Collaborative e-learning and Learning Objects

The Learning Object (OA) is any digital resource that can be reused to support learning with specific functions and objectives. The OA specifications are commonly offered in SCORM model without considering activities in groups. This deficiency was overcome by the solution presented in this paper. This work specified OA for e-learning activities in groups based on SCORM model. This solution allows the creation of dynamic objects which include content and software resources for the collaborative learning processes. That results in a generalization of the OA definition, and in a contribution with e-learning specifications.

Learning Profile Identification Based on the Analysis of the User Context of Interaction

One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

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.

Reliability concepts applied to cutting tool change time

This paper presents a reliability-based analysis for calculating critical tool life in machining processes. It is possible to determine the running time for each tool involved in the process by obtaining the operations sequence for the machining procedure. Usually, the reliability of an operation depends on three independent factors: operator, machine-tool and cutting tool. The reliability of a part manufacturing process is mainly determined by the cutting time for each job and by the sequence of operations, defined by the series configuration. An algorithm is presented to define when the cutting tool must be changed. The proposed algorithm is used to evaluate the reliability of a manufacturing process composed of turning and drilling operations. The reliability of the turning operation is modeled based on data presented in the literature, and from experimental results, a statistical distribution of drilling tool wear was defined, and the reliability of the drilling process was modeled. (C) 2010 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.

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.

Real exchange rate and elasticity of labour supply in a balance-of-payments-constrained macrodynamics

A macrodynamic model is proposed in which the real exchange rate and the elasticity of labour supply interact defining different trajectories of growth and income distribution in a developing economy. Growth depends on imports of capital goods which are paid with exports (there are no capital flows) and hence is constrained by equilibrium in current account. The role of the elasticity of labour supply is to prevent the real exchange rate from appreciating as the economy grows, thereby sustaining international competitiveness. The model allows for endogenous technological change and considers the impact of migration from the subsistence to the modern sector on the cumulative (Kaldor-Verdoorn) process of learning.

Structural change, balance-of-payments constraint, and economic growth: evidence from the multisectoral Thirlwall`s law

This paper contributes to the literature on balance-of-payments constrained growth by investigating how structural change identified with changes in the sectoral composition of exports and imports affects the external constraint We test both the original and a multisectoral version of Thirlwall`s law for a sample of Latin American and Asian countries The original Thirlwall s law is found to hold for all sample countries except South Korea, whereas the multisectoral analogue holds for all of them As the sectoral composition of exports and imports is found to matter for growth we analyze the evolution of each country`s weighted trade income elasticities

GREEN MANAGEMENT, CLIMATE CHANGE AND SMALL BUSINESS IN BRAZIL: IMPLICATIONS FOR TRAINING AND EDUCATION FOR SUSTAINABLE DEVELOPMENT

This paper presents the results of a study on the analysis of training needs regarding environmental (green) management and climate change topics in micro and small enterprises (MSEs) in Brazil and its implications on education for sustainable development. It reports on an e-mail survey of Brazilian small enterprises, whose results indicate that they are indeed interested in environmental management and climate change topics in an education for sustainable development context. The study indicates that proposals for courses on environmental management and climate change should follow a systemic perspective and take sustainable development into account. By applying factor analysis, it was found that the topics of interest can be grouped into thematic modules, which can be useful in the design of training courses for the top management leaders of those companies.

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.

Gabaergic mechanisms of hypothalamic nuclei in the expression of conditioned fear

The amygdala, the dorsal periaqueductal gray (dPAG), and the media] hypothalamus have long been recognized to be a neural system responsible for the generation and elaboration of unconditioned fear in the brain. It is also well known that this neural substrate is under a tonic inhibitory control exerted by GABA mechanisms. However, whereas there is a growing body of evidence to suggest that the amygdala and dPAG are also able to integrate conditioned fear, it is still unclear, however, how the distinct hypothalamic nuclei participate in fear conditioning. In this work we aimed to examine the extent to which the gabaergic mechanisms of this brain region are involved in conditioned fear using the fear-potentiated startle (FPS). Muscimol, a GABA-A receptor agonist, and semicarbazide, an inhibitor of the GABA synthesizing enzyme glutamic acid decarboxylase (GAD), were used as an enhancer and inhibitor of the GABA mechanisms, respectively. Muscimol and semicarbazide were injected into the anterior hypothalamus (AHN). the dorsomedial part of the ventromedial nucleus (VMHDM), the dorsomedial (DMH) or the dorsal premammillary (PMD) nuclei of male Wistar rats before test sessions of the fear conditioning paradigm. The injections into the DMH and PMD did not produce any significant effects on FPS. On the other hand, muscimol injections into the AHN and VMHDM caused significant reduction in FPS. These results indicate that injections of muscimol and semicarbazide into the DMH and PMD fail to change the FPS, whereas the enhancement of the GABA transmission in the AHN and VMHDM produces a reduction of the conditioned fear responses. On the other hand, the inhibition of this transmission led to an increase of this conditioned response in the AHN. Thus, whereas DMH and PMD are known to be part of the caudal-most region of the medial hypothalamic defensive system, which integrates unconditioned fear, systems mediating conditioned fear select the AHN and VMHDM nuclei that belong to the rostral-most portion of the hypothalamic defense area. Thus, distinct subsets of neurons in the hypothalamus could mediate different aspects of the defensive responses. (C) 2008 Elsevier Inc. All rights reserved.