Deep learning using neural networks is becoming more and more popular. It is frequently used in areas like video analysis, image retrieval, traffic forecast and speech recognition. In this respect, the learning and training process usually requires a lot of data. However, in many areas, data is scarce which is definitely the case in our medical application scenario, i.e., polyp detection in the ...

In this paper, we propose two secure virtual private network architectures for the long‐term evolution backhaul network. They are layer 3 Internet protocol (IP) security virtual private network architectures based on Internet key exchange version 2 mobility and multihoming protocol and host identity protocol. Both architectures satisfy a complete set of 3GPP backhaul security requirements such as ...

We report on a prototype system helping actors on a stage to interact and perform with actors on other stages as if they were on the same stage. At each stage four 3D cameras tiled back to back for an almost 360 degree view, continuously record actors. The system processes the recorded data on-the-fly to discover actions by actors that it should react to, and it streams data about actors and their ...

<i>Background</i> - Wearable devices with an ability to collect various type of physiological data are increasingly becoming seamlessly integrated into everyday life of people. In the area of electronic health (eHealth), many of these devices provide remote transfer of health data, as a result of the increasing need for ambulatory monitoring of patients. This has a potential to reduce the cost ...

We have attempted to reproduce the results in <i>Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs</i>, published in JAMA 2016; 316(22), using publicly available data sets. We re-implemented the main method in the original study since the source code is not available. The original study used non-public fundus images from EyePACS ...

We applied deep learning to create an algorithm for breathing phase detection in lung sound recordings, and we compared the breathing phases detected by the algorithm and manually annotated by two experienced lung sound researchers. Our algorithm uses a convolutional neural network with spectrograms as the features, removing the need to specify features explicitly. We trained and evaluated the ...

The Unified Parallel C (UPC) programming language offers parallelism via logically partitioned shared memory, which typically spans physically disjoint memory subsystems. One convenient feature of UPC is its ability to automatically execute between-thread data movement, such that the entire content of a shared data array appears to be freely accessible by all the threads. The programmer friendliness, ...

<i>Background</i>: Accelerometers, often in conjunction with heart rate sensors, are extensively used to track physical activity (PA) in research. Research-grade instruments are often expensive and have limited battery capacity, limited storage, and high participant burden. Consumer-based activity trackers are equipped with similar technology and designed for long-term wear, and can therefore ...

Obesity and other health problems have a high prevalence in people with intellectual disabilities. Many lead a sedentary lifestyle and often have low scores on fitness indicators such as muscle strength and cardiovascular fitness. The purpose of this research is to identify design techniques and features of a mobile application that can help promote physical activity in people with intellectual ...

The potential for knowledge discovery is currently underutilized on pharmacoepidemiologic data sets. A big dataset enables finding and assessing rare drug consumption patterns that are associated with adverse drug reactions causing hospitalization, or death. To enable such exploration of big pharmacoepidemiology data, four key issues need so be addressed. First, to ingest, transform, preprocess ...