arXiv subjects

Wen Dong

Publications and source records attributed to Wen Dong.

27 records · Page 2Linked to original sources

arXiv2016

Variational Inference with Agent-Based Models

In this paper, we develop a variational method to track and make predictions about a real-world system from continuous imperfect observations about this system, using an agent-based model that describes the system dynamics. By combining the power of big data with the power of model-thinking in the stochastic process framework, we can make many valuable predictions. We show how to track the spread of an epidemic at the individual level and how to make short-term predictions about traffic congestion. This method points to a new way to bring together modelers and data miners by turning the real world into a living lab.

cs.MA↗

arXiv2015

Virtual Networks and Poverty Analysis in Senegal

Do today's communication technologies hold potential to alleviate poverty? The mobile phone's accessibility and use allows us with an unprecedented volume of data on social interactions, mobility and more. Can this data help us better understand, characterize and alleviate poverty in one of the poorest nations in the world. Our study is an attempt in this direction. We discuss two concepts, which are both interconnected and immensely useful for securing the important link between mobile accessibility and poverty. First, we use the cellular-communications data to construct virtual connectivity maps for Senegal, which are then correlated with the poverty indicators to learn a model. Our model predicts poverty index at any spatial resolution. Thus, we generate Poverty Maps for Senegal at an unprecedented finer resolution. Such maps are essential for understanding what characterizes poverty in a certain region, and how it differentiates from other regions, for targeted responses for the demographic of the population that is most needy. An interesting fact, that is empirically proved by our methodology, is that a large portion of all communication, and economic activity in Senegal is concentrated in Dakar, leaving many other regions marginalized. Second, we study how user behavioral statistics, gathered from cellular-communications, correlate with the poverty indicators. Can this relationship be learnt as a model to generate poverty maps at a finer resolution? Surprisingly, this relationship can give us an alternate poverty map, that is solely based on the user behavior. Since poverty is a complex phenomenon, poverty maps showcasing multiple perspectives, such as ours, provide policymakers with better insights for effective responses for poverty eradication.

cs.CY↗

arXiv2014

Modeling Infection with Multi-agent Dynamics

Developing the ability to comprehensively study infections in small populations enables us to improve epidemic models and better advise individuals about potential risks to their health. We currently have a limited understanding of how infections spread within a small population because it has been difficult to closely track an infection within a complete community. The paper presents data closely tracking the spread of an infection centered on a student dormitory, collected by leveraging the residents' use of cellular phones. The data are based on daily symptom surveys taken over a period of four months and proximity tracking through cellular phones. We demonstrate that using a Bayesian, discrete-time multi-agent model of infection to model real-world symptom reports and proximity tracking records gives us important insights about infec-tions in small populations.

stat.AP↗

arXiv2012

Graph-Coupled HMMs for Modeling the Spread of Infection

We develop Graph-Coupled Hidden Markov Models (GCHMMs) for modeling the spread of infectious disease locally within a social network. Unlike most previous research in epidemiology, which typically models the spread of infection at the level of entire populations, we successfully leverage mobile phone data collected from 84 people over an extended period of time to model the spread of infection on an individual level. Our model, the GCHMM, is an extension of widely-used Coupled Hidden Markov Models (CHMMs), which allow dependencies between state transitions across multiple Hidden Markov Models (HMMs), to situations in which those dependencies are captured through the structure of a graph, or to social networks that may change over time. The benefit of making infection predictions on an individual level is enormous, as it allows people to receive more personalized and relevant health advice.

cs.SI↗

arXiv2012

Automatic Prediction Of Small Group Performance In Information Sharing Tasks

In this paper, we describe a novel approach, based on Markov jump processes, to model small group conversational dynamics and to predict small group performance. More precisely, we estimate conversational events such as turn taking, backchannels, turn-transitions at the micro-level (1 minute windows) and then we bridge the micro-level behavior and the macro-level performance. We tested our approach with a cooperative task, the Information Sharing task, and we verified the relevance of micro- level interaction dynamics in determining a good group performance (e.g. higher speaking turns rate and more balanced participation among group members).

cs.SI↗

arXiv2012

Modeling Dynamical Influence in Human Interaction Patterns

How can we model influence between individuals in a social system, even when the network of interactions is unknown? In this article, we review the literature on the "influence model," which utilizes independent time series to estimate how much the state of one actor affects the state of another actor in the system. We extend this model to incorporate dynamical parameters that allow us to infer how influence changes over time, and we provide three examples of how this model can be applied to simulated and real data. The results show that the model can recover known estimates of influence, it generates results that are consistent with other measures of social networks, and it allows us to uncover important shifts in the way states may be transmitted between actors at different points in time.

cs.SI↗

arXiv2002

The Effects of a Non-Ferroelectric Slab on the Polarization and the Susceptibility of the Ferroelectric Multilayer

The polarization and the susceptibility of a ferroelectric multilayer with a non-ferroelectric slab are investigated within the framework of transverse Ising model with a four-spin interaction term. The effect of the thickness and the position of the non-ferroelectric slab are investigated in this paper. We find that the increase of the thickness of the non-ferroelectric will decrease the polarization and the susceptibility of the film. If the position of the non-ferroelcetric slab shifts from the center of the film to the surface, the number of the peaks of the susceptibility will change. And a step-like polarization curve is found.

cond-mat.mtrl-sci↗

arXiv2002

Long-range Effects on the Pyroelectric Coefficient and Dielectric Susceptibility of a Ferroelectric Bilayer

Long-range effects on the pyroelectric coefficient and susceptibility of a ferroelectric bilayer with a ferroelectric interfacial coupling are investigated by use of the transverse Ising model within the framework of mean-field theory. The effects of the interfacial coupling and the transverse field on the pyroelectric coefficient and susceptibility of the bilayer are investigated by taking into account the long-range interaction. It is found that the pyroelectric coefficient and susceptibility increase with the decrease of the magnitude of the long-range interaction and the interfacial coupling when the temperature is lower than the phase transition temperature. We also find that the strong long-range interaction, the large transverse field and weak interfacial coupling can lead to the disappearance of some of the peaks of the pyroelectric coefficient and susceptibility of the ferroelectric bilayer. The phase transition temperature increases with the increase of the strength of the long-range interaction, which is similar to the results obtained in ferroelectric multi-layers or superlattice.

cond-mat.mtrl-sci↗

arXiv2002

Long-range Effects on the Pyroelectric Coefficient of Ferroelectric Superlattice

Long-range effects on the pyroelectric coefficient of a ferroelectric superlattice consisting of two different ferroelectric materials are investigated based on the Transverse Ising Model. The effects of the interfacial coupling and the thickness of one period on the pyroelectric coefficient of the ferroelectric superlattice are studied by taking into account the long-range interaction. It is found that with the increase of the strength of the long-range interaction, the pyroelectric coefficient decreases when the temperature is lower than the phase transition temperature; the number of the pyroelectric peaks decreases gradually and the phase transition temperature increases. It is also found that with the decrease of the interfacial coupling and the thickness of one period, the phase transition temperature and the number of the pyroelectric peaks decrease.

cond-mat.mtrl-sci↗