HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

Learning about knowledge management for improving environmental impact assessment in a government agency: The Western Australian experience

How does knowledge management (KM) by a government agency responsible for environmental impact assessment (EIA) potentially contribute to better environmental assessment and management practice? Staff members at government agencies in charge of the EIA process are knowledge workers who perform judgement-oriented tasks highly reliant on individual expertise, but also grounded on the agency`s knowledge accumulated over the years. Part of an agency`s knowledge can be codified and stored in an organizational memory, but is subject to decay or loss if not properly managed. The EIA agency operating in Western Australia was used as a case study. Its KM initiatives were reviewed, knowledge repositories were identified and staff surveyed to gauge the utilisation and effectiveness of such repositories in enabling them to perform EIA tasks. Key elements of KM are the preparation of substantive guidance and spatial information management. It was found that treatment of cumulative impacts on the environment is very limited and information derived from project follow-up is not properly captured and stored, thus not used to create new knowledge and to improve practice and effectiveness. Other opportunities for improving organizational learning include the use of after-action reviews. The learning about knowledge management in EIA practice gained from Western Australian experience should be of value to agencies worldwide seeking to understand where best to direct their resources for their own knowledge repositories and environmental management practice. (C) 2011 Elsevier Ltd. All rights reserved.

On Building a Memory Evolutive System for Application to Learning and Cognition Modeling

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

Podzolization as a deferralitization process: dynamics and chemistry of ground and surface waters in an Acrisol-Podzol sequence of the upper Amazon Basin

Hydrochemical processes involved in the development of hydromorphic Podzols are a major concern for the upper Amazon Basin because of the extent of the areas affected by such processes and the large amounts of organic carbon and associated metals exported to the rivers. The dynamics and chemical composition of ground and surface waters were studied along an Acrisol-Podzol sequence lying in an open depression of a plateau. Water levels were monitored along the sequence over a period of 2 years by means of piezometers. Water was sampled in zero-tension lysimeters for groundwater and for surface water in the drainage network of the depression. The pH and concentrations of organic carbon and major elements (Si, Fe and Al) were determined. The contrasted changes reported for concentrations of Si, organic carbon and metals (Fe, Al) mainly reflect the dynamics of the groundwater and the weathering conditions that prevail in the soils. Iron is released by the reductive dissolution of Fe oxides, mostly in the Bg horizons of the upslope Acrisols. It moves laterally under the control of hydraulic gradients and migrates through the iron-depleted Podzols where it is exported to the river network. Aluminium is released from the dissolution of Al-bearing minerals (gibbsite and kaolinite) at the margin of the podzolic area but is immobilized as organo-Al complexes in spodic horizons. In downslope positions, the quick recharge of the groundwater and large release of organic compounds lead to acidification and a loss of metals (mainly Al), previously stored in the Podzols.

A lipocalin sequence signature modulates cell survival

Lipocalins are beta-barrel proteins, which share three conserved motifs in their amino acid sequence. In this study, we identified by a peptide mapping approach, a seven-amino acid sequence related to one of these motifs (motif 2) that modulates cell survival. A synthetic peptide based on an insect lipocalin displayed cytoprotective activity in serum-deprived endothelial cells and leucocytes. This activity was dependent on nitric oxide synthase. This sequence was found within several lipocalins, including apolipoprotein D, retinol binding protein, lipocalin-type prostaglandin D synthase, and many unknown proteins, suggesting that it is a sequence signature and a lipocalin conserved property. (C) 2010 Federation of European Biochemical Societies. Published by Elsevier B. V. All rights reserved.

Novel sequence types (STs) of Staphylococcus aureus isolates causing clinical and subclinical mastitis in flocks of sheep in the northeast of Brazil

Staphylococcus aureus is one of the most important infectious mastitis causative agents in small ruminants. In order to know the distribution of Staph. aureus strains associated with infectious mastitis in flocks of sheep in the northeast of Brazil and establish whether these clones are related to the strains distributed internationally, this study analysed the genetic diversity of Staph. aureus isolates from cases of clinical and subclinical mastitis in ewes by pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST). In this research, 135 ewes with mastitis from 31 sheep flocks distributed in 15 districts were examined. Staph. aureus was isolated from sheep milk in 9 (29%) out of 31 herds located in 47% of the districts surveyed. MLST analysis allowed the identification of four STs (ST750, ST1728, ST1729 and ST1730). The last three with their respective novel alleles (g/p-220; pta-182 and yqil-180) were recently reported in the Staph. aureus MLST database (http://www.mlst.net). Each novel allele showed only a nucleotide different from those already described. The occurrence of CC133 (ST750 and ST1729) in this study is in agreement with other reports that only a few clones of Staph. aureus seem to be responsible for most cases of mastitis in dairy farms and that some of these clones may have broad geographic distribution. However, the prevalence of CC5 (ST1728 and ST1730)-an important group related to cases of colonization or infection in humans-differs from previous studies by its widespread occurrence and may suggest human contamination followed by selective pressures of the allelic diversifications presented for these STs.

Antiviral and antiparasite properties of an L-amino acid oxidase from the Snake Bothrops jararaca: Cloning and identification of a complete cDNA sequence (Retracted article. See vol. 80, pg. 288, 2010)

L-Amino acid oxidases (LAAOs, EC 1.4.3.2) are flavoenzymes that catalyze the stereospecific oxidative deamination of an L-amino acid substrate to the corresponding a-ketoacid with hydrogen peroxide and ammonia production. The present work describes the first report on the antiviral (Dengue virus) and antiprotozoal (trypanocidal and leishmanicide) activities of a Bothrops jararaca L-amino acid oxidase (BjarLAAO-I) and identify its cDNA sequence. Antiparasite effects were inhibited by catalase, suggesting that they are mediated by H(2)O(2) production. Cells infected with DENV-3 virus previously treated with BjarLAAO-I, showed a decrease in viral titer (13-83-fold) when compared with cells infected with untreated viruses. Untreated and treated promastigotes (T. cruzi and L. amazonensis) were observed by transmission electron microscopy with different degrees of damage. Its complete cDNA sequence, with 1452 bp, encoded an open reading frame of 484 amino acid residues with a theoretical molecular weight and pl of 54,771.8 and 5.7, respectively. The cDNA-deduced amino acid sequence of BjarLAAO shows high identity to LAAOs from other snake venoms. Further investigations will be focused on the related molecular and functional correlation of these enzymes. Such a study should provide valuable information for the therapeutic development of new generations of microbicidal drugs. (C) 2008 Elsevier Inc. All rights reserved.

Clonal relationships determined by multilocus sequence typing among enteropathogenic Escherichia coli isolated in Brazil

Enteropathogenic Escherichia coli (EPEC) infections are a leading cause of infantile diarrhea in developing nations. Multilocus sequence typing (MLST) characterizes bacterial strains based on the sequences of internal fragments in housekeeping genes. Little is known about strains of EPEC analyzed by MLST from Brazil. In this study, a diverse collection of 29 EPEC strains isolated from patients with diarrhea, admitted to the University Hospital of Ribeirao Preto, was characterized by MLST. Strain analysis demonstrated 22 different sequence types (STs), of which almost half (48%) were new, indicating a high genotype diversity. The 22 STs were divided by eBURST into 12 clonal complexes. It was not possible to correlate typical and atypical EPEC with other strains in the MLST database. This is the first study that analyzed EPEC strains from South America that are included in the E. coli MLST database. Nine (31%) out of 29 strains are part of the CC10 clonal complex, the major clonal complex in the database, which comprises 174 strains and 86 different STs, suggesting that these strains might be the most important intestinal pathogenic E. coli worldwide. Genetic relationships between typical and atypical EPEC, enterohemorrhagic E. coli, and enteroaggregative E. coli strains were not established by MLST.

Information Society, Teaching, and Learning: Education Reforms in Brazil

This article examines the subject matter of learning within the context of information society, through an inquiry concerning both the reforms in education adopted in Brazil in the last thirty years and their results. It provides a revision on the explanations of school failure based on assumptions of learning problems due to cognitive and linguistic deficits. From the guidelines related with written school forms as well as the constant cultural oppression accomplished inside the school, the article claims the necessity of changing the psychological and pedagogic views that, under the label of democratic practices, determine school institutions and its daily life, by means of instrumental relations with knowledge that disregard the reading practices which are congenial to popular culture.

Learning for fun: The unique contribution of educational leisure experiences

What do visitors want or expect from an educational leisure activity such as a visit to a museum, zoo, aquarium or other such experience? Is it to learn something or to experience learning? This paper uses the term 'learning for fun' to refer to the phenomenon in which visitors engage in a learning experience because they value and enjoy the process of learning itself. Five propositions regarding the nature of learning for fun are discussed, drawing on quantitative and qualitative data from visitors to a range of educational leisure activities. The commonalities between learning for fun and other theoretical constructs such as 'experience,' 'flow', 'intrinsic motivation', and 'curiosity' are explored. It is concluded that learning for fun is a unique and distinctive offering of educational leisure experiences, with implications for future research and experience design.

Parameter setting and statistical learning

Three main models of parameter setting have been proposed: the Variational model proposed by Yang (2002; 2004), the Structured Acquisition model endorsed by Baker (2001; 2005), and the Very Early Parameter Setting (VEPS) model advanced by Wexler (1998). The VEPS model contends that parameters are set early. The Variational model supposes that children employ statistical learning mechanisms to decide among competing parameter values, so this model anticipates delays in parameter setting when critical input is sparse, and gradual setting of parameters. On the Structured Acquisition model, delays occur because parameters form a hierarchy, with higher-level parameters set before lower-level parameters. Assuming that children freely choose the initial value, children sometimes will miss-set parameters. However when that happens, the input is expected to trigger a precipitous rise in one parameter value and a corresponding decline in the other value. We will point to the kind of child language data that is needed in order to adjudicate among these competing models.

Mummy! Ball! Fish!: Why English-learning children produce nouns earlier than verbs

When English-learning children begin using words the majority of their early utterances (around 80%) are nouns. Compared to nouns, there is a paucity of verbs or non-verb relational words, such as 'up' meaning 'pick me up'. The primary explanations to account for these differences in use either argue in support of a 'cognitive account', which claims that verbs entail more cognitive complexity than nouns, or they provide evidence challenging this account. In this paper I propose an additional explanation for children's noun/verb asymmetry. Presenting a 'multi-modal account' of word-learning based on children's gesture and word combinations, I show that at the one-word stage English-learning children use gestures to express verb-like elements which leaves their words free to express noun-like elements.

Fundamental Skills in Physics: Embedded Learning

Student attitudes towards a subject affect their learning. For students in physics service courses, relevance is emphasised by vocational applications. A similar strategy is being used for students who aspire to continued study of physics, in an introduction to fundamental skills in experimental physics – the concepts, computational tools and practical skills involved in appropriately obtaining and interpreting measurement data. An educational module is being developed that aims to enhance the student experience by embedding learning of these skills in the practicing physicist’s activity of doing an experiment (gravity estimation using a rolling pendulum). The group concentrates on particular skills prompted by challenges such as: • How can we get an answer to our question? • How good is our answer? • How can it be improved? This explicitly provides students the opportunity to consider and construct their own ideas. It gives them time to discuss, digest and practise without undue stress, thereby assisting them to internalise core skills. Design of the learning activity is approached in an iterative manner, via theoretical and practical considerations, with input from a range of teaching staff, and subject to trials of prototypes.

Algorithms for sequence analysis via mutagenesis

Despite many successes of conventional DNA sequencing methods, some DNAs remain difficult or impossible to sequence. Unsequenceable regions occur in the genomes of many biologically important organisms, including the human genome. Such regions range in length from tens to millions of bases, and may contain valuable information such as the sequences of important genes. The authors have recently developed a technique that renders a wide range of problematic DNAs amenable to sequencing. The technique is known as sequence analysis via mutagenesis (SAM). This paper presents a number of algorithms for analysing and interpreting data generated by this technique.