Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

Data Mining Applied to Harmonic Current Sources Identification in Residential Consumers

This work proposes a method based on both preprocessing and data mining with the objective of identify harmonic current sources in residential consumers. In addition, this methodology can also be applied to identify linear and nonlinear loads. It should be emphasized that the entire database was obtained through laboratory essays, i.e., real data were acquired from residential loads. Thus, the residential system created in laboratory was fed by a configurable power source and in its output were placed the loads and the power quality analyzers (all measurements were stored in a microcomputer). So, the data were submitted to pre-processing, which was based on attribute selection techniques in order to minimize the complexity in identifying the loads. A newer database was generated maintaining only the attributes selected, thus, Artificial Neural Networks were trained to realized the identification of loads. In order to validate the methodology proposed, the loads were fed both under ideal conditions (without harmonics), but also by harmonic voltages within limits pre-established. These limits are in accordance with IEEE Std. 519-1992 and PRODIST (procedures to delivery energy employed by Brazilian`s utilities). The results obtained seek to validate the methodology proposed and furnish a method that can serve as alternative to conventional methods.

A solid-like FEM for geometrically non-linear 3D frames

This study presents a solid-like finite element formulation to solve geometric non-linear three-dimensional inhomogeneous frames. To achieve the desired representation, unconstrained vectors are used instead of the classic rigid director triad; as a consequence, the resulting formulation does not use finite rotation schemes. High order curved elements with any cross section are developed using a full three-dimensional constitutive elastic relation. Warping and variable thickness strain modes are introduced to avoid locking. The warping mode is solved numerically in FEM pre-processing computational code, which is coupled to the main program. The extra calculations are relatively small when the number of finite elements. with the same cross section, increases. The warping mode is based on a 2D free torsion (Saint-Venant) problem that considers inhomogeneous material. A scheme that automatically generates shape functions and its derivatives allow the use of any degree of approximation for the developed frame element. General examples are solved to check the objectivity, path independence, locking free behavior, generality and accuracy of the proposed formulation. (C) 2009 Elsevier B.V. All rights reserved.

Improvements on the Porter`s Stemming Algorithm for Portuguese

The amount of textual information digitally stored is growing every day. However, our capability of processing and analyzing that information is not growing at the same pace. To overcome this limitation, it is important to develop semiautomatic processes to extract relevant knowledge from textual information, such as the text mining process. One of the main and most expensive stages of the text mining process is the text pre-processing stage, where the unstructured text should be transformed to structured format such as an attribute-value table. The stemming process, i.e. linguistics normalization, is usually used to find the attributes of this table. However, the stemming process is strongly dependent on the language in which the original textual information is given. Furthermore, for most languages, the stemming algorithms proposed in the literature are computationally expensive. In this work, several improvements of the well know Porter stemming algorithm for the Portuguese language, which explore the characteristics of this language, are proposed. Experimental results show that the proposed algorithm executes in far less time without affecting the quality of the generated stems.

Anodic porous alumina structural characteristics study based on SEM image processing and analysis

The present work reports the porous alumina structures fabrication and their quantitative structural characteristics study based on mathematical morphology analysis by using the SEM images. The algorithm used in this work was implemented in 6.2 MATLAB software. Using the algorithm it was possible to obtain the distribution of maximum, minimum and average radius of the pores in porous alumina structures. Additionally, with the calculus of the area occupied by the pores, it was possible to obtain the porosity of the structures. The quantitative results could be obtained and related to the process fabrication characteristics, showing to be reliable and promising to be used to control the pores formation process. Then, this technique could provide a more accurate determination of pore sizes and pores distribution. (C) 2008 Elsevier Ltd. All rights reserved.

Effect of image analysis software on neurofunctional activation during processing of emotional human faces

Functional brain imaging techniques such as functional MRI (fMRI) that allow the in vivo investigation of the human brain have been exponentially employed to address the neurophysiological substrates of emotional processing. Despite the growing number of fMRI studies in the field, when taken separately these individual imaging studies demonstrate contrasting findings and variable pictures, and are unable to definitively characterize the neural networks underlying each specific emotional condition. Different imaging packages, as well as the statistical approaches for image processing and analysis, probably have a detrimental role by increasing the heterogeneity of findings. In particular, it is unclear to what extent the observed neurofunctional response of the brain cortex during emotional processing depends on the fMRI package used in the analysis. In this pilot study, we performed a double analysis of an fMRI dataset using emotional faces. The Statistical Parametric Mapping (SPM) version 2.6 (Wellcome Department of Cognitive Neurology, London, UK) and the XBAM 3.4 (Brain Imaging Analysis Unit, Institute of Psychiatry, Kings College London, UK) programs, which use parametric and non-parametric analysis, respectively, were used to assess our results. Both packages revealed that processing of emotional faces was associated with an increased activation in the brain`s visual areas (occipital, fusiform and lingual gyri), in the cerebellum, in the parietal cortex, in the cingulate cortex (anterior and posterior cingulate), and in the dorsolateral and ventrolateral prefrontal cortex. However, blood oxygenation level-dependent (BOLD) response in the temporal regions, insula and putamen was evident in the XBAM analysis but not in the SPM analysis. Overall, SPM and XBAM analyses revealed comparable whole-group brain responses. Further Studies are needed to explore the between-group compatibility of the different imaging packages in other cognitive and emotional processing domains. (C) 2009 Elsevier Ltd. All rights reserved.

Nop53p interacts with 5.8S rRNA co-transcriptionally, and regulates processing of pre-rRNA by the exosome

In eukaryotes, pre-rRNA processing depends on a large number of nonribosomal trans-acting factors that form intriguingly organized complexes. One of the early stages of pre-rRNA processing includes formation of the two intermediate complexes pre-40S and pre-60S, which then form the mature ribosome subunits. Each of these complexes contains specific pre-rRNAs, ribosomal proteins and processing factors. The yeast nucleolar protein Nop53p has previously been identified in the pre-60S complex and shown to affect pre-rRNA processing by directly binding to 5.8S rRNA, and to interact with Nop17p and Nip7p, which are also involved in this process. Here we show that Nop53p binds 5.8S rRNA co-transcriptionally through its N-terminal region, and that this protein portion can also partially complement growth of the conditional mutant strain Delta nop53/GAL:NOP53. Nop53p interacts with Rrp6p and activates the exosome in vitro. These results indicate that Nop53p may recruit the exosome to 7S pre-rRNA for processing. Consistent with this observation and similar to the observed in exosome mutants, depletion of Nop53p leads to accumulation of polyadenylated pre-rRNAs.

Investigation of AISI 1040 steel corrosion H(2)S solution containing chloride ions by digital image processing coupled with in electrochemical techniques

This paper presents a study of AISI 1040 steel corrosion in aqueous electrolyte of acetic acid buffer containing 3.1 and 31 x 10(-3) mol dm(-3) of Na(2)S in both the presence and absence of 3.5 wt.% NaCl. This investigation of steel corrosion was carried out using potential polarization, and open-circuit and in situ optical microscopy. The morphological analysis and classification of types of surface corrosion damage by digital image processing reveals grain boundary corrosion and shows a non-uniform sulfide film growth, which occurs preferentially over pearlitic grains through successive formation and dissolution of the film. (C) 2011 Elsevier Ltd. All rights reserved.

Utp25p, a nucleolar Saccharomyces cerevisiae protein, interacts with U3 snoRNP subunits and affects processing of the 35S pre-rRNA

In eukaryotes, pre-rRNA processing depends on a large number of nonribosomal trans-acting factors that form intriguingly organized complexes. Two intermediate complexes, pre-40S and pre-60S, are formed at the early stages of 35S pre-rRNA processing and give rise to the mature ribosome subunits. Each of these complexes contains specific pre-rRNAs, some ribosomal proteins and processing factors. The novel yeast protein Utp25p has previously been identified in the nucleolus, an indication that this protein could be involved in ribosome biogenesis. Here we show that Utp25p interacts with the SSU processome proteins Sas10p and Mpp10p, and affects 18S rRNA maturation. Depletion of Utp25p leads to accumulation of the pre-rRNA 35S and the aberrant rRNA 23S, and to a severe reduction in 40S ribosomal subunit levels. Our results indicate that Utp25p is a novel SSU processome subunit involved in pre-40S maturation.

Nutrition and health: the issue is not food, nor nutrients, so much as processing [Invited commentary]

Orthodox teaching and practice on nutrition and health almost always focuses on nutrients, or else on foods and drinks. Thus, diets that are high in folate and in green leafy vegetables are recommended, whereas diets high in saturated fat and in full-fat milk and other dairy products are not recommended. Food guides such as the US Food Guide Pyramid are designed to encourage consumption of healthier foods, by which is usually meant those higher in vitamins, minerals and other nutrients seen as desirable.What is generally overlooked in such approaches, which currently dominate official and other authoritative information and education programmes, and also food and nutrition public health policies, is food processing. It is now generally acknowledged that the current pandemic of obesity and related chronic diseases has as one of its important causes increased consumption of convenience including pre-prepared foods(1,2). However, the issue of food processing is largely ignored or minimised in education and information about food, nutrition and health, and also in public health policies.A short commentary cannot be comprehensive, and a general proposal such as that made here is bound to have some problems and exceptions. Also, the social, cultural, economic and environmental consequences of food processing are not discussed here. Readers comments and queries are invited

Proposal for DICOM Multiframe Medical Image Integrity and Authenticity

This paper presents a novel algorithm to successfully achieve viable integrity and authenticity addition and verification of n-frame DICOM medical images using cryptographic mechanisms. The aim of this work is the enhancement of DICOM security measures, especially for multiframe images. Current approaches have limitations that should be properly addressed for improved security. The algorithm proposed in this work uses data encryption to provide integrity and authenticity, along with digital signature. Relevant header data and digital signature are used as inputs to cipher the image. Therefore, one can only retrieve the original data if and only if the images and the inputs are correct. The encryption process itself is a cascading scheme, where a frame is ciphered with data related to the previous frames, generating also additional data on image integrity and authenticity. Decryption is similar to encryption, featuring also the standard security verification of the image. The implementation was done in JAVA, and a performance evaluation was carried out comparing the speed of the algorithm with other existing approaches. The evaluation showed a good performance of the algorithm, which is an encouraging result to use it in a real environment.

Incidence of black spot in citrus fruits from different processing stages in packinghouses and from Sao Paulo`s wholesale market

The purposes of this work were a) to evaluate citrus black spot (CBS) incidence in `Valencia` oranges and `Murcott` tangors aimed at the export market, and in Pera`, `Lima` and `Natal` oranges, and `Murcott` tangors, aimed at the domestic market after different processing stages in packinghouses in 2004/05 and 2005/06; b) to evaluate CBS incidence in Pera` and `Lima` oranges and `Murcott` tangors sold at Ceagesp-SP, the biggest wholesale market in the State of Sao Paulo, in 2006. Citrus fruits were collected at the packinghouse, on their arrival, after pre-washing and de-greening, from the packing table, from the pallet and at Ceagesp. They were stored for 14 to 21 days at 25 degrees C and 85-90% RH. The incidence of CBS was visually evaluated after one day and at the end of the storage period. CBS incidence in fruits aimed at the export market decreased, with values under 2.0% on arrival and no CBS symptoms observed on fruits from the pallet. The average incidence of CBS in `Pera`, `Lima` and `Natal` oranges, and `Murcott` tangors in the packinghouse aimed at the domestic market were 64.1, 39.0, 32.1 and 19.3%, respectively, after one day of storage, then remaining constant in all processing stages. The incidence of CBS in Ceagesp fruits was low in winter months and increased in the spring. The increase in disease incidence during the storage period (21 days) was not significant in collected fruits.

Trypanosoma cruzi: evaluation of (-)-cubebin derivatives activity in the messenger RNAs processing

No fully effective treatment has been developed since the discovery of Chagas` disease. Since drug-resistant Trypanosoma cruzi strains are occurring and the current therapy is effective in the acute phase but with various adverse side effects, more studies are needed to characterize the susceptibility of T. cruzi to new drugs. Pre-mRNA maturation in trypanosomatids occurs through a process called trans-splicing, which is unusual RNA processing reaction, and it implies the processing of polycistronic transcription units into individual mRNAs; a short transcript spliced leader (SL RNA) is trans-spliced to the acceptor pre-mRNA, giving origin to the mature mRNA. Cubebin derivatives seem to provide treatments with less collateral effects than benznidazole and showed similar or better trypanocidal activities than benznidazole. Therefore, the cubebin derivatives ((-)-6,6`-dinitrohinokinin (DNH) and (-)-hinokinin (HQ)) interference in the mRNA processing was evaluated using T. cruzi permeable cells (Y and BOL (Bolivia) strains) following by RNase protection reaction. These substances seem to intervene in any step of the RNA transcription, promoting alterations in the RNA synthesis, even though the RNA processing mechanism still occurs. Furthermore, HQ presented better activity against the parasites than DNH, meaning that BOL strain seems to be more resistant than Y.