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2021 IEEE Congress on Evolutionary Computation, CEC 2021 ; : 1296-1303, 2021.
Article in English | Scopus | ID: covidwho-1706619


The COVID-19 pandemic has created an urgency for studies to understand the spread of the virus, in particular, to predict the number of daily cases. This type of investigation depends heavily on the data collected and made available manually. Therefore, data are susceptible to human errors which can cause anomalies in the dataset. Understanding and correcting anomalies in real-world application data is an important task to ensure the reliability of the data analysis and prediction tools. This paper presents a spectral anomaly detection and correction strategy that uses concepts from the graph signal processing (GSP) theory. The main advantage of the introduced strategy is to analyze the variation in the daily number of cases with the proximity relation between the investigated locations. Experiments were carried out with real meteorological and mobility data for predicting the number of COVID-19 cases by the classic prediction model known as autoregressive integrated moving average exogenous (ARIMAX). Then, the anomaly detection method was applied to determine the relationship between the prediction errors and the anomalous variations identified by the tool. The results show a strong relationship between the anomalous variations and the errors made by the model and attest to the increase in the accuracy of the prediction model after the normalization of the anomalies. © 2021 IEEE

Ars Veterinaria ; 37(3):128-133, 2021.
Article in Portuguese | CAB Abstracts | ID: covidwho-1478721


The pandemic caused by SARS-CoV-2 brought to society a health crisis that drastically affected the global economy and brought more restrictive measures to food supply establishments, which are classified as essential activities. However, they had to adapt to the new hygienic-sanitary operating protocol, established through regulations published by the Federal and State Governments in order to reduce the chances of viral spread. The objective of the study was to evaluate the hygienic and sanitary conditions of fish sold in fish markets in the city of Nova Iguacu/RJ, through questionnaires on the application of good marketing and handling practices, during the lockdown related to the coronavirus pandemic. An observational "checklist" type questionnaire was used to assess the hygienic and sanitary conditions of fish in 13 fish markets located in 7 districts of Nova Iguacu/RJ. It was observed that in 92% of the establishments visited had materials and equipment in disuse in the outdoor area, had failures in conservation, sanitation and adequate maintenance, without vector and pest control, without a suitable container for waste collection, lack of personal cleanliness and did not present the amount of flaky ice adequate to coat the fish. Thus, it was possible to check that the establishments did not follow the basic rules of hygiene and safety of the fish to reduce the dissemination of the coronavirus, confirming that the commercialization of fish in the fish markets visited in the municipality of Nova Iguacu/RJ does not meet the recommended standards of hygiene and packaging of the products sold. Therefore, the relevance of this study is to provide fishmongers in the municipality of Nova Iguacu, practical and viable guidelines for adapting to the legislation, with the main objective of updating and favoring the reinforcement of Good Handling Practices through an illustrative folder distributed later on visits to establishments.