8 resultados para non separable data

em Cochin University of Science


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The present investigation on the Muvattupuzha river basin is an integrated approach based on hydrogeological, geophysical, hydrogeochemical parameters and the results are interpreted using satellite data. GIS also been used to combine the various spatial and non-spatial data. The salient finding of the present study are accounted below to provide a holistic picture on the groundwaters of the Muvattupuzha river basin. In the Muvattupuzha river basin the groundwaters are drawn from the weathered and fractured zones. The groundwater level fluctuations of the basin from 1992 to 2001 reveal that the water level varies between a minimum of 0.003 m and a maximum of 3.45 m. The groundwater fluctuation is affected by rainfall. Various aquifer parameters like transmissivity, storage coefficient, optimum yield, time for full recovery and specific capacity indices are analyzed. The depth to the bedrock of the basin varies widely from 1.5 to 17 mbgl. A ground water prospective map of phreatic aquifer has been prepared based on thickness of the weathered zone and low resistivity values (<500 ohm-m) and accordingly the basin is classified in three phreatic potential zones as good, moderate and poor. The groundwater of the Muvattupuzha river basin, the pH value ranges from 5.5 to 8.1, in acidic nature. Hydrochemical facies diagram reveals that most of the samples in both the seasons fall in mixing and dissolution facies and a few in static and dynamic natures. Further study is needed on impact of dykes on the occurrence and movement of groundwater, impact of seapages from irrigation canals on the groundwater quality and resources of this basin, and influence of inter-basin transfer of surface water on groundwater.

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An Overview of known spatial clustering algorithms The space of interest can be the two-dimensional abstraction of the surface of the earth or a man-made space like the layout of a VLSI design, a volume containing a model of the human brain, or another 3d-space representing the arrangement of chains of protein molecules. The data consists of geometric information and can be either discrete or continuous. The explicit location and extension of spatial objects define implicit relations of spatial neighborhood (such as topological, distance and direction relations) which are used by spatial data mining algorithms. Therefore, spatial data mining algorithms are required for spatial characterization and spatial trend analysis. Spatial data mining or knowledge discovery in spatial databases differs from regular data mining in analogous with the differences between non-spatial data and spatial data. The attributes of a spatial object stored in a database may be affected by the attributes of the spatial neighbors of that object. In addition, spatial location, and implicit information about the location of an object, may be exactly the information that can be extracted through spatial data mining

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The Schiff base, 3-hydroxyquinoxaline-2-carboxalidine-4-aminoantipyrine, was synthesized by the condensation of 3-hydroxyquinoxaline-2-carboxaldehyde with 4-aminoantipyrine. HPLC, FT-IR and NMR spectral data revealed that the compound exists predominantly in the amide tautomeric form and exhibits both absorption and fluorescence solvatochromism, large stokes shift, two electron quasireversible redox behaviour and good thermal stability, with a glass transition temperature of 104oC. The third-order non-linear optical character was studied using open aperture Z-scan methodology employing 7 ns pulses at 532 nm. The third-order non-linear absorption coefficient, b, was 1.48 x 10-6 cm W-1 and the imaginary part of the third-order non-linear optical susceptibility, Im c(3), was 3.36 x10-10 esu. The optical limiting threshold for the compound was found to be 340 MW cm-2.

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The Schiff base, 3-hydroxyquinoxaline-2-carboxalidine-4-aminoantipyrine, was synthesized by the condensation of 3-hydroxyquinoxaline-2-carboxaldehyde with 4-aminoantipyrine. HPLC, FT-IR and NMR spectral data revealed that the compound exists predominantly in the amide tautomeric form and exhibits both absorption and fluorescence solvatochromism, large stokes shift, two electron quasireversible redox behaviour and good thermal stability, with a glass transition temperature of 104 oC. The third-order non-linear optical character was studied using open aperture Z-scan methodology employing 7 ns pulses at 532 nm. The third-order non-linear absorption coefficient, b, was 1.48 x 10-6 cm W-1 and the imaginary part of the third-order non-linear optical susceptibility, Im c(3), was 3.36x10-10 esu. The optical limiting threshold for the compound was found to be 340 MW cm-2.

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Non-destructive testing (NDT) is the use of non-invasive techniques to determine the integrity of a material, component, or structure. Engineers and scientists use NDT in a variety of applications, including medical imaging, materials analysis, and process control.Photothermal beam deflection technique is one of the most promising NDT technologies. Tremendous R&D effort has been made for improving the efficiency and simplicity of this technique. It is a popular technique because it can probe surfaces irrespective of the size of the sample and its surroundings. This technique has been used to characterize several semiconductor materials, because of its non-destructive and non-contact evaluation strategy. Its application further extends to analysis of wide variety of materials. Instrumentation of a NDT technique is very crucial for any material analysis. Chapter two explores the various excitation sources, source modulation techniques, detection and signal processing schemes currently practised. The features of the experimental arrangement including the steps for alignment, automation, data acquisition and data analysis are explained giving due importance to details.Theoretical studies form the backbone of photothermal techniques. The outcome of a theoretical work is the foundation of an application.The reliability of the theoretical model developed and used is proven from the studies done on crystalline.The technique is applied for analysis of transport properties such as thermal diffusivity, mobility, surface recombination velocity and minority carrier life time of the material and thermal imaging of solar cell absorber layer materials like CuInS2, CuInSe2 and SnS thin films.analysis of In2S3 thin films, which are used as buffer layer material in solar cells. The various influences of film composition, chlorine and silver incorporation in this material is brought out from the measurement of transport properties and analysis of sub band gap levels.The application of photothermal deflection technique for characterization of solar cells is a relatively new area that requires considerable attention.The application of photothermal deflection technique for characterization of solar cells is a relatively new area that requires considerable attention. Chapter six thus elucidates the theoretical aspects of application of photothermal techniques for solar cell analysis. The experimental design and method for determination of solar cell efficiency, optimum load resistance and series resistance with results from the analysis of CuInS2/In2S3 based solar cell forms the skeleton of this chapter.

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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.

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In this paper we try to fit a threshold autoregressive (TAR) model to time series data of monthly coconut oil prices at Cochin market. The procedure proposed by Tsay [7] for fitting the TAR model is briefly presented. The fitted model is compared with a simple autoregressive (AR) model. The results are in favour of TAR process. Thus the monthly coconut oil prices exhibit a type of non-linearity which can be accounted for by a threshold model.

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Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially useful and ultimately understandable patterns from data. The term Data mining refers to the process which does the exploratory analysis on the data and builds some model on the data. To infer patterns from data, data mining involves different approaches like association rule mining, classification techniques or clustering techniques. Among the many data mining techniques, clustering plays a major role, since it helps to group the related data for assessing properties and drawing conclusions. Most of the clustering algorithms act on a dataset with uniform format, since the similarity or dissimilarity between the data points is a significant factor in finding out the clusters. If a dataset consists of mixed attributes, i.e. a combination of numerical and categorical variables, a preferred approach is to convert different formats into a uniform format. The research study explores the various techniques to convert the mixed data sets to a numerical equivalent, so as to make it equipped for applying the statistical and similar algorithms. The results of clustering mixed category data after conversion to numeric data type have been demonstrated using a crime data set. The thesis also proposes an extension to the well known algorithm for handling mixed data types, to deal with data sets having only categorical data. The proposed conversion has been validated on a data set corresponding to breast cancer. Moreover, another issue with the clustering process is the visualization of output. Different geometric techniques like scatter plot, or projection plots are available, but none of the techniques display the result projecting the whole database but rather demonstrate attribute-pair wise analysis