Dynamic multi-relational Chinese restaurant process for analyzing influences on users in social media

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

A critical examination of the paradox of strength and ductility in ultrafine-grained metals

The paradox of strength and ductility is now well established and denotes the difficulty of simultaneously achieving both high strength and high ductility. This paradox was critically examined using a cast Al-7% Si alloy processed by high-pressure torsion (HPT) for up to 10 turns at a temperature of either 298 or 445 K. This processing reduces the grain size to a minimum of similar to 0.4 mu m and also decreases the average size of the Si particles. The results show that samples processed to high numbers of HPT turns exhibit both high strength and high ductility when tested at relatively low strain rates and the strain rate sensitivity under these conditions is similar to 0.14 which suggests that flow occurs by some limited grain boundary sliding and crystallographic slip. The results are also displayed on the traditional diagram for strength and ductility and they demonstrate the potential for achieving high strength and high ductility by increasing the number of turns in HPT.

DTM AT 25: ESSAYS ON THEMES AND FUTURE DIRECTIONS

This paper describes the development and evolution of research themes in the Design Theory and Methodology (DTM) conference. Essays containing reflections on the history of DTM, supported by an analysis of session titles and papers winning the ``best paper award'', describe the development of the research themes. A second set of essays describes the evolution of several key research themes. Two broad trends in research themes are evident, with a third one emerging. The topics of the papers in the first decade or so reflect an underlying aim to apply artificial intelligence toward developing systems that could `design'. To do so required understanding how human designers behave, formalizing design processes so that they could be computed, and formalizing representations of design knowledge. The themes in the first DTM conference and the recollections of the DTM founders reflect this underlying aim. The second decade of DTM saw the emergence of product development as an underlying concern and included a growth in a systems view of design. More recently, there appears to be a trend toward design-led innovation, which entails both executing the design process more efficiently and understanding the characteristics of market-leading designs so as to produce engineered products and systems of exceptional levels of quality and customer satisfaction.