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Cyber attacks are a critical threat to government infrastructure, commercial enterprises and personal devices. When belligerents attack cyber systems, they need to spread laterally to reach high value targets and communicate with their command and control sites. Intuitively, a layered defense including intrusion detection systems will limit the adversary's exploitation of the target. We apply lessons...
Modeling epidemiological dynamics of AIDS infection is an indispensable method to track the spread of such fatal disease. In this paper, the Differential Infectivity and Staged Progression Model, DISP, is modified to include the possibility of recovery, hence the new proposed model is called the DISPR model. The DISPR model is also generalized to the fractional order domain to allow more flexibility...
Sexual contact networks for disease transmission have been used extensively with HIV and provide valuable insight into the way the disease spreads through a population. These computationally intensive models often suffer from lack of reusability which makes them expensive to create, use, and escalate. We take an innovated approach to build an HIV transmission model designed for expansion and reusability,...
Controlling the spread of infectious diseases in large populations is animportant societal challenge. Mathematically, the problem is best captured as acertain class of reaction-diffusion processes (referred to as contagionprocesses) over appropriate synthesized interaction networks. Agent-basedmodels have been successfully used in the recent past to study such contagionprocesses. We describe EpiSimdemics,...
Forecasting an epidemic outbreak is important for planning and interventions of health authorities. This paper presents a study of particle filtering based algorithms for estimation and forecasting the number of Ebola cases, using the World Health Organisation (WHO) observations collected during the 2014/2015 epidemic in West Africa. The dynamics of the Ebola epidemic is modelled using a stochastic...
Microblogs play an important role in online social communications. Different from ordinary pieces of information, some hot topics and emerging news will become much more popular in a very short time with the help of this information spreading platform of microblogs. In these "super spreading events", messages are transmitted to a vast range of individuals through a small portion of users...
The epidemiology of X-linked recessive diseases, a class of genetic disorders, has been modeled through a discrete time, structured, non linear mathematical system. The model version presented in this paper completely captures the disease epidemiology as it includes the spread of affected women within a population that has not been considered in other works. Moreover the model allows for de novo mutations...
Computational epidemiology employs computer models and informatics tools to reason about the spatio-temporal spread of diseases. The diversity of models, data sources, data representations, and modalities that are collected, used, and modified motivate the development of a digital library (DL) framework to support computational epidemiology. The heterogeneous content includes metadata, text, tables,...
The study of epidemic's propagation in cities has become a crucial problem because of the importance of population mobility and promoting rapid contagion between individuals. The authorities of contaminated cities have not, in general, a more or less clear understanding of the evolution of the disease in order to take suitable decisions to fight efficiently against the epidemic. This paper presents...
Extracting interesting and useful patterns from spatio-temporal datasets is more difficult than extracting the corresponding patterns from traditional numeric and categorical data due to the complexity of spatial data types and the embedded topologies, spatial and temporal relationships, and spatial autocorrelation. The objective of epidemiology is to identify disease causes and correlating them to...
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