Search results for: Pernille K. Christiansen

Authors: Pernille K. Christiansen, Mette Maria Skjøth, Line Lorenzen, Eva Draborg, Christina Anne Vinter, Trine Kjær, Mette Juel Rothmann

Abstract:

Background and aims: Overweight and obesity are an increasing challenge on a global level. In Denmark, more than one-third of all pregnant women are overweight or obese, and many women exceed the gestational weight gain recommendations from the Institute of Medicine. Being overweight or obese, is associated with a higher risk of adverse maternal and fetal outcomes, including gestational diabetes and childhood obesity. Thus, it is important to focus on the women’s lifestyles between their pregnancies to lower the risk of gestational weight retention in the long run. The objective of this study was to explorer what barriers and challenges postpartum women experience with respect to healthy lifestyles during the postpartum period and to access whether an Information Technology based intervention might be a supportive tool to assist and motivate postpartum women to a healthy lifestyle. Materials and methods: The method is inspired by participatory design. A systematic text condensation was applied to semi-structured focus groups. Five focus group interviews were carried out with a total of 17 postpartum women and two interviews with a total of six health professionals. Participants were recruited through the municipality in Svendborg, Denmark, and at Odense University Hospital in Odense, Denmark, during a four-month period in early 2018. Results: From the women’s perspective, better assistance is needed from the health professionals to obtain or maintain a healthy lifestyle. The women need tools that inform and help them understand and prioritise their own health-related risks, and to motivate them to plan and take care of their own health. As the women use Information Technology on a daily basis, the solution could be delivered through Information Technology. Finally, there is room for engaging the partner more in the communication related to the baby and family’s lifestyle. Conclusion: Postpartum women need tools that inform and motivate a healthy lifestyle postpartum. The tools should allow access to high-quality information from health care professionals, when the information is needed, and also allow engagement from the partner. Finally, Information Technology is a potential tool for delivering tools.

Keywords: information technology, lifestyle, overweight, postpartum

Procedia PDF Downloads 109

Authors: Ranjeet Sable, Mahotsavi Patil, Aadesh Nimbalkar, Prajakta Palaskar, Ritu Sagar

Abstract:

The exact amount of water used by various crops in different climatic conditions is necessary to step for design, planning, and management of irrigation schemes, water resources, scheduling of irrigation systems. Evaporation and transpiration are combinable called as evapotranspiration. Water loss from trees during photosynthesis is called as transpiration and when water gets converted into gaseous state is called evaporation. For calculation of correct evapotranspiration, we have to choose the method in such way that is should be suitable and require minimum climatic data also it should be applicable for wide range of climatic conditions. In hydrology, there are multiple correlations and regression is generally used to develop relationships between three or more hydrological variables by knowing the dependence between them. This research work includes the study of various methods for calculation of evapotranspiration and selects reasonable and suitable one Pune region (Maharashtra state). As field methods are very costly, time-consuming and not give appropriate results if the suitable climate is not maintained. Observation recorded at Pune metrological stations are used to calculate evapotranspiration with the help of Radiation Method (RAD), Modified Penman Method (MPM), Thornthwaite Method (THW), Blaney-Criddle (BCL), Christiansen Equation (CNM), Hargreaves Method (HGM), from which Hargreaves and Thornthwaite are temperature based methods. Performance of all these methods are compared with Modified Penman method and method which showing less variation with standard Modified Penman method (MPM) is selected as the suitable one. Evapotranspiration values are estimated on a monthly basis. Comparative analysis in this research used for selection for raw data-dependent methods in case of missing data.

Keywords: Blaney-Criddle, Christiansen equation evapotranspiration, Hargreaves method, precipitations, Penman method, water use efficiency

Procedia PDF Downloads 239

Authors: Nicole Christiansen, Hanne Marie Motzfeldt

Abstract:

In recent years, more and more HR professionals have been using cyber-vetting in job recruitment in an effort to find the perfect match for the company. These practices are growing rapidly, accessing a vast amount of data from social networks, some of which is privileged and protected information. Thus, there is a risk that the right to privacy is becoming a duty to manage your private data. This paper investigates to which degree a job applicant's fundamental rights are protected adequately in current and future legislation in the EU. This paper argues that current data protection regulations and forthcoming regulations on the use of AI ensure sufficient protection. However, even though the regulation on paper protects employees within the EU, the recruitment sector may not pay sufficient attention to the regulation as it not specifically targeting this area. Therefore, the lack of specific labor and employment regulation is a concern that the social partners should attend to.

Keywords: AI, cyber vetting, data protection, job recruitment, online privacy

Procedia PDF Downloads 41

Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

Abstract:

Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

Procedia PDF Downloads 359