Abstract
From social networks to health and fitness, everyday a lot of mobile devices applications (apps) are being developed. The variety and availability is such that people start to think that indeed "there's an app for everything". Many of these apps address either problems or characteristics that affect older people and that are related with the ageing process (e.g. memory and visual aids apps). They can effectively help people and are under constant evolution. However, the lack of knowledge about these available technological aids can undermine its dissemination and consequently the help that people really receive, especially those who need it the most: older people. As such, a methodological search for available aid apps was made both in Google Play and in iTunes: 536 were selected, their classification analysed and the kind of help that they provide identified. It was noted that either in Google Play or in iTunes the apps' categories are similar. Furthermore, it is not easily perceived what the type of help that each app can provide is and how is it provided. Hence, based on the results from the aforementioned methodological search, this paper proposes a new scalable tree-based classification methodology for aid apps, which is considered more suited to perceive what the available aid apps for mobile devices are. The existing apps were then characterized based on the proposed classification, to determine what the main aid that they provide is. (C) 2016 The Authors. Published by Elsevier BAT.

Abstract
In the latest years, the number of elderly people that has been living alone and need regular support has highly increased. Meal intake monitoring is a well-known strategy that enables premature detection of health problems. There are several attempts to develop automatic meal intake monitoring systems, but they are inadequate to monitor elderly people at home. In this context, we propose an automatic meal intake monitoring system that helps tracking people's eating behaviors, and is adequate for elderly remote monitoring at home due to its nonintrusive features. The system uses the MS Kinect sensor that provides the coordinates of the user's sitting skeleton during his meals. It analyzes the coordinates, detects eating gestures, and classifies them using Hidden Markov Models (HMMs) to estimate the user's eating behavior. A demonstrative prototype for detection and classification of gestures was implemented and tested. The detection module got satisfactory percentages of sensitivity, having a minimum of 72.7% and a maximum of 90%. The Classification module was tested with 3 proposed methods and the best method had a good average percentage of success (approximately 83%) in the classification of Soup and Main dish; regarding the left hand transporting Liquids, the results were less successful. (C) 2016 The Authors. Published by Elsevier B.V.

Abstract
There are many factors that influence the success of the management of Customer Relationship Management systems projects (CRM). This article presents a systematic review of the literature of the past fifteen years, identifying and discussing the key success factors in CRM project management. The identified success factors were structured into four categories: strategic factors; operating factors; organizational factors; technological factors. The obtained results allow a better understanding of the success factors for the implementation of CRM projects and provide a theoretical basis for further work focused on the evaluation of such projects.

Abstract
This study uses the InSAR technique to analyse ground subsidence due to intensive exploitation of an aquifer for agricultural and urban purposes in the Montellano town (SW Spain). The detailed deformation maps clearly show that the spatial and temporal extent of subsidence is controlled by piezometric level fluctuations and the thickness of compressible sediments. The total vertical displacement measured with multi-temporal InSAR, between 1992 and 2010, is 33 mm that corresponds with a decrease of 43 m in the groundwater level. This technique allows monitoring the evolution of settlement related to water level fall in an area where subsidence has not yet been reported by population or authorities through infrastructure damages and to discuss the effect of the aquifer recovery. This information is, therefore, valuable for implementing effective groundwater management schemes and land-use planning and to propose new building regulations in the most affected areas.

Abstract
Warri is one of the mega cities in Delta State in the coastal region of Nigeria hosting many industries. One of the three of Nigeria oil refineries is located in Warn. This study reveals the occurence of land deformation in the Warri area which is not only because it was formed in a tectonic setting but because of the high demand of the underground water for indutrial and domestics uses, high population density and oil and gas exploration in the area. Land deformation in this area is currently being accelerated by this indiscriminate withdrawal of underground water from the aquifers and exploration of the oil and gas leading to the compacting sediments. In this study Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique was applied to monitor land deformation in Warri metropolis in the period between 09/02/2006 and 12/08/2010 with Envisat data obtained from European Space Agency (ESA). The processing was done using Stanford Method for Persistent Scatterers/Multi-Temporal InSAR (StaMPS). From the analysis of the results, land deformation is occurring in Warri metropolis at a moderate rates (+/-5 mm/yr). During the preliminary investigations, structures, particularly buildings, were physically observed subsiding while some others with cracks of various types and degrees. (C) 2016 The Authors. Published by Elsevier B.V.

Abstract
The integrated use of multiple Synthetic Aperture Radar (SAR) platforms for the deformation monitoring via satellite radar interferometry offers several perspectives for investigation of the behaviour of new and ageing structures, such as buildings and infrastructures, under varying or hazardous environment. Spanning almost 24 years of space-borne radar observations, this study aims to perform classical PSInSAR (Persistent Scatterer Interferometric Synthetic Aperture Radar) analysis incorporating measurements of ERS, Envisat, TerraSAR-X, Sentinel-1A and Radarsat-2 satellites. The results from the processing of different sensing geometries over Bratislava (Slovakia) urban area are presented, focusing on the description of characteristics associated with the specifics of every satellite platform in use. The discussion over technical feasibility of infrastructure monitoring is accompanied by the outline of possible future needs for the utilisation of the wealth source of information provided by the satellite radar imagery. (C) 2016 The Authors. Published by Elsevier B.V.