Managing environmental training in organizations: Theoretical review and proposal of a model

Purpose: The aim of this work is to address the issue of environmental training in organizations, presenting a theoretical review on the subject and proposing a model that highlights the importance of this type of training for organizations. Design/methodology/approach: The paper presents a thorough, updated literature review, discusses typology and the best practices of environmental training, and presents a framework integrating environmental training and organizational results. Findings: A careful consideration allows identifying a significant theoretical gap related to the lack of theoretical references, best practices, and an alignment between environmental training and organizational results. To overcome this gap, a model was proposed that helps to manage the environmental training process in organizations. Research limitations/implications: The paper needs to be complemented with empirical research on the topic. Originality/value: Environmental training is considered to be an essential element for organizations seeking to mitigate their environmental impacts. ISO 14001 states that environmental management is a duty of certified organizations. However, there have been few published articles that suggest models and insights to improve the environmental training in organizations. © Emerald Group Publishing Limited.

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

Identification of lubricant contamination by biodiesel using vibration analysis and neural network

Purpose - The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approach - The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.Findings - Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. on other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implications - This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implications Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy-to-use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/value - This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

Educação permanente em saúde: uma estratégia para a formação dos agentes comunitários de saúde

Este artigo teve por objetivo descrever e analisar o processo de educação dos Agentes Comunitários da Saúde (ACS) utilizado pelos enfermeiros na Estratégia Saúde da Família. Trata-se de uma pesquisa qualitativa, e contou com 17 sujeitos. Para a coleta de dados, utilizou-se entrevista semiestruturada, e a análise dos dados foi realizada por meio da técnica de análise de conteúdo. Identificou-se a categoria: organização do processo de educação nas unidades de saúde da família, cujas temáticas elencadas foram: enfermeiros como líderes da equipe de referência, educação permanente, metodologias tradicionais e educação centrada nas necessidades dos ACS. Através deste estudo, pudemos compreender que os enfermeiros têm pouco contato com a ferramenta da Educação Permanente, realizando as atividades de capacitação fundamentadas na metodologia tradicional de ensino, sendo necessário um investimento dos gestores no sentido de capacitá-los, no que se refere à educação permanente, possibilitando-lhes a atuação com os ACS.

(Mal) adaptações metabólicas ao treinamento contínuo: concepções não consensuais de terminologia e diagnóstico

Altos desempenhos esportivos demandam treinamentos pesados necessários ao estímulo adaptativo específico a cada esporte. A elevada carga de treino é geralmente acompanhada de discreta fadiga e reduções agudas no desempenho, mas caso acompanhada de períodos apropriados de recuperação, resulta em supercompensação metabólica ao treinamento, refletida como aumento na capacidade aeróbica e/ou força muscular. Visto como contínuo, os processos de intensificação do treinamento e o estresse relacionado à supercompensação, o aumento da sobrecarga ou do estresse poderá, em algum momento, acarretar a quebra da homeostase e a queda temporária da função (supra-alcance - OR ou supra-alcance funcional - FOR). Quando a sobrecarga excessiva de treinamento é combinada com recuperação inadequada há instalação do estado de supratreinamento (OT) ou supra-alcance não funcional (NFOR). O OT excede o OR, cujo pico é também o limiar do OT resultando em desadaptações fisiológicas e queda crônica do desempenho físico. A forma crônica de desadaptação fisiológica ao treinamento físico é chamada de síndrome do supertreinamento (OTS). A própria expressão da síndrome denota a etiologia multifatorial do estado e reconhece que o exercício não é necessariamente seu único fator causal. O diagnóstico de OTS é baseado na recuperação ou não do desempenho. Não há biomarcador objetivo para OTS. A distinção entre OTS e NFOR (supratreinamento extremo) é dependente de desfecho clínico e exclusão diagnóstica de doenças orgânicas, mais comuns na OTS. Também a diferença entre OR e OT é sutil e nenhum de seus marcadores bioquímicos pode ser universalizado. Não há evidências confirmatórias que OR evolui para OT ou que os sintomas de OT são piores dos que os de OR. Apenas pela fadiga aguda e queda de rendimento experimentada em sessões isoladas de treinamento, não é possível diferenciar presentemente os estados de OR e OT. Isto é devido, parcialmente, à variabilidade das respostas individuais ao treinamento e à falta de ambos instrumentos diagnósticos e estudos bem controlados.

An alternative approach to solve convergence problems in the backpropagation algorithm

The multilayer perceptron network has become one of the most used in the solution of a wide variety of problems. The training process is based on the supervised method where the inputs are presented to the neural network and the output is compared with a desired value. However, the algorithm presents convergence problems when the desired output of the network has small slope in the discrete time samples or the output is a quasi-constant value. The proposal of this paper is presenting an alternative approach to solve this convergence problem with a pre-conditioning method of the desired output data set before the training process and a post-conditioning when the generalization results are obtained. Simulations results are presented in order to validate the proposed approach.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

Speech therapy intervention before dental management in patients with special needs: A case report

Fragile X syndrome is a cytogenetic abnormality related to chromosomal X. This syndrome is frequently associated to intellectual disability, psychological problems, as well as heart, skeletal and join alterations. Intraoral anomalies include malloclusion, ogival palate, cleft palate, presence of mesiodens, dental hypomineralization and abrasion of the occlusal surfaces and incisai edges. The study of characteristics of this syndrome is important for the dentist in order to guide dental treatment and prevention. The aim of this study is to present a myofunctional therapy protocol, evaluated by surface electromyography. A case of a 21 year-old young man who attended the Training Program in Dentistry for Persons with Disabilities, School of Dentistry of São José dos Campos/UNESP is reported. He underwent myofunctional therapy before dental treatment and the masticatory muscles were evaluated by surface electromyography. The exercises of myofunctional therapy consisted of active and passive simple movements of opening and closing the mouth, tongue protrusion and retrusion, digital manipulation and also by using an electric massager on intraoral and perioral region of the masseter, buccinator and orbicularis oris. Action potentials of the masticatory muscles decreased in almost all the muscles and values for the bite force and mandibular opening capacity increased. This study showed that brief and immediate myofunctional therapy optimized clinical practice with positive repercussion on dental care.

Formação continuada do professor de arte: dialogia com a experiência

Pós-graduação em Artes - IA

Utilização de redes neurais recorrentes na caracterização de cargas não lineares em sistemas elétricos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Formulação do controle preventivo em sistemas de distribuição de energia elétrica baseada na lógica fuzzy e redes neurais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A dimensão valorativa da educação ambiental na formação continuada de professores apresentada em teses e dissertações brasileiras

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Epistemologia da prática e da prática docente: um estudo dos seus fundamentos com vistas à proposição de abordagens críticas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Professores-multiplicadores: uma maneira de organizar a formação de professores de matemática para o uso da informática na escola

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Professores de matemática e a educação inclusiva: análises de memórias de formação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)