Much of the content of popular Internet information sources is highly dynamic: urgent in nature and sometimes relevant only for a short time. The typical approach to querying such dynamic sources is polling for updates often.1 This strains the traditional pull-based Internet and wastes network resources on transmitting redundant information. This paper focuses on how to structure the Internet to ...

This Master’s thesis investigates the application of Machine Learning (ML) in predicting blast-induced ground vibrations in mining, with the aim of sur- passing the precision of the current industry-standard model that utilizes an empirical, regression-based method. The study applied a Deep Neural Network (DNN) model, selected for its capability to consider a broader range of variables than the ...

Accurate detection of accelerometer non-wear time is crucial for calculating physical activity summary statistics. In this study, we evaluated three epoch-based non-wear algorithms (Hecht, Troiano, and Choi) and one raw-based algorithm (Hees). In addition, we performed a sensitivity analysis to provide insight into the relationship between the algorithms’ hyperparameters and classification performance, ...

Background: An increasing quantity of research in the domain of telemedicine show a growing popularity and acceptance of care over distance systems among both clinicians and patients. We focus on telementoring solutions, developed for providing remote guidance to less experienced surgeons. Telestration is often regarded as an extra functionality of some telementoring systems. However, we advocate ...

In this study we compare the performance and power efficiency of Unified Parallel C (UPC), MPI and OpenMP by running a set of kernels from the NAS Benchmark. One of the goals of this study is to focus on the Partitioned Global Address Space (PGAS) model, in order to describe it and compare it to MPI and OpenMP. In particular we consider the power effi- ciency expressed in millions operations ...

Patient self-management is vital to improved health outcomes for patients with chronic diseases. The objective of this study was to understand the role of wearable sensors in patients’ self-management. A survey encompassing factors related to motivation in mHealth was conducted. Ease of use and sensory accuracy was found most important when choosing a wearable. Manual registration of most health-related ...

Graphics processors (GPUs) are emerging as a promising platform for highly parallel, compute-intensive, general-purpose computations, which usually need support for inter-process synchronization. Using the traditional lock-based synchronization (e.g. mutual exclusion) makes the computation vulnerable to faults caused by both scientists’ inexperience and hardware transient errors. It is notoriously ...

Professional sports achievements combine not only the individual physical abilities of athletes but also many modern technologies in areas such as medicine, equipment production, nutrition, and physical and mental health monitoring. In this work, we address the problem of predicting soccer players’ ability to perform, from subjective self-reported wellness parameters collected using a commercially ...

IoT is a field of technology of ever growing importance in our daily lives. From smart cities, health devices, climate observations, appliances, and so much more, IoT surrounds us now more than ever. The types of devices being added to IoT networks is ever growing, and as this variety of hardware and software increases, so does the difficulty of working with them. Ensuring inter-compatibility between ...