Twitter, Facebook and Ten Red Balloons: Social Network Problem Solving and Homeland Security
The winner of the Center for Homeland Defense and Security (CHDS) Essay Contest in 2010, this essay looks at how homeland security could benefit from crowd-sourced applications accessed through social networking tools such as Twitter and Facebook. Christopher M. Ford looks at the apparent efficacy of two such endeavors: the Defense Advanced Research Projects Agency’s (DARPA) competition to find ten 8-foot balloons moored across the continental U.S. and Wired Magazine challenge to “find” author Evan Ratliff. Based on these and other crowd-sourced applications, Ford suggests that the U.S. government could utilize the internet and social networking sites to potentially solve an array of discrete problems through the active participation of interested citizens.
The Whodunit Challenge: Mobilizing the Crowd in India
While there has been a surge of interest in mobilizing the crowd to solve large-scale time-critical challenges, to date such work has focused on high-income countries and Internet-based solutions. In developing countries, approaches for crowd mobilization are often broader and more diverse, utilizing not only the Internet but also face-to-face and mobile communications. In this paper, we describe the Whodunit Challenge, the first social mobilization contest to be launched in India. The contest enabled participation via basic mobile phones and required rapid formation of large teams in order to solve a fictional mystery case. The challenge encompassed 7,700 participants in a single day and was won by a university team in about 5 h. To understand teams’ strategies and experiences, we conducted 84 phone interviews. While the Internet was an important tool for most teams, in contrast to prior challenges we also found heavy reliance on personal networks and offline communication channels. We synthesize these findings and offer recommendations for future crowd mobilization challenges targeting low-income environments in developing countries.
Applying particle swarm optimization algorithm to roundness error evaluation based on minimum zone circle
Abstract Minimum zone circle (MZC) method and least square circle (LSC) method are two most commonly used methods to evaluate roundness, but only the MZC method complies with the standard definition and can obtain the minimum roundness error value. The determination of the center of MZC is a nonlinear optimization problem which is suitable to be solved by particle swarm optimization (PSO) algorithms. In this paper, the standard PSO algorithm was introduced and theory analysis about the impact of value selection of some important parameters, such as inertia weight ω , on the algorithm’s stability and convergence was carried on so as to provide basis for giving these parameters better values. Furthermore, the superiority of making ω decrease linearly with iterations was verified through a computation experiment in terms of stability and accuracy, compared with the other three cases of ω  = 1, 0.5, 0. Based on the analysis, the novel PSO algorithm, with ω decreasing linearly from 0.9 to 0.4 and the LSC center as the initial positions of the particles, is implemented to obtain MZC-based roundness errors of sampling points collected from circular section profiles by a coordinate measuring machine (CMM). By comparing the novel PSO–MZC results with the LSC-based results, it is concluded that the former are a little smaller than the latter, which verifies that the novel PSO algorithm is feasible to calculate roundness error and the fact that a LSC-based one is generally larger than a MZC-based result; the values of the two roundness errors are both related to sample size and increase with an increase in the sample size with a decreasing increment.