No abstract

A graphene (GN)/carbon nanotubes (CNTs) nanocomposite electrode material were prepared via reduction of exfoliated graphite oxides in the presence of CNTs pretreated by mixed acid. The GN/CNTs nanocomposite characterized by X-ray di®raction (XRD), Raman spectrum (Raman) and scanning electron microscope (SEM) has a layered structure with CNTs uniformly sandwiched between the GN sheets, which e±ciently decreased the agglomeration GN sheets. Electrochemical data demonstrate that the GN/CNT exhibited higher speci¯c capacitance than that of graphene.

No abstract

To draw reconstruction plans following great earthquakes, it is necessary to quickly estimate the amount of disaster waste, with the use of remote sensing data affecting all subsequent processing. However, the digital number (DN) of each pixel represents the average land cover conditions, i.e., the information provided by a pixel should be represented as a one-pixel mixed-class ("mixel") instead of a one-pixel one-class. In a previous study, we proposed a method for unmixing mixels using the DNs and texture features from THEOS data. In this paper, we propose a method of land cover classification using RapidEye data, whose effectiveness was confirmed by our results.

No abstract