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Quantum key distribution is renowned for information-theoretic security on point-to-point connections, while it is by itself not directly capable of end-to-end security. Multipath transmission is known for perfect end-to-end security, provided that perfect point-to-point security is achievable. The marriage of the two is as natural as it is difficult to achieve in real life networks: secure multipath transmission imposes stringent requirements on the network connectivity, perhaps rarely found in a real-life network infrastructure. We consider the problem of network augmentation to support perfect end-to-end security in a network in which adjacent nodes share a perfectly confidential channel. Quantum networks are one example for this. Starting with a decision-theoretic formalization of risk and confidentiality, we cast the network augmentation task into a nonlinear optimization problem, whose computational complexity is studied. With the problem turning out NP-hard in at least two of its variants, we sketch heuristics that can help to keep calculations feasible in practical applications.

Research has shown that learning programs with well designed animated virtual pedagogical agents engage and motivate students, produce greater reported satisfaction and enjoyment by students, and produce greater learning gains than programs without these agents. How to design an animated virtual pedagogical agent behaves much like a sensitive and effective human tutor is a very challenge work to do. In this paper, we developed a procedure for producing head and face movements during speech by a virtual pedagogical agent by combining different voice recordings, different facial expressions and different head movement patterns. We then developed three experimental conditions to evaluate how the facial expressions and head movements contribute to learning experiences and outcomes. Results showed that facial expressions and head movements have great impact on student’s impressions and engagement with the virtual pedagogical agent. Experimental results suggest that virtual pedagogical agent that produce natural head movements and appropriate facial expressions while narrating a story produce much more positive user experiences than virtual pedagogical agent that lack these behaviors.

Dynamic Partial Reconfiguration (DPR) allows the targeted FieldProgrammable Array (FPGA) to selectively update portions of the programmable logic while the remainder of the fabric stays active. Previously, designers were required to manually create DPR systems with minimal support from Computer Aided Design (CAD) tools. Xilinx ® ’s PlanAhead TM software now automates much of the DPR system generation process for ISE-based DPR systems. This paper presents EuTOPIA (EDK TO PlanAhead Implementation Automation), a CAD tool that extends the automation in Xilinx’s current DPR design flow to include microprocessor based designs. Given an architecture described in Xilinx’s Embedded Design Kit (EDK), EuTOPIA automates the process of converting it into a PlanAhead project for a DPR design. EuTOPIA abstracts the low level details of DPR implementation so that designers need only have nominal knowledge of the underlying process to create their initial DPR system. EuTOPIA is shown to reduce implementation time by a factor of 18 times over manual implementations by experienced designers, and can be further increased for novice designers. Over the design-cycle of a product where designers may generate tens or even hundreds of different implementations of their DPR design, these time savings could be extremely significant.