Researching homelessness: Challenging exclusion?

This themed issue of Social Inclusion provides a timely opportunity to reflect on how contemporary research is addressing the multi-dimensional issue of homelessness around the world. The papers presented here provide a wide range of new evidence on homelessness including theoretical, methodological and empirical contributions. They draw on a range of national experiences in Europe and beyond, and addressing the issue of social inclusion and social exclusion of homeless or previously homeless people from a range of perspectives and approaches. It is hoped that the contributions to this themed issue will prove influential in terms of both scholarship and potential to enhance policy making and service delivery to some of our most excluded citizens.

A service-oriented user interaction analysis framework supporting adaptive applications

A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.

Delivering mobile cloud services to the user: description, discovery, and consumption

The mobile cloud computing paradigm can offer relevant and useful services to the users of smart mobile devices. Such public services already exist on the web and in cloud deployments, by implementing common web service standards. However, these services are described by mark-up languages, such as XML, that cannot be comprehended by non-specialists. Furthermore, the lack of common interfaces for related services makes discovery and consumption difficult for both users and software. The problem of service description, discovery, and consumption for the mobile cloud must be addressed to allow users to benefit from these services on mobile devices. This paper introduces our work on a mobile cloud service discovery solution, which is utilised by our mobile cloud middleware, Context Aware Mobile Cloud Services (CAMCS). The aim of our approach is to remove complex mark-up languages from the description and discovery process. By means of the Cloud Personal Assistant (CPA) assigned to each user of CAMCS, relevant mobile cloud services can be discovered and consumed easily by the end user from the mobile device. We present the discovery process, the architecture of our own service registry, and service description structure. CAMCS allows services to be used from the mobile device through a user's CPA, by means of user defined tasks. We present the task model of the CPA enabled by our solution, including automatic tasks, which can perform work for the user without an explicit request.

Investigation into a best practice model for providing an integrated user experience with mobile cloud applications

Mobile Cloud Computing promises to overcome the physical limitations of mobile devices by executing demanding mobile applications on cloud infrastructure. In practice, implementing this paradigm is difficult; network disconnection often occurs, bandwidth may be limited, and a large power draw is required from the battery, resulting in a poor user experience. This thesis presents a mobile cloud middleware solution, Context Aware Mobile Cloud Services (CAMCS), which provides cloudbased services to mobile devices, in a disconnected fashion. An integrated user experience is delivered by designing for anticipated network disconnection, and low data transfer requirements. CAMCS achieves this by means of the Cloud Personal Assistant (CPA); each user of CAMCS is assigned their own CPA, which can complete user-assigned tasks, received as descriptions from the mobile device, by using existing cloud services. Service execution is personalised to the user's situation with contextual data, and task execution results are stored with the CPA until the user can connect with his/her mobile device to obtain the results. Requirements for an integrated user experience are outlined, along with the design and implementation of CAMCS. The operation of CAMCS and CPAs with cloud-based services is presented, specifically in terms of service description, discovery, and task execution. The use of contextual awareness to personalise service discovery and service consumption to the user's situation is also presented. Resource management by CAMCS is also studied, and compared with existing solutions. Additional application models that can be provided by CAMCS are also presented. Evaluation is performed with CAMCS deployed on the Amazon EC2 cloud. The resource usage of the CAMCS Client, running on Android-based mobile devices, is also evaluated. A user study with volunteers using CAMCS on their own mobile devices is also presented. Results show that CAMCS meets the requirements outlined for an integrated user experience.

The impact of user charges on patient choice of healthcare services in Ireland

This research assesses the impact of user charges in the context of consumer choice to ascertain how user charges in healthcare impact on patient behaviour in Ireland. Quantitative data is collected from a subset of the population in walk-in Urgent Care Clinics and General Practitioner surgeries to assess their responses to user charges and whether user charges are a viable source of part-funding healthcare in Ireland. Examining the economic theories of Becker (1965) and Grossman (1972), the research has assessed the impact of user charges on patient choice in terms of affordability and accessibility in healthcare. The research examined a number of private, public and part-publicly funded healthcare services in Ireland for which varying levels of user charges exist depending on patients’ healthcare cover. Firstly, the study identifies the factors affecting patient choice of privately funded walk-in Urgent Care Clinics in Ireland given user charges. Secondly, the study assesses patient response to user charges for a mainly public or part-publicly provided service; prescription drugs. Finally, the study examines patients’ attitudes towards the potential application of user charges for both public and private healthcare services when patient choice is part of a time-money trade-off, convenience choice or preference choice. These services are valued in the context of user charges becoming more prevalent in healthcare systems over time. The results indicate that the impact of user charges on healthcare services vary according to socio-economic status. The study shows that user charges can disproportionately affect lower income groups and consequently lead to affordability and accessibility issues. However, when valuing the potential application of user charges for three healthcare services (MRI scans, blood tests and a branded over a generic prescription drug), this research indicates that lower income individuals are willing to pay for healthcare services, albeit at a lower user charge than higher income earners. Consequently, this study suggests that user charges may be a feasible source of part-financing Irish healthcare, once the user charge is determined from the patients’ perspective, taking into account their ability to pay.

A next application prediction service using the BaranC framework

Predicting user behaviour enables user assistant services provide personalized services to the users. This requires a comprehensive user model that can be created by monitoring user interactions and activities. BaranC is a framework that performs user interface (UI) monitoring (and collects all associated context data), builds a user model, and supports services that make use of the user model. A prediction service, Next-App, is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts, based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic, reflecting the current context, and is also dynamic in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.