Abstract
IPTV services consist of multiple video channels grouped in bundles, such as sports, movies or generic bundles; users typically subscribe multiple bundles, including the generic bundle. Secure IP multicast can be used to implement IPTV services, but it still has problems to be addressed. Current solutions require high computational power in video channel zapping situations, lack support for groups sourced at the users, and present a weak support for admission control in IP multicast for both sources and receivers in dynamically configured environments. This work proposes a new, secure and efficient IPTV solution that, cumulatively: (a) enforces individual access control to groups of real-time IPTV video channels; (b) enforces IP multicast admission control for both multicast senders and receivers; (c) supports user generated videos; (d) generates low signaling overheads; (e) does not introduce perceivable delays, particularly in video channel zapping situations. Moreover, this solution can be easily integrated in the IPTV architectures being developed by ETSI and ITU-T.

Abstract
The volume of health data is rising and health information technologies which include electronic health records are a promising solution, on data management and collection, to achieve greater quality outcomes. However, they often cause errors instead of preventing them. To study the main barriers to high quality data collection from electronic health records, a qualitative review study was conducted using 5 different database engines having only considered data quality and documentation issues, opportunities and challenges for proper data collection, electronic health records data and corresponding databases quality. It were included 16 articles from which data availability, format, accuracy and data accessibility were the most focused problems to address. Still, solutions are available: early recognition of those problems, well structured and designed EHRs, standard coding use, periodic accuracy monitoring and feedback and broad use of such systems for the most daily tasks possible, among others. Altogether they can improve EHR data quality for everyday use.

Abstract
Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by increased predisposition for tumor development and cognitive deficits. In this work, we used maps of grey matter density obtained from Magnetic Resonance (MR) brain structural scans to distinguish between NF1 patients and healthy controls with a multivariate pattern analysis technique, Support Vector Machines. Up to 83% of all participants were correctly classified (mean sensitivity of 82%; mean specificity of 84%; significance level p< 0.01). This high level of classification accuracy of NF1 patients suggests this technique as a potential diagnostic tool. In addition, we determined the brain regions that the algorithm used to distinguish between NF1 patients and healthy controls. These regions were not identified as abnormal using univariate voxel-by-voxel comparison indicating that multivariate techniques are a useful powerful tool with which to identify potential structural defects in the NF1 brain. © 2011 IEEE.

Abstract
The constant evolution of access technologies are turning Internet access more ubiquitous, faster, better and cheaper. In connection with the proliferation of Internet access, Cloud Computing is changing the way users look at data, moving from local applications and installations to remote services, accessible from any device. This new paradigm presents numerous opportunities that even traditional businesses like telecoms cannot ignore, in particular, enabling new and more cost effective solutions to old problems. The work presented in this paper provides a detailed description of how a telecom application can be migrated to a NoSQL database. Particularly, by pointing out the necessary change of how we reason about data as well as the data structures that support it, in order to take full advantage of Cloud Computing. In addition, we also present a preliminary evaluation of different data persistency paradigms based on a fully tunable simulation platform that mimics the operation of a telecom business.

Abstract
With today's hospital demands and financial constraints, hospital inpatient bed management is becoming increasingly complex. The use of decision support systems could enable hospital staff and health decision makers to perform more focused management of the hospital inpatient beds, thus potentially reducing costs and inpatient length of stay. A literature review was carry out on both PubMed and ISI Web of Knowledge in order to identify studies evaluating the use of decision support systems when applied to hospital inpatient bed management. Two different approaches were identified: one approach based on the use of mathematical models to support the planning and allocation of hospital inpatient beds and another approach consisting in the utilization of information technologies to support timely inpatient placement. It was perceived that mathematical models could be safely used to model annual patient arrival rates and bed occupancy, thus forecasting hospital/department bed demand and underlying cost structures/revenues. It was also perceived that the use of bed management information systems provides hospital staff (administrative clerk, clinicians and housekeepers) with the necessary information to timely assess performance measures based on the hospital/department activity thus increasing resource effectiveness, optimizing established clinical pathways, reducing inpatient length of stay and associated costs.

Abstract
Due to the severity of patients treated in the intensive care units, these units are commonly equipped with a variety of equipment that is handled by a multidisciplinary team. In order to identify problems, present and future, clinicians perform periodic assessments that produce huge amount of data, which availability is of vital importance. This study was performed in order to assess the impact of clinical data centralized in a clinical information system for inpatients in an intensive care unit, when compared with data disseminated in different systems. A literature search was conducted on PubMed in order to identify relevant articles published between 2000 and 2010. From a total of 48 articles, 7 articles were selected for assessment. 2 articles studied the impact of system integration, 4 articles studied the impact of computerized medical records and 1 article studied both the impact of computerized medical records and system integration. A centralized clinical information system was proved to have a positive impact for inpatients in an intensive care unit. These systems allow time savings on vital signs transcription, reduced medication errors, a quicker access to clinical data and a reduction in prescription errors.