493 resultados para Automatized Indexing


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The wealth of information available freely on the web and medical image databases poses a major problem for the end users: how to find the information needed? Content –Based Image Retrieval is the obvious solution.A standard called MPEG-7 was evolved to address the interoperability issues of content-based search.The work presented in this thesis mainly concentrates on developing new shape descriptors and a framework for content – based retrieval of scoliosis images.New region-based and contour based shape descriptor is developed based on orthogonal Legendre polymomials.A novel system for indexing and retrieval of digital spine radiographs with scoliosis is presented.

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To assess the prevalence of faecal coliform bacteria and multiple drug resistance among Escherichia coli and Salmonella serotypes from Vembanadu Lake. Study design: Systematic microbiological testing. Methods: Monthly collection of water samples were made from ten stations on the southern and northern parts of a salt water regulator constructed in Vembanadu Lake in order to prevent incursion of seawater during certain periods of the year. Density of faecal colifrom bacteria was estimated. E. coli and Salmonella were isolated and their different serotypes were identified. Antibiotic resistance analysis of E. coli and Salmonella serotypes was done and the MAR index of individual isolates was calculated. Results: Density of faecal coliform bacteria ranged from mean MPN value 2900 -7100/100ml. Results showed multiple drug resistance pattern among the bacterial isolates. E. coli showed more than 50% resistance to amickacin, oxytetracycline, streptomycin, tetracycline and kanamycin while Salmonella showed high resistance to oxytetracycline, streptomycin, tetracycline and ampicillin. The MAR indexing of the isolates showed that they have originated from high risk source such as humans, poultry and dairy cows. Conclusions: The high density of faecal coliform bacteria and prevalence of multi drug resistant E. coli and Salmonella serotypes in the lake may pose severe public health risk through related water borne and food borne outbreaks

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Water quality of rooftop-collected rainwater is an issue of increased interest particularly in developing countries where the collected water is used as a source of drinking water. Bacteriological and chemical parameters of 25 samples of rooftop-harvested rainwater stored in ferrocement tanks were analyzed in the study described in this article. Except for the pH and lower dissolved oxygen levels, all other physicochemical parameters were within World Health Organization guidelines. Bacteriological results revealed that the rooftop-harvested rainwater stored in tanks does not often meet the bacteriological quality standards prescribed for drinking water. Fifty percent of samples of harvested rainwater for rural and urban community use and 20% of the samples for individual household use showed the presence of E. coli. Fecal coliform/fecal streptococci ratios revealed nonhuman animal sources of fecal pollution. Risk assessment of bacterial isolates from the harvested rainwater showed high resistance to ampicillin, erythromycin, penicillin, and vancomycin. Multiple antibiotic resistance (MAR) indexing of the isolates and elucidation of the resistance patterns revealed that 73% of the isolates exhibited MAR

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A total of eighty-one Escherichia coli isolates belonging to forty-three different serotypes including several pathogenic strains such as enterotoxigenic E. coli (ETEC), enterohaemorrhagic E. coli (EHEC), enteropathogenic E. coli (EPEC) and uropathogenic E. coli (UPEC) isolated from Cochin estuary between November 2001 and October 2002 were tested against twelve antibiotics to determine the prevalence of multiple antibiotic resistance (MAR) and antimicrobial resistance profiles as a measure of high risk source of contamination. The results revealed that more than 95% of the isolates were multiple antibiotic resistant (resistant to more than three antibiotics). The MAR indexing of the isolates showed that all these strains originated from high risk source of contamination. The incidence of multiple antibiotic resistant E. coli especially the pathogenic strains in natural waters will pose a serious threat to human population

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A toatal of 81 Escherichia coliisolates belonging to 43 different serotypes including several pathogenic strains such as enterotoxigenic E.coli isolated from a tropical estuary were tested against 12 antibiotics to determine the prevelance of multiple antibiotic resistance, antimicrobial resistance profiles and also to find out high risk source of contamination by MAR indexing.

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Prevalence and antibiotic resistance of Escherichia coli in the water and sediment samples of brackish water aquaculture ponds adjacent to Cochin backwaters was analysed. More than 50% of the water samples and more than 80% of sediment samples from all the sampling stations were tested positive for £. coli. Risk assessment of the E. coli strains was carried out using multiple antibiotic resistance (MAR) indexing. Majority of the strains were found to be multiple antibiotic resistant suggesting their origin from high risk sources of contamination such as human where antibiotics are frequently used. While none of the £. coli strains were resistant against amikacin, chloramphenicol, streptomycin and trimethoprim, considerable levels of resistance was encountered against ampicillin, erythromycin, penicillin G and vancomycin. High prevalence of £. coli in the water and sediment samples of this extensive brackish water ponds indicates high degree of faecal pollution of this environment. The high risk nature of the strains warrants efficient post harvest and processing measures to avoid health risk to consumers

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A total of 319 strains of Aeromonas hydrophila were isolated from 536 fish and 278 prawns for a 2-year period. All the strains were tested for resistance to 15 antibiotics and 100% of the strains was resistant to methicillin and rifampicin followed by bacitracin and novobiocin (99%). Only 3% of the strains exhibited resistance against chloramphenicol. The multiple antibiotic resistance (MAR) indexing of A. hydrophila strains showed that all of them originated from high-risk sources

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This paper presents a Robust Content Based Video Retrieval (CBVR) system. This system retrieves similar videos based on a local feature descriptor called SURF (Speeded Up Robust Feature). The higher dimensionality of SURF like feature descriptors causes huge storage consumption during indexing of video information. To achieve a dimensionality reduction on the SURF feature descriptor, this system employs a stochastic dimensionality reduction method and thus provides a model data for the videos. On retrieval, the model data of the test clip is classified to its similar videos using a minimum distance classifier. The performance of this system is evaluated using two different minimum distance classifiers during the retrieval stage. The experimental analyses performed on the system shows that the system has a retrieval performance of 78%. This system also analyses the performance efficiency of the low dimensional SURF descriptor.

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The paper discusses the use of online information resources for organising knowledge in library and information centres in Cochin University of Science and Technology (CUSAT). The paper discusses the status and extent of automation in CUSAT library. The use of different online resources and the purposes for which these resources are being used, is explained in detail. Structured interview method was applied for collecting data. It was observed that 67 per cent users consult online resources for assisting knowledge organisation. Library of Congress catalogue is the widely used (100 per cent) online resource followed by OPAC of CUSAT and catalogue of British Library. The main purposes for using these resources are class number building and subject indexing

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This thesis describes the development of a model-based vision system that exploits hierarchies of both object structure and object scale. The focus of the research is to use these hierarchies to achieve robust recognition based on effective organization and indexing schemes for model libraries. The goal of the system is to recognize parameterized instances of non-rigid model objects contained in a large knowledge base despite the presence of noise and occlusion. Robustness is achieved by developing a system that can recognize viewed objects that are scaled or mirror-image instances of the known models or that contain components sub-parts with different relative scaling, rotation, or translation than in models. The approach taken in this thesis is to develop an object shape representation that incorporates a component sub-part hierarchy- to allow for efficient and correct indexing into an automatically generated model library as well as for relative parameterization among sub-parts, and a scale hierarchy- to allow for a general to specific recognition procedure. After analysis of the issues and inherent tradeoffs in the recognition process, a system is implemented using a representation based on significant contour curvature changes and a recognition engine based on geometric constraints of feature properties. Examples of the system's performance are given, followed by an analysis of the results. In conclusion, the system's benefits and limitations are presented.

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The report describes a recognition system called GROPER, which performs grouping by using distance and relative orientation constraints that estimate the likelihood of different edges in an image coming from the same object. The thesis presents both a theoretical analysis of the grouping problem and a practical implementation of a grouping system. GROPER also uses an indexing module to allow it to make use of knowledge of different objects, any of which might appear in an image. We test GROPER by comparing it to a similar recognition system that does not use grouping.

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Two formulations of model-based object recognition are described. MAP Model Matching evaluates joint hypotheses of match and pose, while Posterior Marginal Pose Estimation evaluates the pose only. Local search in pose space is carried out with the Expectation--Maximization (EM) algorithm. Recognition experiments are described where the EM algorithm is used to refine and evaluate pose hypotheses in 2D and 3D. Initial hypotheses for the 2D experiments were generated by a simple indexing method: Angle Pair Indexing. The Linear Combination of Views method of Ullman and Basri is employed as the projection model in the 3D experiments.

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En este trabajo se describe la utilización de herramientas de software libre, básicamente GRASS y R, para obtener una serie de mapas de coberturas del suelo (1976-2006) a partir de imágenes de satélite Landsat MSS y Landsat TM. Se trata de un proyecto concedido a un año, por lo que se requería una metodología que permitiera realizar el análisis de forma rápida y sencilla, aún tratando de aplicar técnicas de clasificación avanzadas. Dada la complejidad del trabajo y la premura de tiempo, se ha tratado de automatizar gran parte del trabajo mediante diversos scripts con BASH y R. (...)

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