A game model for the multimodality phenomena of coauthorship networks

We provided a game model to simulate the evolution of coauthorship networks, a geometric hypergraph built on a circle. The model expresses kin selection and network reciprocity, two typically cooperative mechanisms, through a cooperation condition called positive benefit-minus-cost. The costs are modelled through space distances. The benefits are modelled through geometric zones that depend on node hyperdegree, which gives an expression of the cumulative advantage on the reputations of authors. Our findings indicate that the model gives a reasonable fitting to empirical coauthorship networks on their degree distribution, node clustering, and so on. It reveals two properties of node attractions, namely node heterogeneity and fading with the growth of hyperdegrees, can deduce the dichotomy of nodes' clustering behavior and assortativity, as well as the trichotomy of degree and hyperdegree distributions: generalized Poisson, power law and exponential cutoff

Modelling the Dropout Patterns of MOOC Learners

We adopted survival analysis for the viewing durations of massive open online courses. The hazard function of empirical duration data is dominated by a bathtub curve and has the Lindy effect in its tail. To understand the evolutionary mechanisms underlying these features, we categorized learners into two classes due to their different distributions of viewing durations, namely lognormal distribution and power law with exponential cutoff. Two random differential equations are provided to describe the growth patterns of viewing durations for the two classes respectively. The expected duration change rate of the learners featured by lognormal distribution is supposed to be dependent on their past duration, and that of the rest learners is supposed to be inversely proportional to time. Solutions to the equations predict the features of viewing duration distributions, and those of the hazard function. The equations also reveal the feature of memory and that of memorylessness for the viewing behaviors of the two classes respectively.Comment: 8 figure

Assessing the level of merging errors for coauthorship data: a Bayesian model

Robust analysis of coauthorship networks is based on high quality data. However, ground-truth data are usually unavailable. Empirical data suffer several types of errors, a typical one of which is called merging error, identifying different persons as one entity. Specific features of authors have been used to reduce these errors. We proposed a Bayesian model to calculate the information of any given features of authors. Based on the features, the model can be utilized to calculate the rate of merging errors for entities. Therefore, the model helps to find informative features for detecting heavily compromised entities. It has potential contributions to improving the quality of empirical data

Westervelt Equation Simulation on Manifold using DEC

The Westervelt equation is a model for the propagation of finite amplitude ultrasound. The method of discrete exterior calculus can be used to solve this equation numerically. A significant advantage of this method is that it can be used to find numerical solutions in the discrete space manifold and the time, and therefore is a generation of finite difference time domain method. This algorithm has been implemented in C++.Comment: 8 pages,4 figure

Two unconditional stable schemes for simulation of heat equation on manifold using DEC

To predict the heat diffusion in a given region over time, it is often necessary to find the numerical solution for heat equation. With the techniques of discrete differential calculus, we propose two unconditional stable numerical schemes for simulation heat equation on space manifold and time. The analysis of their stability and error is accomplished by the use of maximum principle.Comment: 8 pages,3figure

Analysis and simulations of a Viscoelastic Model of Angiogenesis

The work analyzes a one-dimensional viscoelastic model of blood vessel growth under nonlinear friction with surroundings, and provides numerical simulations for various growing cases. For the nonlinear differential equations, two sufficient conditions are proven to guarantee the global existence of biologically meaningful solutions. Examples with breakdown solutions are captured by numerical approximations. Numerical simulations demonstrate this model can reproduce angiogenesis experiments under various biological conditions including blood vessel extension without proliferation and blood vessel regression.Comment: 20 pages, 15 figure

Scale-invariant geometric random graphs

We introduce and analyze a class of growing geometric random graphs that are invariant under rescaling of space and time. Directed connections between nodes are drawn according to influence zones that depend on node position in space and time, mimicking the heterogeneity and increased specialization found in growing networks. Through calculations and numerical simulations we explore the consequences of scale-invariance for geometric random graphs generated this way. Our analysis reveals a dichotomy between scale-free and Poisson distributions of in- and out-degree, the existence of a random number of hub nodes, high clustering, and unusual percolation behaviour. These properties are similar to those of empirically observed web graphs.Comment: 7 pages, 8 figure

Kernelized Locality-Sensitive Hashing for Semi-Supervised Agglomerative Clustering

Large scale agglomerative clustering is hindered by computational burdens. We propose a novel scheme where exact inter-instance distance calculation is replaced by the Hamming distance between Kernelized Locality-Sensitive Hashing (KLSH) hashed values. This results in a method that drastically decreases computation time. Additionally, we take advantage of certain labeled data points via distance metric learning to achieve a competitive precision and recall comparing to K-Means but in much less computation time

Computation of Maxwell's equations on manifold using implicit DEC scheme

Maxwell's equations can be solved numerically in space manifold and the time by discrete exterior calculus as a kind of lattice gauge theory.Since the stable conditions of this method is very severe restriction, we combine the implicit scheme of time variable and discrete exterior calculus to derive an unconditional stable scheme. It is an generation of implicit Yee-like scheme, since it can be implemented in space manifold directly. The analysis of its unconditional stability and error is also accomplished.Comment: 9pages,4figure

Modeling the coevolution between citations and coauthorships in scientific papers

Collaborations and citations within scientific research grow simultaneously and interact dynamically. Modelling the coevolution between them helps to study many phenomena that can be approached only through combining citation and coauthorship data. A geometric graph for the coevolution is proposed, the mechanism of which synthetically expresses the interactive impacts of authors and papers in a geometrical way. The model is validated against a data set of papers published on PNAS during 2007-2015. The validation shows the ability to reproduce a range of features observed with citation and coauthorship data combined and separately. Particularly, in the empirical distribution of citations per author there exist two limits, in which the distribution appears as a generalized Poisson and a power-law respectively. Our model successfully reproduces the shape of the distribution, and provides an explanation for how the shape emerges via the decisions of authors. The model also captures the empirically positive correlations between the numbers of authors' papers, citations and collaborators