46,605 research outputs found
Lightening Global Types
Global session types prevent participants from waiting for never coming
messages. Some interactions take place just for the purpose of informing
receivers that some message will never arrive or the session is terminated. By
decomposing a big global type into several light global types, one can avoid
such kind of redundant interactions. Lightening global types gives us cleaner
global types, which keep all necessary communications. This work proposes a
framework which allows to easily decompose global types into light global
types, preserving the interaction sequences of the original ones but for
redundant interactions.Comment: In Proceedings PLACES 2014, arXiv:1406.331
Models of Neutrino Masses and Mixing
Neutrino physics has entered an era of precision measurements. With these
precise measurements, we may be able to distinguish different models that have
been constructed to explain the small neutrino masses and the large mixing
among them. In this talk, I review some of the existing theoretical models and
their predictions for neutrino oscillations.Comment: Talk presented at the 2nd International Colliders to Cosmic Rays
Conference (C2CR07), Lake Tahoe, CA, February 25 - March 1, 2007; 8 pages; 2
figure
Binary Biometric Representation through Pairwise Adaptive Phase Quantization
Extracting binary strings from real-valued biometric templates is a fundamental step in template compression and protection systems, such as fuzzy commitment, fuzzy extractor, secure sketch, and helper data systems. Quantization and coding is the straightforward way to extract binary representations from arbitrary real-valued biometric modalities. In this paper, we propose a pairwise adaptive phase quantization (APQ) method, together with a long-short (LS) pairing strategy, which aims to maximize the overall detection rate. Experimental results on the FVC2000 fingerprint and the FRGC face database show reasonably good verification performances.\ud
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Quantum Robot: Structure, Algorithms and Applications
A kind of brand-new robot, quantum robot, is proposed through fusing quantum
theory with robot technology. Quantum robot is essentially a complex quantum
system and it is generally composed of three fundamental parts: MQCU (multi
quantum computing units), quantum controller/actuator, and information
acquisition units. Corresponding to the system structure, several learning
control algorithms including quantum searching algorithm and quantum
reinforcement learning are presented for quantum robot. The theoretic results
show that quantum robot can reduce the complexity of O(N^2) in traditional
robot to O(N^(3/2)) using quantum searching algorithm, and the simulation
results demonstrate that quantum robot is also superior to traditional robot in
efficient learning by novel quantum reinforcement learning algorithm.
Considering the advantages of quantum robot, its some potential important
applications are also analyzed and prospected.Comment: 19 pages, 4 figures, 2 table
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