Living near Prairie Potholes : What could go wrong?

Canada First Research Excellence FundNon-Peer ReviewedExposure to the societal impacts of hydrology on the Canadian Prairies influences a young scientific modeler's work direction

Leveraging Equivariant Features for Absolute Pose Regression

While end-to-end approaches have achieved state-of-the-art performance in many perception tasks, they are not yet able to compete with 3D geometry-based methods in pose estimation. Moreover, absolute pose regression has been shown to be more related to image retrieval. As a result, we hypothesize that the statistical features learned by classical Convolutional Neural Networks do not carry enough geometric information to reliably solve this inherently geometric task. In this paper, we demonstrate how a translation and rotation equivariant Convolutional Neural Network directly induces representations of camera motions into the feature space. We then show that this geometric property allows for implicitly augmenting the training data under a whole group of image plane-preserving transformations. Therefore, we argue that directly learning equivariant features is preferable than learning data-intensive intermediate representations. Comprehensive experimental validation demonstrates that our lightweight model outperforms existing ones on standard datasets.Comment: 11 pages, 8 figures, CVPR202

Temporal 3D Human Pose Estimation for Action Recognition from Arbitrary Viewpoints

This work presents a new view-invariant action recognition system that is able to classify human actions by using a single RGB camera, including challenging camera viewpoints. Understanding actions from different viewpoints remains an extremely challenging problem, due to depth ambiguities, occlusion, and a large variety of appearances and scenes. Moreover, using only the information from the 2D perspective gives different interpretations for the same action seen from different viewpoints. Our system operates in two subsequent stages. The first stage estimates the 2D human pose using a convolution neural network. In the next stage, the 2D human poses are lifted to 3D human poses, using a temporal convolution neural network that enforces the temporal coherence over the estimated 3D poses. The estimated 3D poses from different viewpoints are then aligned to the same camera reference frame. Finally, we propose to use a temporal convolution network-based classifier for cross-view action recognition. Our results show that we can achieve state of art view-invariant action recognition accuracy even for the challenging viewpoints by only using RGB videos, without pre-training on synthetic or motion capture data

Leveraging Equivariant Features for Absolute Pose Regression

Pose estimation enables vision-based systems to refer to their environment, supporting activities ranging from scene navigation to object manipulation. However, end-to-end approaches, that have achieved state-of-the-art performance in many perception tasks, are still unable to compete with 3D geometry-based methods in pose estimation. Indeed, absolute pose regression has been proven to be more related to image retrieval than to 3D structure. Our assumption is that statistical features learned by classical convolutional neural networks do not carry enough geometrical information for reliably solving this task. This paper studies the use of deep equivariant features for end-to-end pose regression. We further propose a translation and rotation equivariant Convolutional Neural Network whose architecture directly induces representations of camera motions into the feature space. In the context of absolute pose regression, this geometric property allows for implicitly augmenting the training data under a whole group of image plane-preserving transformations. Therefore, directly learning equivariant features efficiently compensates for learning intermediate representations that are indirectly equivariant yet data-intensive. Extensive experimental validation demonstrates that our lightweight model outperforms existing ones on standard datasets

A Transportable Solar Power Generator

This paper presents the design of a 2kW portable photovoltaic (PV) stand-alone facility (PV generator) that converts directly solar irradiance into electricity for immediate use or storage. The project aims to build a stand-alone solar power source for use in rural villages, mountainous and remote areas that are distant from the national grid. It can also be very useful for powering camping tents, fishing boats, small farms, and greenhouses. Equally, it could be used for disaster stricken areas and during power outages. However, the proposed generator will be more suited for camping trips that Emiratis take almost in weekly basis. The paper will focus on presenting the main features of the designed prototype. It will also investigate the performance of the proposed stand-alone PV generator. Parameters investigated include geographic location, climate condition, solar irradiance, load consumption, ambient temperature, array voltage, battery voltage, and energy output from the array. The work presented is based entirely on the work carried out by final year electrical engineering students, during their capstone design project. The project work, presented, is a manifestation of the students learning during earlier semesters. It puts into practice the application of solar energy technology, that the student learned in his course on renewable energy systems

Evaluation of the impact of COVID-19 pandemic on hospital-acquired infections in a tertiary hospital in Malaysia

Background: Infection prevention measures are the gold standard for preventing the spread of hospital-acquired infections (HAIs). COVID-19 pandemic caused major disruptions in infection prevention measures, and this has implications on the rate of HAIs. This study assessed the impact of COVID-19 pandemic on the rate and the types of HAIs at Sultan Ahmed Shah Hospital. Method: This is a retrospective cohort study that compared the rate of HAIs from April to October 2019 (pre COVID period) and April to October 2020 (during COVID period). Data was collected through the review of patients’ electronic medical records. Results: There were a total of 578 patients included in the selected wards during the pre- and during the pandemic. Thirty-nine episodes (12.1%) of HAIs were report in the pre COVID period and 29 (11.3%) during COVID-19. In both periods, hospital-acquired pneumonia (HAP) was the most frequent HAI among the patients. There was a rise in catheter-associated bloodstream infections (CLABSI) (0.8%) and ventilator associated pneumonia (VAP) (1.1%) during the COVID-19 period. The most common bacteria were methicillin-resistant Staphylococcus aureus (MRSA) (28.2%) and Enterococcus faecalis (17.9%) in the Pre COVID-19 period, and Pseudomonas aeruginosa (27.6%) and Stenotrophomonas maltophilia (6.9%) during COVID-19. Conclusion: Our research concluded that the rates of HAIs during the COVID-19 pandemic were not significantly impacted by the improved in-hospital infection prevention efforts to control the pandemic. There is need for further efforts to promote adherence to preventive practices

Updated upper limit of normal for serum alanine aminotransferase value in Vietnamese population

Background: Alanine aminotransferase (ALT) is a marker of hepatic damage and its range can be affected by viral hepatitis, alcoholic hepatitis and non-alcoholic fatty liver diseases. We aimed to study the factors associated with higher ALT level and update the upper limit of normal (ULN) in the Vietnamese population.Methods: This cross-sectional study enrolled 8383 adults, aged 18 years and older who visited the Medical Center at Ho Chi Minh City for a health check-up. Following the exclusion criteria, 6677 subjects were included in the analysis.Results: Age ≤40 years, male gender, body mass index >23 kg/m2, diastolic blood pressure >85 mm Hg, cholesterol >5.2 mmol/L, triglyceride >1.7 mmol/L, positivity, anti-hepatitis C virus positivity and fatty liver (p40 U/L). Without considering age and gender, healthy group is defined after exclusion of participants with one of the mentioned contributing factors. The median ALT level in the healthy group was 18 in men and 13 in women. The ULN at the 95th percentile of the healthy group was 40 U/L in men and 28 U/L in women.Conclusion: The ULN for ALT in healthy women was lower than in healthy men. Updated ULN for ALT level can promote the identification of unhealthy subjects. More studies that involve ethnicity and lifestyle factors are needed to confirm the new ULN in the Vietnamese population