Multimedia big data computing for in-depth event analysis

While the most part of ”big data” systems target text-based analytics, multimedia data, which makes up about 2/3 of internet traffic, provide unprecedented opportunities for understanding and responding to real world situations and challenges. Multimedia Big Data Computing is the new topic that focus on all aspects of distributed computing systems that enable massive scale image and video analytics. During the course of this paper we describe BPEM (Big Picture Event Monitor), a Multimedia Big Data Computing framework that operates over streams of digital photos generated by online communities, and enables monitoring the relationship between real world events and social media user reaction in real-time. As a case example, the paper examines publicly available social media data that relate to the Mobile World Congress 2014 that has been harvested and analyzed using the described system.Peer ReviewedPostprint (author's final draft

Rediscovering Renaissance Recipes: Digital Presentation for a 16th Century Text

This project seeks to create a web-based system for working with a French text from 1509, Platine en francoys, which has been transcribed into an XML (Extensible Markup Language)-based file format using the conventions of TEI. Through incorporation of several web technologies such as NodeJS, the application provides a section by section navigation capability that allows versions of the text to be seen in multiple configurations. The options include a side-by-side presentation mode that allows for easy compare/contrast of the original versus a regularized spelling or other variants. A facsimile-focused view is also planned, along with tools leveraging the specialized markup and focused searches on non-recipe text, recipes, and ingredients. It is expected that these features will allow for a deeper understanding of the text as well as function as a foundation for future development work as part of the ongoing cross-disciplinary computing/language collaboration efforts

A Cultural Heritage Forum Celebrating Technological Innovation at Station X

We aim to encourage and support public participation in heritage through the development of Cultural Heritage Forums, a kind of cultural web portal that enables active participation of communities of interest in a way that complements rather than replaces visits to physical cultural institutions. The cultural heritage forum described here (Station X) is concerned with promoting an understanding of technology innovation in the areas of computing and cryptography. We propose a number of scenarios concerning how the forum can be designed, drawing on our earlier work in using knowledge modelling and text analysis to support the exploration of digital resources

What Makes a Good Descriptor for Heterogeneous Ice Nucleation on OH-Patterned Surfaces

Freezing of water is arguably one of the most common phase transitions on Earth and almost always happens heterogeneously. Despite its importance, we lack a fundamental understanding of what makes substrates efficient ice nucleators. Here we address this by computing the ice nucleation (IN) ability of numerous model hydroxylated substrates with diverse surface hydroxyl (OH) group arrangements. Overall, for the substrates considered, we find that neither the symmetry of the OH patterns nor the similarity between a substrate and ice correlate well with the IN ability. Instead, we find that the OH density and the substrate-water interaction strength are useful descriptors of a material's IN ability. This insight allows the rationalization of ice nucleation ability across a wide range of materials, and can aid the search and design of novel potent ice nucleators in the future.Comment: main text + S

Noise and Correlations in a Spatial Population Model with Cyclic Competition

Noise and spatial degrees of freedom characterize most ecosystems. Some aspects of their influence on the coevolution of populations with cyclic interspecies competition have been demonstrated in recent experiments [e.g. B. Kerr et al., Nature {\bf 418}, 171 (2002)]. To reach a better theoretical understanding of these phenomena, we consider a paradigmatic spatial model where three species exhibit cyclic dominance. Using an individual-based description, as well as stochastic partial differential and deterministic reaction-diffusion equations, we account for stochastic fluctuations and spatial diffusion at different levels, and show how fascinating patterns of entangled spirals emerge. We rationalize our analysis by computing the spatio-temporal correlation functions and provide analytical expressions for the front velocity and the wavelength of the propagating spiral waves.Comment: 4 pages of main text, 3 color figures + 2 pages of supplementary material (EPAPS Document). Final version for Physical Review Letter

Facilitating Image and Document Retrieval Using Image Content and Querying Keyword

Evolution of ubiquitous computing in the areas of personal computing technology has produced staggeringly large data It is difficult to search mainly the image data by understanding   users objective only by keywords and phrases and this leads to uncertain outcomes. For producing these outcomes effectively, this paper introduces a new approach to the problem of image learning to enable search engines to learn about visual content over time based on user feedback through one click activity and images from a pool recovered by text based query are re-ranked depending on both visual and text based query. Content Based Image Retrieval (CBIR) techniques are used for accessing semantically-relevant images from an image data source depending on automatically-derived image functions for features like Geometric moments, Global histogram, Color Moments, Local histogram. Documents can also be retrieved using the text based query by the user