This article reviews significant advances in networked signal and information processing (SIP), which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments ...
Author summary In nature, many organisms grow in crowded biofilms that protect against stressful conditions, making their control/eradication a challenge. Modeling these microbial systems is a valuable tool for studying the interactions among cells and exp ...
This dissertation focuses on collective forms or organizing that through crowds or communities undertake production or innovation activities. Such organizations deviate from the traditional notions of hierarchy, authority, and control; however, they are st ...
Crowding refers to the detrimental effect of nearby elements on target perception. Recently, Harrison and Bex (Curr Biol, 2015) modeled performance in a novel orientation crowding paradigm where observers reported the orientation of a Landolt C presented a ...
Machine learning applications can benefit greatly from vast amounts of data, provided that reliable labels are available. Mobilizing crowds to annotate the unlabeled data is a common solution. Although the labels provided by the crowd are subjective and no ...
In this paper, we introduce a simple Monte Carlo method for simulating the dynamics of a crowd. Within our model a collection of hard-disk agents is subjected to a series of two-stage steps, implying (i) the displacement of one specific agent followed by ( ...
Simulating crowds in real time is a challenging problem that touches many different aspects of Computer Graphics: rendering, animation, path planning, behavior, etc. Our work has mainly focused on two particular aspects of real-time crowds: motion planning ...
