Research lectures, seminars and events
The events listed in this area are research seminars, workshops and lectures hosted by Durham University departments and research institutes. If you are not a member of the University, but wish to enquire about attending one of the events please contact the organiser or host department.
|September 2020||November 2020|
Events for 21 October 2020
The theory of metric measure spaces verifying the Riemannian-Curvature-Dimension condition RCD(K,N) has attracted a lot of interest in the last years.
They can be thought as a non smooth counterpart of the class of Riemannian manifolds with Ricci curvature bounded from below by K and dimension bounded from above by N.
So far we have reached a good understanding of their structure up to negligible sets and it seems natural to push the study further, up to codimension one.
In this talk I will outline some recent developments about the structure of boundaries of sets of finite perimeter obtained in joint works with Ambrosio, Brue’ and Pasqualetto, where we extended De Giorgi’s celebrated theorem to this framework. The results are expected to be useful to improve our knowledge on the fine structure of these spaces and on their global shape.
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Understanding the cycle (or anticycle) structure in a given graph is fundamentally related to graph families such as trees, perfect graphs, bipartite graphs, (weakly) chordal graphs, pancyclic graphs, and many others. A particularly strong cycle-related property is the notion of cycle-regularity, introduced by Mollard, which has been used to better understand the structure of graph families such as hypercubes or generalized Petersen graphs. In this talk we present three graph families, namely I-graphs, double generalized Petersen graphs and folded cubes and show how their cyclic structure helped us devise linear time recognition algorithms for them.
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Prof Susanne Lajoie: Application of Cognitive Theories to the Design of Advanced Technologies for Learning
Psychological theories can inform the design of technology rich learning environments (TREs) to provide better learning and training opportunities. Research shows that learners do better when interacting with material that is situated in meaningful, authentic contexts. Recently, psychologists are interested in the role that emotion plays in learning with technology. Lajoie investigates the situations under which technology works best to facilitate learning and performance by examining the relations between cognition (problem solving, decision making), metacognition (self-regulation) and affect (emotion, beliefs, attitudes, interests, etc.). Convergent methodologies will be described (i.e., physiological and behavioral indices, think aloud protocols, eye tracking, etc.) in terms of how they are used to identify how learners think and feel in the context of TREs. TREs can include simulations, intelligent tutoring systems, agent-based systems, augmented reality systems, and serious games. Examples will be presented of how TREs can determine when learners are engaged and happy as opposed to bored and angry while learning. Findings from this type of research helps identify the best way to tailor the learning experience to the cognitive and affective needs of the learner. Furthermore, social and emotional competencies of learning in teams in the context of technology rich learning environments (TREs) will be discussed as they pertain to: (a) the ability to adapt to new situations and challenges and engage in complex problem solving; (b) social skills necessary for communicating and collaborating productively and proficiently; (c) social-emotional skills and empathy necessary for tackling challenging problems and regulating emotion, and (d) ability to take initiative, set goals, and monitor self and others.
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