Publications

Abstract

It has been argued that we map observed actions onto our own motor system. Here we added to this issue by investigating whether hand preference influences the neural correlates of action observation of simple, essentially meaningless hand actions. Such an influence would argue for an intricate neural coupling between action production and action observation, which goes beyond effects of motor repertoire or explicit motor training, as has been suggested before. Indeed, parts of the human motor system exhibited a close coupling between action production and action observation. Ventral premotor and inferior and superior parietal cortices showed differential activation for left- and right-handers that was similar during action production as well as during action observation. This suggests that mapping observed actions onto the observer's own motor system is a core feature of action observation - at least for actions that do not have a clear goal or meaning. Basic differences in the way we act upon the world are not only reflected in neural correlates of action production, but can also influence the brain basis of action observation.

Abstract

Set is widely used as a kind of basic data structure. However, when it is used for large scale data set the cost of storage, search and transport is overhead. The bloom filter uses a fixed size bit string to represent elements in a static set, which can reduce storage space and search cost that is a fixed constant. The time-space efficiency is achieved at the cost of a small probability of false positive in membership query. However, for many applications the space savings and locating time constantly outweigh this drawback. Dynamic bloom filter (DBF) can support concisely representation and approximate membership queries of dynamic set instead of static set. It has been proved that DBF not only possess the advantage of standard bloom filter, but also has better features when dealing with dynamic set. This paper proposes a time-dependent multiple bit-strings bloom filter (TMBF) which roots in the DBF and targets on dynamic incremental set. TMBF uses multiple bit-strings in time order to present a dynamic increasing set and uses backward searching to test whether an element is in a set. Based on the system logs from a real P2P file sharing system, the evaluation shows a 20% reduction in searching cost compared to DBF.

Abstract

The Corpus NGT