arXiv subjects

Tingting Zhu

Publications and source records attributed to Tingting Zhu.

77 records · Page 5Linked to original sources

arXiv2019

Complete classification of the asymptotical behavior for singular C-S Model on the real line

In this paper, we study the singular Cucker-Smale (C-S) model on the real line. For long range case, i.e. $β<1$, we prove the uniqueness of the solution in the sense of Definition 2.1 and the unconditional flocking emergence. Moreover, the sufficient and necessary condition for collision and sticking phenomenon will be provided. For short range case, i.e. $β>1$, we construct the uniform-in-time lower bound of the relative distance between particles and provide the sufficient and necessary condition for the emergence of multi-cluster formation. For critical case, i.e. $β=1$, we show the uniform lower bound of the relative distance and unconditional flocking emergence. These results provide a complete classification of the collective behavior for C-S model on the real line.

math.DS↗

arXiv2019

Emergent behaviors of the discrete-time Kuramoto model for generic initial configuration

In this paper, we will study the emergent dynamics of the discrete Kuramoto model for generic initial data. This is an extension of the previous work S.-Y. Ha et al. (2019), in which the initial configurations are supposed to be within a half circle. More precisely, we will provide the theory of discrete gradient flow which can be applied to general Euler iteration scheme. Therefore, as a direct application, we conclude the emergence of synchronization of discrete Kuramoto model. Moreover, we obtain for small mesh size that, the synchronization will occur exponentially fast for initial data in A_1 (see definition in (4.1)).

math.DS↗

arXiv2018

X-ray total scattering study of regular and magic-size nanoclusters of cadmium sulphide

Four kinds of magic-size CdS clusters and two different regular CdS quantum dots have been studied by x-ray total scattering technique and pair distribution function method. Results for the regular CdS quantum dots could be modelled as a mixed phase of atomic structures based on the two bulk crystalline phases, which is interpreted as representing the effects of stacking disorder. However, the results for the magic-size clusters were significantly different. On one hand, the short-range features in the pair distribution function reflect the bulk, indicating that these structures are based on the same tetrahedral coordination found in the bulk phases (and therefore excluding new types of structures such as cage-like arrangements of atoms). But on the other hand, the longer- range atomic structure clearly does not reflect the layer structures found in the bulk and the regular quantum dots. We compare the effects of two ligands, phenylacetic acid and oleic acid, showing that in two cases the ligand has little effect on the atomic structure of the magic-size nanocluster and in another it has a significant effect.

cond-mat.mes-hall↗

arXiv2017

Benford's law first significant digit and distribution distances for testing the reliability of financial reports in developing countries

We discuss a common suspicion about reported financial data, in 10 industrial sectors of the 6 so called "main developing countries" over the time interval [2000-2014]. These data are examined through Benford's law first significant digit and through distribution distances tests. It is shown that several visually anomalous data have to be a priori removed. Thereafter, the distributions much better follow the first digit significant law, indicating the usefulness of a Benford's law test from the research starting line. The same holds true for distance tests. A few outliers are pointed out.

q-fin.ST↗

arXiv2015

Fusing Continuous-valued Medical Labels using a Bayesian Model

With the rapid increase in volume of time series medical data available through wearable devices, there is a need to employ automated algorithms to label data. Examples of labels include interventions, changes in activity (e.g. sleep) and changes in physiology (e.g. arrhythmias). However, automated algorithms tend to be unreliable resulting in lower quality care. Expert annotations are scarce, expensive, and prone to significant inter- and intra-observer variance. To address these problems, a Bayesian Continuous-valued Label Aggregator(BCLA) is proposed to provide a reliable estimation of label aggregation while accurately infer the precision and bias of each algorithm. The BCLA was applied to QT interval (pro-arrhythmic indicator) estimation from the electrocardiogram using labels from the 2006 PhysioNet/Computing in Cardiology Challenge database. It was compared to the mean, median, and a previously proposed Expectation Maximization (EM) label aggregation approaches. While accurately predicting each labelling algorithm's bias and precision, the root-mean-square error of the BCLA was 11.78$\pm$0.63ms, significantly outperforming the best Challenge entry (15.37$\pm$2.13ms) as well as the EM, mean, and median voting strategies (14.76$\pm$0.52ms, 17.61$\pm$0.55ms, and 14.43$\pm$0.57ms respectively with $p<0.0001$).

cs.LG↗