Abstract The reliable operation of monoblock centrifugal pumps (MCP) is crucial in various industrial applications. Achieving optimal performance and minimizing costly downtime requires effectively detecting and diagnosing faults in critical pump components. This study proposes an innovative approach that leverages deep transfer learning techniques. An accelerometer was adopted to capture vibration ...

Many data related problems involve handling multiple data streams of different types at the same time. These problems are both complex and challenging, and researchers often end up using only one modality or combining them via a late fusion based approach. To tackle this challenge, we develop and investigate the usefulness of a novel deep learning method called tower networks. This method is able ...

Like other fundamental abstractions for high-performance computing, search trees need to support both high concurrency and data locality. However, existing locality-aware search trees based on the van Emde Boas layout (vEB-based trees), poorly support concurrent (update) operations. We present DeltaTree, a practical locality-aware concurrent search tree that integrates both locality-optimization ...

Background: In this epidemiological study we described the characteristics of spatio-temporal gait parameters among a representative, population-based sample of 890 community-dwelling people aged 65 to 90 years. In addition, we investigated the associations between certain gait parameters and a history of falls in study participants. <p>Methods: In descriptive analyses spatio-temporal gait parameters ...

<p><i>Background</i>: Widespread access to the Internet and an increasing number of Internet users offers the opportunity of using Web-based recalls to collect detailed physical activity data in epidemiologic studies.</p> <p><i>Objective</i>: The aim of this investigation was to evaluate the validity and reliability of a computer-based 24-hour physical activity recall (cpar24) instrument with ...

Type 2 diabetes mellitus (T2D) and prediabetes prevalence rates are high. Consequences are serious, but current treatment is often not efficient for achieving remission. Remission may be achieved through lifestyle intervention. Frequent follow-up is necessary, and health care personnel (HCP) lack resources, time, and often adequate knowledge. Self-management of T2D can benefit from better use of ...

This study describes a method for extracting the stride parameter ground contact time (GCT) from inertial sensor signals in sprinting. Five elite athletes were equipped with inertial measurement units (IMU) on their ankles and performed 34 maximum 50 and 100-m sprints. The GCT of each step was estimated based on features of the recorded IMU signals. Additionally, a photo-electric measurement ...

Technology has brought us to the point where we are able to digitally sample life experience in rich multimedia detail, often referred to as lifelogging. In this paper we explore the potential of lifelogging for the digitisation and archiving of life experience into a longitudinal media archive for an individual. We motivate the historical archive potential for rich digital memories, enabling ...

Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image segmentation tasks. To improve the performance of U-Net on various segmentation tasks, we propose a novel architecture called DoubleU-Net, which is a combination of two U-Net ...

Distributed applications that span mobile devices, computing clusters, and cloud services, require robust and flexible mechanisms for dynamically loading code. This paper describes lady: a system that augments the .net platform with a highly reliable mechanism for resolving and loading assemblies, and arranges for safe execution of partially trusted code. Key benefits of lady are the low latency and ...