Pattern recognition theory in nonlinear signal processing

A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

Automated extraction of road network from medium-and high-resolution images

This paper presents an automatic methodology for road network extraction from medium-and high-resolution aerial images. It is based on two steps. In the first step, the road seeds (i.e., road segments) are extracted using a set of four road objects and another set of connection rules among road objects. Each road object is a local representation of an approximately straight road fragment and its construction is based on a combination of polygons describing all relevant image edges, according to some rules embodying road knowledge. Each road seed is composed by a sequence of connected road objects in which each sequence of this type can be geometrically structured as a chain of contiguous quadrilaterals. In the second step, two strategies for road completion are applied in order to generate the complete road network. The first strategy is based on two basic perceptual grouping rules, i.e., proximity and collinearity rules, which allow the sequential reconstruction of gaps between every pair of disconnected road segments. This strategy does not allow the reconstruction of road crossings, but it allows the extraction of road centerlines from the contiguous quadrilaterals representing connected road segments. The second strategy for road completion aims at reconstructing road crossings. Firstly, the road centerlines are used to find reference points for road crossings, which are their approximate positions. Then these points are used to extract polygons representing the contours of road crossings. This paper presents the proposed methodology and experimental results. © Pleiades Publishing, Inc. 2006.

Labour markets, worker protection and lifelong learning in a global economy: experiences and perspectives of Latin America and the Caribbean

Includes bibliography

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Trade in services in Latin America and the Caribbean: an analysis of recent trends

Includes bibliography

The Role of Wing Pigmentation, UV and Fluorescence as Signals in a Neotropical Damselfly

Pigmentation patterns, ultraviolet reflection and fluorescent emission are often involved in mate recognition and mate quality functions in many animal taxa. We investigated the role of wing ultra-violet reflection, fluorescence emission, and pigmentation on age and sexual signals in the damselfly Mnesarete pudica. In this species, wings are sexually dimorphic in colour and exhibit age dependency: males and females show a smoky black colouration when young, turning red in mature males while it turns brown in females. First, we investigated wing UV patterns through reflectance and emission spectra. Second, behavioural experiments were undertaken to show male and female responses to manipulated wing pigmentation and experimentally reduced UV (UV-). Reflectance spectra of the wings of juvenile and mature males and females were used to show the differences between controls and individuals with manipulated colouration used in the behavioural experiment. UV-reduced, females with wings painted red, and control males and females were tethered and presented to conspecific males and females, and their behavioral responses were recorded. The male red wing pigmentation and females with red wings elicited an aggressive response in territorial males and a sexual response in females. Both males and females showed neutral responses towards individuals with reduced UV. Wing signals of juvenile individuals also provoked neutral responses. These results suggest that UV, together with pigmentation, plays a role during mate recognition in males and females. Other than butterflies and spiders, it seems that fluorescence signals and UV reflectance can also be part of communication in odonates. © 2013 Springer Science+Business Media New York.

Pattern recognition issues on anisotropic smoothed particle hydrodynamics

This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.

Ineraction Model Between HRSV G-Protein and Flavonoids

Background: Acute respiratory infections (ARI) are the leading cause of infant mortality in the world, and human respiratory syncytial virus (HRSV) is one of the main agents of ARI. One of the key targets of the adaptive host immune response is the RSV G-protein, which is responsible for attachment to the host cell. There is evidence that compounds such as flavonoids can inhibit viral infection in vitro. With this in mind, the main purpose of this study was to determine, using computational tools, the potential sites for interactions between G-protein and flavonoids. Results: Our study allowed the recognition of an hRSV G-protein model, as well as a model of the interaction with flavonoids. These models were composed, mainly, of -helix and random coil proteins. The docking process showed that molecular interactions are likely to occur. The flavonoid kaempferol-3-O-α-L-arabinopyranosil-(2 → 1)-α-L-apiofuranoside-7-O-α-L-rhamnopyranoside was selected as a candidate inhibitor. The main forces of the interaction were hydrophobic, hydrogen and electrostatic. Conclusions: The model of G-protein is consistent with literature expectations, since it was mostly composed of random coils (highly glycosylated sites) and -helices (lipid regions), which are common in transmembrane proteins. The docking analysis showed that flavonoids interact with G-protein in an important ectodomain region, addressing experimental studies to these sites. The determination of the G-protein structure is of great importance to elucidate the mechanism of viral infectivity, and the results obtained in this study will allow us to propose mechanisms of cellular recognition and to coordinate further experimental studies in order to discover effective inhibitors of attachment proteins.

Means to an end: Neotropical parrots manage to pull strings to meet their goals

Although parrots share with corvids and primates many of the traits believed to be associated with advanced cognitive processing, knowledge of parrot cognition is still limited to a few species, none of which are Neotropical. Here we examine the ability of three Neotropical parrot species (Blue-Fronted Amazons, Hyacinth and Lear`s macaws) to spontaneously solve a novel physical problem: the string-pulling test. The ability to pull up a string to obtain out-of-reach food has been often considered a cognitively complex task, as it requires the use of a sequence of actions never previously assembled, along with the ability to continuously monitor string, food and certain body movements. We presented subjects with pulling tasks where we varied the spatial relationship between the strings, the presence of a reward and the physical contact between the string and reward to determine whether (1) string-pulling is goal-oriented in these parrots, (2) whether the string is recognized as a means to obtain the reward and (3) whether subjects can visually determine the continuity between the string and the reward, selecting only those strings for which no physical gaps between string and reward were present. Our results show that some individuals of all species were able to use the string as a means to reach a specific goal, in this case, the retrieval of the food treat. Also, subjects from both macaw species were able to visually determine the presence of physical continuity between the string and reward, making their choices consistently with the recognition that no gaps should be present between the string and the reward. Our findings highlight the potential of this taxonomic group for the understanding of the underpinnings of cognition in evolutionarily distant groups such as birds and primates.

Cocaine effects on mouse incentive-learning and human addiction are linked to alpha 2 subunit-containing GABA(A) receptors

Because GABA(A) receptors containing alpha 2 subunits are highly represented in areas of the brain, such as nucleus accumbens (NAcc), frontal cortex, and amygdala, regions intimately involved in signaling motivation and reward, we hypothesized that manipulations of this receptor subtype would influence processing of rewards. Voltage-clamp recordings from NAcc medium spiny neurons of mice with alpha 2 gene deletion showed reduced synaptic GABA(A) receptor-mediated responses. Behaviorally, the deletion abolished cocaine`s ability to potentiate behaviors conditioned to rewards (conditioned reinforcement), and to support behavioral sensitization. In mice with a point mutation in the benzodiazepine binding pocket of alpha 2-GABA(A) receptors (alpha 2H101R), GABAergic neurotransmission in medium spiny neurons was identical to that of WT (i.e., the mutation was silent), but importantly, receptor function was now facilitated by the atypical benzodiazepine Ro 15-4513 (ethyl 8-amido-5,6-dihydro-5-methyl-6-oxo-4H-imidazo [1,5-a] [1,4] benzodiazepine-3-carboxylate). In alpha 2H101R, but not WT mice, Ro 15-4513 administered directly into the NAcc-stimulated locomotor activity, and when given systemically and repeatedly, induced behavioral sensitization. These data indicate that activation of alpha 2-GABA(A) receptors (most likely in NAcc) is both necessary and sufficient for behavioral sensitization. Consistent with a role of these receptors in addiction, we found specific markers and haplotypes of the GABRA2 gene to be associated with human cocaine addiction.

Acute promyelocytic leukemia associated with the PLZF-RARA fusion gene: two additional cases with clinical and laboratorial peculiar presentations

Acute promyelocytic leukemia (APL) is characterized by the presence of the t(15;17) and PML-RARa rearrangement, with good response to treatment with retinoids. However, few cases of variant APL involving alternative chromosomal aberrations have been reported, including t(11;17)(q23;q21) (Wells et al. in Nat Genet 17:109-113, 1; Arnould et al. in Hum Mol Genet 8:1741-1749, 2) t(5;17)(q35;q12-21), t(11;17)(q13;q21) (Grimwade et al in Blood 96:1297-1308, 3) and der(17) (Rego et al. in Blood (ASH Annual Meeting Abstracts)114:Abstract 6, 4), whereby RARa is fused to the PLZF, NPM, NuMA, and STAT5b genes, respectively, have been described. These cases are characterized by distinct morphology, clinical presentation, and in respect to PLZF, a lack of differentiation response to retinoids leading to the need of different approaches concerning diagnostic methods and therapeutics. This paper describes two cases of APL associated with the PLZF-RARA fusion gene enrolled in the IC-APL trial that is a non-randomized, multicenter study conducted in Brazil, Mexico, Chile and Uruguay with the aim to improve the treatment outcome of APL patients in developing countries. These cases, although rare, offer a challenge to its early recognition and proper conduction.

Galactose Recognition by the Apicomplexan Parasite Toxoplasma gondii

Toxosplasma gondii is the model parasite of the phylum Apicomplexa, which contains numerous obligate intracellular parasites of medical and veterinary importance, including Eimeria, Sarcocystis, Cryptosporidium, Cyclospora, and Plasmodium species. Members of this phylum actively enter host cells by a multistep process with the help of microneme protein (MIC) complexes that play important roles in motility, host cell attachment, moving junction formation, and invasion. T. gondii (Tg)MIC1-4-6 complex is the most extensively investigated microneme complex, which contributes to host cell recognition and attachment via the action of TgMIC1, a sialic acid-binding adhesin. Here, we report the structure of TgMIC4 and reveal its carbohydrate-binding specificity to a variety of galactose-containing carbohydrate ligands. The lectin is composed of six apple domains in which the fifth domain displays a potent galactose-binding activity, and which is cleaved from the complex during parasite invasion. We propose that galactose recognition by TgMIC4 may compromise host protection from galectin-mediated activation of the host immune system.

Social Mobilization in Health and Sanitation in an Action Research Process in an Indigenous Community in Northwestern Amazon

The living conditions of the inhabitants of Iauarete, an indigenous area in the municipality of Sao Gabriel da Cachoeira, State of Amazonas (Northern Brazil), have been negatively affected by population density, poor sanitation and maintenance of sanitation practices that are incompatible with that reality. To improve the population's quality of life, sanitation systems that are adequate to the local socio-cultural characteristics should be implemented, as well as educational processes with emphasis on social mobilization and community empowerment. The aim of this paper is to report and discuss a training course on health and sanitation using action research, directed to the mobilization of the Iauarete indigenous people, with the objective of assisting other studies of this nature. In the meetings, issues related to environmental health were discussed, a Community Newspaper was constructed, the course participants made interviews and drew up claims documents. This experience has enhanced the participants' understanding of local problems and of the importance of social mobilization for the dialogue with governmental institutions that are responsible for providing sanitation services and for seeking better living conditions. The researchers and teachers of the training course benefitted from the construction of collective knowledge resulting from interaction with subjects of the investigated situation and from the recognition and redefinition of their representations, fulfilling the fundamental premise of action research.

An evolutive approach for smile recognition in video sequences

Facial expression recognition is one of the most challenging research areas in the image recognition ¯eld and has been actively studied since the 70's. For instance, smile recognition has been studied due to the fact that it is considered an important facial expression in human communication, it is therefore likely useful for human–machine interaction. Moreover, if a smile can be detected and also its intensity estimated, it will raise the possibility of new applications in the future

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.