Automatic best wireless network selection based on key performance indicators

Introducing cognitive mechanisms at the application layer may lead to the possibility of an automatic selection of the wireless network that can guarantee best perceived experience by the final user. This chapter investigates this approach based on the concept of Quality of Experience (QoE), by introducing the use of application layer parameters, namely Key Performance Indicators (KPIs). KPIs are defined for different traffic types based on experimental data. A model for an ap- plication layer cognitive engine is presented, whose goal is to identify and select, based on KPIs, the best wireless network among available ones. An experimenta- tion for the VoIP case, that foresees the use of the One-way end-to-end delay (OED) and the Mean Opinion Score (MOS) as KPIs is presented. This first implementation of the cognitive engine selects the network that, in that specific instant, offers the best QoE based on real captured data. To our knowledge, this is the first example of a cognitive engine that achieves best QoE in a context of heterogeneous wireless networks

On the need for multi-dimensional models for the safety analysis of (fast-spectrum) Molten Salt Reactors

This paper aims at characterizing the impact of adopting numerical models with different dimensionalities on the predicted behavior of fast-spectrum Molten Salt Reactors (MSRs). The study encompasses 1-D, 2-D, and 3-D representations of thermal-hydraulics and precursor transport/diffusion, along with spatial and point kinetics models for neutronics. We evaluate the accuracy of each model based on steady-state results and on the reactor response to 2 different transient initiators. The findings emphasize the significance of utilizing a 3-D representation with accurate thermal-hydraulics modeling, and with either spatial kinetics or carefully calibrated point kinetics incorporating a spatial description of precursors transport. 2-D and 1-D models can reproduce main trends and remain valuable tools for e.g. reactor design, control-oriented studies or uncertainty quantification. However, proper calibration of these models is needed and the user should be aware that alterations in flow patterns could jeopardize model calibration and hide first-order local effects

How Polarized Have We Become? A Multimodal Classification of Trump Followers and Clinton Followers

Polarization in American politics has been extensively documented and analyzed for decades, and the phenomenon became all the more apparent during the 2016 presidential election, where Trump and Clinton depicted two radically different pictures of America. Inspired by this gaping polarization and the extensive utilization of Twitter during the 2016 presidential campaign, in this paper we take the first step in measuring polarization in social media and we attempt to predict individuals' Twitter following behavior through analyzing ones' everyday tweets, profile images and posted pictures. As such, we treat polarization as a classification problem and study to what extent Trump followers and Clinton followers on Twitter can be distinguished, which in turn serves as a metric of polarization in general. We apply LSTM to processing tweet features and we extract visual features using the VGG neural network. Integrating these two sets of features boosts the overall performance. We are able to achieve an accuracy of 69%, suggesting that the high degree of polarization recorded in the literature has started to manifest itself in social media as well.Comment: 16 pages, SocInfo 2017, 9th International Conference on Social Informatic

The education crisis : business and government's role in reform

Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management, 1989.Includes bibliographical references (leaves 157-159).by Carleton S. Fiorina.M.S

A term-by-term direct numerical simulation validation study of the multi-environment conditional probability-density-function model for turbulent reacting flows

The multi-environment conditional probability-density-function (MECPDF) approach for modeling extinction and re-ignition in turbulent nonpremixed reacting flows in analyzed. A unique derivation of the model is given, which makes use of numerical Gaussian quadrature in addition to physical assumptions. The new derivation offers insight into the physical meaning of model terms and offers a more rigorous method for model validation. The assumptions required to close the dissipation terms are validated term by term using data from direct numerical simulations of an inert and a reacting scalar in decaying isotropic turbulence. Results show convergence of the numerical quadrature with an increasing number of quadrature points. Also, good agreement is shown for the physical model assumptions required to close the mixed dissipation and the progress-variable dissipation terms. The MECPDF methods is also demonstrated to offer the flexibility to incorporate either micromixing or otherwise more sophisticated models for the mixing between regions of the flow that exhibit differing degrees of extinction

Channeler Ant Model: 3D segmentation of medical images through ant colonies

In this paper the Channeler Ant Model (CAM) and some results of its applications to the analysis of medical images are described. The CAM is an algorithm able to segment 3D structures with different shapes, intensity and background. It makes use of virtual ant colonies and exploits their natural capabilities to modify the environment and communicate with each other by pheromone deposition. Its performance has been validated with the segmentation of 3D artificial objects and it has been already used successfully in lung nodules detection on Computer Tomography images. This work tries to evaluate the CAM as a candidate to solve the quantitative segmentation problem in Magnetic Resonance brain images: to evaluate the percentage of white matter, gray matter and cerebrospinal fluid in each voxel

Analyzing Ideological Communities in Congressional Voting Networks

We here study the behavior of political party members aiming at identifying how ideological communities are created and evolve over time in diverse (fragmented and non-fragmented) party systems. Using public voting data of both Brazil and the US, we propose a methodology to identify and characterize ideological communities, their member polarization, and how such communities evolve over time, covering a 15-year period. Our results reveal very distinct patterns across the two case studies, in terms of both structural and dynamic properties

Presidential Influence on Parliamentary Election Timing and the Electoral Fate of Prime Ministers

Most presidential heads of state in parliamentary and semi-presidential democracies have constitutional powers to influence early election calling. They can therefore affect under which conditions prime ministers are held accountable by the electorate. Do these presidents use their powers to shape the timing of early elections for partisan advantage and to influence the electoral performance of incumbent prime ministers? We examine this question using data from 193 elections in eighteen European democracies (1945-2013). Our results indicate that presidents use their dissolution powers to shape the frequency of early elections and to influence under which conditions elections occur, affecting the electoral success of prime ministers. Presidents with significant influence on the dissolution of parliament enable prime ministers of governments that include the president's party to realize a significant electoral bonus compared to governments that exclude the party of the president

It is Hobbes, not Rousseau:an experiment on voting and redistribution

We perform an experiment which provides a laboratory replica of some important features of the welfare state. In the experiment, all individuals in a group decide whether to make a costly effort, which produces a random (independent) outcome for each one of them. The group members then vote on whether to redistribute the resulting and commonly known total sum of earnings equally amongst themselves. This game has two equilibria, if played once. In one of them, all players make effort and there is little redistribution. In the other one, there is no effort and nothingWe thank Iris Bohnet, Tim Cason, David Cooper, John Duffy, Maia Guell, John Van Huyck and Robin Mason for helpful conversations and encouragement. The comments of the Editor and two referees helped improve the paper. We gratefully acknowledge the financial support from Spain’s Ministry of Science and Innovation under grants CONSOLIDER INGENIO 2010 CSD2006-0016 (all authors), ECO2009-10531 (Cabrales), ECO2008-01768 (Nagel) and the Comunidad de Madrid under grant Excelecon (Cabrales), the Generalitat de Catalunya and the CREA program (Nagel), and project SEJ2007-64340 of Spain’s Ministerio de Educación y Ciencia (Rodríguez Mora).Publicad

Evaluation of polyneuropathy markers in type 1 diabetic kidney transplant patients and effects of islet transplantation: Neurophysiological and skin biopsy longitudinal analysis

OBJECTIVE - The purpose of this study was to evaluate whether islet transplantation may stabilize polyneuropathy in uremic type 1 diabetic patients (end-stage renal disease [ESRD] and type 1 diabetes), who received a successful islet-after-kidney transplantation (KI-s). RESEARCH DESIGN AND METHODS - Eighteen KI-s patients underwent electroneurographic tests of sural, peroneal, ulnar, and median nerves: the nerve conduction velocity (NCV) index and amplitudes of both sensory action potentials (SAPs) and compound motor action potentials (CMAPs) were analyzed longitudinally at 2, 4, and 6 years after islet transplantation. Skin content of advanced glycation end products (AGEs) and expression of their specific receptors (RAGE) were also studied at the 4-year follow-up. Nine patients with ESRD and type 1 diabetes who received kidney transplantation alone (KD) served as control subjects. RESULTS - The NCV score improved in the KI-s group up to the 4-year time point (P = 0.01 versus baseline) and stabilized 2 years later, whereas the same parameter did not change significantly in the KD group throughout the follow-up period or when a cross-sectional analysis between groups was performed. Either SAP or CMAP amplitudes recovered in the KI-s group, whereas they continued worsening in KD control subjects. AGE and RAGE levels in perineurium and vasa nervorum of skin biopsies were lower in the KI-s than in the KD group (P < 0.01 for RAGE). CONCLUSIONS - Islet transplantation seems to prevent long-term worsening of polyneuropathy in patients with ESRD and type 1 diabetes who receive islets after kidney transplantation. No statistical differences between the two groups were evident on cross-sectional analysis. A reduction in AGE/RAGE expression in the peripheral nervous system was shown in patients receiving islet transplantation. © 2007 by the American Diabetes Association