18,114 research outputs found
Investigating UI displacements in an Adaptive Mobile Homescreen
The authors present a system that adapts application shortcuts (apps) on the homescreen of an Android smartphone, and investigate the effect of UI displacements that are caused by the choice of adaptive model and the order of apps in the homescreen layout. They define UI displacements to be the distance that items move between adaptations, and they use this as a measure of stability. An experiment with 12 participants is performed to evaluate the impact of UI displacements on the homescreen. To make the distribution of apps in the experiment task less contrived, naturally generated data from a pilot study is used. The authorsâ results show that selection time is correlated to the magnitude of the previous UI displacement. Additionally, selection time and subjective rating improve significantly when the model is easy to understand and an alphabetical order is used, conditions that increase stability. However, rank order is preferred when the model updates frequently and is less easy to understand. The authors present their approach to adapting apps on the homescreen, and initial insights into UI displacements
Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges
Today's mobile phones are far from mere communication devices they were ten
years ago. Equipped with sophisticated sensors and advanced computing hardware,
phones can be used to infer users' location, activity, social setting and more.
As devices become increasingly intelligent, their capabilities evolve beyond
inferring context to predicting it, and then reasoning and acting upon the
predicted context. This article provides an overview of the current state of
the art in mobile sensing and context prediction paving the way for
full-fledged anticipatory mobile computing. We present a survey of phenomena
that mobile phones can infer and predict, and offer a description of machine
learning techniques used for such predictions. We then discuss proactive
decision making and decision delivery via the user-device feedback loop.
Finally, we discuss the challenges and opportunities of anticipatory mobile
computing.Comment: 29 pages, 5 figure
Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol
The screening of digital footprint for clinical purposes relies on the capacity of wearable technologies
to collect data and extract relevant informationâs for patient management. Artificial intelligence (AI) techniques
allow processing of real-time observational information and continuously learning from data to build
understanding. We designed a system able to get clinical sense from digital footprints based on the smartphoneâs
native sensors and advanced machine learning and signal processing techniques in order to identify suicide risk.
Method/design: The Smartcrisis study is a cross-national comparative study. The study goal is to determine the
relationship between suicide risk and changes in sleep quality and disturbed appetite. Outpatients from the
Hospital FundaciĂłn JimĂ©nez DĂaz Psychiatry Department (Madrid, Spain) and the University Hospital of Nimes
(France) will be proposed to participate to the study. Two smartphone applications and a wearable armband will
be used to capture the data. In the intervention group, a smartphone application (MEmind) will allow for the
ecological momentary assessment (EMA) data capture related with sleep, appetite and suicide ideations.
Discussion: Some concerns regarding data security might be raised. Our system complies with the highest level of
security regarding patientsâ data. Several important ethical considerations related to EMA method must also be
considered. EMA methods entails a non-negligible time commitment on behalf of the participants. EMA rely on
daily, or sometimes more frequent, Smartphone notifications. Furthermore, recording participantsâ daily experiences
in a continuous manner is an integral part of EMA. This approach may be significantly more than asking a
participant to complete a retrospective questionnaire but also more accurate in terms of symptoms monitoring.
Overall, we believe that Smartcrises could participate to a paradigm shift from the traditional identification of risks
factors to personalized prevention strategies tailored to characteristics for each patientThis study was partly funded by FundaciĂłn JimĂ©nez DĂaz Hospital, Instituto
de Salud Carlos III (PI16/01852), DelegaciĂłn del Gobierno para el Plan
Nacional de Drogas (20151073), American Foundation for Suicide Prevention
(AFSP) (LSRG-1-005-16), the Madrid Regional Government (B2017/BMD-3740
AGES-CM 2CM; Y2018/TCS-4705 PRACTICO-CM) and Structural Funds of the
European Union. MINECO/FEDER (âADVENTUREâ, id. TEC2015â69868-C2â1-R)
and MCIU Explora Grant âaMBITIONâ (id. TEC2017â92552-EXP), the French Embassy
in Madrid, Spain, The foundation de lâavenir, and the Fondation de
France. The work of D. RamĂrez and A. ArtĂ©s-RodrĂguez has been partly supported
by Ministerio de EconomĂa of Spain under projects: OTOSIS
(TEC2013â41718-R), AID (TEC2014â62194-EXP) and the COMONSENS Network
(TEC2015â69648-REDC), by the Ministerio de EconomĂa of Spain jointly with
the European Commission (ERDF) under projects ADVENTURE (TEC2015â
69868-C2â1-R) and CAIMAN (TEC2017â86921-C2â2-R), and by the Comunidad
de Madrid under project CASI-CAM-CM (S2013/ICE-2845). The work of P.
Moreno-Muñoz has been supported by FPI grant BES-2016-07762
Going beyond Quietness: Determining the Emotionally Restorative Effect of Acoustic Environments in Urban Open Public Spaces
The capacity of natural settings to promote psychological restoration has attracted increasing research attention, especially with regards to the visual dimension. However, there is a need to extend these studies to urban settings, such as squares, parks or gardens, due to the global trend towards urbanisation, and to integrate the dimension of sound into landscape. Such was the main aim of this study, in which 53 participants assessed four public spaces in Vitoria-Gasteiz (Spain) as part of the CITI-SENSE Project (137 observations were used for analysis). A smartphone application was used to simultaneously collect objective and subjective data. The results show that at the end of the urban environmental experience, there was a statistically significant reduction in negative emotions and perceived stress, and a slight increase in positive emotions. Emotional restoration was mainly associated with prior emotional states, but also with global environmental comfort and acoustic comfort. The soundscape characteristics that contributed to greater emotional restoration and a reduction in perceived stress were pleasantness, calm, fun and naturalness. Therefore, in agreement with previous research, the findings of the present study indicate that besides contributing to the quietness of the urban environment, the urban soundscape can promote psychological restoration in users of these spaces.This research formed part of the CITI-SENSE project funded under the European Union Seventh Framework Programme for research, technological development and demonstration, grant agreement no 308524
Context-driven progressive enhancement of mobile web applications: a multicriteria decision-making approach
Personal computing has become all about mobile and embedded devices. As a result, the adoption rate of smartphones is rapidly increasing and this trend has set a need for mobile applications to be available at anytime, anywhere and on any device. Despite the obvious advantages of such immersive mobile applications, software developers are increasingly facing the challenges related to device fragmentation. Current application development solutions are insufficiently prepared for handling the enormous variety of software platforms and hardware characteristics covering the mobile eco-system. As a result, maintaining a viable balance between development costs and market coverage has turned out to be a challenging issue when developing mobile applications. This article proposes a context-aware software platform for the development and delivery of self-adaptive mobile applications over the Web. An adaptive application composition approach is introduced, capable of autonomously bypassing context-related fragmentation issues. This goal is achieved by incorporating and validating the concept of fine-grained progressive application enhancements based on a multicriteria decision-making strategy
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