Holographic optical elements: State-of-the-art review: Part 2

This is the second part of a two part review on the state-of-the-art in holographic optical elements (HOEs). The aspects of fabrication, evaluation, and applications of HOEs, are discussed in this part. It details the direction of future efforts towards finding work-horse type recording media, developing new methods for the evaluation of HOE, and identifying the areas of application where HOEs are to be considered as indispensable components/tools. Finally a summary of all the suggestions for future work made in the two parts is displayed in Table 2 of this part of the review.

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.