2 resultados para Complexity of Distribution
em Cochin University of Science
Resumo:
The overall focus of the thesis involves the systematics,germplasm evaluation and pattern of distribution and abundance of freshwater fishes of kerala (india).Biodiversity is the measure of variety of Life.With the signing on the convention on biodiversity, the countries become privileged with absolute rights and responsibility to conserve and utilize their diverse resources for the betterment of mankind in a sustainable way. South-east Asia along with Africa and South America were considered to be the most biodiversity rich areas in the world .The tremendous potential associated with the sustainable utilization of fish germplasm resources of various river systems of Kerala for food, aquaculture and ornamental purposes have to be fully tapped for economic upliftment of fisherman community and also for equitable sharing of benefits among the mankind without compromising the conservation of the rare and unique fish germplasm resources for the future generations.The study was carried during April 2000 to December 2004. 25 major river systems of Kerala were surveyed for fish fauna for delineating the pattern of distribution and abundance of fishes both seasonally and geographically.The results of germplasm inventory and evaluation of fish species were presented both for the state and also river wise. The results of evaluation of fish species for their commercial utilization revealed that, of the 145, 76 are ornamental, 47 food and 22 cultivable. 21 species are strictly endemic to Kerala rivers. The revalidation on biodiversity status of the fishes assessed based on IUCN is so alarming that a high percentage of fishes (59spp.) belong to threatened category which is inclusive of 8 critically ndangered (CR), 36 endangered and 15 species under vulnerable (VU) category.The river wise fish germplasm inventory surveys were conducted in 25 major river systems of Kerala.The results of the present study is indicative of existence of several new fish species in the streams and rivulets located in remote areas of the forests and therefore, new exclusive surveys are required to surface fish species new to science, new distributional records etc, for the river systems.The results of fish germplasm evaluation revealed that there exist many potential endemic ornamental and cultivable fishes in Kerala. It is found imperative to utilize these species sustainably for improving the aquaculture production and aquarium trade of the country which would definitely fetch more income and generate employment.
Resumo:
Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.