We present new distributed deterministic solutions to two communication problems in n-node ad-hoc radio networks: rumor gathering and multi-broadcast. In these problems, some or all nodes of the network initially contain input data called rumors, which have to be learned by other nodes. In rumor gathering, there are k rumors initially distributed arbitrarily among the nodes, and the goal is to ...

Here we propose a registration process for population genetic isolates, usually geographic clusters of genetic disorders, based on the systematic search of rumors, defined as any type of account regardless of its reliability. Systematically ascertained rumors are recorded, and validated through a progressive process of pre-established steps. This paper outlines the conceptual basis for this app...

We describe recent research into using the visual primitive of texture to analyze and manage large collections of remote sensed image and video data. Texture is regarded as the spatial dependence of pixel intensity. It is characterized by the amount of dependence at different scales and orientations, as measured with frequency-selective filters. A homogeneous texture descriptor based on the fil...

Rumors or information can spread quickly and reach many users in social networks. Models for understanding, preventing or increasing the diffusion of information are of greatest interest to companies, governments, scientists, etc. In this paper, we propose an approach for maximizing the information diffusion by selecting the most important (central) users from communities. We also analyze the s...

We present a multiagent organization for data interpretation and fusion in which each agent uses an encapsulated Bayesian network for knowledge representation, and agents communicate by exchanging beliefs (marginal posterior probabilities) on shared variables. We call this organization an Agent-Encapsulated Bayesian Network (AEBN) system. Communication of probabilities among agents leads to rum...

How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we address in this work. Our goal is to build a model that generates realistic cascades, so that it can help us with link prediction and outlier detection. Blogs (weblogs) have become an important medium of information bec...