Abstract
Grid environments are dynamic and heterogeneous by nature, therefore requiring adaptive scheduling strategies. Reinforcement learning is an interesting and simple adaptive approach that may work well in actual grid environments. In this work, we employ reinforcement learning to classify available resources in a grid environment, giving support to two scheduling algorithms, AG and MQD. We study the makespan optimisation and load balancing. An algorithm known as RR is used for normalising purposes. Copyright © 2009 Inderscience Enterprises Ltd.

Abstract
From an application point of view, the Grid computing with its powerful processing power and large amounts of data storage offers the possibility to process large quantities of data, to run computationally-intensive operations, or both. For instance, in computational biological pipelines, one often has to process large quantities of data in individually computationally-intensive operations. To process this data in the Grid, hundreds, or even thousands of jobs need to be submitted and their results processed. Obviously, performing these tasks manually is unfeasible. On the other hand, developing software to this end, specifically for a single application, is unproductive because if the application changes, or the Grid submission engine changes, then the code needs to be rewritten. In this paper we present a middleware that facilitates the submission of jobs to grids (or clusters) and helps handling their results. The middleware, that we call UbiDis (Ubiquitous Distribution), copies all files necessary for running the program to the UI or front-end host (in a Grid or cluster), compiles programs on the UI or front-end (if necessary), generates and submits the jobs, and copies the outputs to the local machine. Furthermore, UbiDis transparently generates jobs to different job managers, allowing the user to easily and quickly change the location to where the jobs are submitted. Finally, we illustrate the usefulness of UbiDis using two applications.

Abstract
Throughout the modern world, healthcare is in a crisis. In response, health information systems are going through major changes: focusing more on the patient and what the patient can do to help to improve his own health care. A lot has been said about what the patient's role should be in the 21(st) century. However, in a way, the patient is still being left out, without the ability to decide about his role and impotent to exercise his rights as the owner of his own EHR. Moreover, there exists a general lack of awareness among the general public about the major risks involved in the unbounded disclosure of personal health related data. The continuous growth of privacy incidents, resulting from target profiling and mining off individual health histories, by human resource departments or insurance companies, demonstrates the fragile perception the general public has for these matters. To help us in assessing this situation we have conducted several interviews with patients older than 18 years in order to determine their opinion on matters regarding 'patient empowerment' and their associated EHRs: particularly who should have access and what were the real reasons behind those answers. In this paper we analyze the results of our questionnaire and present and discuss in detail the answers provided by 100 patients: 70 female and 30 male from diverse strata of the Portuguese population.

Abstract
Several studies have demonstrated the advantages of using IVR (Interactive Voice Response) technologies[5], which allow the users to phone a computer and access services by pressing the appropriate touch-tone keys on their telephones. Because it offers substantial benefits in terms of cost and time efficiency, there is a continuous pursuit for increased automation using IVR. The real challenge lies in providing a user-friendly, yet cost-effective interface to users in order to improve their interaction with existing services, making them more usable and useful, providing an experience that fits their specific objectives and utilization contexts. This paper describes a method and system for providing customizable audio access to email messages kept in several IMAP (Internet Message Access Protocol) backstorages using an IVR application that takes full advantage of TTS (Text-To-Speech) software.

Abstract
With the massive migration of real world bureaucratic and business processes to the virtual world comes an ever increasing dependency on the security of the Internet infrastructure. To ensure the secure exchange of sensitive personal information and to help support the provisioning of a multitude of identity mechanisms and protocols there is an increased need for a very flexible, interoperable and user-centric Identity Management infrastructure. OpenID is a decentralized system protocol for user-centric identification and digital identity management in the Internet that is being largely deployed all over the world. In this paper we present Extended OpenID (EOID), an Identity Provider which leverages a secured OpenID 2.0 infrastructure with the recently released Portuguese Citizen Card (CC). EOID is composed by an OpenID server that uses the CC for strong authentication and a Firefox Plugin for an easier much more secure user experience.

Abstract
Automatically evaluating source program files is a crucial part of programming contests. The evaluation aims at discriminating programs according to their correctness and efficiency. Given the performance of today's computers, in order to be able to distinguish the complexity of solutions, it is often necessary to use very large data sets. This is awkward, because it is against the nature of the stated problem and puts an unintended burden on the input operations. Besides, by advertizing a limit for the size of the input, the problem description gives away information with which the contestants may guess the algorithmic complexity that their solutions must attain. It would be more realistic to omit that information and let the contestants discover the limits by analyzing the problem, using a scientific approach. The complexity of the solution can then be estimated automatically by measuring the execution time of the function that solves the problem in incremental test cases, and plotting it against the size of the input. By calling the function multiple times and taking the overall time, we may use only data files the size of which is related to the nature of the problem being solved. © 2009 Institute of Mathematics and Informatics, Vilnius.