Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living

TL;DR: Smartphones are used in an unobtrusive way to capture body movements by collecting data using embedded accelerometer and gyroscope sensors and results indicate that neural networks outperform other classifiers by offering an accuracy ranging from 87% to 97% for user-dependent and 62% to 96% foruser-independent categories.

TL;DR: OSCAR4 offers a domain-independent architecture upon which chemistry specific text-mining tools can be built, and its development and usage are discussed.

TL;DR: This Review assesses the current literature and content of existing apps that target patients with CVD risk factors and that can facilitate behaviour change and evaluates how apps can be used throughout all age groups with different CVD prevention needs.

TL;DR: It is found that time series of WiFi scans contain a strong latent location signal, and it is possible to assign location to WiFi access points based on a very small number of GPS samples and then use these access points as location beacons.

TL;DR: In this paper, the authors describe a self-organizing system in which the signal representations are automatically mapped onto a set of output responses in such a way that the responses acquire the same topological order as that of the primary events.

TL;DR: An incremental network model is introduced which is able to learn the important topological relations in a given set of input vectors by means of a simple Hebb-like learning rule.

TL;DR: In this paper, an algorithm for solving the stereoscopic matching problem is proposed, which consists of five steps: (1) each image is filtered at different orientations with bar masks of four sizes that increase with eccentricity.