885 resultados para Semi-Automatic Indexing System (SISA)


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The indexing automation has been discussed by researches in the area of Information Science however the discussions have not been so clear on the use of indexing software. Thus, it is necessary to know the indexing software, as well as its application in the analysis of documentary contents. To do so, it is proposed, here, to investigate both the consistency of indexing and the exhaustiveness and precision of the information retrieval, by means of comparative analysis between SISA (Sistema de Indizacion Semi-Automatico) automatic index and BIREME ( Centro Latino-Americano e do Caribe de Informação em Ciencias da Saude) manual indexing. The aim of this paper is to contribute to the theoretical development of the indexing automation and the improvement of SISA. Thus, SISA application and evaluation was used based on the calculation of the consistency indexes between the two types of indexing, and the calculation of the exhaustiveness and precision indexes in information retrieval, by means of searching into BDSISA and BIREME databases, composed by descriptors taken from SISA and manual indexing respectively. The differences among the terms used in scientific papers comparing to the DeCS ones were the main difficult factor to achieve higher consistency indexes in the indexing. These differences influenced the exhaustiveness and precision indexes in the information retrieval, showing that it is necessary to improve the documentary language used by SISA software and to incorporate linguistic methods.

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Automatic indexing and retrieval of digital data poses major challenges. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions, or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. For a number of years research has been ongoing in the field of ontological engineering with the aim of using ontologies to add such (meta) knowledge to information. In this paper, we describe the architecture of a system (Dynamic REtrieval Analysis and semantic metadata Management (DREAM)) designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval. The DREAM Demonstrator has been evaluated as deployed in the film post-production phase to support the process of storage, indexing and retrieval of large data sets of special effects video clips as an exemplar application domain. This paper provides its performance and usability results and highlights the scope for future enhancements of the DREAM architecture which has proven successful in its first and possibly most challenging proving ground, namely film production, where it is already in routine use within our test bed Partners' creative processes. (C) 2009 Published by Elsevier B.V.

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There are still major challenges in the area of automatic indexing and retrieval of multimedia content data for very large multimedia content corpora. Current indexing and retrieval applications still use keywords to index multimedia content and those keywords usually do not provide any knowledge about the semantic content of the data. With the increasing amount of multimedia content, it is inefficient to continue with this approach. In this paper, we describe the project DREAM, which addresses such challenges by proposing a new framework for semi-automatic annotation and retrieval of multimedia based on the semantic content. The framework uses the Topic Map Technology, as a tool to model the knowledge automatically extracted from the multimedia content using an Automatic Labelling Engine. We describe how we acquire knowledge from the content and represent this knowledge using the support of NLP to automatically generate Topic Maps. The framework is described in the context of film post-production.

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The ability to create accurate geometric models of neuronal morphology is important for understanding the role of shape in information processing. Despite a significant amount of research on automating neuron reconstructions from image stacks obtained via microscopy, in practice most data are still collected manually. This paper describes Neuromantic, an open source system for three dimensional digital tracing of neurites. Neuromantic reconstructions are comparable in quality to those of existing commercial and freeware systems while balancing speed and accuracy of manual reconstruction. The combination of semi-automatic tracing, intuitive editing, and ability of visualizing large image stacks on standard computing platforms provides a versatile tool that can help address the reconstructions availability bottleneck. Practical considerations for reducing the computational time and space requirements of the extended algorithm are also discussed.

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This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.

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This paper reports a research to evaluate the potential and the effects of use of annotated Paraconsistent logic in automatic indexing. This logic attempts to deal with contradictions, concerned with studying and developing inconsistency-tolerant systems of logic. This logic, being flexible and containing logical states that go beyond the dichotomies yes and no, permits to advance the hypothesis that the results of indexing could be better than those obtained by traditional methods. Interactions between different disciplines, as information retrieval, automatic indexing, information visualization, and nonclassical logics were considered in this research. From the methodological point of view, an algorithm for treatment of uncertainty and imprecision, developed under the Paraconsistent logic, was used to modify the values of the weights assigned to indexing terms of the text collections. The tests were performed on an information visualization system named Projection Explorer (PEx), created at Institute of Mathematics and Computer Science (ICMC - USP Sao Carlos), with available source code. PEx uses traditional vector space model to represent documents of a collection. The results were evaluated by criteria built in the information visualization system itself, and demonstrated measurable gains in the quality of the displays, confirming the hypothesis that the use of the para-analyser under the conditions of the experiment has the ability to generate more effective clusters of similar documents. This is a point that draws attention, since the constitution of more significant clusters can be used to enhance information indexing and retrieval. It can be argued that the adoption of non-dichotomous (non-exclusive) parameters provides new possibilities to relate similar information.

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This is a discussion of the journal article: "Construcing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation". The article and discussion have appeared in the Journal of the Royal Statistical Society: Series B (Statistical Methodology).

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INTRODUCTION There is a large range in the reported prevalence of end plate lesions (EPLs), sometimes referred to as Schmorl's nodes in the general population (3.8-76%). One possible reason for this large range is the differences in definitions used by authors. Previous research has suggested that EPLs may potentially be a primary disturbance of growth plates that leads to the onset of scoliosis. The aim of this study was to develop a technique to measure the size, prevalence and location of EPLs on Computed Tomography (CT) images of scoliosis patients in a consistent manner. METHODS A detection algorithm was developed and applied to measure EPLs for five adolescent females with idiopathic scoliosis (average age 15.1 years, average major Cobb 60°). In this algorithm, the EPL definition was based on the lesion depth, the distance from the edge of the vertebral body and the gradient of the lesion edge. Existing low-dose, CT scans of the patients' spines were segmented semi-automatically to extract 3D vertebral endplate morphology. Manual sectioning of any attachments between posterior elements of adjacent vertebrae and, if necessary, endplates was carried out before the automatic algorithm was used to determine the presence and position of EPLs. RESULTS EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 73% of the EPLs were seen in the lumbar spines (11/15). A sensitivity study demonstrated that the algorithm was most sensitive to changes in the minimum gradient required at the lesion edge. CONCLUSION An imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs on CT images has been developed. Although the technique was tested on scoliosis patients, it can be used to analyse other populations without observer errors in EPL definitions.

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In a time when Technology Supported Learning Systems are being widely used, there is a lack of tools that allows their development in an automatic or semi-automatic way. Technology Supported Learning Systems require an appropriate Domain Module, ie. the pedagogical representation of the domain to be mastered, in order to be effective. However, content authoring is a time and effort consuming task, therefore, efforts in automatising the Domain Module acquisition are necessary.Traditionally, textbooks have been used as the main mechanism to maintain and transmit the knowledge of a certain subject or domain. Textbooks have been authored by domain experts who have organised the contents in a means that facilitate understanding and learning, considering pedagogical issues.Given that textbooks are appropriate sources of information, they can be used to facilitate the development of the Domain Module allowing the identification of the topics to be mastered and the pedagogical relationships among them, as well as the extraction of Learning Objects, ie. meaningful fragments of the textbook with educational purpose.Consequently, in this work DOM-Sortze, a framework for the semi-automatic construction of Domain Modules from electronic textbooks, has been developed. DOM-Sortze uses NLP techniques, heuristic reasoning and ontologies to fulfill its work. DOM-Sortze has been designed and developed with the aim of automatising the development of the Domain Module, regardless of the subject, promoting the knowledge reuse and facilitating the collaboration of the users during the process.

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P. monodon juveniles prefer natural food than artificial feed in their initial stage of rearing. However, the percentage preference towards artificial feed increases as the days of culture/average body weight increases. Consumption of artificial feed was high during evening meal (1700h) and low during night meal (2200h). The index of intestine fullness was high (8.4±0.7) during initial stage of rearing, compared to that of final stage of rearing (4.9±0.4), probably due to low nutritional value of intake material and low water depth at initial stage. At all stage of rearing omnivorous feeding habit was established and no evidence of diet periodicity in feeding activity was observed.

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Small indigenous fish species (SIS) provide food, nutrition, subsistence and supplemental income to a great majority of the people particularly the poor and disadvantaged people of Bangladesh. To date nobody explored the possibilities of culturing these species in combination with the indigenous major carps viz. catla, Catla catla; rohu, Labeo rohita, and mrigal Cirrhinus cirrhosus and grass carp, Ctenopharyngodon idellus. An experiment on the polyculture of carps with a popular SIS, bata (Labeo bata) was carried out to evaluate the production performance of carp-SIS culture in on-farm condition during 15 March to 15 September 2003. Three treatments each having three replications with different stocking densities of bata were tested keeping the carp species combination and stocking density similar in all the treatments viz. treatment 1 (T1), bata (5,000/ha) + catla, rohu and mrigal (5,000/ha at the ratio of 1:1:1) + grass carp (250/ha); treatment 2 (T2), bata (7,500/ha) + catla, rohu and mrigal (5,000/ha at the ratio of 1:1:1) + grass carp (250/ha); and treatment 3 (T3), bata (1 0,000/ha) + catla, rohu and mrigal (5,000/ha at the ratio of 1:1:1) + grass carp (250/ha). After six months rearing, the production obtained were 2,466±77, 2,395±85 and 2,074±72 kg/ha from T1, T2 and T3, respectively. The highest production was obtained from T1, where the stocking density of bata was the minimum (5,000/ha) while the lowest production was obtained from T1 [sic], where the stocking density of bata was maximum (10,000/ha). Significant difference (P<0.05) exists in the production levels as obtained from different treatments. The contribution of bata to total production was 10.31%, 13.96% and 14.38% in case of T1, T2 and T3, respectively.