The generation of electric energy by photovoltaic (PV) panels depends on many parameters, one of them is the sun’s angle of incidence. By using solar active trackers, it is possible to maximize generation capacity through real-time positioning. However, if the engines that update the position of the panels use more energy than the difference in efficiency, the solar tracker system becomes ineffective. In this way, a time series forecasting method can be assumed to determine the generation capacity in a pre-established horizon prediction to evaluate if a position update would provide efficient results. Among a wide range of algorithms that can be used in forecasting, this work considered a Neuro-Fuzzy Inference System due to its combined advantages such as smoothness property from Fuzzy systems and adaptability property from neural networks structures. Focusing on time series forecasting, this article presents a model and evaluates the solar prediction capacity using the Wavelet Neuro-Fuzzy algorithm, where Wavelets were included in the model for feature extraction. In this sense, this paper aims to evaluate whether it is possible to obtain reasonable accuracy using a hybrid model for electric power generation forecasting considering solar trackers. The main contributions of this work are related to the efficiency improvement of PV panels. By assuming a hybrid computational model, it is possible to make a forecast and determine if the use of solar tracking is interesting during certain periods. Finally, the proposed model showed promising results when compared to traditional Nonlinear autoregressive model structures.

The long short-term memory (LSTM) is a high-efficiency model for forecasting time series, for being able to deal with a large volume of data from a time series with nonlinearities. As a case study, the stacked LSTM will be used to forecast the growth of the pandemic of COVID-19, based on the increase in the number of contaminated and deaths in the State of Santa Catarina, Brazil. COVID-19 has been spreading very quickly, causing great concern in relation to the ability to care for critically ill patients. Control measures are being imposed by governments with the aim of reducing the contamination and the spreading of viruses. The forecast of the number of contaminated and deaths caused by COVID-19 can help decision making regarding the adopted restrictions, making them more or less rigid depending on the pandemic’s control capacity. The use of LSTM stacking shows an R2 of 0.9625 for confirmed cases and 0.9656 for confirmed deaths caused by COVID-19, being superior to the combinations among other evaluated models.

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This article aims to understand the perceptions of young rural entrepreneurs about the difficulties in investing in family farms in which they work. Ninety-eight people were interviewed at the event “Meeting of Young Entrepreneurs of the Rural Environment of Santa Catarina: the rural youth leading the sustainable development”, held in May 2019. The methodology applied in this paper is qualitative and quantitative, through a bibliographic review and a numerical analysis on work conditions and workers’ profile. A brief theoretical background is presented to facilitate the understanding of the results and their relation to family farming, entrepreneurship and its reality in Brazil. As a result, the economic issue was pointed out with 34% of the cases, as a hinter to undertake in rural properties, followed by the lack and low qualification of the workforce available with 12.6% of the cases and the lower selling price for the producer with 7.6% of the cases.

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Currently, renewable energies and their methods of use are being increasingly discussed due to the energy crisis in some regions and the environmental problems caused by pollution from other forms of electricity generation. One of the alternatives for electricity is solar energy, however, it is known that the cost for the construction of a photovoltaic plant in Brazil is still has a high and not feasible for some regions. Therefore, this work aims to make a study of the use of solar energy in the form of a Grid-Connected Photovoltaic Power System in the Serrana Meso-Region. For the development of this study will be conducted a study of the operation, factors that influence this type of electricity generation and its costs in the city of Lages/SC, this way evaluating its viability.

This research thematic is the Economic Viability Study, in order to implement a cogeneration system, in a logging company, located in the Santa Catarina highland plateau region. Thus, reducing its production cost, since much of it is due electricity purchase. Data collection of both production, consumption and expenses with electricity purchase and billing were carried out together with the company. Descriptive method was used, with case study. For the economic analysis, both net present value (NPV), internal rate of return (IRR) and payback period were used. With this information and crossing the data, the economic viability for this project became evident, as it can be visualized throughout of this article.

This article aims to identify the challenges that women engineers face in their field of work. The main theoretical references are: Silva (1992), Hirata; Kergoat (2007), Carvalho; Casagrande (2011); Carvalho (2008); Casagrande et al. (2004); Lombardi (2006a, 2006b); Cabral; Bazzo (2005); Lime; Souza (2011); among others. It is a qualitative-quantitative research and data were collected through questionnaires. The 69 women who graduated from 2011 to 2018 were invited to participate in the survey. Of these 33 answered the instrument. The data show that women engineers experience gender discrimination, sexism, racism and sexual and moral harassment in their work field. Finally, these women, in 2019, reported cases of gender inequality experienced in the labor market. In this perspective, the study points out the following strategies to fight gender discrimination in the production engineering course: - include publications by renowned engineers in the teaching plans; - discuss with students and professors of the course about gender equity in the labor market.