An Integrated Model for User Attribute Discovery: A Case Study on Political Affiliation Identification

Discovering user demographic attributes from social media is a problem of considerable interest. The problem setting can be generalized to include three components - users, topics and behaviors. In recent studies on this problem, however, the behavior between users and topics are not effectively incorporated. In our work, we proposed an integrated unsupervised model which takes into consideration all the three components integral to the task. Furthermore, our model incorporates collaborative filtering with probabilistic matrix factorization to solve the data sparsity problem, a computational challenge common to all such tasks. We evaluated our method on a case study of user political affiliation identification, and compared against state-of-the-art baselines. Our model achieved an accuracy of 70.1% for user party detection task. ? 2014 Springer International Publishing.EI

Low-speed impact damage in hybrid 2D-braided composite plates

Glass-carbon hybrid braided composite plates with 50, 75 and 100% carbon are impacted with hemispherically-tipped impactors, using a gas gun at energies up to 50 J. The damage area, as measured by ultrasonic C-scanning and contact profilometry, increases roughly linearly with impact energy. At the same energy level, damage is more severe but more localised with increasing mass of the impactor. The peak contact force is roughly independent of material and impactor mass, for the same impact energy, but is significantly less than expected from the static stiffness of the plate. Only a small proportion of the impactor energy is retained on rebound, illustrating the need for a dynamic analysis