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A computerised algorithm was developed to predict child psychiatric diagnoses on the basis of the symptom and impact scores derived from Strengths and Difficulties Questionnaires (SDQs) completed by parents, teachers and young people. The predictive algorithm generates "unlikely", "possible" or "probable" ratings for four broad categories of disorder,(More)
Traffic signal control is an effective way to improve the efficiency of traffic networks and reduce users' delays. Ant Colony Optimization (ACO) is a meta-heuristic algorithm based on the behavior of ant colonies searching for food. ACO has successfully been employed to solve many complicated combinatorial optimization problems and its stochastic and(More)
Using a generalized random recurrent neural network model, and by extending our recently developed mean-field approach [J. Aljadeff, M. Stern, and T. Sharpee, Phys. Rev. Lett. 114, 088101 (2015)], we study the relationship between the network connectivity structure and its low-dimensional dynamics. Each connection in the network is a random number with mean(More)
One of the aims of this workshop was to present basic notions from random matrix theory, with a particular focus on providing background material so that all participants can interact successfully with more experienced and senior researchers involved in the program. Many of the senior participants are experts in one area of random matrix theory and have(More)
The numerical range of a bounded linear operator T on a Hilbert space H is defined to be the subset W (T) = {Tv, v : v ∈ H, v = 1} of the complex plane. For operators on a finite-dimensional Hilbert space, it is known that if W (T) is a circular disk then the center of the disk must be a multiple eigenvalue of T. In particular, if T has minimal polynomial z(More)
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