Abstract
We present a framework designed to mine sequential temporal patterns from multi-relational databases. In order to exploit logic-relational information without using aggregation methodologies, we convert the multi-relational dataset into what we name a multi-sequence database. Each example in a multi-relational target table is coded into a sequence that combines intra-table and inter-table relational temporal information. This allows us to find heterogeneous temporal patterns through standard sequence miners. Our framework is grounded in the excellent results achieved by previous propositionalization strategies. We follow a pipelined approach, where we first use a sequence miner to find frequent sequences in the multi-sequence database. Next, we select the most interesting findings to augment the representational space of the examples. The most interesting sequence patterns are discriminative and class correlated. In the final step we build a classifier model by taking an enlarged target table as input to a classifier algorithm. We evaluate the performance of this work through a motivating application, the hepatitis multi-relational dataset. We prove the effectiveness of our methodology by addressing two problems of the hepatitis dataset.

Abstract
This paper presents an artificial immune system (AIS) based on Grossman's tunable activation threshold (TAT) for temporal anomaly detection. We describe the generic AIS framework and the TAT model adopted for simulating T Cells behaviour, emphasizing two novel important features: the temporal dynamic adjustment of T Cells clonal size and its associated homeostasis mechanism. We also 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. We conclude by discussing results obtained thus far with artificially generated data sets.

Abstract
With the advent of more sophisticated and comprehensive healthcare information systems, system builders are becoming more interested in patient interaction and what he can do to help to improve his own health care. Information systems play nowadays a crucial and fundamental role in hospital work-flows, thus providing great opportunities to introduce and improve upon "patient empowerment" processes for the personalization and management of Electronic Health Records (EHRs). In this paper, we present a patient's privacy generic control mechanisms scenarios based on the Extended OpenID (eOID), a user centric digital identity provider previously developed by our group, which leverages a secured OpenID 2.0 infrastructure with the recently released Portuguese Citizen Card (CC) for secure authentication in a distributed health information environment. eOID also takes advantage of Oauth assertion based mechanisms to implement patient controlled secure qualified role based access to his EHR, by third parties.

Abstract
To understand the importance of technologies like the Internet and Learning Management Systems to Higher Education students' learning activities, this study characterizes the Internet access behaviour of Polytechnic of Porto (IPP)' students. Student's habits were obtained through a questionnaire that was answered by 10% of all IPP students. Our analysis is focused not only on the global Internet usage profile under the Polytechnic of Porto, but also on the differences between the students born before and after 1980. International trends are confirmed in this Portuguese Higher Education institution.

Abstract
In recent years, mobile learning has merged as an educational approach to decrease the limitation of learning location and adapt the teaching-learning process to all type of students. However, the large number and variety of Web-enabled devices poses challenges for Web content creators who want to automatic get the delivery context and adapt the content to mobile devices. In this paper we study several approaches to adapt the learning content to mobile phones. We present an architecture for deliver uniform m-Learning content to students in a higher School. The system development is organized in two phases: firstly enabling the educational content to mobile devices and then adapting it to all the heterogeneous mobile platforms. With this approach, Web authors will not need to create specialized pages for each kind of device, since the content is automatically transformed to adapt to any mobile device capabilities from WAP to XHTML MP-compliant devices.

Abstract
This paper presents a combination of two techniques for high-resolution ultrasonic distance measurements in air. The first is the cross correlation between transmitted and received signals to determine the time of flight (TOF), and the second is sine fitting of other transmitted and received signals to determine the phase shift (PS) between them. Sine fitting can estimate the PS with very high accuracy. The result of this synergy is a very accurate distance measurement. For example, the final uncertainty is less than 100 mu m for distances up to 1200 mm.