919 resultados para NFC Android Pagamenti Ricariche smartphone


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Private data stored on smartphones is a precious target for malware attacks. A constantly changing environment, e.g. switching network connections, can cause unpredictable threats, and require an adaptive approach to access control. Context-based access control is using dynamic environmental information, including it into access decisions. We propose an "ecosystem-in-an-ecosystem" which acts as a secure container for trusted software aiming at enterprise scenarios where users are allowed to use private devices. We have implemented a proof-of-concept prototype for an access control framework that processes changes to low-level sensors and semantically enriches them, adapting access control policies to the current context. This allows the user or the administrator to maintain fine-grained control over resource usage by compliant applications. Hence, resources local to the trusted container remain under control of the enterprise policy. Our results show that context-based access control can be done on smartphones without major performance impact.

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Static anaylsis represents an approach of checking source code or compiled code of applications before it gets executed. Chess and McGraw state that static anaylsis promises to identify common coding problems automatically. While manual code checking is also a form of static analysis, software tools are used in most cases in order to perform the checks. Chess and McGraw additionaly claim that good static checkers can help to spot and eradicate common security bugs.

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Driving can be dangerous, especially for young and inexperienced drivers. To help address the issue of inexperience a gamified logbook application was developed for Learner drivers. The application aims to encourage learners to undertake a wider range of practice, while also making it easier to record their mandatory practice sessions. This paper reports on the design of this application, focusing on the effect that adding gamification can have on the usability and user experience of the application and the importance of playability testing for gamified systems. Two versions of the application were developed, one with game elements and one without game elements. This paper presents findings from a study that compares the user experience of these two versions of the application with twelve recent Learner drivers. Overall, participants reported that the gamified version was more engaging and motivating than the non-gamified version, however neither versions were preferred over the other. We theorise that this may have occurred due to a number of usability issues that arose, including an increased difficulty in learnability due to the added game elements. These design issues are important to address in future gamified system designs.

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This chapter gives an overview of the smartphone app economy and its various constituent ecosystems. It examines the role of the app store model and the proliferation of mobile apps in the shift from value chains controlled by network operators and handset manufacturers, to value networks – or ecosystems – focused around operating systems and apps. It outlines some of the benefits and disadvantages for developers of the app store model for remuneration and distribution. The chapter concludes with a discussion of recent research on the size and employment effects of the app economy.

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The banking industry is under pressure. In order to compete, banks should adapt to concentrating on the specific customer needs, following an outside-in perspective. This paper presents the design of a business model for banks that considers this development by providing flexible and comprehensive support for retail banking clients. It is demonstrated that the identification of customer processes and the consequent alignment of banking services to those processes implies great potential to increase customer retention in banking. It will be shown that information technology – especially smartphones – can serve as an interface between customer and suppliers to enable an alignment of offerings to customer processes. This approach enables the integration of banks into their customers’ lifestyle, creating emotional value added, improving the personal relationship and the customers’ affiliation with the bank. The paper presents the design of such a customer-process-centric smartphone application and derives success factors for implementation.

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Background Rapid developments in technology have encouraged the use of smartphones in physical activity research, although little is known regarding their effectiveness as measurement and intervention tools. Objective This study systematically reviewed evidence on smartphones and their viability for measuring and influencing physical activity. Data Sources Research articles were identified in September 2013 by literature searches in Web of Knowledge, PubMed, PsycINFO, EBSCO, and ScienceDirect. Study Selection The search was restricted using the terms (physical activity OR exercise OR fitness) AND (smartphone* OR mobile phone* OR cell phone*) AND (measurement OR intervention). Reviewed articles were required to be published in international academic peer-reviewed journals, or in full text from international scientific conferences, and focused on measuring physical activity through smartphone processing data and influencing people to be more active through smartphone applications. Study Appraisal and Synthesis Methods Two reviewers independently performed the selection of articles and examined titles and abstracts to exclude those out of scope. Data on study characteristics, technologies used to objectively measure physical activity, strategies applied to influence activity; and the main study findings were extracted and reported. Results A total of 26 articles (with the first published in 2007) met inclusion criteria. All studies were conducted in highly economically advantaged countries; 12 articles focused on special populations (e.g. obese patients). Studies measured physical activity using native mobile features, and/or an external device linked to an application. Measurement accuracy ranged from 52 to 100 % (n = 10 studies). A total of 17 articles implemented and evaluated an intervention. Smartphone strategies to influence physical activity tended to be ad hoc, rather than theory-based approaches; physical activity profiles, goal setting, real-time feedback, social support networking, and online expert consultation were identified as the most useful strategies to encourage physical activity change. Only five studies assessed physical activity intervention effects; all used step counts as the outcome measure. Four studies (three pre–post and one comparative) reported physical activity increases (12–42 participants, 800–1,104 steps/day, 2 weeks–6 months), and one case-control study reported physical activity maintenance (n = 200 participants; >10,000 steps/day) over 3 months. Limitations Smartphone use is a relatively new field of study in physical activity research, and consequently the evidence base is emerging. Conclusions Few studies identified in this review considered the validity of phone-based assessment of physical activity. Those that did report on measurement properties found average-to-excellent levels of accuracy for different behaviors. The range of novel and engaging intervention strategies used by smartphones, and user perceptions on their usefulness and viability, highlights the potential such technology has for physical activity promotion. However, intervention effects reported in the extant literature are modest at best, and future studies need to utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better explore the physical activity measurement and intervention capabilities of smartphones.

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Background The capacity to diagnosys, quantify and evaluate movement beyond the general confines of a clinical environment under effectiveness conditions may alleviate rampant strain on limited, expensive and highly specialized medical resources. An iPhone 4® mounted a three dimensional accelerometer subsystem with highly robust software applications. The present study aimed to evaluate the reliability and concurrent criterion-related validity of the accelerations with an iPhone 4® in an Extended Timed Get Up and Go test. Extended Timed Get Up and Go is a clinical test with that the patient get up from the chair and walking ten meters, turn and coming back to the chair. Methods A repeated measure, cross-sectional, analytical study. Test-retest reliability of the kinematic measurements of the iPhone 4® compared with a standard validated laboratory device. We calculated the Coefficient of Multiple Correlation between the two sensors acceleration signal of each subject, in each sub-stage, in each of the three Extended Timed Get Up and Go test trials. To investigate statistical agreement between the two sensors we used the Bland-Altman method. Results With respect to the analysis of the correlation data in the present work, the Coefficient of Multiple Correlation of the five subjects in their triplicated trials were as follows: in sub-phase Sit to Stand the ranged between r = 0.991 to 0.842; in Gait Go, r = 0.967 to 0.852; in Turn, 0.979 to 0.798; in Gait Come, 0.964 to 0.887; and in Turn to Stand to Sit, 0.992 to 0.877. All the correlations between the sensors were significant (p < 0.001). The Bland-Altman plots obtained showed a solid tendency to stay at close to zero, especially on the y and x-axes, during the five phases of the Extended Timed Get Up and Go test. Conclusions The inertial sensor mounted in the iPhone 4® is sufficiently reliable and accurate to evaluate and identify the kinematic patterns in an Extended Timed Get and Go test. While analysis and interpretation of 3D kinematics data continue to be dauntingly complex, the iPhone 4® makes the task of acquiring the data relatively inexpensive and easy to use.

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The significant physical, emotional, educational and social developmental challenges faced by adolescents and young adults are associated with high levels of emotional vulnerability. Thus, the development and use of effective emotion-regulation strategies during this period is critical. Music listening is commonly used by young people to identify, express, enhance and regulate their emotions. Modern mobile technology provides an engaging, easily accessible means of assisting young people with identifying and managing emotions through music. A systematic contextual review of iPhone applications addressing emotions through music was conducted. Their quality was evaluated by two independent raters using the Mobile App Rating Scale (MARS). Three participatory design workshops (PDW; N=13, 6 males, 7 females; age 15-25) were conducted, exploring young people’s use of music to enhance wellbeing. Young people were also asked to trial existing mood and music apps and to conceptualise their ultimate mood-targeting music application. Of the identified 117 music apps, 20 met inclusion criteria (to play songs, not sounds; priced below $5.00). Characteristics and overall quality of the music apps are described and key features of the five highest- rating apps are presented. Thematic analysis of the PDW content identified the following music affect- regulation strategies: relationship building, modifying cognitions, modifying emotions, and immersing in emotions (i.e. habituation or mood enhancement). The application of key learnings from the mobile app review and PDW to the design and development of the new music eScape app will be presented. Implications for future research and for applying the new app in clinical practice are discussed.

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Background People with intellectual disabilities (ID) have lower levels of physical activity and quality of life and they have a lot of barriers to face when taking part in physical activity. Other problems are the poor adherence to physical activity such people have so this study is designed to improve adherence to physical activity for people with intellectual disabilities with the assistance of an application for smartphones. The aim of the study will be to improve physical activity and physical condition after multimodal intervention and to analyse the promotion of adherence to physical activity through a multimodal intervention and an app intervention (mHealth) in people with ID. Methods A two-stage study will be conducted. In stage 1 a multimodal intervention will take place will be done with physical activity and educational advice over eight weeks, two days a week. Data will be measured after and before the intervention. In stage 2 a randomized controlled trial will be conducted. In the intervention group we will install an application to a smartphone; this application will be a reminder to do a physical activity and they have to select whether they have or haven’t done a physical activity every day. This application will be installed for 18 weeks. Data will be measured after and before the application is installed in two groups. We will measure results 10 weeks later when the two groups don’t have the reminder. The principal outcome used to measure the adherence to physical activity will be the International Physical Activity Questionnaire; secondary outcomes will be a fun-fitness test and self-report survey about quality of life, self-efficacy and social support. Samples will be randomized by sealed envelope in two groups, with approximately 20 subjects in each group. It’s important to know that the therapist will be blinded and won’t know the subjects of each group. Discussion Offering people with ID a multimodal intervention and tool to increase the adherence to a physical activity may increase the levels of physical activity and quality of life. Such a scheme, if beneficial, could be implemented successfully within public health sense. Trial registration ClinicalTrials.gov Identifier: NCT01915381.

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Development of irrigation sceduling application for Smartphone use by irrigators and consultants.

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- Objective This study examined chronic disease risks and the use of a smartphone activity tracking application during an intervention in Australian truck drivers (April-October 2014). - Methods Forty-four men (mean age=47.5 [SD 9.8] years) completed baseline health measures, and were subsequently offered access to a free wrist-worn activity tracker and smartphone application (Jawbone UP) to monitor step counts and dietary choices during a 20-week intervention. Chronic disease risks were evaluated against guidelines; weekly step count and dietary logs registered by drivers in the application were analysed to evaluate use of the Jawbone UP. - Results Chronic disease risks were high (e.g. 97% high waist circumference [≥94 cm]). Eighteen drivers (41%) did not start the intervention; smartphone technical barriers were the main reason for drop out. Across 20-weeks, drivers who used the Jawbone UP logged step counts for an average of 6 [SD 1] days/week; mean step counts remained consistent across the intervention (weeks 1–4=8,743[SD 2,867] steps/day; weeks 17–20=8,994[SD 3,478] steps/day). The median number of dietary logs significantly decreased from start (17 [IQR 38] logs/weeks) to end of the intervention (0 [IQR 23] logs/week; p<0.01); the median proportion of healthy diet choices relative to total diet choices logged increased across the intervention (weeks 1–4=38[IQR 21]%; weeks 17–20=58[IQR 18]%). - Conclusions Step counts were more successfully monitored than dietary choices in those drivers who used the Jawbone UP. - Implications Smartphone technology facilitated active living and healthy dietary choices, but also prohibited intervention engagement in a number of these high-risk Australian truck drivers.

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Programming environments for smartphones expose a concurrency model that combines multi-threading and asynchronous event-based dispatch. While this enables the development of efficient and feature-rich applications, unforeseen thread interleavings coupled with non-deterministic reorderings of asynchronous tasks can lead to subtle concurrency errors in the applications. In this paper, we formalize the concurrency semantics of the Android programming model. We further define the happens-before relation for Android applications, and develop a dynamic race detection technique based on this relation. Our relation generalizes the so far independently studied happens-before relations for multi-threaded programs and single-threaded event-driven programs. Additionally, our race detection technique uses a model of the Android runtime environment to reduce false positives. We have implemented a tool called DROIDRACER. It generates execution traces by systematically testing Android applications and detects data races by computing the happens-before relation on the traces. We analyzed 1 5 Android applications including popular applications such as Facebook, Twitter and K-9 Mail. Our results indicate that data races are prevalent in Android applications, and that DROIDRACER is an effective tool to identify data races.

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El presente proyecto tiene como finalidad realizar aplicaciones de realidad aumentada en Android. Como al desarrollar dichas aplicaciones se han reutilizado librerías existentes implementadas en C++, también se ha realizado un estudio de las alternativas para poder incluirlas en una aplicación Android.