967 resultados para Mobile Services
Resumo:
Nonadherence to treatment is a worldwide problem among people with severe mental disorders. Patient treatment adherence may be supported with simple reminding methods e.g. text message reminders. However, there is limited evidence of its benefits. Intervention evaluation is essential in mHealth research. Therefore, this evaluative study was conducted. This study aimed to evaluate text message reminder use in encouraging patients’treatment adherence among people with antipsychotic medication. The data were collected between September 2011 and December 2013. First, a systematic literature review revealed that text message reminders were widely used in healthcare. However, its impacts were conflicting. Second, a sub-sample (n = 562) analysis showed that patients preferred humorous text message reminders and preferred to receive them in the morning, at the beginning of the week. Age, gender and marital status seemed to have different effects on the preferred amount and timing of the selected reminders. Third, a cross-sectional survey revealed that people with antipsychotic medication (n = 408) expressed overall satisfaction towards the reminder system. Finally, the evaluative design showed that patient recruitment for a randomized controlled trial concerning people with antipsychotic medication was challenging due to low rates of eligible participants. Follow-up drop-out rates varied depending on the data collection method. Participants’ demographic characteristics were associated with the risk of dropping out from the trial. This study suggests that text messages are a potential reminder system in healthcare services among people with antipsychotic medication. More research is needed to gain a comprehensive picture of the impacts and effectiveness of text message reminders.
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Enterprise apps on mobile devices typically need to communicate with other system components by consuming web services. Since most of the current mobile device platforms (such as Android) do not provide built-in features for consuming SOAP services, extensions have to be designed. Additionally in order to accommodate the typical enhanced security requirements of enterprise apps, it is important to be able to deal with SOAP web service security extensions on client side. In this article we show that neither the built-in SOAP capabilities for Android web service clients are sufficient for enterprise apps nor are the necessary security features supported by the platform as is. After discussing different existing extensions making Android devices SOAP capable we explain why none of them is really satisfactory in an enterprise context. Then we present our own solution which accommodates not only SOAP but also the WS-Security features on top of SOAP. Our solution heavily relies on code generation in order to keep the flexibility benefits of SOAP on one hand while still keeping the development effort manageable for software development. Our approach provides a good foundation for the implementation of other SOAP extensions apart from security on the Android platform as well. In addition our solution based on the gSOAP framework may be used for other mobile platforms in a similar manner.
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Despite widespread controversy surrounding zero-rating—that is, the practice of subsidizing mobile data—the field suffers from a lack of inquiry into user understanding of and experience with zero-rated services. This paper explores how Ghanaian mobile users interact with zero-rated mobile applications Free Basics and Wikipedia Zero. Based on semi-structured interviews with users and non-users of the applications, I discuss how mobile phone users perceive Free Basics and Wikipedia Zero, what motivates them to use or not use the applications, and how the availability of the applications influences their data-buying strategies. Findings suggest that respondents, including those who did not actively use the applications, understood and experienced Free Basics and Wikipedia Zero in ways divergent from the providers’ aim of expanding access to online content and services.
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The adoption of Augmented Reality (AR) technologies can make the provision of field services to industrial equipment more effective. In these situations, the cost of deploying skilled technicians in geographically dispersed locations must be accurately traded off with the risks of not respecting the service level agreements with the customers. This paper, through the case study of a leading OEM in the production printing industry, presents the challenges that have to be faced in order to favour the adoption of a particular kind of AR named Mobile Collaborative Augmented Reality (MCAR). In particular, this study uses both qualitative and quantitative research. Firstly, a demonstration to show how MCAR can support field service was settled in order to achieve information about the use experience of the people involved. Then, the entire field force of Océ Italia – Canon Group was surveyed in order to investigate quantitatively the technicians’ perceptions about the usefulness and ease of use of MCAR, as well as their intentions to use this technology.
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Digitalization has been widely adopted by private organizations of all sizes. As customers we are starting to expect a certain level of digital services from businesses and these expectations are evolving to consider the public sector services as well. Moreover, the Finnish municipalities are under pressure to cut costs and make their operation more efficient. This research aims in exploring the field of municipal digitalization in Finland with three main questions to answer: what are the motivations for municipalities for digital service transformation, what the main benefits of this transformation are and what are the challenges for the transformation. The research starts with examining the characteristics of municipal operation and reviewing some of the relevant digital service opportunities. In the empirical part of the research, 11 professionals related to the municipal field were interviewed using a semi-structured interview design. These interviewees were chosen from three important groups for the change: the service provider, municipal administration and municipal employees. The data gained from the interviews was first summarized according to the main topics chosen from the literature and then reflected on the digital services opportunities presented in the research. The motivations discovered in both the service provider and the city of Porvoo interviews were: tightening resources combined with increasing expectations, transparent structuring of information, supporting the shift into mobile and providing new channels for customers to participate. The benefits discovered in all groups were: efficiency, customer experience, transparent structuring of information, reducing manual input and responding to customer needs in service development. The challenges perceived by multiple groups were: change resistance, innovating new with no best practices and defining the scope and new operation model. The results of this research suggest that even with some challenges along the way, digitalization is a likely future for the Finnish public sector. The business case for the transformation is becoming increasingly evident on both municipal- and governmental levels.
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Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.
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This study examines the services provided by the bookmobile of SINABI-Public Libraries in rural communities visited Costa Rica during 2009 and 2010 according to the sample selected for the presentation of a proposed Mobile Library Network to Costa Rica.Each country has very heterogeneous populations and the populations in unfavorable geographical areas (rural or urban fringe areas) and areas without library service or cultural institution, they have specific information needs. By its terms can not exercise the right to information, while urban areas have greater influence and social advantage to have easy access to various information resources.The mobile library services are presented as an ideal tool to deliver library services to any population, mainly those remote communities and vulnerable state as rural areas. Bookmobile is defined as any means of transport (buses, trains, boats, motorcycles, boats, animals, etc.), which shifts documentary material.
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Part 20: Health and Care Networks
Resumo:
Sensor networks are becoming popular nowadays in the development of smart environments. Heavily relying on static sensor and actuators, though, such environments usually lacks of versatility regarding the provided services and interaction capabilities. Here we present a framework for smart environments where a service robot is included within the sensor network acting as a mobile sensor and/or actuator. Our framework integrates on-the-shelf technologies to ensure its adaptability to a variety of sensor technologies and robotic software. Two pilot cases are presented as evaluation of our proposal.
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Nowadays words like Smart City, Internet of Things, Environmental Awareness surround us with the growing interest of Computer Science and Engineering communities. Services supporting these paradigms are definitely based on large amounts of sensed data, which, once obtained and gathered, need to be analyzed in order to build maps, infer patterns, extract useful information. Everything is done in order to achieve a better quality of life. Traditional sensing techniques, like Wired or Wireless Sensor Network, need an intensive usage of distributed sensors to acquire real-world conditions. We propose SenSquare, a Crowdsensing approach based on smartphones and a central coordination server for time-and-space homogeneous data collecting. SenSquare relies on technologies such as CoAP lightweight protocol, Geofencing and the Military Grid Reference System.
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With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.
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Mobile and wireless networks have long exploited mobility predictions, focused on predicting the future location of given users, to perform more efficient network resource management. In this paper, we present a new approach in which we provide predictions as a probability distribution of the likelihood of moving to a set of future locations. This approach provides wireless services a greater amount of knowledge and enables them to perform more effectively. We present a framework for the evaluation of this new type of predictor, and develop 2 new predictors, HEM and G-Stat. We evaluate our predictors accuracy in predicting future cells for mobile users, using two large geolocation data sets, from MDC [11], [12] and Crawdad [13]. We show that our predictors can successfully predict with as low as an average 2.2% inaccuracy in certain scenarios.
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Healthcare systems have assimilated information and communication technologies in order to improve the quality of healthcare and patient's experience at reduced costs. The increasing digitalization of people's health information raises however new threats regarding information security and privacy. Accidental or deliberate data breaches of health data may lead to societal pressures, embarrassment and discrimination. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance. This thesis consists of publications contributing to mHealth security and privacy in various ways: with a comprehensive literature review about mHealth in Brazil; with the design of a security framework for MDCSs (SecourHealth); with the design of a MDCS (GeoHealth); with the design of Privacy Impact Assessment template for MDCSs; and with the study of ontology-based obfuscation and anonymisation functions for health data.
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The idea of Grid Computing originated in the nineties and found its concrete applications in contexts like the SETI@home project where a lot of computers (offered by volunteers) cooperated, performing distributed computations, inside the Grid environment analyzing radio signals trying to find extraterrestrial life. The Grid was composed of traditional personal computers but, with the emergence of the first mobile devices like Personal Digital Assistants (PDAs), researchers started theorizing the inclusion of mobile devices into Grid Computing; although impressive theoretical work was done, the idea was discarded due to the limitations (mainly technological) of mobile devices available at the time. Decades have passed, and now mobile devices are extremely more performant and numerous than before, leaving a great amount of resources available on mobile devices, such as smartphones and tablets, untapped. Here we propose a solution for performing distributed computations over a Grid Computing environment that utilizes both desktop and mobile devices, exploiting the resources from day-to-day mobile users that alternatively would end up unused. The work starts with an introduction on what Grid Computing is, the evolution of mobile devices, the idea of integrating such devices into the Grid and how to convince device owners to participate in the Grid. Then, the tone becomes more technical, starting with an explanation on how Grid Computing actually works, followed by the technical challenges of integrating mobile devices into the Grid. Next, the model, which constitutes the solution offered by this study, is explained, followed by a chapter regarding the realization of a prototype that proves the feasibility of distributed computations over a Grid composed by both mobile and desktop devices. To conclude future developments and ideas to improve this project are presented.
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This study sought to identify factors involved in access to the services of a basic health unit. It is a cross-sectional, population-based study involving 101 randomly-selected families residing in the area covered by the health unit. An adult resident of each household was interviewed. The response variable was whether or not the resident frequented the health unit if he/she or anyone in the family required assistance to resolve a health issue. The independent variables investigated were service provision aspects, demographic and socio-economic characteristics, individual habits, morbidities and use of the health unit. In addition to descriptive and univariate analysis, logistic regression was applied in the multivariate analysis. The results show that access to the basic health unit is associated with the treatment received previously (OR = 3,224) with accessibility (OR = 0,146) and micro-area of residence (OR = 10,918). These findings suggest that access is related to the impressions created by the care received at the health unit and is based on experiences with the service, but can also be strongly modulated by individual aspects and factors related to the territory.