Abstract
This paper presents an Artificial Immune System (AIS) based on Grossman's Tunable Activation Threshold (TAT) for anomaly detection. We describe the immunological metaphor and the algorithm adopted for T-cells, emphasizing two important features: the temporal dynamic adjustment of T-cells clonal size and its associated homeostasis mechanism. We present some promising results obtained with artificially generated data sets, aiming to test the appropriateness of using TAT in dynamic changing environments, to distinguish new unseen patterns as part of what should be detected as normal or as anomalous.

Abstract
One emergent, widely used metaphor and rich source of inspiration for computer security has been the vertebrate Immune System (IS). This is mainly due to its intrinsic nature of having to constantly protect the body against harm inflicted by external (non-self) harmful entities. The bridge between metaphor and the reality of new practical systems for anomaly detection is cemented by recent biological advancements and new proposed theories on the dynamics of immune cells by the field of theoretical immunology. In this paper we present a work in progress research on the deployment of an immune-inspired architecture, based on Grossman's Tunable Activation Threshold (TAT) hypothesis, for temporal anomaly detection, where there is a strict temporal ordering on the data, such as network intrusion detection. We start by briefly describing the overall architecture. Then, we present some preliminary results obtained in a Production network. Finally, we conclude by presenting the main lines of research we intend to pursue in the near future.

Abstract
The detection of anomalies in computer environments, like network intrusion detection, computer virus or spam classification, is usually based on some form of pattern search on a database of "signatures " for known anomalies. Although very successful and widely deployed, these approaches are only able to cope with anomalous events that have already been seen. To cope with these weaknesses, the "behaviour" based systems has been deployed. Although conceptually more appealing, they have still an impractical high rate of false alarms. The vertebrate Immune System is an emergent and appealing metaphor for new ideas on anomaly detection, being already adopted some algorithms and theoretical theories in particular fields, such as network intrusion detection. In this paper we present a temporal anomaly detection architecture based on the Grossman's Tunable Activation Threshold (TAT) hypothesis. The basic idea is that the repertoire of immune cells is constantly tuned according to the cells temporal interactions with the environment and yet retains responsiveness to an open-ended set of abnormal events. We describe some preliminary work on the development of an anomaly detection algorithm derived from TAT and present the results obtained thus far using some synthetic data-sets.

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.