Event-triggered Learning

The efficient exchange of information is an essential aspect of intelligent collective behavior. Event-triggered control and estimation achieve some efficiency by replacing continuous data exchange between agents with intermittent, or event-triggered communication. Typically, model-based predictions are used at times of no data transmission, and updates are sent only when the prediction error grows too large. The effectiveness in reducing communication thus strongly depends on the quality of the prediction model. In this article, we propose event-triggered learning as a novel concept to reduce communication even further and to also adapt to changing dynamics. By monitoring the actual communication rate and comparing it to the one that is induced by the model, we detect a mismatch between model and reality and trigger model learning when needed. Specifically, for linear Gaussian dynamics, we derive different classes of learning triggers solely based on a statistical analysis of inter-communication times and formally prove their effectiveness with the aid of concentration inequalities

E-democracy as the frame of networked public discourse : information, consensus and complexity

The quest for democracy and the political reflection about its future are to be understood nowadays in the horizon of the networked information revolution. Hence, it seems difficult to speak of democracy without speaking of e-democracy, the key issue of which is the re-configuration of models of information production and concentration of attention, which are to be investigated both from a political and an epistemological standpoint. In this perspective, our paper aims at analyzing the multi-agent dimension of networked public discourse, by envisaging two competing models of structuring this discourse (those of dialogue and of claim) and by suggesting to endorse the epistemic idea of complementarity as a guidance principle for elaborating a form of partnership between traditional and electronic media

Null Models of Economic Networks: The Case of the World Trade Web

In all empirical-network studies, the observed properties of economic networks are informative only if compared with a well-defined null model that can quantitatively predict the behavior of such properties in constrained graphs. However, predictions of the available null-model methods can be derived analytically only under assumptions (e.g., sparseness of the network) that are unrealistic for most economic networks like the World Trade Web (WTW). In this paper we study the evolution of the WTW using a recently-proposed family of null network models. The method allows to analytically obtain the expected value of any network statistic across the ensemble of networks that preserve on average some local properties, and are otherwise fully random. We compare expected and observed properties of the WTW in the period 1950-2000, when either the expected number of trade partners or total country trade is kept fixed and equal to observed quantities. We show that, in the binary WTW, node-degree sequences are sufficient to explain higher-order network properties such as disassortativity and clustering-degree correlation, especially in the last part of the sample. Conversely, in the weighted WTW, the observed sequence of total country imports and exports are not sufficient to predict higher-order patterns of the WTW. We discuss some important implications of these findings for international-trade models.Comment: 39 pages, 46 figures, 2 table

Access and usability issues of scholarly electronic publications

This chapter looks at the various access and usability issues related to scholarly information resources. It first looks at the various channels through which a user can get access to scholarly electronic publications. It then discusses the issues and studies surrounding usability. Some important parameters for measuring the usability of information access systems have been identified. Finally the chapter looks at the major problems facing the users in getting access to scholarly information through today's hybrid libraries, and mentions some possible measures to resolve these problems

Adaptive Sampling with Mobile Sensor Networks

Mobile sensor networks have unique advantages compared with wireless sensor networks. The mobility enables mobile sensors to flexibly reconfigure themselves to meet sensing requirements. In this dissertation, an adaptive sampling method for mobile sensor networks is presented. Based on the consideration of sensing resource constraints, computing abilities, and onboard energy limitations, the adaptive sampling method follows a down sampling scheme, which could reduce the total number of measurements, and lower sampling cost. Compressive sensing is a recently developed down sampling method, using a small number of randomly distributed measurements for signal reconstruction. However, original signals cannot be reconstructed using condensed measurements, as addressed by Shannon Sampling Theory. Measurements have to be processed under a sparse domain, and convex optimization methods should be applied to reconstruct original signals. Restricted isometry property would guarantee signals can be recovered with little information loss. While compressive sensing could effectively lower sampling cost, signal reconstruction is still a great research challenge. Compressive sensing always collects random measurements, whose information amount cannot be determined in prior. If each measurement is optimized as the most informative measurement, the reconstruction performance can perform much better. Based on the above consideration, this dissertation is focusing on an adaptive sampling approach, which could find the most informative measurements in unknown environments and reconstruct original signals. With mobile sensors, measurements are collect sequentially, giving the chance to uniquely optimize each of them. When mobile sensors are about to collect a new measurement from the surrounding environments, existing information is shared among networked sensors so that each sensor would have a global view of the entire environment. Shared information is analyzed under Haar Wavelet domain, under which most nature signals appear sparse, to infer a model of the environments. The most informative measurements can be determined by optimizing model parameters. As a result, all the measurements collected by the mobile sensor network are the most informative measurements given existing information, and a perfect reconstruction would be expected. To present the adaptive sampling method, a series of research issues will be addressed, including measurement evaluation and collection, mobile network establishment, data fusion, sensor motion, signal reconstruction, etc. Two dimensional scalar field will be reconstructed using the method proposed. Both single mobile sensors and mobile sensor networks will be deployed in the environment, and reconstruction performance of both will be compared.In addition, a particular mobile sensor, a quadrotor UAV is developed, so that the adaptive sampling method can be used in three dimensional scenarios

11 11 remembered

I wanted to look at the next step from “experience captured” (Sontag, 1977) to the online art forms about ‘experience shared’ and therefore networked in our participatory culture, which conceptually inspired project two. My work will be experimental so that I can explore sharing (and communicating with) images and possibly audio on a particular subject or theme. My assertion is that we are innate communicators with a natural desire to connect with others. It has been customary for us to communicate and connect since ancient times – from drawings carved out in caves to tales told around communal fires and from Plato’s shadow-playing to religious preaching. We have always communicated/connected throughout history by reading books, listening to the radio and watching the television. Now we are embedded in the World Wide Web ‘public sphere’ where images have become a part of our sharing culture. Thus photo essays and photo sharing are other mediums to communicate and connect. Civic engagement to connect has shifted into a shared online socio, economic, cultural and political space. Historically we have developed from a local geographical community into the ‘digital commons’ - a global landscape of web 2.0 digital media (Merrin, 2008). My project plan is to research and evidence to inform my mobile phone capture idea. I wanted to understand mo-blogging and the method of producing a photo essay. According to an online photography and social media organisation creating a photo essay is an art form as well as journalistically communicating a message

Ignorance and political representation in the net : on public Infosphere and the Spanish 'indignants' movement

The aim of this paper is to explore the case of the Spanish ‘indignants’ movement of May 2011 as an example of the structural changes occurring in the public sphere after the emergence of a new type of social movement characterized by the widespread use of the ICTs. First I focus on the ideological dimension of discourse of the ‘indignants’ movement, so as to reconstruct the protesters’ self-image. They thought that ICTs were playing a prominent role in a wider trend towards a regeneration of democracy, but they were rather misguided because they lack an accurate description of what really happened. In the second part of this paper I will challenge some features of my case study, emphasizing three basic elements of a democratic public sphere. I aim to call into question the idea that a ‘truly’ democratic public may be hosted by the emergent communicative environment