Abstract
This paper discusses the effective contribution of a Learning Object (LO) to teach circuit theory based on research conducted with students of higher education, and their interaction with a teacher of Electronics. From the results of such research, it is pointed out which features one wants in the LO so that it successfully promotes learning. It is in this perspective that this work was conceived having as goal the development of LO, admitting that this may be a possible alternative to represent models of interactions, which occur within the area, thereby improving understanding of physical concepts, in particular those involved with the subject of electrical circuits. It has also as objective to characterize the learning process through a series of situations that are replicated leading to a set of behaviors from the students. It is assumed that the use of this tool can lead to acquiring a specific set of skills, a better practice and meaningful learning.

Abstract
It is widely recognized that information systems constitute a key tool for the overall performance improvement of administrative tasks in academic institutions. However at their genesis lies a latent promise of a paper-less environment that stays most of the time unfulfilled due to the lack of appropriate digital document integrity and accountability mechanisms. Academic institutions are thus most of the time still relying on traditional security trust methods based on paper documents for signing and archiving critical documents. While this method delivers an inefficient, inconvenient and costly workflow, it is still a common method to provide some sort of workable verifiable integrity and accountability that is still considered to be appropriate for the digital data that is being managed by the institutional information systems. Paper based documents have been relying on physical signatures and stamping policies and the physical properties of paper and ink for their integrity and authenticity for a long time. However, the evaluation of a paper document signature or stamp is not a straight forward process. It requires the recipient to have a notarized copy of the signer's signature or stamp for comparison and requires handwritten signature evaluation training that is often beyond the scope of many office employee training. This can lead to situations where the level of credibility and integrity of paper based document is not adequate and makes the verification process entirely dependent on the administrative staff capacity of recognizing hand written signatures and puts too much trust on physical stamps, some of which are non-locally issued and thus very difficult to authenticate. In critical contexts this clearly is not enough to provide appropriate levels of non-repudiation and integrity for critical documents issued by institutions. Digitally signed structured XML documents provide an interesting solution to this problem. Not only can the validation of the document be fully automatized and its integrity verifiable in real time by the information system, but it can also be implemented in such way that the information contained in such structured documents can be safely and more easily integrated into different information systems without human intervention, thus allowing for substantial cost reduction and leading to faster process work-flows with increased security and data quality. In this paper we propose a PDF based document framework where any signed XML (PDF) document, produced by the institution can be at a later stage directly dematerialized and integrated into any compliant information system in a secure way while maintaining the information integrity and the ability to be self-verifiable. This framework involves the embedding of an encapsulated XAdES signed XML document with the information used on its production as an attachment to a PDF document with an institutional rendering visualization of the signed XML data. The attached XML document and the PDF are both time stamped by an external entity and signed by employees and the issuing institution.

Abstract
Given the wide spread of social networks, research efforts to retrieve information using tagging from social networks communications have increased. In particular, in Twitter social network, hashtags are widely used to define a shared context for events or topics. While this is a common practice often the hashtags freely introduced by the user become easily biased. In this paper, we propose to deal with this bias defining semantic meta-hashtags by clustering similar messages to improve the classification. First, we use the user-defined hashtags as the Twitter message class labels. Then, we apply the meta-hashtag approach to boost the performance of the message classification. The meta-hashtag approach is tested in a Twitter-based dataset constructed by requesting public tweets to the Twitter API. The experimental results yielded by comparing a baseline model based on user-defined hashtags with the clustered meta-hashtag approach show that the overall classification is improved. It is concluded that by incorporating semantics in the meta-hashtag model can have impact in different applications, e.g. recommendation systems, event detection or crowdsourcing.

Abstract

Abstract
Mobile phones are a ubiquitous and preferred communication, entertainment, and information access platform. Smartphones may provide an opportunity to better assess mood and behavior and to provide intervention timely, economical, rapid and effective intervention for those with mental disorders. This is an important target because behavioral health problems are associated with many of the medical disorders most responsible for morbidity and cost. Today, psychiatrists seek for various channels of mobile technology that can reduce evaluation costs and increase accuracy and also facilitate ubiquitous longitudinal monitoring of treatment and outcome measures on patients' smartphone. Facial expression recognition is one of the active research areas in the field of psychiatry to evaluate a patient's emotional health. Smartphone technology for recognizing facial expression of emotions is still emerging and offers an open platform for the research areas such as ubiquitous intelligence and computing. In this research, we present a framework to track user's emotional engagement to videos played on a smartphone. The presented framework processes user's video recorded from the front-facing camera of a smartphone and tracks facial features to detect joyful durations induced by the played videos. We also conducted subject studies on healthy individuals to evaluate the applied approach of emotional engagement. We believe that the presented results are promising and present a valuable insight to build ubiquitous intelligent systems that can help various areas of psychiatric research. © 2013 IEEE.

Abstract