Privacy policies for shared content in social network sites

Social networking is one of the major technological phenomena of the Web 2.0, with hundreds of millions of subscribed users. Social networks enable a form of self-expression for users and help them to socialize and share content with other users. In spite of the fact that content sharing represents one of the prominent features of existing Social network sites, they do not provide any mechanisms for collective management of privacy settings for shared content. In this paper, using game theory, we model the problem of collective enforcement of privacy policies on shared data. In particular, we propose a solution that offers automated ways to share images based on an extended notion of content ownership. Building upon the Clarke-Tax mechanism, we describe a simple mechanism that promotes truthfulness and that rewards users who promote co-ownership. Our approach enables social network users to compose friendship based policies based on distances from an agreed upon central user selected using several social networks metrics. We integrate our design with inference techniques that free the users from the burden of manually selecting privacy preferences for each picture. To the best of our knowledge, this is the first time such a privacy protection mechanism for social networking has been proposed. We also extend our mechanism so as to support collective enforcement across multiple social network sites. In the paper, we also show a proof-of-concept application, which we implemented in the context of Facebook, one of today’s most popular social networks. Through our implementation, we show the feasibility of such approach and show that it can be implemented with a minimal increase in overhead to end-users. We complete our analysis by conducting a user study to investigate users’ understanding of co-ownership, usefulness and understanding of our approach. Users responded favorably to the approach, indicating a general understanding of co-ownership and the auction, and found the approach to be both useful and fair.     

Gremlin: an interactive visualization model for analyzing genomic rearrangements

In this work we present, apply, and evaluate a novel, interactive visualization model for comparative analysis of structural variants and rearrangements in human and cancer genomes, with emphasis on data integration and uncertainty visualization. To support both global trend analysis and local feature detection, this model enables explorations continuously scaled from the high-level, complete genome perspective, down to the low-level, structural rearrangement view, while preserving global context at all times. We have implemented these techniques in Gremlin, a genomic rearrangement explorer with multi-scale, linked interactions, which we apply to four human cancer genome data sets for evaluation. Using an insight-based evaluation methodology, we compare Gremlin to Circos, the state-of-the-art in genomic rearrangement visualization, through a small user study with computational biologists working in rearrangement analysis. Results from user study evaluations demonstrate that this visualization model enables more total insights, more insights per minute, and more complex insights than the current state-of-the-art for visual analysis and exploration of genome rearrangements.     

Fuzzy induced generalized aggregation operators and its application in multi-person decision making

We present a wide range of fuzzy induced generalized aggregation operators such as the fuzzy induced generalized ordered weighted averaging (FIGOWA) and the fuzzy induced quasi-arithmetic OWA (Quasi-FIOWA) operator. They are aggregation operators that use the main characteristics of the fuzzy OWA (FOWA) operator, the induced OWA (IOWA) operator and the generalized (or quasi-arithmetic) OWA operator. Therefore, they use uncertain information represented in the form of fuzzy numbers, generalized (or quasi-arithmetic) means and order inducing variables. The main advantage of these operators is that they include a wide range of mean operators such as the FOWA, the IOWA, the induced Quasi-OWA, the fuzzy IOWA, the fuzzy generalized mean and the fuzzy weighted quasi-arithmetic average (Quasi-FWA). We further generalize this approach by using Choquet integrals, obtaining the fuzzy induced quasi-arithmetic Choquet integral aggregation (Quasi-FICIA) operator. We also develop an application of the new approach in a strategic multi-person decision making problem.     

Strategies for collaborative writing and phases of knowledge construction in CSCL environments

Within the framework of research that describes the processes of collaborative knowledge construction in computer-supported collaborative learning (CSCL) environments, the present work has three objectives: (i) the identification of the strategies of six small groups of university students for the elaboration of written products in a CSCL environment; (ii) seek relations between the identified writing strategies and the processes and phases of collaborative knowledge construction in the groups; and (iii) relate these strategies and phases with the learning results obtained by the groups. We carried out a multiple-case study, with the analysis of four different didactic sequences, in two different virtual learning and teaching settings. In each setting, three student groups were studied, where each had to collaboratively develop between four and eight written products. For all the studied groups, the analysis enabled the identification of five types of strategies in the preparation of the elaboration of written products, and four types of phases of collaborative knowledge construction, which are interrelated and also connected with the grades that the groups obtained in each case.     

On the convective nature of the instability of a front undergoing a supercritical Turing bifurcation

Fronts are traveling waves in spatially extended systems that connect two different spatially homogeneous rest states. If the rest state behind the front undergoes a supercritical Turing instability, then the front will also destabilize. On the linear level, however, the front will be only convectively unstable since perturbations will be pushed away from the front as it propagates. In other words, perturbations may grow but they can do so only behind the front. It is of interest to show that this behavior carries over to the full nonlinear system. It has been successfully done in a case study by Ghazaryan and Sandstede [A. Ghazaryan, B. Sandstede, Nonlinear convective instability of Turing-unstable fronts near onset: a case study, SIAM J. Appl. Dyn. Syst. 6 (2007) 319–347]. In the present paper, analogous results are obtained for the same system as in Ghazaryan and Sandstede (2007), but for a different parameter regime.     

Interaction of Langmuir–Blodgett and spin-coated films of μ-carbido-bridged ironphthalocyanine with NO2: Optical and conductimetric behaviour

The present study investigates the interaction of NO₂ gas and μ-carbido-bridged iron phthalocyanine (PcFeCFePc) films obtained by Langmuir–Blodgett (LB) and spin-coating (SC) techniques. The phthalocyanine bridged dimer under study belongs to the polynuclear unsubstituted phthalocyanines class and presents poor solubility: in contrast the corresponding N-base bis-adducts are soluble enough in organic solvents to be deposited by Langmuir–Blodgett and spin-coating techniques. The reaction with NO₂ is monitored by visible spectra variation that shows identical behaviour for both kinds of films, indicating that the chemical reaction between the gas and the films is independent of the deposition method. The electrical conductivity change as a function of time with NO₂ is instead dissimilar: for spin-coated films it shows a behaviour already observed for sandwich-type phthalocyanine whereas for LB films it resembles that of monomeric phthalocyanine. Such a response implies that the charges (holes) generated in the oxidation/reduction process are carried differently through the material, and we attempt to explain this behaviour taking into account the two different structural and morphological features induced by the two techniques.     

Will musculoskeletal and visual stress change when Visual Display Unit (VDU) operators move from small offices to an ergonomically optimized office landscape?

This study investigated the effect of moving from small offices to a landscape environment for 19 Visual Display Unit (VDU) operators at Alcatel Denmark AS. The operators reported significantly improved lighting condition and glare situation. Further, visual discomfort was also significantly reduced on a Visual Analogue Scale (VAS). There was no significant correlation between lighting condition and visual discomfort neither in the small offices nor in the office landscape. However, visual discomfort correlated significantly with glare in small offices i.e. more glare is related to more visual discomfort. This correlation disappeared after the lighting system in the office landscape had been improved. There was also a significant correlation between glare and itching of the eyes as well as blurred vision in the small offices, i.e. more glare more visual symptoms. Experience of pain was found to reduce the subjective assessment of work capacity during VDU tasks. There was a significant correlation between visual discomfort and reduced work capacity in small offices and in the office landscape. When moving from the small offices to the office landscape, there was a significant reduction in headache as well as back pain. No significant changes in pain intensity in the neck, shoulder, forearm, and wrist/hand were observed.The pain levels in different body areas were significantly correlated with subjective assessment of reduced work capacity in small offices and in the office landscape.By careful design and construction of an office landscape with regard to lighting and visual conditions, transfer from small offices may be acceptable from a visual-ergonomic point of view.     

Using hash tables to manage the time-storage complexity in a point location problem: Application to explicit model predictive control

The online computational burden of linear model predictive control (MPC) can be moved offline by using multi-parametric programming, so-called explicit MPC. The solution to the explicit MPC problem is a piecewise affine (PWA) state feedback function defined over a polyhedral subdivision of the set of feasible states. The online evaluation of such a control law needs to determine the polyhedral region in which the current state lies. This procedure is called point location; its computational complexity is challenging, and determines the minimum possible sampling time of the system. A new flexible algorithm is proposed which enables the designer to trade off between time and storage complexities. Utilizing the concept of hash tables and the associated hash functions, the proposed method solves an aggregated point location problem that overcomes prohibitive complexity growth with the number of polyhedral regions, while the storage–processing trade-off can be optimized via scaling parameters. The flexibility and power of this approach is supported by several numerical examples.     

Correcting for the influence of frozen lakes in satellite microwave radiometer observations through application of a microwave emission model

The spatial resolution of passive microwave observations from space is of the order of tens of kilometers with currently available instruments, such as the Special Sensor Microwave/Imager (SSM/I) and Advanced Microwave Scanning Radiometer (AMSR-E). The large field of view of these instruments dictates that the observed brightness temperature can originate from heterogeneous land cover, with different vegetation and surface properties.In this study, we assess the influence of freshwater lakes on the observed brightness temperature of AMSR-E in winter conditions. The study focuses on the geographic region of Finland, where lakes account for 10% of the total terrestrial area. We present a method to mitigate for the influence of lakes through forward modeling of snow covered lakes, as a part of a microwave emission simulation scheme of space-borne observations. We apply a forward model to predict brightness temperatures of snow covered sceneries over several winter seasons, using available data on snow cover, vegetation and lake ice cover to set the forward model input parameters. Comparison of model estimates with space-borne observations shows that the modeling accuracy improves in the majority of examined cases when lakes are accounted for, with respect to the case where lakes are not included in the simulation. Moreover, we present a method for applying the correction to the retrieval of Snow Water Equivalent (SWE) in lake-rich areas, using a numerical inversion method of the forward model. In a comparison to available independent validation data on SWE, also the retrieval accuracy is seen to improve when applying the influence of snow covered lakes in the emission model.