Pré-Processamento e Classificação de Imagens NIR das Veias da Palma da Mão e Pulso Utilizando Análise por Componentes Principais

O objetivo deste trabalho é pré-processar imagens das palmas da mãos e punhos de indivíduos no intuito de aprimorar a acurácia de um modelo classificador. Tal processamento é feito para evidenciar as veias nas imagens como fator a ser usado para o reconhecimento do indivíduo. A classificação é feita empregando a análise por componentes principais, a partir de um banco de imagens no espectro do infravermelho, contendo 2400 imagens de 50 indivíduos diferentes. Os resultados obtidos utilizando o pré-processamento proposto mostram uma melhora da acurácia média de 18% em relação ao modelo que utilizou as imagens originais

Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble Approaches

Aspect-based Sentiment Analysis (ABSA) is a task whose objective is to classify the individual sentiment polarity of all entities, called aspects, in a sentence. The task is composed of two subtasks: Aspect Term Extraction (ATE), identify all aspect terms in a sentence; and Sentiment Orientation Extraction (SOE), given a sentence and its aspect terms, the task is to determine the sentiment polarity of each aspect term (positive, negative or neutral). This article presents we present our participation in Aspect-Based Sentiment Analysis in Portuguese (ABSAPT) 2022 at IberLEF 2022. We submitted the best performing systems, achieving new state-of-the-art results on both subtasks.Comment: 11 pages, 3 figures, In Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2022), Online. CEUR. or

Microscopic Image Segmentation to Quantification of Leishmania Infection in Macrophages

The determination of infection rate parameter from in vitro macrophages infected by Leishmania amastigotes is fundamental in the study of vaccine candidates and new drugs for the treatment of leishmaniasis. The conventional method that consists in the amastigotes count inside macrophages, normally is done by a trained microscope technician, which is liable to misinterpretation and sampling. The objective of this work is to develop a method for the segmentation of images to enable the automatic calculation of the infection rate by amastigotes. Segmentation is based on mathematical morphology in the context of a computer vision system. The results obtained by computer vision system presents a 95% accuracy in comparison to the conventional method. Therefore, the proposed method can contribute to the speed and accuracy of analysis of infection rate, minimizing errors from the traditional methods, especially in situations where exhaustive repetitions of the procedure are required from the technician.A determinação de parâmetros como taxa de infecção em monocultura de macrófagos cultivados in vitro com Leishmania é fundamental no estudo de candidatos vacinais e novos fármacos para o tratamento de leishmanioses. O método convencional que consiste na contagem de amastigotas no interior de macrófagos, normalmente é realizada por um especialista treinado em microscopia óptica, o que está sujeito a erros de interpretação e amostragem. O objetivo do trabalho é desenvolver um método para a segmentação de imagens como etapa preliminar para o cálculo automático da taxa de infecção por amastigotas. A segmentação é baseada em morfologia matemática no contexto de um sistema de visão computacional. Os resultados obtidos pelo método computacional demonstraram acerto de 95% quando comparados ao método convencional. Conclui-se que a metodologia computacional baseada na segmentação de imagem como pré-requisito para o cálculo de taxa de infecção, pode contribuir para a rapidez e a precisão na obtenção dos resultados e na minimização de erros cometidos no método tradicional, especialmente em situações em que exaustivas repetições do procedimento são exigidas ao observador

Strategies for allocating optimal control resources in stochastic scenario

Submitted by Liliane Ferreira ([email protected]) on 2019-06-18T14:32:00Z No. of bitstreams: 2 Tese - Arlindo Rodrigues Galvão Filho - 2019.pdf: 21607516 bytes, checksum: 286771ba862264442d6bc8cb0f7ed42b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Rejected by Luciana Ferreira ([email protected]), reason: Na citação fica: Tese (Doutorado em Ciência da Computação em Rede) - Universidade Federal de Goiás, Goiânia, 2xxx. on 2019-06-18T15:57:36Z (GMT)Submitted by Liliane Ferreira ([email protected]) on 2019-06-25T16:36:56Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Tese - Arlindo Rodrigues Galvão Filho - 2019.pdf: 21607516 bytes, checksum: 286771ba862264442d6bc8cb0f7ed42b (MD5)Approved for entry into archive by Luciana Ferreira ([email protected]) on 2019-06-27T12:47:06Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Tese - Arlindo Rodrigues Galvão Filho - 2019.pdf: 21607516 bytes, checksum: 286771ba862264442d6bc8cb0f7ed42b (MD5)Made available in DSpace on 2019-06-27T12:47:06Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Tese - Arlindo Rodrigues Galvão Filho - 2019.pdf: 21607516 bytes, checksum: 286771ba862264442d6bc8cb0f7ed42b (MD5) Previous issue date: 2019-06-10OutroApplication of computational models has contributed to understanding of different dynamics as well as possible more effective control strategies. Three widely used examples are deterministic formulations of compartmental models, individuals based models, and complex networks based models. An alternative to such models is a stochastic approach, which allows uncertainties insertion to models, providing more realistic results. In this context, this work proposes use of deterministic compartmental models to obtain optimum control policies, and later evaluation of such policy applied in a stochastic scenario using a equivalent individual based model. It also proposes three new control strategies based on dynamics and topology in complex network models. To models validation, a case study based on epidemiological dynamics was done, in which proposed strategies resulted in significant reductions in number of infected individuals, optimizing resource spending. Insertion of uncertainty in models was positive for average behavior analysis of dynamics. In addition, a parallel MBI model was proposed to be processed in graphic cards. With this improvement it was possible to obtain a reduction by a factor of twenty in processing time.A aplicação de modelos computacionais tem contribuído para o entendimento de diferentes dinâmicas, bem como possíveis estratégias de controle mais eficazes. Três exemplos amplamente utilizados são formulações determinísticas dos modelos compartimentais, modelos baseados em indivíduos e modelos baseados em redes complexas. Uma alternativa a tais modelos é uma abordagem estocástica, que possibilita a inserção de incertezas aos modelos proporcionando resultados mais realistas. Neste contexto, este trabalho propõe o uso de modelos compartimentais determinísticos para obtenção de políticas de controle ótimo, e posteriormente a avaliação de tal política aplicada em um cenário estocástico utilizando uma modelagem baseada em indivíduo equivalente. Também propõe três novas estratégias de controle baseado na dinâmica e topologia para modelos de redes complexas. Os modelos foram validados por meio de um estudo de caso baseado em dinâmicas epidemiológicas. As estratégias propostas resultaram em reduções significativas na quantidade de indivíduos infectados, otimizando o gasto de recursos. A inserção de incerteza nos modelos se mostrou positivo para a análise do comportamento médio das dinâmicas. Adicionalmente, foi proposto um modelo MBI paralelizado para ser processado em placas gráficas. Com este aprimoramento foi possível obter uma redução por um fator de vinte no tempo de processamento

Image-Based River Water Level Estimation for Redundancy Information Using Deep Neural Network

Monitoring and management of water levels has become an essential task in obtaining hydroelectric power. Activities such as water resources planning, supply basin management and flood forecasting are mediated and defined through its monitoring. Measurements, performed by sensors installed on the river facilities, are used for precisely information about water level estimations. Since weather conditions influence the results obtained by these sensors, it is necessary to have redundant approaches in order to maintain the high accuracy of the measured values. Staff gauge monitored by conventional cameras is a common redundancy method to keep track of the measurements. However, this method has low accuracy and is not reliable once it is monitored by human eyes. This work proposes to automate this process by using image processing methods of the staff gauge to measure and deep neural network to estimate the water level. To that end, three models of neural networks were compared: the residual networks (ResNet50), a MobileNetV2 and a proposed model of convolutional neural network (CNN). The results showed that ResNet50 and MobileNetV2 present inferior results compared to the proposed CNN

Artificial intelligence systems for the design of magic shotgun drugs

Designing magic shotgun compounds, i.e., compounds hitting multiple targets using artificial intelligence (AI) systems based on machine learning (ML) and deep learning (DL) approaches, has a huge potential to revolutionize drug discovery. Such intelligent systems enable computers to create new chemical structures and predict their multi-target properties at a low cost and in a time-efficient manner. Most examples of AI applied to drug discovery are single-target oriented and there is still a lack of concise information regarding the application of this technology for the discovery of multi-target drugs or drugs with broad-spectrum action. In this review, we focus on current developments in AI systems for the next generation of automated design of multi-target drugs. We discuss how classical ML methods, cutting-edge generative models, and multi-task deep neural networks can help de novo design and hit-to-lead optimization of multi-target drugs. Moreover, we present state-of-the-art workflows and highlight some studies demonstrating encouraging experimental results, which pave the way for de novo drug design and multi-target drug discovery

<i>Staphylococcus</i> spp. Causatives of Infections and Carrier of <i>blaZ</i>, <i>femA</i>, and <i>mecA</i> Genes Associated with Resistance

Staphylococcus spp. have been associated with cases of healthcare associated infections due to their high incidence in isolates from the hospital environment and their ability to cause infections in immunocompromised patients; synthesize biofilms on medical instruments, in the case of negative coagulase species; and change in genetic material, thus making it possible to disseminate genes that code for the acquisition of resistance mechanisms against the action of antibiotics. This study evaluated the presence of blaZ, femA, and mecA chromosomal and plasmid genes of Staphylococcus spp. using the qPCR technique. The results were associated with the phenotypic expression of resistance to oxacillin and penicillin G. We found that the chromosomal femA gene was present in a greater proportion in S. intermedius when compared with the other species analyzed, while the plasmid-borne mecA gene was prevalent in the S. aureus samples. The binary logistic regression performed to verify the association among the expression of the genes analyzed and the acquisition of resistance to oxacillin and penicillin G were not significant in any of the analyses, p > 0.05

Detection of Oxacillin/Cefoxitin Resistance in <i>Staphylococcus aureus</i> Present in Recurrent Tonsillitis

Background: Recurrent tonsillitis is one of the most common diseases in childhood, caused many times by ß-lactam-resistant S. aureus. The objective of this study was to investigate an alternative method to identify resistance to oxacillin/cefoxitin in S. aureus from hospitalized children with recurrent tonsillitis. Methods: The samples of S. aureus came from patients with recurrent tonsillitis and were used in 16S rRNA sequencing and an antibiogram test for identification and verifying resistance, after which HSI methodology were applied for separation of S. aureus resistances. Results: The S. aureus isolated showed sensitivity to oxacillin/cefoxitin and the diagnostic images show a visual description of the resistance different groups formed, that may be related to sensitivity and resistance to oxacillin/cefoxitin, characterizing the MRSA S. aureus. Conclusions: Samples that showed phenotypic resistance to oxacillin/cefoxitin were clearly separated from samples that did not show this resistance. A PLS-DA model predicted the presence of resistance to oxacillin/cefoxitin in S. aureus samples and it was possible to observe the pixels classified as MRSA. The HSI was able to successfully discriminate samples in replicas that were sensitive and resistant, based on the calibration model it received