Quantum Critical Phenomena of 4He in Nanoporous Media

The superfluid transition in liquid 4He filled in Gelsil glass observed in recent experiments is discussed in the framework of quantum critical phenomena. We show that quantum fluctuations of phase are indeed important at the experimentally studied temperature range owing to the small pore size of Gelsil, in contrast to 4He filled in previously studied porous media such as Vycor glass. As a consequence of an effective particle-hole symmetry, the quantum critical phenomena of the system are described by the 4D XY universality class, except at very low temperatures. The simple scaling agrees with the experimental data remarkably well.Comment: 4 pages, 3 figure

Human-machine cooperation in large-scale multimedia retrieval : a survey

Large-Scale Multimedia Retrieval(LSMR) is the task to fast analyze a large amount of multimedia data like images or videos and accurately find the ones relevant to a certain semantic meaning. Although LSMR has been investigated for more than two decades in the fields of multimedia processing and computer vision, a more interdisciplinary approach is necessary to develop an LSMR system that is really meaningful for humans. To this end, this paper aims to stimulate attention to the LSMR problem from diverse research fields. By explaining basic terminologies in LSMR, we first survey several representative methods in chronological order. This reveals that due to prioritizing the generality and scalability for large-scale data, recent methods interpret semantic meanings with a completely different mechanism from humans, though such humanlike mechanisms were used in classical heuristic-based methods. Based on this, we discuss human-machine cooperation, which incorporates knowledge about human interpretation into LSMR without sacrificing the generality and scalability. In particular, we present three approaches to human-machine cooperation (cognitive, ontological, and adaptive), which are attributed to cognitive science, ontology engineering, and metacognition, respectively. We hope that this paper will create a bridge to enable researchers in different fields to communicate about the LSMR problem and lead to a ground-breaking next generation of LSMR systems