High resolution dynamical mapping of social interactions with active RFID

In this paper we present an experimental framework to gather data on face-to-face social interactions between individuals, with a high spatial and temporal resolution. We use active Radio Frequency Identification (RFID) devices that assess contacts with one another by exchanging low-power radio packets. When individuals wear the beacons as a badge, a persistent radio contact between the RFID devices can be used as a proxy for a social interaction between individuals. We present the results of a pilot study recently performed during a conference, and a subsequent preliminary data analysis, that provides an assessment of our method and highlights its versatility and applicability in many areas concerned with human dynamics

MLP: a MATLAB toolbox for rapid and reliable auditory threshold estimation

In this paper, we present MLP, a MATLAB toolbox enabling auditory thresholds estimation via the adaptive Maximum Likelihood procedure proposed by David Green (1990, 1993). This adaptive procedure is particularly appealing for those psychologists that need to estimate thresholds with a good degree of accuracy and in a short time. Together with a description of the toolbox, the current text provides an introduction to the threshold estimation theory and a theoretical explanation of the maximum likelihood adaptive procedure. MLP comes with a graphical interface and it is provided with several built-in, classic psychoacoustics experiments ready to use at a mouse click

Relaxed 2-D Principal Component Analysis by LpL_p Norm for Face Recognition

A relaxed two dimensional principal component analysis (R2DPCA) approach is proposed for face recognition. Different to the 2DPCA, 2DPCA-$L_1$ and G2DPCA, the R2DPCA utilizes the label information (if known) of training samples to calculate a relaxation vector and presents a weight to each subset of training data. A new relaxed scatter matrix is defined and the computed projection axes are able to increase the accuracy of face recognition. The optimal $L_p$-norms are selected in a reasonable range. Numerical experiments on practical face databased indicate that the R2DPCA has high generalization ability and can achieve a higher recognition rate than state-of-the-art methods.Comment: 19 pages, 11 figure

The uniting of Europe and the foundation of EU studies: revisiting the neofunctionalism of Ernst B. Haas

This article suggests that the neofunctionalist theoretical legacy left by Ernst B. Haas is somewhat richer and more prescient than many contemporary discussants allow. The article develops an argument for routine and detailed re-reading of the corpus of neofunctionalist work (and that of Haas in particular), not only to disabuse contemporary students and scholars of the normally static and stylized reading that discussion of the theory provokes, but also to suggest that the conceptual repertoire of neofunctionalism is able to speak directly to current EU studies and comparative regionalism. Neofunctionalism is situated in its social scientific context before the theory's supposed erroneous reliance on the concept of 'spillover' is discussed critically. A case is then made for viewing Haas's neofunctionalism as a dynamic theory that not only corresponded to established social scientific norms, but did so in ways that were consistent with disciplinary openness and pluralism

Sociomateriality Implications of Software As a Service Adoption on IT-workers’ Roles and Changes in Organizational Routines of IT Systems Support

This paper aims to deepen our understanding on how sociomateriality practices influence IT workers’ roles and skill set requirements and changes to the organizational routines of IT systems support, when an organization migrates an on-premise IT system to a software as a service (SaaS) model. This conceptual paper is part of an ongoing study investigating organizations that migrated on-premise IT email systems to SaaS business models, such as Google Apps for Education (GAE) and Microsoft Office 365 systems, in New Zealand tertiary institutions. We present initial findings from interpretive case studies. The findings are, firstly, technological artifacts are entangled in sociomaterial practices, which change the way humans respond to the performative aspects of the organizational routines. Human and material agencies are interwoven in ways that reinforce or change existing routines. Secondly, materiality, virtual realm and spirit of the technology provide elementary levels at which human and material agencies entangle. Lastly, the elementary levels at which human and material entangle depends on the capabilities or skills set of an individual

Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

The spread of infectious diseases crucially depends on the pattern of contacts among individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. Few empirical studies are however available that provide estimates of the number and duration of contacts among social groups. Moreover, their space and time resolution are limited, so that data is not explicit at the person-to-person level, and the dynamical aspect of the contacts is disregarded. Here, we want to assess the role of data-driven dynamic contact patterns among individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population. We consider high resolution data of face-to-face interactions between the attendees of a conference, obtained from the deployment of an infrastructure based on Radio Frequency Identification (RFID) devices that assess mutual face-to-face proximity. The spread of epidemics along these interactions is simulated through an SEIR model, using both the dynamical network of contacts defined by the collected data, and two aggregated versions of such network, in order to assess the role of the data temporal aspects. We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation which retains only the topology of the contact network fails in reproducing the size of the epidemic. These results have important implications in understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics

Bag-of-Colors for Biomedical Document Image Classification

The number of biomedical publications has increased noticeably in the last 30 years. Clinicians and medical researchers regularly have unmet information needs but require more time for searching than is usually available to find publications relevant to a clinical situation. The techniques described in this article are used to classify images from the biomedical open access literature into categories, which can potentially reduce the search time. Only the visual information of the images is used to classify images based on a benchmark database of ImageCLEF 2011 created for the task of image classification and image retrieval. We evaluate particularly the importance of color in addition to the frequently used texture and grey level features. Results show that bags–of–colors in combination with the Scale Invariant Feature Transform (SIFT) provide an image representation allowing to improve the classification quality. Accuracy improved from 69.75% of the best system in ImageCLEF 2011 using visual information, only, to 72.5% of the system described in this paper. The results highlight the importance of color for the classification of biomedical images