In this paper, four conductive polyaniline powders doped in hydrochloric acid, sulfuric acid, phosphoric acid, and sulfonic acid were selected and blended with polydimethylsiloxane to prepare coatings with an electromagnetic absorption effect and fouling desorption effect, respectively. A UV spectrophotometer was used to evaluate the settling rate of the powders. Fourier transform infrared spectrometry, laser confocal microscopy, and scanning electron microscopy were used to observe the morphology and structure of the powder and the coating. The interface properties of the coatings were characterized using a contact angle measurement, the mechanical properties of the coatings using a tensile test, and the electromagnetic properties of the powders and microwave absorption properties of the coatings using vector network analyzers. Meanwhile, the antifouling performance of the coatings was evaluated via the marine bacteria adhesion test and benthic diatom adhesion test, and the effect of conductive polyaniline on the antifouling performance of the coating was analyzed. The results show that adding polyaniline reduced the surface energy of the coating and increased the roughness, mechanical properties and anti-fouling properties of the coating. Moreover, adding appropriate polyaniline powder can enhance the electromagnetic wave loss of the coating. The followings values were recorded for a hydrochloric-acid-doped polyaniline coating: lowest surface energy of 17.17 mJ/m2, maximum fracture strength of 0.95 MPa, maximum elongation of 155%, maximum bandwidth of 3.81 GHz, and peak of reflection loss of −23.15 dB. The bacterial detachment rate of the polydimethylsiloxane (PDMS) samples was only 30.37%. The bacterial adhesion rates of the composite coating containing hydrochloric-acid-doped polyaniline were 4.95% and 2.72% after rinsing and washing, respectively, and the desorption rate was 45.35%. The chlorophyll concentration values were 0.0057 mg/L and 0.0028 mg/L, respectively, and the desorption rate was 54.62%.
Detecting Detecting the boundary of each cluster in a data set is a tough problem for many existed boundary detecting algorithms. In order to solve that problem, a clustering boundary detecting algorithm based on DBSCAN named BDAEC(Boundary Detecting Algorithm for Each Cluster based on DBSCAN: BDAEC) is proposed. Firstly, according to the core point percent and the density value of each data object, all the core points are extracted by this algorithm from the data set. Then, many connected undirected graphs will be constituted by these core points. And the cluster numbers of the data set can be known by those connected undirected graphs for each one of them represents a cluster. Finally, Eps field will be diveded into two fields: the positive field and the negative field. And the boundary of each cluster or the whole data set can be detected by the distribution characteristics of the data objects which are located in the positive field and negative field of the given data object. The experimental results on many data sets with noise show that BDAEC algorithm can obtain the numbers and the boundaries of the clusters with different size or shapes effectively.
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