Avaliação do potencial eólico em uma região do sul do Brasil

Knowledge of wind behavior plays a key role in the production of wind energy, in ambient ventilation and in air quality. In this study the wind speed behavior in Cachoeira do Sul (RS) is analyzed. Wind speed data was measured by a sonic anemometer and it was used to estimate the potential for power generation in the period from 2010 to 2014. One of the methodologies used for the study of wind was the statistical analysis using functions of probability density. There are several models of probability distribution in the literature for time series of data. For wind data, the most commonly used distribution is the Weibull function.This distribution is considered to be the most adequate for wind characterization and is also applied in the analysis of rainfall data,clarity index, water level prediction, among other applications. Thus, the objective of the present study is to obtain preliminary estimates of the wind potential of Cachoeira do Sul (RS) using the Weibull probability distribution to estimate the wind power. The results show that wind power is below 500W=m2 (in 50 m) which indicates low wind potential.O conhecimento do comportamento do vento desempenha um papel fundamental na produção de energia eólica, em ventilaçãode ambientes e na qualidade do ar. Assim, neste estudo o comportamento da velocidade do vento em Cachoeira do Sul (RS) éanalisado. Dados de velocidade do vento medidos por um anemômetro sônico são empregados para estimar o potencial de geraçãode energia no período de 2010 à 2014. Uma das metodologias empregadas para o estudo do vento é a análise estatística utilizandofunções de densidade de probabilidade. Existem diversos modelos de distribuição de probabilidade na literatura para sériestemporais de dados. Para dados de vento a distribuição mais utilizada é a função de Weibull. Esta distribuição é considerada amais adequada para caracterização do vento e é aplicada também na análise de dados de chuvas, índice de claridade, previsãodo nível de água dentre outras aplicações. Assim, o objetivo do presente estudo é obter estimativas preliminares do potencialeólico de Cachoeira do Sul no RS empregando a distribuição de probabilidade de Weibull para estimar a potência do vento. Osresultados mostram que a potência do vento está abaixo de 500W/m2 (em 50m), o que indica baixa potencial eólico

Towards Semantic-Awareness for Information Management and Planning in Health Dialogues

Dialogue systems for the health domain are expected to be reliable and to reason in accordance to medical experts' reasoning. Given the complexities of the health domain, these systems are frequently aided by semantic-aware approaches implementing technologies such as ontologies. However, the automated generation of such systems is still a challenging task. In this work, we propose an approach that integrates automated planning and information management with the aim of automating the generation of efficient dialogue managers. Resulting dialogue managers are capable of handling multi-turn goal-oriented dialogue sessions within the healthcare domain. By evaluating a prototype on the asthma domain, our results reveal the suitability of our approach to generate dialogue policies on real-time scenarios

U-Agro Ontology

<p>U-Agro Ontology</p

A metric for Filter Bubble measurement in recommender algorithms considering the news domain

International audienceRecommender systems have been constantly refined to improve the accuracy of rating prediction and ranking generation. However, when a recommender system is too accurate in predicting the users’ interests, negative impacts can arise. One of the most critical is the filter bubbles creation, a situation where a user receives less content diversity. In the news domain, such effect is critical once they are ways of opinion formation. In this paper, we aim to assess the role that a specific set of recommender algorithms has in the creation of filter bubbles and if diversification approaches can decrease such effect. We also verify the effects of such an environment in the users’ exposition and interaction to fake news in the Brazilian presidential election of 2018. To perform such a study, we developed a prototype that recommends news stories and presents these recommendations in a feed. To measure the filter bubble, we introduce a new metric based on the homogenization of a recommended items’ set. Our results show KNN item-based recommendation with the MMR diversification algorithm performs slightly better in putting the user in contact with less homogeneous content while presenting a lower index of likes in fake news

ResEnControl: um sistema de monitoramento de consumo de energia elétrica residencial em tempo real

The worldwide concern about the energy sector has been growing gradually. Several systems that seek to combine control and energy efficiency have been developed over the years. Given this problem, this work proposes a system of control of residential electricity consumption, which aims to give the user flexibility and real-time monitoring of the electrical energy expenditure by home appliances. The proposed system has a server developed in Python programming language that offers a web user interface and uses micro controllers to perform the energy measurement and data transmission to the control server. By applying the developed prototypes in a use scenario, it was observed that the prototypes met the requirements defined at the beginning of development.A preocupação mundial em relação ao setor energético vem crescendo gradativamente. Diversos sistemas que buscam aliar controle e eficiência energética vêm sendo desenvolvidos no decorrer dos anos. Diante de tal problemática, este trabalho propõe um sistema de controle de consumo de energia elétrica residencial, que visa dar ao usuário flexibilidade e monitoramento em tempo real dos gastos em energia elétrica por eletrodomésticos em sua residência. O sistema proposto conta com um servidor desenvolvido em linguagem de programação Python que oferece uma interface web ao usuário e utiliza micro controladores para realizar a medição de energia e transmissão de dados para o servidor de controle. Através da aplicação dos protótipos desenvolvidos em um cenário de uso, foi possível observar que os protótipos atenderam aos requisitos definidos no início do desenvolvimento

Aplicativo móvel multiplataforma de suporte para o sistema AgroFert

Currently, liming and fertilizing recommendations for crops in the main regions of Brazil is made using the knowledge generated by researchers and summarized in liming and fertilizing manuals. This requires professionals to refer to these manuals for recommendations, which are often made manually. In this context, the AgroFert system was created to be an automated liming and fertilizing recommendation tool, assisting professionals and small producers in monitoring crop-related information. The system acts on the recommendation of correctives and fertilizers for the states of Rio Grande do Sul / Santa Catariana and Paraná for the main grain crops and to evaluate the evolution of the chemical characteristics of the soil. This work presents a multiplatform mobile application, which integrated with AgroFert system, allows users to make recommendations in the field, without the need for constant connection with the application server to make recommendations.Atualmente, recomendações de calagem e adubação para culturas nas principais regiões do Brasil é realizada com a utilização do conhecimento gerado por pesquisadores e sumarizado em manuais de calagem e adubação. Isto exige que profissionais consultem estes manuais para realizar recomendações, que frequentemente são realizadas de forma manual. Neste contexto, o sistema AgroFert foi criado para ser uma ferramenta automatizada de recomendação de calagem e adubação, auxiliando profissionais da área e pequenos produtores no acompanhamento de informações relacionadas às culturas. O sistema atua na recomendação de corretivos e fertilizantes para os estados do Rio Grande do Sul/Santa Catariana e Paraná para as principais culturas de grãos e avaliar as evolução das características químicas do solo. Neste trabalho, é apresentada uma aplicação móvel multiplataforma, que integrada ao sistema AgroFert, permite que os usuários realizem as recomendações em campo, sem a necessidade de conexão constante com o servidor de aplicação para a realização de recomendações

CoMPARA : Collaborative Modeling Project for Androgen Receptor Activity

BACKGROUND: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling. OBJECTIVES: In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP). METHODS: The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast (TM) metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast (TM)/Tox21 HTS in vitro assays. RESULTS: The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set. DISCUSSION: The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of similar to 875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment