Abstract
The organizations' demand to integrate several disparate data sources and an ever-increasing amount of data is intensifying the occurrence of data quality problems. Currently, data cleaning approaches are tailored for data sources having different schemas but sharing the same data model (e.g. relational model), and are highly dependent on a domain expert to specify data cleaning operations. This paper presents a novel and generic data cleaning methodology aiming to assist the domain expert during the specification of data cleaning operations through reusing knowledge previously expressed for other data sources even if those sources have different data models and/or schemas. This is achieved by abstracting data source models and schemas to a closer human level and by the use of vocabulary to describe the structure and the semantics of data cleaning operations.

Abstract
Wireless Sensor Networks, in particular Wireless Body Area Networks, is a technology suggested by the research community as allowing elderly people, or people with some kind of disability, to live in a safer, responsive and comfortable environment while at their homes. One of the most active threats to the autonomous life of blind people is the quantity and variety of obstacles they face while moving, whether they are obstacles in the footpath or obstacles coming out from the walls of buildings. Hence, it is necessary to develop a solution that helps or assists blind people while moving either in indoor or outdoor scenarios, simultaneously allowing the use of the use of white cane or the Seeing Eye dog. In this article, the authors propose the use of an ultra-sound based body area network for obstacle detection and warning as a complementary and effective solution for aiding blind people when moving from place to place. According to the cost estimates of the solution and to the negligible setup time, this could be a real effective complementary solution for blind people. (c) 2015 The Authors. Published by Elsevier B.V.

Abstract
Technology is present in almost all aspects of our modern lives, and technological advances have been more and more prevalent. One would expect this to facilitate everybody's life, rendering common tasks more practical and easier to perform, but that is often not the case - at least not for the elderly. Older people have significant difficulties in using technological equipment due to the visual, physical, cognitive and hearing limitations associated with the natural aging process; these aspects must be taken into account if the intention is that of integrating technology in the lives of the elderly. In order to improve the quality of life of the elderly, as well as to prevent their social isolation, a mobile device application was developed to act as an intelligent remote control. This mobile application deals with data from two different platforms that were previously developed for improving the quality of life of the senior population: HbbTV and +Social. The features built into this virtual remote control include the integration with the +Social platform, as well as a speech recognition mechanism, and the possibility of making and receiving video calls with an integrated contacts list. A comprehensive study was carried out, focusing on recommendations and rules for graphical interfaces for the elderly, so as to allow equipping the application with adequate usability standards. The most relevant result was the definition of a list of guidelines used to steer the development of the interface. An investigation of mechanisms and technologies for enabling the implementation of the required functionalities was also carried out in order to define methodologies for freeing the user from the need of possessing any level of computer literacy. A series of usability tests was also performed to validate the viability of the remote control application. These tests allowed assessing the quality of the application, especially concerning the Graphical User Interface, as well as to receive feedback from potential end users. Based on the data collected during the test phase we conclude that this product is useful and that it responds to a current need.

Abstract
The analysis and interpretation of high-resolution computed tomography (HRCT) images of the chest in the presence of interstitial lung disease (ILD) is a time-consuming task which requires experience. In this paper, a computer-aided diagnosis (CAD) scheme is proposed to assist radiologists in the differentiation of lung patterns associated with ILD and healthy lung parenchyma. Regions of interest were described by a set of texture attributes extracted using differential lacunarity (DLac) and classical methods of statistical texture analysis. The proposed strategy to compute DLac allowed a multiscale texture analysis, while maintaining sensitivity to small details. Support Vector Machines were employed to distinguish between lung patterns. Training and model selection were performed over a stratified 10-fold cross-validation (CV). Dimensional reduction was made based on stepwise regression (F-test, p value < 0.01) during CV. An accuracy of 95.8 +/- 2.2% in the differentiation of normal lung pattern from ILD patterns and an overall accuracy of 94.5 +/- 2.1% in a multiclass scenario revealed the potential of the proposed CAD in clinical practice. Experimental results showed that the performance of the CAD was improved by combining multiscale DLac with classical statistical texture analysis.

Abstract
The organizations' demand to integrate several heterogeneous data sources and an ever-increasing volume of data is revealing the presence of quality problems in data. Currently, most of the data cleaning approaches (for detection and correction of data quality problems) are tailored for data sources with the same schema and sharing the same data model (e.g., relational model). On the other hand, these approaches are highly dependent on a domain expert to specify the data cleaning operations. This paper extends a previously proposed data cleaning methodology that reuses cleaning knowledge specified for other data sources. The methodology is further detailed/refined by specifying the requirements that a data cleaning operations vocabulary must satisfy. Ontologies in RDF/OWL are proposed as the data model for an abstract representation of the data schemas, no matter which data model is used (e.g., relational; graph). Existing approaches, methods and techniques that support the implementation of the proposed methodology, in general, and specifically of the data cleaning operations vocabulary are also presented and discussed in this paper. Copyright

Abstract
As the amount of content and the number of users in social relationships is continually growing in the Internet, resource sharing and access policy management is difficult, time-consuming and error-prone. Cross-domain recommendation of private or protected resources managed and secured by each domain’s specific access rules is impracticable due to private security policies and poor sharing mechanisms. This work focus on exploiting resource’s content, user’s preferences, users’ social networks and semantic information to cross-relate different resources through their meta information using recommendation techniques that combine collaborative-filtering techniques with semantics annotations, by generating associations between resources. The semantic similarities established between resources are used on a hybrid recommendation engine that interprets user and resources’ semantic information. The recommendation engine allows the promotion and discovery of unknownunknown resources to users that could not even know about the existence of those resources thus providing means to solve the cross-domain recommendation of private or protected resources. © Springer International Publishing AG 2016.