preconcentration/removal or separation of trace and ultra trace amounts of toxic and nutrient elements. SPE effectively simplifies the labour intensive sample preparation, increase its reliability and eliminate the clean up step by using more selective extraction procedures. The synthesis of sorbents with a simplified procedure and diminution of the risks of errors shows the interest in the areas of environmental monitoring, geochemical exploration, food, agricultural, pharmaceutical, biochemical industry and high purity metal designing, etc. There is no universal SPE method because the sample pretreatment depends strongly on the analytical demand. But there is always an increasing demand for more sensitive, selective, rapid and reliable analytical procedures. Among the various materials, chelate modified naphthalene, activated carbon and chelate functionalized highly cross linked polymers are most important. In the biological and environmental field, large numbers of samples are to be analysed within a short span of time. Hence, online flow injection methods are preferred as they allow extraction, separation, identification and quantification of many numbers of analytes. The flow injection online preconcentration flame AAS procedure developed allows the determination of as low as 0.1 µg/l of nickel in soil and cobalt in human hair samples. The developed procedure is precise and rapid and allows the analysis of 30 samples per hour with a loading time of 60 s. The online FI manifold used in the present study permits high sampling, loading rates and thus resulting in higher preconcentration/enrichment factors of -725 and 600 for cobalt and nickel respectively with a 1 min preconcentration time compared to conventional FAAS signal. These enrichment factors are far superior to hitherto developed on line preconcentration procedures for inorganics. The instrumentation adopted in the present study allows much simpler equipment and low maintenance costs compared to costlier ICP-AES or ICP-MS instruments.

Inventory management in public sector electrical industry in Kerala

The thesis entitled Inventory Management In Public Sector Electrical Industry In Kerala. Investigations were carried out on inventory management in public sector electrical industry in Kerala and suggest methods to improve their efficiency. Various aspects of inventory management, its scope and need in industry are detailed. The objectives of the present study concentrates to get an overall view of the system of inventory management, assess the positions and levels of inventory. It analyzes the inventory management policies and practices, the organizational set-up for materials by the electrical undertakings. The study examines the liquidity of the electrical undertakings as well as techniques of inventory management in the electrical industry in Kerala. Hypotheses state that the existing organizational systems and practices are inadequate to ensure efficient management of inventories in electrical industry. Introduction of scientific inventory techniques has a favourable effect on the workings of inventory departments. The financial performance of the public sector electrical undertakings is not at all satisfactory on account of the high raw material costs, heavy borrowings and huge interest burdens. The scope of this study is limited to the assessment of savings, in inventories of electrical products due to inventory management. The methodology of the study is to project the cost reduction of the inventory department on the basis of data collected and to validate this projection with the aid of analysis and survey. The limitations of the study is that the data obtained relate to the period 1989-90 and earlier and the current position is not available and uniform norms cannot be applied to evaluate different inventory management organisation.

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.