Cost-Effective Platform for Particulate Matter Rapid Monitoring

Particles in the air with volume ≤ 2.5 μm3 have been classified as carcinogenic by the World Health Organization (WHO). Therefore, rapid monitoring systems are crucial to obtain information about particulate matter (PM) concentrations and make this information publicly available. Supported by WHO criteria, this text focuses on the development of a field-portable cost-effective platform for rapid monitoring, data acquisition of particulate matter (PM10 and PM2.5) and measurements of environmental variables (relative air humidity and temperature) at the micrometeorological level, in addition to providing access via the Internet of Thing (IoT). The platform was tested, as well as validating its results when compared to those made available at the National Meteorology Institute-INMET (Instituto Nacional de Meteorologia). Based on this technology, tests and measurements have been performed in the local presence of the population and vehicle traffic, in order to identify the concentrations of PM in public places. Between the results obtained, the device recorded higher temperature and low humidity, at 12 noon, and the average hourly reached 175.3 µg/m3 (PM10) and 164.2 µg/m3 (PM2.5), which means a warning sign. This computational platform would be useful for cost-effective and rapid quantification of PM density even in field and resource-poor settings

Internet of Things-Aided Smart Home Off-Grid Photovoltaic-Powered

Nowadays, smart devices which can be controlled remotely by the Internet appear in the preference setting rather than the manual control to improve the standard of living. In this paper, a domotic system integrated into PV power generation has been developed on the Internet of Things (IoT). The system uses sensors for fire detection and monitoring of the temperature and relative air humidity. Based on real-time, the home automation off-grid system is developed so that makes the system cost-effective and portable

Quantitative and Qualitative Approach of Scientific Paper Popularity By Naïve Bayes Classifier

Usually, scientific research begins with the collection of data in which online social media tools can be some of the most rewarding and informative resources. The extensive measure of accessible information pulls in users from undergraduate students to postdoc. The search for scientific themes has popularized due to the availability of abundant publications that resides in scientific social networks such as Mendeley, ResearchGate etc. Articles are published on these media inform of text for knowledge dissemination, scientific support, research, updates etc, and are frequently uploaded after its publication in a proceedings or journal. In this sense, data collected from database often contains high noise and its analysis can be treated as a characterization undertaking as it groups the introduction of a content into either good or bad. In this text, we present quantitative and qualitative analysis of papers popularity in Mendeley repository by using naive Bayes Classifier

Quantitative Analysis Powered by Naïve Bayes Classifier Algorithm to Data-Related Publications Social-Scientific Network

Quantitative evaluation of a dataset can play an important role in pattern recognition of technical-scientific research involving behavior and dynamics in social networks. As an example, are the adaptive feature weighting approaches by naive Bayes text algorithm. This work aims to present an exploratory data analysis with a quantitative approach that involves pattern recognition using the Mendeley research network; to identify logics given the popularity of document access. To better analyze the results, the work was divided into four categories, each with three subcategories, that is, five, three, and two output classes. The name for these categories came up due to data collection, which also presented documents with open access, dismembering proceedings, and journals for two more categories. As a result, the performance for the test examples showed a lower error rate related to the subcategory two output classes in the criterion of popularity by using the naive Bayes algorithm in Mendeley

Usage of Arduino-based Datalogger for thermal comfort variables monitoring

Environmental monitoring is an effective tool to identify problems in anthropic areas, and the emergence of cyber-physical sensors contributes to technological advances in the area. This paper introduces a device based on the Arduino cyber-physical platform to monitor air temperature and relative humidity in real-time with high efficiency. With the relationship between these two environmental variables, it will be possible to calculate the Heat Index (CI), the Temperature and Humidity Index (ITU), the Effective Temperature Index (ET), and the Thermal Discomfort Index (IDT). The Datalogger developed is easily programmable and easy to assemble and presented stable operation and proper functioning

Time-series forecasting models: An application for climatological parameters in the city of Belém, Pará, Brazil

Statistical and mathematical models of forecasting are of paramount importance for the understanding and study of databases, especially when applied to data of climatological variables, which enables the atmospheric study of a city or region, enabling greater management of the anthropic activities and actions that suffer the direct or indirect influence of meteorological parameters, such as precipitation and temperature. Therefore, this article aimed to analyze the behavior of monthly time series of Average Minimum Temperature, Average Maximum Temperature, Average Compensated Temperature, and Total Precipitation in Belém (Pará, Brazil) on data provided by INMET, for the production and application forecasting models. A 30-year time series was considered for the four variables, from January 1990 to December 2020. The Box and Jenkins methodology was used to determine the statistical models, and during their applications, models of the SARIMA and Holt-Winters class were estimated. For the selection of the models, analyzes of the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Autocorrelation Correlogram (ACF), and Partial Autocorrelation (PACF) and tests such as Ljung-Box and Shapiro-Wilk were performed, in addition to Mean Square Error (NDE) and Absolute Percent Error Mean (MPAE) to find the best accuracy in the predictions. It was possible to find three SARIMA models: (0,1,2) (1,1,0) [12], (1,1,1) (0,0,1) [12], (0,1,2) (1,1,0) [12]; and a Holt-Winters model with additive seasonality. Thus, we found forecasts close to the real data for the four-time series worked from the SARIMA and Holt-Winters models, which indicates the feasibility of its applicability in the study of weather forecasting in the city of Belém. However, it is necessary to apply other possible statistical models, which may present more accurate forecasts

Holt-Winters Forecasting for Brazilian Natural Gas Production

Nowadays, the market for natural gas production and its use as a source of energy supply has been growing substantially in Brazil. However, the use of tools that assist the industry in the management of production can be essential for the strategic decision-making process. In this intuit, this work aims to evaluate the formulation of Holt Winter\u27s additive and multiplicative time series to forecast Brazilian natural gas production. A comparison between the models and their forecast play a vital role for policymakers in the strategic plan, and the models estimated production values ​​for the year 2018 based on the information contained in the interval between 2010 and 2017. Therefore, It was verified that the multiplicative method had a good performance so that we can conclude this formulation is ideal for such an application since all the predicted results by this model showed greater accuracy within the 95% confidence interval

MECANISMO DE DIFUSÃO-OSMOSE EM SISTEMAS VEGETAIS SOB INFLUÊNCIAS DE CAMPOS MAGNÉTICOS ESTACIONÁRIOS DE NEODÍMIO

In order to explain the operating mechanisms of electromagnetic influences on plant development and the facts found in the literature, this article has the general objective of studying such influences and the mechanism acting in this phenomenon, in order to describe it as a possible scientific solution. The quali-quantitative methodology, defined by main experimentation that will evaluate the water and nutrient transport mechanism, namely: observation of water absorption by seeds of 3 species, lettuce, tomato and melon, divided into two groups, control and experimental. The latter being under the influence of permanent bar magnets of Neodymium, magnetic induction, performing collections of Total Dissolved Solids (TDS), from TDS Meter V1.0 sensors, compatible with Arduino software, in time intervals of 2 hours. The results obtained corroborate what is described in the literature, demonstrating an intensified decrease in the amount of water and also solutes in the experimental groups, compared to the controls, so that the seeds under magnetic influences absorbed all the water and nutrients in a shorter time than the same under natural conditions, which is plausible in relation to the intensification of plant metabolism resulting from electromagnetic influences, and the identification of a possible synergistic mechanism of Diffusion-Osmosis.Para explicar os mecanismos operantes das influências eletromagnéticas sobre o desenvolvimento vegetal, o presente artigo tem por objetivo investigar as influências e mecanismos atuantes neste fenômeno, a fim de descrever o processo difusivo com e sem presença de campo magnético sobre as amostras. A metodologia utilizada é de cunho quali-quantitativo, definida por experimentação principal que avaliará o mecanismo de transporte de água e nutrientes, à saber: observação da absorção de água por sementes de 3 espécies, alface, tomate e melão, divididas em dois grupos, controle e experimental. Sendo que este último estava sob a influência de imãs permanentes de Neodímio em barra, de indução magnética, realizando coletas de Sólidos Totais Dissolvidos, a partir de sensores TDS Meter V1.0, compatíveis com o software Arduino, em intervalos de tempo de 2 h. Os resultados obtidos corroboram com o que é descrito na literatura, demonstrando a diminuição intensificada da quantidade de água e também solutos nos grupos experimentais, em comparação aos controles, de modo que as sementes sob influências magnéticas absorveram toda a água e nutrientes em menor tempo do que as mesmas em condições naturais, o que é plausível em relação a intensificação no metabolismo vegetal oriundo das influências eletromagnéticas, e a identificação de um possível mecanismo sinérgico de Difusão-Osmose. Palavras-chave: eletromagnetismo; termodinâmica; metabolismo vegetal; canais iônicos.   Diffusion-osmosis mechanism in plant systems under influences of neodymium stationary magnetic fields   ABSTRACT: To explain the operating mechanisms of electromagnetic influences on plant development and the facts found in the literature, this article aims to investigate the influences and mechanisms acting on the specific mechanisms, to describe the diffusive process with and without the presence of magnetic field on the samples. The methodology used is a quality-quantitative methodology, defined by main experimentation that will evaluate the water and nutrient transport mechanism: observation of water absorption by seeds of 3 species, lettuce, tomato and melon, divided into two groups, control and experimental. The latter is under the influence of permanent bar magnets of Neodymium, magnetic induction, performing collections of Total Dissolved Solids (TDS), from TDS Meter V1.0 sensors, compatible with Arduino software, in time intervals of 2 hours. The results obtained corroborate what is described in the literature, demonstrating an intensified decrease in the amount of water and solutes in the experimental groups, compared to the controls, so that the seeds under magnetic influences absorbed all the water and nutrients in a shorter time than the same under natural conditions, which is plausible in relation to the intensification of plant metabolism resulting from electromagnetic influences, and the identification of a possible synergistic mechanism of Diffusion-Osmosis. Keywords: electromagnetism; thermodynamics; plant metabolism; ionic channels

Forecasting incidence of tuberculosis cases in Brazil based on various univariate time-series models

Tuberculosis (TB) remains the world\u27s deadliest infectious disease and is a serious public health problem. Control for this disease still presents several difficulties, requiring strategies for the execution of immediate combat and intervention actions. Given that changes through the decision-making process are guided by current information and future prognoses, it is critical that a country\u27s public health managers rely on accurate predictions that can detect the evolving incidence phenomena. of TB. Thus, this study aims to analyze the accuracy of predictions of three univariate models based on time series of diagnosed TB cases in Brazil, from January 2001 to June 2018, in order to establish which model presents better performance. For the second half of 2018. From this, data were collected from the Department of Informatics of the Unified Health System (DATASUS), which were submitted to the methods of Simple Exponential Smoothing (SES), Holt-Winters Exponential Smoothing (HWES) and the Integrated Autoregressive Moving Average (ARIMA) model. In the performance analysis and model selection, six criteria based on precision errors were established: Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percent Error (MAPE) and Theil\u27s U statistic (U1 and U2). According to the results obtained, the HWES (0.2, 0.1, 0.1) presented a high performance in relation to the error metrics, consisting of the best model compared to the other two methodologies compared here

Wind Effect on Microclimate and Thermal Comfort Index in Open-air Public Spaces in the Brazilian Rainforest Cities

Amazon cities and rural villages came to fragment its green spaces, implying changes in the quality of life of its population. Despite clear warning signs, this picture of environmental degradation processes has affected flora and fauna with severe consequences throughout the forest, from points that tend to widen over time. Supported on a literature review of microclimate research in environments, which is based on the dew point temperature, another suitability has been formulated considering the importance of wind speed. By using computational records, when this variable is contained in the characterization of a person\u27s sense of well-being in a given outdoor environment, a thermal comfort index can be established to assist in planning the construction of appropriate leisure areas, as well as identifying unhealthy environments. The results were obtained in different places, during drier summer months in the Amazon rainforest, around the city of Belém, located in the extreme north of Brazil. The best responses were registered in an environment characterized by arboreal architecture planning, followed by an environment with an intact vegetation forest