Interfacial polymerization of pyrrole and in situ synthesis of polypyrrole/silver nanocomposites

We present a new synthetic approach leading to the formation of polypyrrole architectures in submicron level and to silver/polypyrrole nanocomposites via an interfacial polymerization in a water/chloroform interface. The oxidizing agent was either Ag(I) or Fe(III). In the first case, silver nanoparticles resulted. The mean diameter of the polypyrrole structures is in the range of 200-300 nm according to the addition or not of various surfactants. The progress of the reaction was studied by UV-visible spectroscopy, which also revealed the formation of a polaron band during the growth of the oligomers. The crystal structure of the polymers was examined by X ray diffractometry and all samples appeared to be amorphous, while the samples were further characterized by thermogravimetric analysis and FT-IR spectroscopy.     

Transitive node similarity: predicting and recommending links in signed social networks

Online social networks (OSNs) like Facebook, Myspace, and Hi5 have become popular, because they allow users to easily share content. OSNs recommend new friends to registered users based on local features of the graph (i.e., based on the number of common friends that two users share). However, OSNs do not exploit the whole structure of the network. Instead, they consider only pathways of maximum length 2 between a user and his candidate friends. On the other hand, there are global approaches, which detect the overall path structure in a network, being computationally prohibitive for huge-size social networks. In this paper, we define a basic node similarity measure that captures effectively local graph features (i.e., by measuring proximity between nodes). We exploit global graph features (i.e., by weighting paths that connect two nodes) introducing transitive node similarity. We also derive variants of our method that apply to different types of networks (directed/undirected and signed/unsigned). We perform extensive experimental comparison of the proposed method against existing recommendation algorithms using synthetic and real data sets (Facebook, Hi5 and Epinions). Our experimental results show that our FriendTNS algorithm outperforms other approaches in terms of accuracy and it is also time efficient. Finally, we show that a significant accuracy improvement can be gained by using information about both positive and negative edges.     

Parallel and scalable processing of spatio-temporal RDF queries using Spark

The ever-increasing size of data emanating from mobile devices and sensors, dictates the use of distributed systems for storing and querying these data. Typically, such data sources provide some spatio-temporal information, alongside other useful data. The RDF data model can be used to interlink and exchange data originating from heterogeneous sources in a uniform manner. For example, consider the case where vessels report their spatio-temporal position, on a regular basis, by using various surveillance systems. In this scenario, a user might be interested to know which vessels were moving in a specific area for a given temporal range. In this paper, we address the problem of efficiently storing and querying spatio-temporal RDF data in parallel. We specifically study the case of SPARQL queries with spatio-temporal constraints, by proposing the DiStRDF system, which is comprised of a Storage and a Processing Layer. The DiStRDF Storage Layer is responsible for efficiently storing large amount of historical spatio-temporal RDF data of moving objects. On top of it, we devise our DiStRDF Processing Layer, which parses a SPARQL query and produces corresponding logical and physical execution plans. We use Spark, a well-known distributed in-memory processing framework, as the underlying processing engine. Our experimental evaluation, on real data from both aviation and maritime domains, demonstrates the efficiency of our DiStRDF system, when using various spatio-temporal range constraints.

     

Toward a Conceptual Emulation Framework for the Preservation of Archaeological 3D Visualizations

Through the Preservation of Complex Objects Symposia (POCOS), leading researchers and practitioners have managed to propose strategies for preserving digital art and computer games. The same is not true for the preservation of archaeological visualizations. This article therefore discusses the following question: “Can emulation be employed to effectively preserve obsolete computer visualizations from the Archaeology domain?” Guidelines and test results coming from this work would be of great benefit to the archaeological community, and would contribute knowledge to other research communities, specifically those interested in similar data types/3D visualizations.     

On the security of AUTH, a provably secure authentication protocol based on the subspace LPN problem

At the 2011 Eurocrypt, Kiltz et al., in their best paper price awarded paper, proposed an ultra-lightweight authentication protocol, called $AUTH$ . While the new protocol is supported by a delicate security proof based on the conjectured hardness of the learning parity with noise problem, this security proof does not include man-in-the-middle attacks. In this paper, we show that $AUTH$ is weak against MIM adversaries by introducing a very efficient key recovery MIM attack that has only linear complexity with respect to the length of the secret key.     

An experimental investigation of personality types impact on pair effectiveness in pair programming

In this paper, pair programming is empirically investigated from the perspective of developer personalities and temperaments and how they affect pair effectiveness. A controlled experiment was conducted to investigate the impact of developer personalities and temperaments on communication, pair performance and pair viability-collaboration. The experiment involved 70 undergraduate students and the objective was to compare pairs of heterogeneous developer personalities and temperaments with pairs of homogeneous personalities and temperaments, in terms of pair effectiveness. Pair effectiveness is expressed in terms of pair performance, measured by communication, velocity, design correctness and passed acceptance tests, and pair collaboration-viability measured by developers’ satisfaction, knowledge acquisition and participation. The results have shown that there is important difference between the two groups, indicating better communication, pair performance and pair collaboration-viability for the pairs with heterogeneous personalities and temperaments. In order to provide an objective assessment of the differences between the two groups of pairs, a number of statistical tests and stepwise Discriminant Analysis were used.

SABRE: a Sensitive Attribute Bucketization and REdistribution framework for t-closeness

Today, the publication of microdata poses a privacy threat: anonymous personal records can be re-identified using third data sources. Past research has tried to develop a concept of privacy guarantee that an anonymized data set should satisfy before publication, culminating in the notion of t-closeness. To satisfy t-closeness, the records in a data set need to be grouped into Equivalence Classes (ECs), such that each EC contains records of indistinguishable quasi-identifier values, and its local distribution of sensitive attribute (SA) values conforms to the global table distribution of SA values. However, despite this progress, previous research has not offered an anonymization algorithm tailored for t-closeness. In this paper, we cover this gap with SABRE, a SA Bucketization and REdistribution framework for t-closeness. SABRE first greedily partitions a table into buckets of similar SA values and then redistributes the tuples of each bucket into dynamically determined ECs. This approach is facilitated by a property of the Earth Mover’s Distance (EMD) that we employ as a measure of distribution closeness: If the tuples in an EC are picked proportionally to the sizes of the buckets they hail from, then the EMD of that EC is tightly upper-bounded using localized upper bounds derived for each bucket. We prove that if the t-closeness constraint is properly obeyed during partitioning, then it is obeyed by the derived ECs too. We develop two instantiations of SABRE and extend it to a streaming environment. Our extensive experimental evaluation demonstrates that SABRE achieves information quality superior to schemes that merely applied algorithms tailored for other models to t-closeness, and can be much faster as well.     

Information Flow for Optimized Management of Spectrum and Radio Resources in Cognitive B3G Wireless Networks

The Beyond 3G (B3G) radio landscape will consist of cognitive heterogeneous wireless networks, operating in the framework of diverse co-operative associations among different classes of operators and providers, for the accommodation of the demands of users with multimode and/or multihoming enabled terminals. In this context, the optimized spectrum and radio resource utilization will be key factor for accomplishment of the purposes of both users and operators/providers, namely the satisfaction of user’s needs and the augmentation of profit, respectively. In this paper, we focus on an architecture for the management and optimization of spectrum and radio resource utilization in such composite wireless environments, and we analytically present the respective information flow among and from/to the functional entities involved in this architecture. The proposed management architecture can operate in the framework of different business scenarios and is based on related work that has been conducted within the IEEE 1900.4 standard.