Simulation and evaluation of deep learning autoencoders for image compression in multi-UAV network systems

Mobile multi-robot systems are versatile alternatives for improving single-robot capacities in many applications, such as logistics, environmental monitoring, search and rescue, photogrammetry, etc. In this sense, this kind of system must have a reliable communication network between the vehicles, ensuring that information exchanged within the nodes has little losses. This work simulates and evaluates the use of autoencoders for image compression in a multi-UAV simulation with ROS and Gazebo for a generic surveillance application. The autoencoder model was developed with the Keras library, presenting good training and validation results, with training and validation accuracy of 70%, and a Peak Signal Noise Ratio (PSNR) of 40dB. The use of the CPU for the simulated UAVs for processing and sending compressed images through the network is 25% faster. The results showed that this compression methodology is a good choice for improving the system’s performance without losing too much information.The authors thank CEFET/RJ, UFF, UFRJ, and the Brazilian research agencies CAPES, CNPq, and FAPERJ. Besides, the authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021).info:eu-repo/semantics/publishedVersio

DIAGNÓSTICO AUTOMÁTICO DE FALHAS EM MANCAIS DE MÁQUINAS ROTATIVAS

Este artigo apresenta um método para diagnosticar falhas em máquinas rotativas através da análise de sinais de vibração a fim de propor uma nova metodologia de manutenção para as impressoras do tipo offset da Divisão Gráfica da Universidade Federal do Rio de Janeiro (UFRJ). Para tanto, o trabalho faz a classificação de três tipos de classes diferentes: sinais com defeito no mancal afastado do motor, sinais com defeito no mancal próximo ao motor e sinais normais. Além disso, também é feita a classificação dos tipos de defeitos que ocorrem nos mancais próximo e afastado do motor: defeito na gaiola, na pista externa e na esfera. O algoritmo usado para fazer a classificação foi o Random Forest, que atingiu uma acurácia de 98,15%

School attendance management system for students through facial recognition

Currently, in the scenario of the city of Manaus, most of the records of attendance of students in educational institutions are made manually, thus making the process quite laborious and repetitive for teachers, added to this, this system does not present to be fully reliable, because the method used shows itself vulnerable to human error. To save time and ensure that the registration is done without any failure, this work develops and applies a system to register students using facial recognition, and also has a feature that triggers an email message warning the absence of the child to the parents responsible if the student is not present in class. The project uses the Ruby language, for the development of the attendance register management system, and the Python language in conjunction with the OpenCV library for facial recognition

SÍNDROME DOS OVÁRIOS POLICÍSTICOS (SOP): UMA ABORDAGEM ABRANGENTE

Polycystic Ovary Syndrome (PCOS) is a complex endocrine condition that affects women of reproductive age. It is characterized by hormonal imbalances, manifested by chronic anovulation, hyperandrogenism, and the presence of cysts on the ovaries. Diagnosis is established through clinical, laboratory, and ultrasound criteria. PCOS is associated with insulin resistance and often coexists with obesity. This condition can lead to metabolic complications such as type 2 diabetes and cardiovascular diseases. In addition to physical impacts, PCOS can have psychological repercussions, including issues related to self-image and social stigma. The treatment of PCOS encompasses pharmacological approaches, lifestyle modifications, and, in specific cases, surgical procedures. The importance of a multidisciplinary team, involving gynecologists, endocrinologists, nutritionists, and psychologists, stands out in the comprehensive management of the syndrome. Therapeutic strategies aim not only at hormonal regulation and restoration of fertility but also at improving the overall quality of life for the patient.A Síndrome dos Ovários Policísticos (SOP) é uma condição endócrina complexa que afeta mulheres em idade reprodutiva. Caracteriza-se por desequilíbrios hormonais, manifestados por anovulação crônica, hiperandrogenismo e a presença de cistos nos ovários. O diagnóstico é estabelecido por critérios clínicos, laboratoriais e ultrassonográficos. A SOP está associada à resistência à insulina e frequentemente coexiste com a obesidade. Essa condição pode resultar em complicações metabólicas, como diabetes tipo 2 e doenças cardiovasculares. Além dos impactos físicos, a SOP pode ter repercussões psicológicas, incluindo questões relacionadas à autoimagem e estigma social. O tratamento da SOP abrange abordagens farmacológicas, estilo de vida e, em casos específicos, procedimentos cirúrgicos. A importância de uma equipe multidisciplinar, envolvendo ginecologistas, endocrinologistas, nutricionistas e psicólogos, destaca-se na gestão integral da síndrome. Estratégias terapêuticas visam não apenas à regularização hormonal e restauração da fertilidade, mas também à melhoria da qualidade de vida global da paciente

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): study protocol for a randomized controlled trial

BACKGROUND: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). METHODS/DESIGN: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH2O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure 6430 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. DISCUSSION: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration metho

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

MANUTENÇÃO PREDITIVA BASEADA EM ANÁLISE DE VIBRAÇÕES

A manutenção preditiva, foco principal deste trabalho, tem a finalidade de evitar paradas repentinasna produção, que causam enormes transtornos e prejuízos. O trabalho em questão tem a finalidadede descobrir, a partir de sinais de vibração extraídos de mancais de rolamento, o tipo de defeito queestá acontecendo em um equipamento. Diversas máquinas do parque gráfico da Divisão Gráfica daUFRJ possuem mancais de rolamento, tais como: impressoras (Catu 660 bicolor, Catu 660monocolor, Catu 510, Multilith) e a guilhotina Guarani. Foi realizada uma série de experimentoscom a base de dados de defeitos em mancais. Foi utilizado o algoritmo Random Forest juntamentecom um método de validação cruzada (K-fold) para fazer a separação entre os conjuntos detreinamento e teste. Foram geradas 120 combinações para serem processadas pelo algoritmo. Estesexperimentos foram processados em um cluster com clock de 3,5GHz e com memória RAM de32GB. Foi verificado que é vantajoso o investimento econômico na implantação desse algoritmonum sistema industrial de manutenção preditiva, uma vez que os percentuais de acerto nas classesforam na faixa de 90%. Esse sistema diminuiria sensivelmente as paradas de máquinas nãoprogramadas, gerando assim maior produtividade e eficiência para Divisão Gráfica da UFRJ.Palavras-chave: Manutenção Preditiva – Diagnóstico de Falhas – Prognóstico de Falhas –Random Forest – K-Fol