Today, medical image analysis papers require solid experiments to prove the usefulness of proposed methods. However, experiments are often performed on data selected by the researchers, which may come from different institutions, scanners, and populations. Different evaluation measures may be used, making it difficult to compare the methods. In this paper, we introduce a dataset of 7909 breast cancer histopathology images acquired on 82 patients, which is now publicly available from http://web.inf.ufpr.br/vri/breast-cancer-database. The dataset includes both benign and malignant images. The task associated with this dataset is the automated classification of these images in two classes, which would be a valuable computer-aided diagnosis tool for the clinician. In order to assess the difficulty of this task, we show some preliminary results obtained with state-of-the-art image classification systems. The accuracy ranges from 80% to 85%, showing room for improvement is left. By providing this dataset and a standardized evaluation protocol to the scientific community, we hope to gather researchers in both the medical and the machine learning field to advance toward this clinical application.

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Recent public cooperation between the Federal University of Technology – Parana (UTFPR) and the Toledo Municipality plans to implement the concept of smart cities in this city. In this context, one of the applications under development intends to track the recyclable garbage collector trucks in real time over the Internet. Actually, fleet vehicle tracking is one of the main applications for smart cities. LoRaWAN stands out among network technologies for smart cities due to operating in an open frequency range, covering long distances with low power consumption and low equipment cost. However, the coverage and performance of LoRaWAN is directly affected by both the environment and configuration parameters. In addition, tracking devices must be able to send its coordinates to the Internet even when the vehicle goes through zones where there are obstacles for electromagnetic waves such as elevated buildings or valleys. In this paper we perform experimental investigations to evaluate four LoRaWAN tracking devices, two available out of the box and two assembled and programmed. The behavior of each tracking device is analyzed when moving at a constant speed through three representative urban areas totaling 10.71 km2. The two most efficient tracking devices are analyzed in a stretch of 3.5 km with speeds ranging from 0 to 30 km/h, 0 to 50 km/h and 0 to 100 km/h. Results include a quantitative and qualitative aspects, including the received signal strength indication (RSSI), signal-to-noise ratio (SNR), packet delivery ratio (PDR), and spreading factor (SF) for the received geographic coordinates. As the devices depend on the quality of the signal offered by the network, we also present the results of the development and evaluation of the LoRaWAN network, by planning its coverage throughout the city.

In many countries, water quality monitoring is limited due to the high cost of logistics and professional equipment such as multiparametric probes. However, low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks, providing valuable water quality information to the public. To facilitate the widespread adoption of these sensors, it is crucial to identify which sensors can accurately measure key water quality parameters, their manufacturers, and their reliability in different environments. Although there is an increasing body of work utilizing low-cost water quality sensors, many questions remain unanswered. To address this issue, a systematic literature review was conducted to determine which low-cost sensors are being used for remote water quality monitoring. The results show that there are three primary vendors for the sensors used in the selected papers. Most sensors range in price from US$6.9 to US$169.00 but can cost up to US$500.00. While many papers suggest that low-cost sensors are suitable for water quality monitoring, few compare low-cost sensors to reference devices. Therefore, further research is necessary to determine the reliability and accuracy of low-cost sensors compared to professional devices.

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Redes LPWAN (Low-Power Wide-Area Network) são um tipo de rede sem-fio projetada para cobrir uma extensa área a uma baixa taxa de transferência de bits. Entre as tecnologias LPWAN, o padrão aberto LoRaWAN destaca-se por operar em uma faixa de frequência aberta, atingir um longo alcance, pouco consumo de energia e baixo custo dos equipamentos. Este artigo descreve a implantação e avaliação de uma rede LoRaWAN para apoiar a construção do conceito de cidades inteligentes no município de Toledo/PR. A avaliação considera a qualidade do sinal em diversos pontos do município e confronta os dados obtidos com um modelo de simulação. Também são apresentados o plano para expansão da rede e algumas aplicações em desenvolvimento.