Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach

Recent years have witnessed the rapid development of human activity recognition (HAR) based on wearable sensor data. One can find many practical applications in this area, especially in the field of health care. Many machine learning algorithms such as Decision Trees, Support Vector Machine, Naive Bayes, K-Nearest Neighbor, and Multilayer Perceptron are successfully used in HAR. Although these methods are fast and easy for implementation, they still have some limitations due to poor performance in a number of situations. In this paper, we propose a novel method based on the ensemble learning to boost the performance of these machine learning methods for HAR

InAs-AlSb quantum wells in tilted magnetic fields

InAs-AlSb quantum wells are investigated by transport experiments in magnetic fields tilted with respect to the sample normal. Using the coincidence method we find for magnetic fields up to 28 T that the spin splitting can be as large as 5 times the Landau splitting. We find a value of the g-factor of about 13. For small even-integer filling factors the corresponding minima in the Shubnikov-de Haas oscillations cannot be tuned into maxima for arbitrary tilt angles. This indicates the anti-crossing of neighboring Landau and spin levels. Furthermore we find for particular tilt angles a crossover from even-integer dominated Shubnikov-de Haas minima to odd-integer minima as a function of magnetic field

Models of Social Groups in Blogosphere Based on Information about Comment Addressees and Sentiments

This work concerns the analysis of number, sizes and other characteristics of groups identified in the blogosphere using a set of models identifying social relations. These models differ regarding identification of social relations, influenced by methods of classifying the addressee of the comments (they are either the post author or the author of a comment on which this comment is directly addressing) and by a sentiment calculated for comments considering the statistics of words present and connotation. The state of a selected blog portal was analyzed in sequential, partly overlapping time intervals. Groups in each interval were identified using a version of the CPM algorithm, on the basis of them, stable groups, existing for at least a minimal assumed duration of time, were identified.Comment: Gliwa B., Ko\'zlak J., Zygmunt A., Models of Social Groups in Blogosphere Based on Information about Comment Addressees and Sentiments, in the K. Aberer et al. (Eds.): SocInfo 2012, LNCS 7710, pp. 475-488, Best Paper Awar

A new broken U(1)-symmetry in extreme type-II superconductors

A phase transition within the molten phase of the Abrikosov vortex system without disorder in extreme type-II superconductors is found via large-scale Monte-Carlo simulations. It involves breaking a U(1)-symmetry, and has a zero-field counterpart, unlike vortex lattice melting. Its hallmark is the loss of number-conservation of connected vortex paths threading the entire system {\it in any direction}, driving the vortex line tension to zero. This tension plays the role of a generalized ``stiffness'' of the vortex liquid, and serves as a probe of the loss of order at the transition, where a weak specific heat anomaly is found.Comment: 5 pages, 3 figure