Abstract
Empirical mode decomposition (EMD) is a fully unsupervised and data-driven approach to the class of nonlinear and non-stationary signals. A new approach is proposed, namely PHEEMD, to image analysis by using Peano-Hilbert space filling curves to transform 2D data (image) into 1D data, followed by ensemble EMD (EEMD) analysis, i.e., a more robust realization of EMD based on white noise excitation. Tests' results have shown that PHEEMD exhibits a substantially reduced computational cost compared to other 2D-EMD approaches, preserving, simultaneously, the information lying at the EMD domain; hence, new perspectives for its use in low computational power devices, like portable applications, are feasible.

Abstract
In a globalized world members of groups may be anywhere, and the need for ubiquitous Idea Generation emerged. This led to two main needs: the creation of Smart Decision Rooms prepared for this new reality and following the Ambient Intelligence paradigm; and the creation of context aware middleware. This paper describes OLAVAmI a context aware middle-ware system which was tested in LAID environment, a Smart Meeting Room. OLAVAmI allows video production focusing on the speaker, an audio-to-text conversion service, and the multimedia database of meetings produced in an autonomous way. To experiment OLAVAmI usage and functionalities one of the tools present in LAID test bed was used and the results are presented in this article. © 2011 IEEE.

Abstract
Nowadays there are specific video equipments which allow acquisition at very high frame rates, e.g., up to 5000 fps. When observing a high frame rate sequence, it becomes noticeable that a great percentage of the frames' pixels values do not suffer great changes along the sequence. Hence, if a pixel's value remains the same, then a unique sample is enough to represent that particular pixel over several frames. Only pixels that suffer great variations require a higher number of samples to be correctly represented. This work reports a methodology that combines compression and reconstruction techniques to evaluate an alternative to the traditional compression methods 25/30 fps. In the proposed method, sets of pixels are extracted along the temporal direction and by exploiting the high temporal correlation of the signals, a proper decimation process is applied in order to create a sequence with a lower number of frames and consequently smaller rile size. The main objective is to propose a new compression methodology that will take advantage of the signal characteristics using both compression and reconstruction techniques.

Abstract
As we observe society in our days, we can see that people live longer; this means that we have an older population. As we know, elder are more likely to have health issues. The special needs presented by elder are gaining a major concern from all of us. Another tendency of our society is the lack of time that people demonstrate and, as a consequence, the lack of time reflects when families can't take care of their own elders. Many solutions are being presented in order to solve this problem. Some of them are taking advantage of the new technology developments in body sensor network area. In this paper we proposed an architecture of a system called Elder Care. The Elder Care solution has two primary goals: monitoring vital signs, sending alerts to family and specialized help and provide a social network in order to wrap all elder to avoid social isolation. © 2008 IEEE.

Abstract
The emergence of new business models, namely, the establishment of partnerships between organizations, the chance that companies have of adding existing data on the web, especially in the semantic web, to their information, led to the emphasis on some problems existing in databases, particularly related to data quality. Poor data can result in loss of competitiveness of the organizations holding these data, and may even lead to their disappearance, since many of their decision-making processes are based on these data. For this reason, data cleaning is essential. Current approaches to solve these problems are closely linked to database schemas and specific domains. In order that data cleaning can be used in different repositories, it is necessary for computer systems to understand these data, i.e., an associated semantic is needed. The solution presented in this paper includes the use of ontologies: (i) for the specification of data cleaning operations and, (ii) as a way of solving the semantic heterogeneity problems of data stored in different sources. With data cleaning operations defined at a conceptual level and existing mappings between domain ontologies and an ontology that results from a database, they may be instantiated and proposed to the expert / specialist to be executed over that database, thus enabling their interoperability. © 2012 IEEE.

Abstract
This study provides some empirical insight on the barriers that chief information officers face in their Job. The findings of the survey we conducted directed to the chief information officers of the 500 large Portuguese companies by gross revenue, suggest; three main barriers: the lack of time to think and define strategies, the overwhelming backlog of requests and projects and inadequate budgets. The knowledge and understanding of the identified barriers contributes to the characterization of chief information officer role state of the art and should be useful for practitioners, who may use it as a basis for developing solutions in order to overcome these barriers.