14,156 research outputs found

    Augmenting entry: the possibilities for utilizing geo-referenced information to improve mobile calendar applications

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    Today's mobile communication devices often offer extensive calendar facilities. However the use of these is often very limited through cumbersome interfaces and inappropriate designs for small devices. Prompted by previous work in mobile calendar usability, this paper discusses how augmentation of calendar entries with mobile spatial information could provide potential advantages and improve the usability of an electronic calendar

    Keyword based categorisation of diary entries to support personal Internet content pre-caching on mobile devices

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    This paper presents a study into the effectiveness of our algorithm for automatic categorisation of real users' diary entries, as a first step towards personal Internet content pre-caching on mobile devices. The study reports an experiment comparing trial subjects allocations of 99 diary entries to those predicted by a keyword-based algorithm. While leaving considerable grounds for improvement, results are positive and show pave the way for supporting mobile services based on categorising users' diary entries

    A novel Big Data analytics and intelligent technique to predict driver's intent

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    Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

    Harnessing Collaborative Technologies: Helping Funders Work Together Better

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    This report was produced through a joint research project of the Monitor Institute and the Foundation Center. The research included an extensive literature review on collaboration in philanthropy, detailed analysis of trends from a recent Foundation Center survey of the largest U.S. foundations, interviews with 37 leading philanthropy professionals and technology experts, and a review of over 170 online tools.The report is a story about how new tools are changing the way funders collaborate. It includes three primary sections: an introduction to emerging technologies and the changing context for philanthropic collaboration; an overview of collaborative needs and tools; and recommendations for improving the collaborative technology landscapeA "Key Findings" executive summary serves as a companion piece to this full report

    Smartphones Adoption and Usage of 50+ Adults in the United Kingdom

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    This is an Accepted Manuscript of a book chapter published by Routledge in Jyoti Choudrie, Sherah Kurnia, and Panayiota Tsatsou, eds., Social Inclusion and Usability of ICT-enabled Services, on October 2017, available online at: https://www.routledge.com/Social-Inclusion-and-Usability-of-ICT-enabled-Services/Choudrie-Kurnia-Tsatsou/p/book/9781138935556. Under embargo until 30 April 2019.Peer reviewedFinal Accepted Versio

    PDAs as Time Management Tools: Experiences with Mobile Digital Calendars

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    A Methodology for Engineering Collaborative and ad-hoc Mobile Applications using SyD Middleware

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    Today’s web applications are more collaborative and utilize standard and ubiquitous Internet protocols. We have earlier developed System on Mobile Devices (SyD) middleware to rapidly develop and deploy collaborative applications over heterogeneous and possibly mobile devices hosting web objects. In this paper, we present the software engineering methodology for developing SyD-enabled web applications and illustrate it through a case study on two representative applications: (i) a calendar of meeting application, which is a collaborative application and (ii) a travel application which is an ad-hoc collaborative application. SyD-enabled web objects allow us to create a collaborative application rapidly with limited coding effort. In this case study, the modular software architecture allowed us to hide the inherent heterogeneity among devices, data stores, and networks by presenting a uniform and persistent object view of mobile objects interacting through XML/SOAP requests and responses. The performance results we obtained show that the application scales well as we increase the group size and adapts well within the constraints of mobile devices

    Self-monitoring Practices, Attitudes, and Needs of Individuals with Bipolar Disorder: Implications for the Design of Technologies to Manage Mental Health

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    Objective To understand self-monitoring strategies used independently of clinical treatment by individuals with bipolar disorder (BD), in order to recommend technology design principles to support mental health management. Materials and Methods Participants with BD (N = 552) were recruited through the Depression and Bipolar Support Alliance, the International Bipolar Foundation, and WeSearchTogether.org to complete a survey of closed- and open-ended questions. In this study, we focus on descriptive results and qualitative analyses. Results Individuals reported primarily self-monitoring items related to their bipolar disorder (mood, sleep, finances, exercise, and social interactions), with an increasing trend towards the use of digital tracking methods observed. Most participants reported having positive experiences with technology-based tracking because it enables self-reflection and agency regarding health management and also enhances lines of communication with treatment teams. Reported challenges stem from poor usability or difficulty interpreting self-tracked data. Discussion Two major implications for technology-based self-monitoring emerged from our results. First, technologies can be designed to be more condition-oriented, intuitive, and proactive. Second, more automated forms of digital symptom tracking and intervention are desired, and our results suggest the feasibility of detecting and predicting emotional states from patterns of technology usage. However, we also uncovered tension points, namely that technology designed to support mental health can also be a disruptor. Conclusion This study provides increased understanding of self-monitoring practices, attitudes, and needs of individuals with bipolar disorder. This knowledge bears implications for clinical researchers and practitioners seeking insight into how individuals independently self-manage their condition as well as for researchers designing monitoring technologies to support mental health management
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