The performance of BPIC method against different size of bucket.

<p>The performance of BPIC method against different size of bucket.</p

The relationship between a point and a boundary vector.

<p><i>b</i> is a boundary point and its boundary vector is marked with a red arrow. <i>b</i>_<i>end</i> represents the end of <i>b</i>’s boundary vector. <i>P</i>_<i>0</i> is a point in the neighbourhood of <i>b</i> and it becomes a new boundary point. <i>P</i>_<i>1</i> is a point outside of the boundary profile since it is closer to <i>b</i> than to <i>b</i>_<i>end</i>. <i>P</i>_<i>2</i> is a point inside of the boundary profile since it is closer to <i>b</i>_<i>end</i> than <i>b</i>.</p

The number of data points maintained in memory by each method with different numbers of new data points.

<p>The number of data points maintained in memory by each method with different numbers of new data points.</p

The evaluations of incremental clustering results by the three methods with different numbers of new points.

<p>(a)Precision of incremental clustering results. (b) Recall of incremental clustering results. (c) F1-measure of incremental clustering results.</p

The discriminant tree of a data point.

<p>The discriminant tree of a data point.</p

The execution time of the three methods against different numbers of new data points.

<p>The execution time of the three methods against different numbers of new data points.</p

The density distribution of a core point <i>c</i> and a boundary point <i>b</i>.

<p>(a) Point b and c are boundary and core point respectively. (b) The boundary vector of core point c within its neighbourhood. (c) The boundary vector of boundary point b within its neighbourhood.</p

The evolution process of the BPIC results, in which the bucket size is 3500.

<p>(a) The initial boundary clustering results on 3000 data points from the Chameleon DS3 dataset. (b) The first updated clustering results after 3500 data points are added. (c) The second updated clustering results after 7000 data points are added.</p

Evaluation of the two methods’ boundary detection results.

<p>Evaluation of the two methods’ boundary detection results.</p

Multicolored Mixed-Organic-Cation Perovskite Quantum Dots (FA_<i>x</i>MA_1–<i>x</i>PbX₃, X = Br and I) for White Light-Emitting Diodes

Organometal halide perovskites (such as CH₃NH₃PbX₃, X = Cl, Br, I) have received enormous interest due to their strikingly photoelectric properties. Here we develop a facile ligand-assisted reprecipitation method to synthesize NH₂CHNH₂PbX₃ (NH₂CHNH₂⁺, FA; X = Br and I) perovskite quantum dots (QDs) at room temperature. The FAPbX₃ perovskite QDs with uniform monodispersity (sized 4–7 nm) display relatively high photoluminescence quantum yields (PLQYs) of 60–75%. Through manipulating the mixed-organic-cation reactions, we achieve a series of multicolored perovskite QDs with continuously controllable emission wavelengths from 460 to 565 nm. Furthermore, we discuss the influence of ligands (oleic acid and n-octylamine) on PL properties and stabilities of perovskite QDs. Finally, we have successfully designed a white LED via compositing perovskite QDs and poly­(methyl methacrylate) (PMMA), which presents a high color rendering index. Considering those remarkable achievements, we believe our work will have great potential to meet various optoelectronic applications