Improving Communication in E-democracy Using Natural Language Processing

E-democracy, the design and development of new techniques for improving communication between public administration and citizens, is a major application field for natural language processing and language engineering. Helping citizens access information in a friendly, intuitive way is the primary objective of a global e-democracy framework. The E-democracy European Network project (EDEN) aimed at discovering whether a particular NLP (natural language processing) approach could further e-democracy by increasing citizens' participation in the decision-making process. The goal was twofold: to test whether e-democracy requirements could be meet using advanced linguistic technology and to test whether augmented phrase structure grammars (APSGs) were robust and well-assessed enough to use in a real-world environment. Also, the aim is to develop two toolsets to improve communication between PAs and citizens in the context of urban planning: a set of NLP-based tools to simplify access to information and knowledge and a set of forum and polling devices     

On the impact of physical layer awareness on scheduling and resource allocation in broadband multicellular IEEE 802.16 systems [Radio Resource Management and Protocol Engineering for IEEE 802.16]

Multicellular networks based on the IEEE 802.16 standard appear to be very promising candidates to provide end users with broadband wireless access. However, they also pose interesting challenges in terms of radio resource management, where several design choices are not specified in the standard, intentionally left open to implementors. For this reason, we focus in this article on scheduling and resource allocation, and investigate how they could operate in a cross-layer fashion. In particular, we describe the principles of joint scheduling and resource allocation for IEEE 802.16 operating in AMC mode, and discuss the critical role played by physical layer considerations, especially intercell interference estimation and channel state awareness, in the obtained performance. This leads to identifying key open issues and possible general solutions     

Large deflections and stability FEM analysis of shear deformable compressed anisotropic flat panels

This paper deals with the non-linear analysis of multilayered axially compressed plates in the static elastic conservative cases. A finite element model based on a Reissner-Mindlin theory involving von Kármán nonlinearity is developed. Results related to the classical Kirchhoff plate approximations are obtained via application of a penalty technique to the shear correction factor. The numerical investigations have concerned the large deflections and postbuckling behaviour of symmetrically and non-symmetrically anisotropic flat panels. The main conclusions are: (1) the non-linear effects very much depend on lay-up and boundary conditions, moreover for the asymmetric laminated long plates the snapping-type instability occurs; (2) the shear deformation effects are very much subordinate to both multilayered lay-up and load levels, furthermore they are greater in the large deflections field; (3) it has been observed that in the neighbourhood of a singularity (of buckling point type) of the tangent stiffness matrix, the use of an arc-length type algorithm could lead to a new buckled path and that happens without employing an appropriate turning bifurcation algorithm with an accompanying eigenvalues calculation, but via a non-convergent iteration in the loadstep.     

When more is less: A counterintuitive effect of distractor frequency in the picture-word interference paradigm.

Pictures were shown with superimposed word distractors of high and low frequency. Low-frequency distractors produced greater interference on picture naming than did high-frequency distractors. This distractor frequency effect was not affected by manipulations that facilitated or hindered distractor recognition. Interference was reduced for distractors that were read aloud several times prior to being shown in the picture-naming task. Together these findings suggest that the distractor frequency effect has its locus at some stage of lexical access for production. Other findings further constrain hypotheses about which level of speech production is involved in the effect. The distractor frequency effect has implications for models of lexical processing in speaking as well as for accounts of picture-word interference and the frequency effect. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

SESF-Fuse: an unsupervised deep model for multi-focus image fusion

Neural Computing and Applications - Muti-focus image fusion is the extraction of focused regions from different images to create one all-in-focus fused image. The key point is that only objects...     

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes.     

Who and what links to the Internet Archive

The Internet Archive’s (IA) Wayback Machine is the largest and oldest public Web archive and has become a significant repository of our recent history and cultural heritage. Despite its importance, there has been little research about how it is discovered and used. Based on Web access logs, we analyze what users are looking for, why they come to IA, where they come from, and how pages link to IA. We find that users request English pages the most, followed by the European languages. Most human users come to Web archives because they do not find the requested pages on the live Web. About 65 % of the requested archived pages no longer exist on the live Web. We find that more than 82 % of human sessions connect to the Wayback Machine via referrals from other Web sites, while only 15 % of robots have referrers. Most of the links (86 %) from Websites are to individual archived pages at specific points in time, and of those 83 % no longer exist on the live Web. Finally, we find that users who come from search engines browse more pages than users who come from external Web sites.     

Preface

Annals of Mathematics and Artificial Intelligence -     

A lagrangian propagator for artificial neural networks in constraint programming

This paper discusses a new method to perform propagation over a (two-layer, feed-forward) Neural Network embedded in a Constraint Programming model. The method is meant to be employed in Empirical Model Learning, a technique designed to enable optimal decision making over systems that cannot be modeled via conventional declarative means. The key step in Empirical Model Learning is to embed a Machine Learning model into a combinatorial model. It has been showed that Neural Networks can be embedded in a Constraint Programming model by simply encoding each neuron as a global constraint, which is then propagated individually. Unfortunately, this decomposition approach may lead to weak bounds. To overcome such limitation, we propose a new network-level propagator based on a non-linear Lagrangian relaxation that is solved with a subgradient algorithm. The method proved capable of dramatically reducing the search tree size on a thermal-aware dispatching problem on multicore CPUs. The overhead for optimizing the Lagrangian multipliers is kept within a reasonable level via a few simple techniques. This paper is an extended version of [27], featuring an improved structure, a new filtering technique for the network inputs, a set of overhead reduction techniques, and a thorough experimentation.     

Contention-based forwarding with multi-hop connectivity awareness in vehicular ad-hoc networks

Recent vehicular routing proposals use real-time road traffic density estimates to dynamically select forwarding paths. Estimating the traffic density in vehicular ad hoc networks requires the transmission of additional dedicated messages increasing the communications load. These proposals are generally based on unicast sender-based forwarding schemes. The greedy nature of sender-based forwarding can result in the selection of forwarders with weak radio links that might compromise the end-to-end performance. To overcome these limitations, this paper presents TOPOCBF, a novel contention-based broadcast forwarding protocol that dynamically selects forwarding paths based on their capability to route packets between anchor points. Such capability is estimated by means of a multi-hop connectivity metric. The obtained results demonstrate that TOPOCBF can provide good packet delivery ratios while reducing the communications load compared to unicast sender-based forwarding schemes using road traffic density estimates.