Being a new kind of nanomaterials, aromatic polyamide nanofibers (ANF) have been much highlighted in recent studies. We here demonstrate an isopropyl alcohol (IPA) accelerated chemical cleavage on poly (p-phenylene terephthalamide) chopped fibers, which provides an efficient preparation method of ANF. The comprehensive study on the processes accelerated by different alcohols revealed that the preparation time of ANF in the mixed medium of dimethyl sulfoxide (DMSO)-alcohol (20:1 in volume) was shorten to 45 min and 75 min for methanol (ethanol) and isopropanol, respectively. However, the nanofibers prepared in DMSO-IPA exhibited the minimum in axial and radial dimensions, providing the finest and most uniform diameter of 16 nm. The corresponding ANF films through vacuum assisted filtration also showed the highest tensile strength of 150 MPa, in comparison with those of the ANF films prepared using other alcohols, which were about 110 MPa. Furthermore, ANF/silicon hybrid films were prepared by the ionic ring-opening reaction followed by the alkoxysilane condensation and nanoparticle fabrication. By changing the organo functional groups in the alkoxysilane, the surface of the films were adjustable in a wide contact angle range from 56° (hydrophilic) to 150° (superhydrophobic), suggesting the amendable interfacial properties potential applicable to composite fabrication with most of the resin matrix. 相似文献
Ob ject recognition has many applications in human-machine interaction and multimedia retrieval. However, due to large intra-class variability and inter-class similarity, accurate recognition relying o... 相似文献
Smart transportation has a significantly impact on city management and city planning, which has received extensive attentions from academic and industrial communities. Different from omni-directional sensing system, as a directional sensing system, the multimedia-directional sensor network holds the special coverage scheme, which is usually used for smart cities, smart transportation, and harsh environment surveillance, for instance, nuclear-pollution regions where are inhospitable for people. This paper advances Virtual Stream Artificial Fish-swarm based Coverage-Enhancing Algorithm (VSAFCEA) as a coverage-enhancing means in multimedia directional sensor networks. Firstly, a concept of virtual streams, based on traditional artificial fish-swarm algorithm, is proposed. Then, the traditional behaviors of fishes in artificial fish-swarm algorithm are modified and expanded with several new behaviors. Finally, the presented VSAFCEA is adopted for coverage-enhancing issue in the situation of directional sensor networks with rotational direction-adjustable model. With a sequence of steps of artificial fishes in virtual stream, the presented VSAFCEA can figure out the approximation to the highest area coverage rate. Based on comparison of these simulation results (results of presented VSAFCEA and that of other typical coverage-enhancing ways in directional sensor networks), the conclusion can be drawn that VSAFCEA could attain higher area coverage rate of directional sensor networks with fewer iterative computing times.
In natural language processing, a crucial subsystem in a wide range of applications is a part-of-speech (POS) tagger, which labels (or classifies) unannotated words of natural language with POS labels corresponding to categories such as noun, verb or adjective. Mainstream approaches are generally corpus-based: a POS tagger learns from a corpus of pre-annotated data how to correctly tag unlabeled data. Presented here is a brief state-of-the-art account on POS tagging. POS tagging approaches make use of labeled corpus to train computational trained models. Several typical models of three kings of tagging are introduced in this article: rule-based tagging, statistical approaches and evolution algorithms. The advantages and the pitfalls of each typical tagging are discussed and analyzed. Some rule-based and stochastic methods have been successfully achieved accuracies of 93–96 %, while that of some evolution algorithms are about 96–97 %. 相似文献