Reconhecimento de Dígitos de Medidores de Energia por meio da Voz no Contexto de um Aplicativo de Autoleitura / Digit Recognition of Energy Meters through Voice in the Context of an Authentication Application

A Agência Nacional de Energia Elétrica (ANEEL) destaca que perdas não-técnicas estão relacionadas a entraves no processo de leitura de consumo. Para a redução dessas falhas, uma alternativa factível e de menor custo seria a leitura realizada pelo próprio consumidor, denominada de autoleitura.  Este processo leva em consideração o uso de plataformas digitais, através das quais o consumidor registraria e enviaria as informações de consumo.  Uma etapa importante desse processo é o reconhecimento automático de dígitos de medidores por meio da voz.  Este trabalho, portanto, propõe um método para a realização dessa tarefa, que utiliza processamento de áudio e inteligência computacional. Para a extração de características de áudio, utiliza-se Mel-frequency Cepstral Coefficients (MFCC) e MelSpectrogram de forma combinada. O método apresenta Recall de 94,74%; Precision de 94,91%; F1 score de 94,72% e 0,9419 de índice Kappa utilizando-se o classificador Support Vector Machine (SVM)

Reconhecimento de Dígitos em Imagens de Medidores de Energia no Contexto de um Aplicativo de Autoleitura / Digit Recognition in Energy Meter Images in the Context of a Self-Reading Application

Segundo a Agência Nacional de Energia Elétrica (ANEEL), perdas não-técnicas são aquelas relacionadas a furtos de energia e impedimento de acesso às unidades consumidoras. Uma alternativa viável e de menor custo para a redução dessas falhas seria a leitura realizada pelo próprio consumidor, denominada de autoleitura.  Esse processo engloba o uso de plataformas digitais, por meio das quais o consumidor registraria e enviaria as informações de consumo. Uma etapa primordial desse processo é o reconhecimento automático de dígitos em medidores por meio de imagens. Este trabalho propõe um método computacional para a realização dessa tarefa. São utilizados os descritores de característica Histogram of Oriented Gradients (HoG) e Local Self-similarity (LSS) de forma combinada e o classificador Máquina de Vetores de Suporte (SVM). O método alcança acurácia de 97,90% e 96,72%, respectivamente, para o reconhecimento de dígitos em medidores digitais e analógicos.

Segmentação Semântica de Medidores de Energia Elétrica e Componentes de Identificação / Semantic Segmentation of Electricity Meters and Identification Components

A Agência Nacional de Energia Elétrica (ANEEL) classifica erros de medição de consumo e processamento de fatura como perdas não-técnicas.  Quando essas irregularidades são identificadas, ´e solicitada a aquisição da imagem do medidor e a captura da localização geográfica do leiturista para registrar a sua presença no local. Essas imagens são enviadas para o setor de auditoria. Este recebe um grande volume de imagens, cuja análise completa é muito lenta. Como alternativa, tem-se a autoleitura, que é a leitura feita pelo próprio cliente através de plataformas digitais. E para garantir a segurança no processo de autoleitura, é necessária uma etapa automática de validação (autoauditoria).  Este trabalho propõe um método baseado em aprendizado profundo para a segmentação semântica de medidores de energia e componentes de identificação, almejando contribuir com mais eficiência ao processo de validação de leitura.  O método apresenta mean average precision (mAP) de 73,10% para os casos em que intersection over union (IoU) ? a 0,50; 42,17% para IoU ? 0,75 e 41,28% quando IoU ? 0,99

METODOLOGÍA PARA LA CONSTRUCCIÓN DE OBJETOS DE APRENDIZAJE PARA EDUCACIÓN A DISTANCIA

Resumen- Este artículo presenta el itinerario utilizado por el equipo de la Univap Virtual para el proyecto, producción y la evaluación del material didáctico destinado a cursos ofrecidos a través de la modalidad a distancia. Este processo es oriundo de la necesidad de construir un material adecuado para la modalidad y destinado a un público alvo específico. La metodología desarrollada está concentrada en cinco fases principales: análise, planificación y desenvolvimiento educativo, pré-producción, producción e integración. El proceso de planificación prevé la creación de objetos de aprendizaje (AO) pretendiendo su futura utilización en ambientes virtuales de aprendizaje (AVA) tomando por base el SCORM. La evaluación del material ocurre durante su desarrollo y en la implementación del curso. Como resultado, se presenta un material didáctico desarrollado con el uso de la tecnología Flash, abordando el tema electricidad por fricción para alumnos de educación primaria y secundaria

The TIGIT+ T regulatory cells subset associates with nosocomial infection and fatal outcome in COVID-19 patients under mechanical ventilation

Abstract: The TIGIT+FOXP3+Treg subset (TIGIT+Tregs) exerts robust suppressive activity on cellular immunity and predisposes septic individuals to opportunistic infection. We hypothesized that TIGIT+Tregs could play an important role in intensifying the COVID-19 severity and hampering the defense against nosocomial infections during hospitalization. Herein we aimed to verify the association between the levels of the TIGIT+Tregs with the mechanical ventilation requirement, fatal outcome, and bacteremia during hospitalization. TIGIT+Tregs were immunophenotyped by flow cytometry from the peripheral blood of 72 unvaccinated hospitalized COVID-19 patients at admission from May 29th to August 6th, 2020. The patients were stratified during hospitalization according to their mechanical ventilation requirement and fatal outcome. COVID-19 resulted in a high prevalence of the TIGIT+Tregs at admission, which progressively increased in patients with mechanical ventilation needs and fatal outcomes. The prevalence of TIGIT+Tregs positively correlated with poor pulmonary function and higher plasma levels of LDH, HMGB1, FGL2, and TNF. The non-survivors presented higher plasma levels of IL-33, HMGB1, FGL2, IL-10, IL-6, and 5.54 times more bacteremia than survivors. Conclusions: The expansion of the TIGIT+Tregs in COVID-19 patients was associated with inflammation, lung dysfunction, bacteremia, and fatal outcome

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data