Summer Research Institute

In collaboration with the Stanford University Library, Harvard University (represented by the University Library, HarvardX, and the Committee for the Digital Humanities) have for the last two years been working to develop a new IIIF-compliant image viewer designed, above all else, to faciliate the study of medieval manuscripts. The viewer, however, can be used for any object that can be reproduced in the form of digital photography, and work is underway to expand the viewer’s capacity to encompass other forms of digital representation, such as time-based media (music, video). In addition to a sophisticated viewer incorporating many features required by scholars (and students), Mirador also incorporates advanced annotation capabilities which will, in due course, be undergirded by a database that links back, not only to specific images, but to specific locations on images.  Annotation user groups can be adjusted, as can the tagging system employed.

In addition to introducing and demonstrating Mirador in its latest incarnation, the presentation will sketch six case studies that are currently in the process of being formulated and that will be proposed to the Mellon Foundation as part of a grant application designed to text and expand Mirador’s functionality in relation to current scholarly and pedagogic requirements. The case studies are i) an edition of a Middle English text, which requires the collation of over 50 manuscripts, ii) an analysis of English legal statutes, which requires complex tagging, iii) the analysis of Latin inscriptions in illuminated manuscripts, whose visual aspects cannot adequately be represented by a conventional edition, iv) aninteroperable database of Byzantine coins, drawing on three of the world’s major collections, v) a liturgical database of French and Flemish Books of Hours, vi) the annotation of ethnographic recordings and films, and vii) the incorporation of Mirador into a series of commissioned works of installation art pieces for which the program will provide both documentation and a means of audience interaction.

The presentation will conclude with discussion of the potential of the program to aid in research on illuminated manuscripts, the speaker’s special area of interest, with a focus on a little-known group of liturgical manuscripts from the Dominican convent, Paradies bei Soest, dating to the period 1300–1425.

With the spread of physical sensors and social sensors, we are living in a world of big sensor data. Though they generate heterogeneous data, they often provide complementary information. Combining these two types of sensors together enables sensor-enhanced social media analysis which can lead to a better understanding of dynamically occurring situations.
We present two works that illustrate this general theme.

In the first work, we utilize event related information detected from physical sensors to filter and then mine the geo-located social media data, to obtain high-level semantic information. Specifically, we apply a suite of visual concept detectors on video cameras to generate "camera tweets" and develop a novel multi-layer tweeting cameras framework.
We fuse "camera tweets" and social media tweets via a "Concept Image"
(Cmage). Cmages
are 2-D maps of concept signals, which serve as common data representation to facilitate event detection. We define a set of operators and analytic functions that can be applied on Cmages by the user not only to discover occurrences of events but also to analyze patterns of evolving situations. The feasibility and effectiveness of our framework is demonstrated with a large-scale dataset containing feeds from 150 CCTV cameras in New York City and Twitter data. We also describe our preliminary "Tweeting Camera" prototype in which a smart camera can tweet semantic information through Twitter such that people can follow and get updated about events around the camera location.

Our second work combines photography knowledge learned from social media with the camera sensors data to provide real-time photography assistance. Professional photographers use their knowledge and exploit the current context to take high quality photographs. However, it is often challenging for an amateur user to do that. Social media and physical sensors provide us an opportunity to improve the photo-taking experience for such users. We have developed a photography model based on machine learning which is augmented with contextual information such as time, geo-location, environmental conditions and type of image, that influence the quality of photo capture. The sensors available in a camera system are utilized to infer the current scene context. As scene composition and camera parameters play a vital role in the aesthetics of a captured image, our method addresses the problem of learning photographic composition and camera parameters. We also propose the idea of computing the photographic composition bases, eigenrules and baserules, to illustrate the proposed composition learning. Thus, the proposed system can be used to provide real-time feedback to the user regarding scene composition and camera parameters while the scene is being captured.

BIOGRAPHY:

Mohan Kankanhalli is a Professor at the Department of Computer Science of the National University of Singapore. He is also the Vice Provost for Graduate Education at NUS. Before becoming the Vice Provost in 2014, he was the Associate Provost (Graduate Education) during 2011-2013. Earlier, he was the Vice-Dean for Academic Affairs & Graduate Studies at the NUS School of Computing during 2008-2010 and Vice-Dean for Research during 2001-2007.
Mohan obtained his BTech from IIT Kharagpur and MS & PhD from the Rensselaer Polytechnic Institute.

His current research interests are in Multimedia Systems (content processing,
retrieval) and Multimedia Security (surveillance and privacy). He directs SeSaMe - the Centre for "Sensor-enhanced Social Media"
(sesame.comp.nus.edu.sg).

Mohan is actively involved in organizing of many major conferences in the area of Multimedia. He was also the Director of Conferences for ACM SIG Multimedia during 2009-2013. He is on the editorial boards of several journals including the ACM Transactions on Multimedia, Springer Multimedia Systems Journal, Pattern Recognition Journal and Springer Multimedia Tools & Applications Journal. He is a Fellow of IEEE.

Positional Games is a branch of Combinatorics which focuses on a variety of two player games, ranging from well-known games such as Tic-Tac-Toe and Hex, to purely abstract games played on graphs. The field has experienced quite a growth in recent years, with more than a few applications in related areas.

We aim to introduce the basic notions, approaches and tools, as well as to survey the recent developments, open problems and promising research directions, keeping the main focus on the games played on graphs.

Bio:
Milos Stojakovic is an Associate Professor in the Department of Mathematics and Informatics at the Faculty of Science, University of Novi Sad. His research interests are in positional games, discrete and computational geometry, discrete random structures, combinatorial algorithms, and graph theory. He earned his Ph.D. in Computer Science from ETH Zurich, advised by Emo Welzl and Tibor Szabo. He earned his M.Sc. and B.Sc. degress from the University of Novi Sad. He is recipient of "Dr Z. Đinđić Award", for the best young (under 35) scientist in Vojvodina in 2008 as well as "Best Student of University of Novi Sad Award" in 1998/99.

There has been growing concern about how children are becoming increasingly distracted by digital technology; notably playing video games for hours on end, perpetually texting during family meals, browsing dizzying amounts of digital content and constantly using various social media apps for existential reassurance. Attention drift appears to be on the rise raising much debate about its detrimental effect on child development. There is, however, as of yet no real evidence to support this. I argue that we should turn this worry on its head: and think instead about the potential benefits of digital technology’s attention grabbing affordances, that can be exploited to good effect in various contexts. This requires determining how to inform and guide attention-switching strategies, temporally and spatially, across a range of activities. In my talk I will present our ‘mechanisms for collaboration’ framework that seeks to achieve this through constraining the interface and activity in specific ways. Our goal is to enable children to learn where, when, what and how to look at relevant foci more effectively during ongoing learning activities in individual, group and whole classroom contexts. I will describe a number of technologies that we have designed and deployed that have been successful at guiding attention and improving learning in terms of increasing awareness, shared decision-making and reflection in problem-solving contexts.
Bio:
Yvonne Rogers is the director of the Interaction Centre at UCL (UCLIC), deputy head of department for Computer Science and a professor of Interaction Design. She is the Principal Investigator for the Intel-funded Cities collaborative research Institute (cities.io) at UCL. She is also an honorary professor at University Cape Town and has spent sabbaticals at Stanford, Apple, Queensland University, Melbourne University, University Cape Town and UCSD. Her research is in the areas of ubiquitous computing, interaction design and human-computer interaction. This involves informing, building and evaluating novel user experiences through creating and assembling a diversity of pervasive technologies. She has been instrumental in promulgating new theories (e.g., external cognition), alternative methodologies (e.g., in the wild studies) and far-reaching research agendas (e.g., “Being Human: HCI in 2020” manifesto), and has pioneered an approach to innovation and ubiquitous learning. She is a co-author of the definitive textbook on Interaction Design and HCI now published in its 4th edition that has sold over 150,000 copies worldwide and has been translated into 6 languages. She has been elected as a fellow of the BCS and the ACM CHI Academy. She was also awarded a prestigious EPSRC dream fellowship concerned with rethinking the relationship between ageing, computing and creativity.

Scheduling work on "warehouse-scale" clusters in modern data centres
is a challenging undertaking: thousands of tasks must be placed
rapidly, and may interact in complex ways on the cluster substrate
consisting of thousands of many-core servers. Moreover, existing
schedulers typically tightly couple policy and implementation. An
ideal cluster scheduler would flexibly support used-defined scheduling
policies, ensure high machine utilisation, avoid pathological
interference on shared resources, and find the optimal assignments quickly.

In this talk, I explain how we square this circle in our Firmament
scheduler. Firmament models the scheduling problem as an incremental
minimum-cost, maximum-flow optimisation. This approach considers all
possible assignments concurrently and makes placement decisions that
are optimal for the given scheduling policy. By modelling tasks'
preferences and interactions as costs on a flow network representing
the cluster topology, Firmament simultaneously optimises for multiple objectives.
Via two case-studies, I illustrate how this enables practical, useful
scheduling policies to be expressed concisely. To scale to large
clusters, Firmament solves the optimisation problem incrementally. On
a Google cluster of 12,500 machines, this takes 200ms on average, a
10x improvement over solving the problem from scratch.

Using test-bed experiments on a physical cluster and trace-driven
simulation on a Google cluster, I show that Firmament is a flexible
scheduling platform (supporting many different policies) which makes
accurate, high-quality decisions (optimal with regards to the policy)
at interactive time-scales (sub-second even at Google-scale).