Abstract
Inspired by recent results on information-theoretic security, we consider the transmission of confidential messages over wireless networks, in which the legitimate communication partners are aided by friendly jammers. We characterize the security level of a confined region in a quasi-static fading environment by computing the probability of secrecy outage in connection with two new measures of physical-layer security: the jamming coverage and the jamming efficiency. Our analysis for various jamming strategies based on different levels of channel state information provides insight into the design of optimal jamming configurations and shows that a single jammer is not sufficient to maximize both figures of merit simultaneously. Moreover, a single jammer requires full channel state information to provide security gains in the vicinity of the legitimate receiver.

Abstract
We consider a wireless network scenario in which the communicating nodes are assisted by a number of jammers. The goal of the jammers is to obstruct potential eavesdroppers while restricting the harmful interference experienced by the legitimate receiver. Based on a stochastic network model, we are able to show that packet collisions caused by jamming nodes can be used effectively to increase the level of secrecy. Various jammer selection policies are investigated depending on the position of source, destination and jamming nodes. Our results shed some light on the trade-off between secure throughput and energy efficiency. © 2011 IEEE.

Abstract
Digital portfolios have recently assumed an increasing importance in e-learning. In this article we report an integrated system that can be used to publish online projects undertaken by students during their courses. The system was then integrated with the Moodle learning management system featuring the possibility to create, evaluate, publish and maintain digital portfolios assigned and corrected by the institution faculty. This integrated process ensures a high quality level of the projects registered. The system uses information imported from Moodle's database to fill in its own database for users, courses and propagates the existing session between the two systems. It also maintains the projects in specific development phases, thus, allowing asynchronous editing, assessing or commenting on projects by different students or teachers. The creation of a new project is boosted by the use of a set of pre-defined templates which in turn give a standard layout and design quality to the final view of the project.

Abstract
This paper describes a conceptual framework for implementing Intelligent Tutoring Systems using SCORM 2004. The main objective is to discuss how the SCORM 2004 sequencing and navigation specification can allow the development of Intelligent Web-Based Learning Environments using the sequencing and navigation tracking data, and rule set. Our main argument is that SCORM 2004 sequencing and navigation specification can be used to implement the two main functionalities of an ITS, (1) the inner loop and (2) the outer loop. © 2010 IEEE.

Abstract
For several years Intelligent Tutoring Systems (ITSs) have been developed and shown to lead to impressive improvement in student learning in a range of domains. Some of the most important limitations of ITSs are that their development is very time consuming, and they cannot be reused or imported to different platforms. The main benefits of the Sharable Content Object Reference Model (SCORM) are interoperability and reusability. Based on the SCORM Sequencing and Navigation (SN) specification we have developed an approach for implementing Web-Based SCORM compliant ITSs that are therefore reusable and interoperable. The main objective of this paper is to describe our approach and explain how to implement SCORM compliant ITSs using as an example, a prototype that we built.

Abstract
Mining meaningful data from complex biological networks is a critical task in many areas of research. One important example is calculating the frequency of all subgraphs of a certain size, also known as the sub graph census problem. This can provide a very comprehensive structural characterization of a network and is also used as an intermediate step in the computation of network motifs, an important basic building block of networks, that try to bridge the gap between structure and function. The subgraph census problem is com-putationally hard and here we present several parallel strategies to solve this problem. Our initial strategies were refined towards achieving an efficient and scalable adaptive parallel algorithm. This algorithm achieves almost linear speedups up to 128 cores when applied to a representative set of biological networks from different domains and makes the calculation of census for larger subgraph sizes feasible.