An enhanced content selection mechanism for personalization of video news programmes

In this paper, we propose a content selection framework that improves the users` experience when they are enriching or authoring pieces of news. This framework combines a variety of techniques to retrieve semantically related videos, based on a set of criteria which are specified automatically depending on the media`s constraints. The combination of different content selection mechanisms can improve the quality of the retrieved scenes, because each technique`s limitations are minimized by other techniques` strengths. We present an evaluation based on a number of experiments, which show that the retrieved results are better when all criteria are used at time.

Use of Information Visualization Methods Eliminating Cross Talk in Multiple Sensing Units Investigated for a Light-Addressable Potentiometric Sensor

The integration of nanostructured films containing biomolecules and silicon-based technologies is a promising direction for reaching miniaturized biosensors that exhibit high sensitivity and selectivity. A challenge, however, is to avoid cross talk among sensing units in an array with multiple sensors located on a small area. In this letter, we describe an array of 16 sensing units, of a light-addressable potentiometric sensor (LAPS), which was made with layer-by-Layer (LbL) films of a poly(amidomine) dendrimer (PAMAM) and single-walled carbon nanotubes (SWNTs), coated with a layer of the enzyme penicillinase. A visual inspection of the data from constant-current measurements with liquid samples containing distinct concentrations of penicillin, glucose, or a buffer indicated a possible cross talk between units that contained penicillinase and those that did not. With the use of multidimensional data projection techniques, normally employed in information Visualization methods, we managed to distinguish the results from the modified LAPS, even in cases where the units were adjacent to each other. Furthermore, the plots generated with the interactive document map (IDMAP) projection technique enabled the distinction of the different concentrations of penicillin, from 5 mmol L(-1) down to 0.5 mmol L(-1). Data visualization also confirmed the enhanced performance of the sensing units containing carbon nanotubes, consistent with the analysis of results for LAPS sensors. The use of visual analytics, as with projection methods, may be essential to handle a large amount of data generated in multiple sensor arrays to achieve high performance in miniaturized systems.

Image indexing and retrieval using an ART-2A neural network architecture

Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

Comparison of roving-window and search-window techniques for characterising landscape morphometry

Brazil`s State of Sao Paulo Research Foundation

Improving data perturbation testing techniques for Web services

The widespread use of service-oriented architectures (SOAs) and Web services in commercial software requires the adoption of development techniques to ensure the quality of Web services. Testing techniques and tools concern quality and play a critical role in accomplishing quality of SOA based systems. Existing techniques and tools for traditional systems are not appropriate to these new systems, making the development of Web services testing techniques and tools required. This article presents new testing techniques to automatically generate a set of test cases and data for Web services. The techniques presented here explore data perturbation of Web services messages upon data types, integrity and consistency. To support these techniques, a tool (GenAutoWS) was developed and applied to real problems. (C) 2010 Elsevier Inc. All rights reserved.

DIAGNOSTIC TECHNIQUES OF LOCAL INFLUENCE IN SPATIAL ANALYSIS OF SOYBEAN YIELD

Modeling of spatial dependence structure, concerning geoestatistics approach, is an indispensable tool for fixing parameters that define this structure, applied on interpolation of values in places that are not sampled, by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations on sampled data. Thus, this trial aimed at using diagnostics techniques of local influence in spatial linear Gaussians models, applied at geoestatistics in order to evaluate sensitivity of maximum likelihood estimators and restrict maximum likelihood to small perturbations in these data. So, studies with simulated and experimental data were performed. Those results, obtained from the study of real data, allowed us to conclude that the presence of atypical values among the sampled data can have a strong influence on thematic maps, changing, therefore, the spatial dependence. The application of diagnostics techniques of local influence should be part of any geoestatistic analysis, ensuring that the information from thematic maps has better quality and can be used with greater security by farmers.