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Eniuce M. de Souza
Department of Statistics, State University of Maringa, PR, Brazil

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Review
Published: 28 June 2020 in Earth-Science Reviews
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The study of outcrop analogues of petroleum reservoirs is well established in the petroleum industry through the use of digital outcrop models (DOMs). These models, which are also known as virtual outcrop models (VOMs) or 3D outcrops, are of great importance for understanding the behavior of actual reservoirs. This topic has been reviewed by many authors, and the studies vary in detail according to the technologies involved. The present study applies systematic review methodology traversing a number of articles to find the trends in studies utilizing DOMs. The articles included in this review indicate that the technologies used to generate DOMs are still predominantly classified as Light Detection and Ranging (LiDAR) and digital photogrammetry, with the first being present in most of the works, and the latter attracting attention owing to the popularity of unmanned aerial vehicles (UAVs). These studies have attracted a significant amount of attention to outcrop analysis, and the information acquired can be used to better fit reservoir simulations. Furthermore, a trend is identified with a focus on outcrop geometry and structural data. This work also discusses some of the available opportunities related to the generation of DOMs as well as emerging technologies that can improve the quality of the outcrop models in order to provide better reservoir simulations. Finally, this work discusses the findings and highlights of the articles answering the initially raised research questions.

ACS Style

Ademir Marques; Rafael Kenji Horota; Eniuce Menezes de Souza; Lucas Kupssinskü; Pedro Rossa; Alysson Soares Aires; Leonardo Bachi; Mauricio Roberto Veronez; Luiz Gonzaga; Caroline Lessio Cazarin. Virtual and digital outcrops in the petroleum industry: A systematic review. Earth-Science Reviews 2020, 208, 103260 .

AMA Style

Ademir Marques, Rafael Kenji Horota, Eniuce Menezes de Souza, Lucas Kupssinskü, Pedro Rossa, Alysson Soares Aires, Leonardo Bachi, Mauricio Roberto Veronez, Luiz Gonzaga, Caroline Lessio Cazarin. Virtual and digital outcrops in the petroleum industry: A systematic review. Earth-Science Reviews. 2020; 208 ():103260.

Chicago/Turabian Style

Ademir Marques; Rafael Kenji Horota; Eniuce Menezes de Souza; Lucas Kupssinskü; Pedro Rossa; Alysson Soares Aires; Leonardo Bachi; Mauricio Roberto Veronez; Luiz Gonzaga; Caroline Lessio Cazarin. 2020. "Virtual and digital outcrops in the petroleum industry: A systematic review." Earth-Science Reviews 208, no. : 103260.

Journal article
Published: 23 June 2020 in Sensors
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Spectral information provided by multispectral and hyperspectral sensors has a great impact on remote sensing studies, easing the identification of carbonate outcrops that contribute to a better understanding of petroleum reservoirs. Sensors aboard satellites like Landsat series, which have data freely available usually lack the spatial resolution that suborbital sensors have. Many techniques have been developed to improve spatial resolution through data fusion. However, most of them have serious limitations regarding application and scale. Recently Super-Resolution (SR) convolution neural networks have been tested with encouraging results. However, they require large datasets, more time and computational power for training. To overcome these limitations, this work aims to increase the spatial resolution of multispectral bands from the Landsat satellite database using a modified artificial neural network that uses pixel kernels of a single spatial high-resolution RGB image from Google Earth as input. The methodology was validated with a common dataset of indoor images as well as a specific area of Landsat 8. Different downsized scale inputs were used for training where the validation used the ground truth of the original size images, obtaining comparable results to the recent works. With the method validated, we generated high spatial resolution spectral bands based on RGB images from Google Earth on a carbonated outcrop area, which were then properly classified according to the soil spectral responses making use of the advantage of a higher spatial resolution dataset.

ACS Style

Ademir Marques Junior; Eniuce Menezes De Souza; Marianne Müller; Diego Brum; Daniel Capella Zanotta; Rafael Kenji Horota; Lucas Silveira Kupssinskü; Maurício Roberto Veronez; Jr. Luiz Gonzaga; Caroline Lessio Cazarin. Improving Spatial Resolution of Multispectral Rock Outcrop Images Using RGB Data and Artificial Neural Networks. Sensors 2020, 20, 3559 .

AMA Style

Ademir Marques Junior, Eniuce Menezes De Souza, Marianne Müller, Diego Brum, Daniel Capella Zanotta, Rafael Kenji Horota, Lucas Silveira Kupssinskü, Maurício Roberto Veronez, Jr. Luiz Gonzaga, Caroline Lessio Cazarin. Improving Spatial Resolution of Multispectral Rock Outcrop Images Using RGB Data and Artificial Neural Networks. Sensors. 2020; 20 (12):3559.

Chicago/Turabian Style

Ademir Marques Junior; Eniuce Menezes De Souza; Marianne Müller; Diego Brum; Daniel Capella Zanotta; Rafael Kenji Horota; Lucas Silveira Kupssinskü; Maurício Roberto Veronez; Jr. Luiz Gonzaga; Caroline Lessio Cazarin. 2020. "Improving Spatial Resolution of Multispectral Rock Outcrop Images Using RGB Data and Artificial Neural Networks." Sensors 20, no. 12: 3559.

Journal article
Published: 28 May 2020 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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This paper proposes a technique named Printgrammetry, a structured workflow that allows the extraction of 3D models from Google Earth platform through the combination of image captures from the screen monitor with Structure from Motion algorithms. This technique was develop to help geologists and other geoscientists in acquiring 3D photo-realistic models of outcrops and natural landscapes of big proportions without the need of field mapping and expensive equipment. The methodology is detailed aiming to permit easy reproducibility and focused on achieving the highest resolution possible by working with the best images that the platform can provide. The results have shown that it is possible to obtain visually high quality models from natural landscapes from Google Earth by acquiring images at high Level of Detail regions of the software, using a 4K monitor, multi-directional screenshots and by marking homogeneously spaced targets for georeferencing and scaling. The geometric quality assessment performed using Light Detection and Ranging ground truth data as comparison shows that the Printgrammetry dense point clouds have reached 98.1\% of the total covered area under 5 meters of distance for the Half Dome case study and 96.7\% for the Raplee Ridge case study. The generated 3D models were then visualized and interacted through an immersive virtual reality software that allowed geologists to manipulate this virtual field environment in different scales. This technique is considered by the authors to have a promising potential for research, industrial and educational projects that doesn't requires highly precision models.

ACS Style

Rafael Kenji Horota; Alysson Soares Aires; Ademir Marques; Pedro Rossa; Eniuce Menezes De Souza; Luiz Gonzaga; Mauricio Roberto Veronez. Printgrammetry—3-D Model Acquisition Methodology From Google Earth Imagery Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2020, 13, 2819 -2830.

AMA Style

Rafael Kenji Horota, Alysson Soares Aires, Ademir Marques, Pedro Rossa, Eniuce Menezes De Souza, Luiz Gonzaga, Mauricio Roberto Veronez. Printgrammetry—3-D Model Acquisition Methodology From Google Earth Imagery Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020; 13 (99):2819-2830.

Chicago/Turabian Style

Rafael Kenji Horota; Alysson Soares Aires; Ademir Marques; Pedro Rossa; Eniuce Menezes De Souza; Luiz Gonzaga; Mauricio Roberto Veronez. 2020. "Printgrammetry—3-D Model Acquisition Methodology From Google Earth Imagery Data." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13, no. 99: 2819-2830.

Journal article
Published: 25 May 2020 in International Journal of Environmental Research and Public Health
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The relationship between the fires occurrences and diseases is an essential issue for making public health policy and environment protecting strategy. Thanks to the Internet, today, we have a huge amount of health data and fire occurrence reports at our disposal. The challenge, therefore, is how to deal with 4 Vs (volume, variety, velocity and veracity) associated with these data. To overcome this problem, in this paper, we propose a method that combines techniques based on Data Mining and Knowledge Discovery from Databases (KDD) to discover spatial and temporal association between diseases and the fire occurrences. Here, the case study was addressed to Malaria, Leishmaniasis and respiratory diseases in Brazil. Instead of losing a lot of time verifying the consistency of the database, the proposed method uses Decision Tree, a machine learning-based supervised classification, to perform a fast management and extract only relevant and strategic information, with the knowledge of how reliable the database is. Namely, States, Biomes and period of the year (months) with the highest rate of fires could be identified with great success rates and in few seconds. Then, the K-means, an unsupervised learning algorithms that solves the well-known clustering problem, is employed to identify the groups of cities where the fire occurrences is more expressive. Finally, the steps associated with KDD is perfomed to extract useful information from mined data. In that case, Spearman’s rank correlation coefficient, a nonparametric measure of rank correlation, is computed to infer the statistical dependence between fire occurrences and those diseases. Moreover, maps are also generated to represent the distribution of the mined data. From the results, it was possible to identify that each region showed a susceptible behaviour to some disease as well as some degree of correlation with fire outbreak, mainly in the drought period.

ACS Style

Lucas Schroeder; Mauricio Roberto Veronez; Eniuce Menezes De Souza; Diego Brum; Jr. Luiz Gonzaga; Vinicius Francisco Rofatto. Respiratory Diseases, Malaria and Leishmaniasis: Temporal and Spatial Association with Fire Occurrences from Knowledge Discovery and Data Mining. International Journal of Environmental Research and Public Health 2020, 17, 3718 .

AMA Style

Lucas Schroeder, Mauricio Roberto Veronez, Eniuce Menezes De Souza, Diego Brum, Jr. Luiz Gonzaga, Vinicius Francisco Rofatto. Respiratory Diseases, Malaria and Leishmaniasis: Temporal and Spatial Association with Fire Occurrences from Knowledge Discovery and Data Mining. International Journal of Environmental Research and Public Health. 2020; 17 (10):3718.

Chicago/Turabian Style

Lucas Schroeder; Mauricio Roberto Veronez; Eniuce Menezes De Souza; Diego Brum; Jr. Luiz Gonzaga; Vinicius Francisco Rofatto. 2020. "Respiratory Diseases, Malaria and Leishmaniasis: Temporal and Spatial Association with Fire Occurrences from Knowledge Discovery and Data Mining." International Journal of Environmental Research and Public Health 17, no. 10: 3718.

Journal article
Published: 09 April 2020 in Sensors
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Total Suspended Solids (TSS) and chlorophyll-a concentration are two critical parameters to monitor water quality. Since directly collecting samples for laboratory analysis can be expensive, this paper presents a methodology to estimate this information through remote sensing and Machine Learning (ML) techniques. TSS and chlorophyll-a are optically active components, therefore enabling measurement by remote sensing. Two study cases in distinct water bodies are performed, and those cases use different spatial resolution data from Sentinel-2 spectral images and unmanned aerial vehicles together with laboratory analysis data. In consonance with the methodology, supervised ML algorithms are trained to predict the concentration of TSS and chlorophyll-a. The predictions are evaluated separately in both study areas, where both TSS and chlorophyll-a models achieved R-squared values above 0.8.

ACS Style

Lucas Silveira Kupssinskü; Tainá Thomassim Guimarães; Eniuce Menezes De Souza; Daniel C. Zanotta; Mauricio Roberto Veronez; Jr. Luiz Gonzaga; Frederico Fábio Mauad. A Method for Chlorophyll-a and Suspended Solids Prediction through Remote Sensing and Machine Learning. Sensors 2020, 20, 2125 .

AMA Style

Lucas Silveira Kupssinskü, Tainá Thomassim Guimarães, Eniuce Menezes De Souza, Daniel C. Zanotta, Mauricio Roberto Veronez, Jr. Luiz Gonzaga, Frederico Fábio Mauad. A Method for Chlorophyll-a and Suspended Solids Prediction through Remote Sensing and Machine Learning. Sensors. 2020; 20 (7):2125.

Chicago/Turabian Style

Lucas Silveira Kupssinskü; Tainá Thomassim Guimarães; Eniuce Menezes De Souza; Daniel C. Zanotta; Mauricio Roberto Veronez; Jr. Luiz Gonzaga; Frederico Fábio Mauad. 2020. "A Method for Chlorophyll-a and Suspended Solids Prediction through Remote Sensing and Machine Learning." Sensors 20, no. 7: 2125.

Original article
Published: 01 December 2019 in Revista Brasileira de Enfermagem
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Objective: to analyze the trend of hospitalizations of adolescents due to mental and behavioral disorders in Paraná, from 1998 to 2015. Method: ecological study of time series. Data were analyzed by means of segmented linear regression modeling for time series, estimated for each of the four health macro-regions. Results: the East macro-region showed a greater trend to increase hospitalizations from January 1998 to November 2003 (β1=0.006, p

ACS Style

Ellen Vanuza Martins Bertelli; Rosana Rosseto De Oliveira; Marcia Lorena Alves Dos Santos; Eniuce Menezes Souza; Carlos Alexandre Molena Fernandes; Ieda Harumi Higarashi. Time series of hospitalizations of adolescents due to mental and behavioral disorders. Revista Brasileira de Enfermagem 2019, 72, 1662 -1670.

AMA Style

Ellen Vanuza Martins Bertelli, Rosana Rosseto De Oliveira, Marcia Lorena Alves Dos Santos, Eniuce Menezes Souza, Carlos Alexandre Molena Fernandes, Ieda Harumi Higarashi. Time series of hospitalizations of adolescents due to mental and behavioral disorders. Revista Brasileira de Enfermagem. 2019; 72 (6):1662-1670.

Chicago/Turabian Style

Ellen Vanuza Martins Bertelli; Rosana Rosseto De Oliveira; Marcia Lorena Alves Dos Santos; Eniuce Menezes Souza; Carlos Alexandre Molena Fernandes; Ieda Harumi Higarashi. 2019. "Time series of hospitalizations of adolescents due to mental and behavioral disorders." Revista Brasileira de Enfermagem 72, no. 6: 1662-1670.

Journal article
Published: 13 August 2019 in Revista de Saúde Pública
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OBJECTIVE: To examine the effect of seasonality on femoral fracture incidence among people residing in the state of São Paulo, Brazil. METHODS: Ecological study based on a consecutive series of 216,348 reports of hospital admissions caused by femoral fractures. A Bayesian statistical model was used for time series analysis, considering the monthly average number of events of femoral fractures per day as a dependent variable. RESULTS: Among the female population, significant seasonal effects were observed only for older women, aged 60 years or more. Among younger men (aged less than 20 years) there is not a clear seasonal effect, but among the other age groups there seems to exist a higher number of cases of femoral fractures during the coldest months of the year. CONCLUSIONS: In general, more cases of fractures occur during the coldest months of the year; however, men and women have different patterns of incidence according to each age group.

ACS Style

Mônica Marin De Souza; Eniuce Menezes De Souza; Altacílio Aparecido Nunes; Edson Zangiacomi Martinez. Seasonal variation of femoral fractures in the state of São Paulo, Southeast Brazil. Revista de Saúde Pública 2019, 53, 55 -55.

AMA Style

Mônica Marin De Souza, Eniuce Menezes De Souza, Altacílio Aparecido Nunes, Edson Zangiacomi Martinez. Seasonal variation of femoral fractures in the state of São Paulo, Southeast Brazil. Revista de Saúde Pública. 2019; 53 ():55-55.

Chicago/Turabian Style

Mônica Marin De Souza; Eniuce Menezes De Souza; Altacílio Aparecido Nunes; Edson Zangiacomi Martinez. 2019. "Seasonal variation of femoral fractures in the state of São Paulo, Southeast Brazil." Revista de Saúde Pública 53, no. : 55-55.

Journal article
Published: 29 March 2019 in Journal of Atmospheric and Solar-Terrestrial Physics
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GNSS (Global Navigation Satellite System) can provide high accuracy positioning with low costs. But, depending on error sources, as atmospheric effects, it can be degraded. Ionosphere is one of the most important error sources in GNSS positioning. Among several effects caused by ionosphere, the irregularities like ionospheric scintillations are very relevant. It can cause cycle slips, degrade the positioning accuracy and, when severe enough, can even lead to a complete loss of signal lock. Brazil, in particular, is located in one of the regions most affected by ionospheric scintillations and these effects were intensified during the last solar maximum. In this paper the main goal is to evaluate the impact of scintillation effects on positioning degradation during the last solar maximum. So far, it was used data of 2012–2014 from three reference stations located in different regions of Brazil. Statistically significant correlations were identified from Spearman's correlation coefficient. From Odds Ratio, an effect-size statistics, it was possible to see that the chance of large discrepancies in 3D positioning coordinates could be three times larger under strong scintillation effects (S4 ≥ 1) than under moderate ones (0.5

ACS Style

Daniele Barroca Marra Alves; Eniuce Menezes De Souza; Tayná Aparecida Ferreira Gouveia. Correlation between ionospheric scintillation effects and GNSS positioning over Brazil during the last solar maximum (2012–2014). Journal of Atmospheric and Solar-Terrestrial Physics 2019, 197, 105019 .

AMA Style

Daniele Barroca Marra Alves, Eniuce Menezes De Souza, Tayná Aparecida Ferreira Gouveia. Correlation between ionospheric scintillation effects and GNSS positioning over Brazil during the last solar maximum (2012–2014). Journal of Atmospheric and Solar-Terrestrial Physics. 2019; 197 ():105019.

Chicago/Turabian Style

Daniele Barroca Marra Alves; Eniuce Menezes De Souza; Tayná Aparecida Ferreira Gouveia. 2019. "Correlation between ionospheric scintillation effects and GNSS positioning over Brazil during the last solar maximum (2012–2014)." Journal of Atmospheric and Solar-Terrestrial Physics 197, no. : 105019.

Journal article
Published: 17 December 2018 in TEMA - Tendências em Matemática Aplicada e Computacional
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The estimation of the correlation between independent data sets using classical estimators, such as the Pearson coefficient, is well established in the literature. However, such estimators are inadequate for analyzing the correlation among dependent data. There are several types of dependence, the most common being the serial (temporal) and spatial dependence, which are inherent to the data sets from several fields. Using a bivariate time-series analysis, the relation between two series can be assessed. Further, as one time series may be related to an other with a time offset (either to the past or to the future), it is essential to also consider lagged correlations. The cross-correlation function (CCF), which assumes that each series has a normal distribution and is not autocorrelated, is used frequently. However, even when a time series is normally distributed, the autocorrelation is still inherent to one or both time series, compromising the estimates obtained using the CCF and their interpretations. To address this issue, analysis using the wavelet cross-correlation (WCC) has been proposed. WCC is based on the non-decimated wavelet transform (NDWT), which is translation invariant and decomposes dependent data into multiple scales, each representing the behavior of a different frequency band. To demonstrate the applicability of this method, we analyze simulated and real time series from different stochastic processes. The results demonstrated that analyses based on the CCF can be misleading; however, WCC can be used to correctly identify the correlation on each scale. Furthermore, the confidence interval (CI) for the results of the WCC analysis was estimated to determine the statistical significance.

ACS Style

Eniuce Menezes De Souza; Vinícius Basseto Félix. Wavelet Cross-correlation in Bivariate Time-Series Analysis. TEMA - Tendências em Matemática Aplicada e Computacional 2018, 19, 391 .

AMA Style

Eniuce Menezes De Souza, Vinícius Basseto Félix. Wavelet Cross-correlation in Bivariate Time-Series Analysis. TEMA - Tendências em Matemática Aplicada e Computacional. 2018; 19 (3):391.

Chicago/Turabian Style

Eniuce Menezes De Souza; Vinícius Basseto Félix. 2018. "Wavelet Cross-correlation in Bivariate Time-Series Analysis." TEMA - Tendências em Matemática Aplicada e Computacional 19, no. 3: 391.

Research article
Published: 16 November 2018 in Meteorological Applications
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A rapid increase in atmospheric water vapor is a fundamental ingredient for many intense rainfall events. High‐frequency precipitable water vapor (PWV) estimates (one minute) from a Global Positioning System (GPS) meteorological site are evaluated here for intense rainfall events during the CHUVA Vale field campaign in Brazil (November and December 2011), in which precipitation events of differing intensities and spatial dimensions, as observed by an X‐band radar, have been explored. A sharp increase in the GPS‐PWV prior to the more intense events has been found and termed GPS‐PWV “jumps”. These jumps are probably associated with water vapor convergence and the continued formation of cloud condensate and precipitation particles. A wavelet correlation analysis between the high temporal resolution GPS‐PWV time series and rainfall events are evaluated in this study and shows that there are oscillations in the PWV time series correlated with the more intense rainfall events. These oscillations are on scales related to time periods from about 32 to 64 min (associated with GPS‐PWV jumps) and 16 to 34 min (associated with positive pulses of PWV). The GPS‐PWV time‐derivative histogram for the time‐window before the rainfall event reveals different distributions influenced by positive pulses of GPS‐PWV (derivative above +9.5 mm h‐1) for higher intensity and extension events. These features are an indicative of the occurrence of intense precipitation and consequently have the potential for application in nowcasting activities. This article is protected by copyright. All rights reserved.

ACS Style

Luiz F. Sapucci; Luiz A. T. Machado; Eniuce Menezes De Souza; Thamiris B. Campos. Global Positioning System precipitable water vapour (GPS-PWV) jumps before intense rain events: A potential application to nowcasting. Meteorological Applications 2018, 26, 49 -63.

AMA Style

Luiz F. Sapucci, Luiz A. T. Machado, Eniuce Menezes De Souza, Thamiris B. Campos. Global Positioning System precipitable water vapour (GPS-PWV) jumps before intense rain events: A potential application to nowcasting. Meteorological Applications. 2018; 26 (1):49-63.

Chicago/Turabian Style

Luiz F. Sapucci; Luiz A. T. Machado; Eniuce Menezes De Souza; Thamiris B. Campos. 2018. "Global Positioning System precipitable water vapour (GPS-PWV) jumps before intense rain events: A potential application to nowcasting." Meteorological Applications 26, no. 1: 49-63.

Journal article
Published: 05 May 2018 in TEMA - Tendências em Matemática Aplicada e Computacional
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Due to the ability of time-frequency location, the wavelet transform hasbeen applied in several areas of research involving signal analysis and processing,often replacing the conventional Fourier transform. The discrete wavelet transformhas great application potential, being an important tool in signal compression,signal and image processing, smoothing and denoising data. It also presentsadvantages over the continuous version because of its easy implementation, goodcomputational performance and perfect reconstruction of the signal upon inversion.Nevertheless, the downsampling required in the discrete wavelet transformcalculous makes it shift variant and not appropriated to some applications, suchas for signals or time series analysis. On the other hand, the Non-Decimated DiscreteWavelet Transform is shift-invariant because it eliminates the downsamplingand, consequently, is more appropriate for identifying both stationary and nonstationarybehaviors in signals. However, the non-decimated wavelet transform hasbeen underused in the literature. This paper intends to show the advantages ofusing the non-decimated wavelet transform in signal analysis. The main theoricaland pratical aspects of the multiscale analysis of time series from non-decimatedwavelets in terms of its formulation using the same pyramidal algorithm of thedecimated wavelet transform was presented. Finally, applications with a simulatedand real time series compare the performance of the decimated and non-decimatedwavelet transform, demonstrating the superiority of non-decimated one, mainly dueto the shift-invariant analysis, patterns detection and more perfect reconstructionof a signal.

ACS Style

Gabriela De Oliveira Nascimento Brassarote; Eniuce Menezes De Souza; Joao Francisco Galera Monico. Non-decimated Wavelet Transform for a Shift-invariant Analysis. TEMA - Tendências em Matemática Aplicada e Computacional 2018, 19, 93 .

AMA Style

Gabriela De Oliveira Nascimento Brassarote, Eniuce Menezes De Souza, Joao Francisco Galera Monico. Non-decimated Wavelet Transform for a Shift-invariant Analysis. TEMA - Tendências em Matemática Aplicada e Computacional. 2018; 19 (1):93.

Chicago/Turabian Style

Gabriela De Oliveira Nascimento Brassarote; Eniuce Menezes De Souza; Joao Francisco Galera Monico. 2018. "Non-decimated Wavelet Transform for a Shift-invariant Analysis." TEMA - Tendências em Matemática Aplicada e Computacional 19, no. 1: 93.

Journal article
Published: 01 June 2017 in Ciência, Cuidado e Saúde
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O objetivo deste estudo foi o de descrever as características sociodemográficas dos motociclistas mortos em acidentes de trânsito e analisar a tendência temporal da mortalidade no período de 1997 a 2012. Estudo epidemiológico da mortalidade de 320 motociclistas, residentes em Maringá, Paraná. Os dados foram extraídos do Sistema de Informação sobre Mortalidade do Departamento de Informática do Sistema Único de Saúde (Datasus). A análise de tendência foi realizada a partir do ajuste de um modelo de regressão de Poisson para séries temporais. A maioria das vítimas (85,00%) era do sexo masculino, na faixa etária entre 20 e 39 anos (62,19%), branca (78,75%), com escolaridade entre oito e 11 anos de estudo (38,75%) e solteira (62,82%). Os óbitos ocorreram com maior frequência nos hospitais (53,13%) e no momento do acidente, e apenas 16,87% dos indivíduos estavam trabalhando. Houve predomínio das colisões com automóvel/caminhonete (38,75%). Observou-se aumento progressivo de mortes de 8,2% ao ano (IC 95%: 7% - 9%). A partir do modelo estimado de tendência, a média de óbitos aumentou de 8,42, em 1997, para 34,5, em 2012. Conclui-se que esses eventos representam um grave problema de saúde pública, aumentando em todo o mundo, em proporções significativas.

ACS Style

Nelson Luiz Batista De Oliveira; Eniuce Menezes De Souza; Guilherme Zubach Da Cunha. Mortalidade de motociclistas em acidentes de trânsito: tendência temporal entre 1997 e 2012/Motorcyclist mortality in traffic accidents: temporal trend between 1997 and 2012. Ciência, Cuidado e Saúde 2017, 16, 1 .

AMA Style

Nelson Luiz Batista De Oliveira, Eniuce Menezes De Souza, Guilherme Zubach Da Cunha. Mortalidade de motociclistas em acidentes de trânsito: tendência temporal entre 1997 e 2012/Motorcyclist mortality in traffic accidents: temporal trend between 1997 and 2012. Ciência, Cuidado e Saúde. 2017; 16 (1):1.

Chicago/Turabian Style

Nelson Luiz Batista De Oliveira; Eniuce Menezes De Souza; Guilherme Zubach Da Cunha. 2017. "Mortalidade de motociclistas em acidentes de trânsito: tendência temporal entre 1997 e 2012/Motorcyclist mortality in traffic accidents: temporal trend between 1997 and 2012." Ciência, Cuidado e Saúde 16, no. 1: 1.

Journal article
Published: 01 May 2017 in Advances in Space Research
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ACS Style

Eniuce Menezes Souza; Tamiris Trevisan Negri. First prospects in a new approach for structure monitoring from GPS multipath effect and wavelet spectrum. Advances in Space Research 2017, 59, 2536 -2547.

AMA Style

Eniuce Menezes Souza, Tamiris Trevisan Negri. First prospects in a new approach for structure monitoring from GPS multipath effect and wavelet spectrum. Advances in Space Research. 2017; 59 (10):2536-2547.

Chicago/Turabian Style

Eniuce Menezes Souza; Tamiris Trevisan Negri. 2017. "First prospects in a new approach for structure monitoring from GPS multipath effect and wavelet spectrum." Advances in Space Research 59, no. 10: 2536-2547.

Proceedings article
Published: 14 April 2017 in CNMAC 2016 - XXXVI Congresso Nacional de Matemática Aplicada e Computacional
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Resumo A solução das ambiguidades é o processo de determinar o número desconhecido de ciclos inteiros de dupla diferença (DDs) da fase da onda portadora, sendo um pré-requisito para a obtenção de alta acurácia no posicionamento baseado em redes. Para realizar este posicionamento com o uso de VRS (Estação de Referência Virtual), deve haver uma comunicação entre o usuário e a estação de base, para que ele possa enviar a sua localização e possa receber dados da VRS. Os dados da VRS são gerados a partir das correções obtidas para uma estação de base localizada perto do usuário. Estas correções são compostas por erros atmosféricos (ionosfera e troposfera), os quais podem ser estimados utilizando os dados das estações de referência da rede. O desafio é solucionar rapidamente as ambiguidades como inteiros. Neste trabalho, são investigadas algumas estratégias de processamento para a obtenção da solução das ambiguidades no posicionamento baseado em redes com dados GPS de dupla frequência. Esta estratégia sugere utilizar o modelo ionosfera ponderada, incorporando as coordenadas das estações de referência da rede e uma informação a priori sobre os atrasos ionosféricos, utilizando os métodos LAMBDA e o Fixed Failure Ratio Test.

ACS Style

Crislaine Menezes Da Silva; Daniele Barroca Marra Alves; Eniuce Menezes De Souza. Avaliac?a?o do desempenho da soluc?a?o das ambiguidades no posicionamento baseado em redes sob influe?ncia da atividade ionosfe?rica. CNMAC 2016 - XXXVI Congresso Nacional de Matemática Aplicada e Computacional 2017, 1 .

AMA Style

Crislaine Menezes Da Silva, Daniele Barroca Marra Alves, Eniuce Menezes De Souza. Avaliac?a?o do desempenho da soluc?a?o das ambiguidades no posicionamento baseado em redes sob influe?ncia da atividade ionosfe?rica. CNMAC 2016 - XXXVI Congresso Nacional de Matemática Aplicada e Computacional. 2017; ():1.

Chicago/Turabian Style

Crislaine Menezes Da Silva; Daniele Barroca Marra Alves; Eniuce Menezes De Souza. 2017. "Avaliac?a?o do desempenho da soluc?a?o das ambiguidades no posicionamento baseado em redes sob influe?ncia da atividade ionosfe?rica." CNMAC 2016 - XXXVI Congresso Nacional de Matemática Aplicada e Computacional , no. : 1.

Journal article
Published: 08 August 2016 in Diabetology & Metabolic Syndrome
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Studies show that educational interventions improve glycemic control in patients with diabetes mellitus (DM), reducing the occurrence of complications associated with the disease. To evaluate the effects of a mobile DM consultancy on clinical and laboratory parameters, disease knowledge, and quality of life in patients with type 2 DM (T2DM) at a primary health care network in Brazil. Randomized clinical trial conducted in a city in southern Brazil with 52 patients with T2DM receiving care at a primary health care setting. The intervention lasted for 6 months and consisted of a follow-up with an endocrinologist (five meetings), treatment adjustment based on clinical evaluation and laboratory tests, and educational activities with conversation maps in DM. The statistical analysis included comparison and association tests, considering p values ≤0.05 as statistically significant. The mean age of the patients was 63.8 years. Most participants were female (63.5 %), had low educational level (59.6 %) and family history of T2DM (71.2 %), used only oral hypoglycemic agents to manage their DM (73.2 %), presented unfavorable anthropometric and laboratory parameters, a high or medium risk of complications (84.6 %), and inadequate glycemic control (67.3 %; with 71 % of the high-risk patients presenting a HbA1c level >9 %). Adjustment in pharmacological treatment was required in 63.5 % of the patients. After the intervention, we observed a significant 0.46 % decrease in mean HbA1c level (p = 0.0218), particularly among individuals with inadequate glycemic control (0.71 %; p = 0.0136). Additionally, there was an increase in disease knowledge scores and a significant decrease in mean body mass index, waist circumference, and disease impact scores. The intervention improved glycemic control and disease knowledge, reduced the values of body mass index and waist circumference, and the impact of the disease on patients’ lives. This indicates that care and educational measures improve the experience of the patients with DM and control of the disease.

ACS Style

Wilson Eik Filho; Letícia Pastorelli Bonjorno; Ana Julia Mendes Franco; Márcia Lorena Alves Dos Santos; Eniuce Menezes De Souza; Sonia Silva Marcon. Evaluation, intervention, and follow-up of patients with diabetes in a primary health care setting in Brazil: the importance of a specialized mobile consultancy. Diabetology & Metabolic Syndrome 2016, 8, 56 .

AMA Style

Wilson Eik Filho, Letícia Pastorelli Bonjorno, Ana Julia Mendes Franco, Márcia Lorena Alves Dos Santos, Eniuce Menezes De Souza, Sonia Silva Marcon. Evaluation, intervention, and follow-up of patients with diabetes in a primary health care setting in Brazil: the importance of a specialized mobile consultancy. Diabetology & Metabolic Syndrome. 2016; 8 (1):56.

Chicago/Turabian Style

Wilson Eik Filho; Letícia Pastorelli Bonjorno; Ana Julia Mendes Franco; Márcia Lorena Alves Dos Santos; Eniuce Menezes De Souza; Sonia Silva Marcon. 2016. "Evaluation, intervention, and follow-up of patients with diabetes in a primary health care setting in Brazil: the importance of a specialized mobile consultancy." Diabetology & Metabolic Syndrome 8, no. 1: 56.

Journal article
Published: 07 September 2015 in TEMA - Tendências em Matemática Aplicada e Computacional
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Due to the numerous application possibilities, the theory of wavelets has been applied in several areas of research. The Discrete Wavelet Transform is the most known version. However, the downsampling required for its calculation makes it sensitive to the origin, what is not ideal for some applications,mainly in time series. On the other hand, the Non-Decimated Discrete Wavelet Transform (or Maximum Overlap Discrete Wavelet Transform, Stationary Wavelet Transform, Shift-invariant Discrete Wavelet Transform, Redundant Discrete Wavelet Transform) is shift invariant, because it considers all the elements of the sample, by eliminating the downsampling and, consequently, represents a time series with the same number of coefficients at each scale. In the present paper, the objective is to present the theorical aspects of the a multiscale/multiresolution analysis of non-stationary time series from non-decimated wavelets in terms of its implementation using the same pyramidal algorithm of the decimated wavelet transform. An application with real time series of the effect of the ionospheric scintillation on artificial satellite signals is investigated. With this analysis some information and hidden patterns which can not be detected in the time domain, may therefore be explained in the space-frequency domain.

ACS Style

Gabriela De Oliveira Nascimento Brassarote; Eniuce Menezes De Souza; Joao Francisco Galera Monico. Multiscale Analysis of GPS Time Series from Non-decimated Wavelet to Investigate the Effects of Ionospheric Scintillation. TEMA - Tendências em Matemática Aplicada e Computacional 2015, 16, 119 .

AMA Style

Gabriela De Oliveira Nascimento Brassarote, Eniuce Menezes De Souza, Joao Francisco Galera Monico. Multiscale Analysis of GPS Time Series from Non-decimated Wavelet to Investigate the Effects of Ionospheric Scintillation. TEMA - Tendências em Matemática Aplicada e Computacional. 2015; 16 (2):119.

Chicago/Turabian Style

Gabriela De Oliveira Nascimento Brassarote; Eniuce Menezes De Souza; Joao Francisco Galera Monico. 2015. "Multiscale Analysis of GPS Time Series from Non-decimated Wavelet to Investigate the Effects of Ionospheric Scintillation." TEMA - Tendências em Matemática Aplicada e Computacional 16, no. 2: 119.

Articles
Published: 21 August 2015 in Genetics and Molecular Biology
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The aim of this study was to determine the frequency of beta S-globin gene (βS globin) haplotypes and alpha thalassemia with 3.7 kb deletion (−α3.7kb thalassemia) in the northwest region of Paraná state, and to investigate the oxidative and clinical-hematological profile of βS globin carriers in this population. Of the 77 samples analyzed, 17 were Hb SS, 30 were Hb AS and 30 were Hb AA. The βSglobin haplotypes and −α3.7kb thalassemia were identified using polymerase chain reaction.Trolox equivalent antioxidant capacity (TEAC) and lipid peroxidation (LPO) were assessed spectophotometrically. Serum melatonin levels were determined using high-performance liquid chromatography coupled to coulometric electrochemical detection. The haplotype frequencies in the SS individuals were as follows: Bantu- 21 (62%), Benin - 11 (32%) and Atypical- 2 (6%). Bantu/Benin was the most frequent genotype. Of the 47 SS and AS individuals assessed, 17% (n = 8) had the −α3.7kb mutation. Clinical manifestations, as well as serum melatonin, TEAC and LPO levels did not differ between Bantu/Bantu and Bantu/Benin individuals (p > 0.05). Both genotypes were associated with high LPO and TEAC levels and decreased melatonin concentration. These data suggest that the level of oxidative stress in patients with Bantu/Bantu and Bantu/Benin genotypes may overload the antioxidant capacity.

ACS Style

Eliana LitsukoTomimatsu Shimauti; Danilo Silva; Eniuce Menezes Souza; Eduardo Alves de Almeida; Francismar Prestes Leal; Claudia Regina Bonini-Domingos. Prevalence of βS-globin gene haplotypes, α-thalassemia (3.7 kb deletion) and redox status in patients with sickle cell anemia in the state of Paraná, Brazil. Genetics and Molecular Biology 2015, 38, 316 -323.

AMA Style

Eliana LitsukoTomimatsu Shimauti, Danilo Silva, Eniuce Menezes Souza, Eduardo Alves de Almeida, Francismar Prestes Leal, Claudia Regina Bonini-Domingos. Prevalence of βS-globin gene haplotypes, α-thalassemia (3.7 kb deletion) and redox status in patients with sickle cell anemia in the state of Paraná, Brazil. Genetics and Molecular Biology. 2015; 38 (3):316-323.

Chicago/Turabian Style

Eliana LitsukoTomimatsu Shimauti; Danilo Silva; Eniuce Menezes Souza; Eduardo Alves de Almeida; Francismar Prestes Leal; Claudia Regina Bonini-Domingos. 2015. "Prevalence of βS-globin gene haplotypes, α-thalassemia (3.7 kb deletion) and redox status in patients with sickle cell anemia in the state of Paraná, Brazil." Genetics and Molecular Biology 38, no. 3: 316-323.

Journal article
Published: 06 August 2015 in GPS Solutions
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The global navigation satellite system (GNSS) can provide centimeter positioning accuracy at low costs. However, in order to obtain the desired high accuracy, it is necessary to use high-quality atmospheric models. We focus on the troposphere, which is an important topic of research in Brazil where the tropospheric characteristics are unique, both spatially and temporally. There are dry regions, which lie mainly in the central part of the country. However, the most interesting area for the investigation of tropospheric models is the wet region which is located in the Amazon forest. This region substantially affects the variability of humidity over other regions of Brazil. It provides a large quantity of water vapor through the humidity convergence zone, especially for the southeast region. The interconnection and large fluxes of water vapor can generate serious deficiencies in tropospheric modeling. The CPTEC/INPE (Center for Weather Forecasting and Climate Studies/Brazilian Institute for Space Research) has been providing since July 2012 a numerical weather prediction (NWP) model for South America, known as Eta. It has yield excellent results in weather prediction but has not been used in GNSS positioning. This NWP model was evaluated in precise point positioning (PPP) and network-based positioning. Concerning PPP, the best positioning results were obtained for the station SAGA, located in Amazon region. Using the NWP model, the 3D RMS are less than 10 cm for all 24 h of data, whereas the values reach approximately 60 cm for the Hopfield model. For network-based positioning, the best results were obtained mainly when the tropospheric characteristics are critical, in which case an improvement of up to 7.2 % was obtained in 3D RMS using NWP models.

ACS Style

Daniele Barroca Marra Alves; Luiz Fernando Sapucci; Haroldo Antonio Marques; Eniuce Menezes De Souza; Tayná Aparecida Ferreira Gouveia; Jackes Akira Magário. Using a regional numerical weather prediction model for GNSS positioning over Brazil. GPS Solutions 2015, 20, 677 -685.

AMA Style

Daniele Barroca Marra Alves, Luiz Fernando Sapucci, Haroldo Antonio Marques, Eniuce Menezes De Souza, Tayná Aparecida Ferreira Gouveia, Jackes Akira Magário. Using a regional numerical weather prediction model for GNSS positioning over Brazil. GPS Solutions. 2015; 20 (4):677-685.

Chicago/Turabian Style

Daniele Barroca Marra Alves; Luiz Fernando Sapucci; Haroldo Antonio Marques; Eniuce Menezes De Souza; Tayná Aparecida Ferreira Gouveia; Jackes Akira Magário. 2015. "Using a regional numerical weather prediction model for GNSS positioning over Brazil." GPS Solutions 20, no. 4: 677-685.

Journal article
Published: 29 May 2015 in TEMA - Tendências em Matemática Aplicada e Computacional
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The identification of the cyclical and seasonal variations can be veryimportant in time series. In this paper, the aim is to identify the presence ofcyclical or seasonal variations in the indices of the multipath effect on continuousGPS (Global Positioning System) stations. Due to the model used to obtain theseindices, there should not have cyclical variations in these series, at least due to themultipath effect. In order to identify the presence of cyclical variations in theseseries, correlograms and Fourier periodograms were analyzed. The Fisher test forseasonality was applied to confirm the presence of statistical significant seasonality.In addition, harmonic models were adjusted to check in which months of the yearthe cyclical effects are occurring in the multipath indices. The possible causes ofthese effects are pointed out, which will direct the upcoming investigations, as wellas the analysis and correlations of other series. The importance of this analysisis mainly due to the fact that errors in the collected signals of these stations willdirectly influence the accuracy of the results of the whole community that directlyor indirectly uses GPS data.

ACS Style

Eniuce Menezes De Souza; Daniele Barroca Marra Alves; Fernanda Lang Schumacher. Harmonic Analysis of Multipath Index Time Series in GPS Stations. TEMA - Tendências em Matemática Aplicada e Computacional 2015, 16, 71 .

AMA Style

Eniuce Menezes De Souza, Daniele Barroca Marra Alves, Fernanda Lang Schumacher. Harmonic Analysis of Multipath Index Time Series in GPS Stations. TEMA - Tendências em Matemática Aplicada e Computacional. 2015; 16 (1):71.

Chicago/Turabian Style

Eniuce Menezes De Souza; Daniele Barroca Marra Alves; Fernanda Lang Schumacher. 2015. "Harmonic Analysis of Multipath Index Time Series in GPS Stations." TEMA - Tendências em Matemática Aplicada e Computacional 16, no. 1: 71.

Observational study
Published: 01 October 2014 in Cadernos de Saúde Pública
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The aim of this study is to investigate the impact of rotavirus vaccine on hospitalization rates for acute diarrhea in children younger than 5 years old after the introduction of the vaccine in 2006. A descriptive analytical observational study was carried out of the hospitalization rates occurred between 2000 and 2011 in 22 Regional Health Centers of Paraná State, Brazil. The effect of the vaccine was assessed by applying the SARIMA/Box-Jenkins time series methodology of intervention analysis, which allows verifying the slopes of the series are different after the introduction of the vaccine and estimating the magnitude of these effects for children younger than five years of age, by age group, for each region center. It was verified a statistically significant reduction by center/month on hospitalization rates for children 1 year old and younger, with averages of 47% and 58%, respectively, in December 2011.

ACS Style

Maria De Lourdes Teixeira Masukawa; Adriana Mayumi Moriwaki; Nelson Shozo Uchimura; Eniuce Menezes De Souza; Taqueco Teruya Uchimura. Intervention analysis of introduction of rotavirus vaccine on hospital admissions rates due to acute diarrhea. Cadernos de Saúde Pública 2014, 30, 2101 -2111.

AMA Style

Maria De Lourdes Teixeira Masukawa, Adriana Mayumi Moriwaki, Nelson Shozo Uchimura, Eniuce Menezes De Souza, Taqueco Teruya Uchimura. Intervention analysis of introduction of rotavirus vaccine on hospital admissions rates due to acute diarrhea. Cadernos de Saúde Pública. 2014; 30 (10):2101-2111.

Chicago/Turabian Style

Maria De Lourdes Teixeira Masukawa; Adriana Mayumi Moriwaki; Nelson Shozo Uchimura; Eniuce Menezes De Souza; Taqueco Teruya Uchimura. 2014. "Intervention analysis of introduction of rotavirus vaccine on hospital admissions rates due to acute diarrhea." Cadernos de Saúde Pública 30, no. 10: 2101-2111.