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.

Resource use pattern analysis for predicting resource availability in opportunistic grids

This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.

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.

Corporate Education and the Role of the Chief Learning Officer

This paper aims to present an overview on characteristics, roles and responsibilities of those who arc in charge. of the Corporate Educational Systems in several organizations from distinct industries in Brazil, based on a research carried out by the authors. The analysis compares what is available in the literature on this subject so that it may provide insights on how Brazilian companies have dealt with the difficult task of developing competences in their employees. Special attention is given to the Chief Learning Officer`s role (or the lack of it) - someone who was supposed to be in charge of the employees` development processes in a given organization. The results show that this role has not been a clear or unanimous concept yet, neither in terms of the functions to be performed nor the so-called strategic importance given to this sort of executive. This research is both exploratory and descriptive, and due to the use of intentional sample, the inferences are limited. Despite these limitations, its comments may enrich the discussion on this subject.

Effects of postnatal protein malnutrition on learning and memory procedures

Protein malnutrition induces structural, neurochemical and functional changes in the central nervous system leading to alterations in cognitive and behavioral development of rats. The aim of this work was to investigate the effects of postnatal protein malnutrition on learning and memory tasks. Previously malnourished (6% protein) and well-nourished rats (16% protein) were tested in three experiments: working memory tasks in the Morris water maze (Experiment I), recognition memory of objects (Experiment II), and working memory in the water T-maze (Experiment III). The results showed higher escape latencies in malnourished animals in Experiment I, lower recognition indexes of malnourished animals in Experiment II, and no differences due to diet in Experiment III. It is suggested that protein malnutrition imposed on early life of rats can produce impairments on both working memory in the Morris maze and recognition memory in the open field tests.

Improving Alzheimer`s Disease Diagnosis with Machine Learning Techniques

There is not a specific test to diagnose Alzheimer`s disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

Heart-lung interactions with different ventilatory settings during acute lung injury and hypovolaemia: an experimental study

Background. The functional haemodynamic variables pulse pressure variation (PPV), stroke volume variation (SVV), and systolic pressure variation (SPV) are widely used to assess haemodynamic status. However, it is not known how these perform during acute lung injury (ALI). This study evaluated the effects of different ventilatory strategies on haemodynamic parameters in pigs with ALI during normovolaemia and hypovolaemia. Methods. Eight anaesthetized Agroceres pigs [40 (1.9) kg] were instrumented with pulmonary artery, PiCCO, and arterial catheters and ventilated. Three ventilatory settings were randomly assigned for 10 min each: tidal volume (VT) 15 ml kg(-1) and PEEP 5 cm H(2)O, VT 8 ml kg(-1) and PEEP 13 cm H(2)O, or VT 6 ml kg(-1) and PEEP 13 cm H(2)O. Data were collected at each setting at baseline, after ALI (lung lavage+Tween 1.5%), and ALI with hypovolaemia (haemorrhage to 30% of estimated blood volume). Results. At baseline, high VT increased PPV, SVV, and SPV (P < 0.05 for all). During ALI, high VT significantly increased PPV and SVV [(P = 0.002 and P = 0.008) respectively.]. After ALI with hypovolaemia, ventilation at VT 6 ml kg(-1) and PEEP 13 cm H(2)O decreased the accuracy of functional haemodynamic variables to predict hypovolaemia, with the exception of PPV (area under the curve 0.875). The parameters obtained by PiCCO were less influenced by ventilatory changes. Conclusions. VT is the ventilatory parameter which influences functional haemodynamics the most. During ventilation with low VT and high PEEP, most functional variables are less able to accurately predict hypovolaemia secondary to haemorrhage, with the exception of PPV.

Influence of ventilatory settings on static and functional haemodynamic parameters during experimental hypovolaemia

Background and objective The influence of ventilatory settings on static and functional haemodynamic parameters during mechanical ventilation is not completely known. The purpose of this study was to evaluate the effect of positive end-expiratory pressure, tidal volume and inspiratory to expiratory time ratio variations on haemodynamic parameters during haemorrhage and after transfusion of shed blood. Methods Ten anaesthetized pigs were instrumented and mechanically ventilated with a tidal volume of 8 ml kg(-1), a positive end-expiratory pressure of 5 cmH(2)O and an inspiratory to expiratory ratio of 1 : 2. Then, they were submitted in a random order to different ventilatory settings (tidal volume 16 ml kg(-1), positive end-expiratory pressure 15 cmH(2)O or inspiratory to expiratory time ratio 2: 1). Functional and static haemodynamic parameters (central venous pressure, pulmonary artery occlusion pressure, right ventricular end-diastolic volume and pulse pressure variation) were evaluated at baseline, during hypovolaemia (withdrawal of 20% of estimated blood volume) and after an infusion of withdrawn blood (posttransfusion). Results During baseline, a positive end-expiratory pressure of 15cmH(2)O significantly increased pulmonary artery occlusion pressure from 14.6 +/- 1.6 mmHg to 17.4 +/- 1.7 mmHg (P<0.001) and pulse pressure variation from 15.8 +/- 8.5% to 25.3 +/- 9.5% (P<0.001). High tidal volume increased pulse pressure variation from 15.8 8.5% to 31.6 +/- 10.4% (P<0.001), and an inspiratory to expiratory time ratio of 2: 1 significantly increased only central venous pressure. During hypovolaemia, high positive end-expiratory pressure influenced all studied variables, and high tidal volume strongly increased pulse pressure variation (40.5 +/- 12.4% pre vs. 84.2 +/- 19.1 % post, P<0.001). The inversion of the inspiratory to expiratory time ratio only slightly increased filling pressures during hypovolaemia, without without affecting pulse pressure variation or right ventricle end-diastolic volume. Conclusion We concluded that pulse pressure variation measurement is influenced by cyclic variations in intrathoracic pressure, such as those caused by augmentations in tidal volume. The increase in mean airway pressure caused by positive end-expiratory pressure affects cardiac filling pressures and also pulse pressure variation, although to a lesser extent. Inversion of the inspiratory to expiratory time ratio does not induce significant changes in static and functional haemodynamic parameters. Eur J Anaesthesiol 26:66-72 (c) 2009 European Society of Anaesthesiology.

Modulation of Mediotemporal and Ventrostriatal Function in Humans by Delta 9-Tetrahydrocannabinol A Neural Basis for the Effects of Cannabis sativa on Learning and Psychosis

Context: Cannabis sativa use can impair verbal learning, provoke acute psychosis, and increase the risk of schizophrenia. It is unclear where C sativa acts in the human brain to modulate verbal learning and to induce psychotic symptoms. Objectives: To investigate the effects of 2 main psychoactive constituents of C sativa, Delta 9-tetrahydrocannabinol (Delta 9-THC) and cannabidiol, on regional brain function during verbal paired associate learning. Design: Subjects were studied on 3 separate occasions using a block design functional magnetic resonance imaging paradigm while performing a verbal paired associate learning task. Each imaging session was preceded by the ingestion of Delta 9-THC (10 mg), cannabidiol (600 mg), or placebo in a double-blind, randomized, placebo-controlled, repeated-measures, within-subject design. Setting: University research center. Participants: Fifteen healthy, native English-speaking, right-handed men of white race/ethnicity who had used C sativa 15 times or less and had minimal exposure to other illicit drugs in their lifetime. Main Outcome Measures: Regional brain activation ( blood oxygen level-dependent response), performance in a verbal learning task, and objective and subjective ratings of psychotic symptoms, anxiety, intoxication, and sedation. Results: Delta 9-Tetrahydrocannabinol increased psychotic symptoms and levels of anxiety, intoxication, and sedation, whereas no significant effect was noted on these parameters following administration of cannabidiol. Performance in the verbal learning task was not significantly modulated by either drug. Administration of Delta 9-THC augmented activation in the parahippocampal gyrus during blocks 2 and 3 such that the normal linear decrement in activation across repeated encoding blocks was no longer evident. Delta 9-Tetrahydrocannabinol also attenuated the normal time-dependent change in ventrostriatal activation during retrieval of word pairs, which was directly correlated with concurrently induced psychotic symptoms. In contrast, administration of cannabidiol had no such effect. Conclusion: The modulation of mediotemporal and ventrostriatal function by Delta 9-THC may underlie the effects of C sativa on verbal learning and psychotic symptoms, respectively.

Relational learning in children with deafness and cochlear implants

This four-experiment series sought to evaluate the potential of children with neurosensory deafness and cochlear implants to exhibit auditory-visual and visual-visual stimulus equivalence relations within a matching-to-sample format. Twelve children who became deaf prior to acquiring language (prelingual) and four who became deaf afterwards (postlingual) were studied. All children learned auditory-visual conditional discriminations and nearly all showed emergent equivalence relations. Naming tests, conducted with a subset of the: children, showed no consistent relationship to the equivalence-test outcomes.. This study makes several contributions: to the literature on stimulus equivalence. First; it demonstrates that both pre- and postlingually deaf children-can: acquire auditory-visual equivalence-relations after cochlear implantation, thus demonstrating symbolic functioning. Second, it directs attention to a population that may be especially interesting for researchers seeking to analyze the relationship. between speaker and listener repertoires. Third, it demonstrates the feasibility of conducting experimental studies of stimulus control processes within the limitations of a hospital, which these children must visit routinely for the maintenance of their cochlear implants.