Towards memory supporting personal information management tools

In this article we discuss re-retrieving personal information objects and relate the task to recovering from lapse(s) in memory. We propose that fundamentally it is lapses in memory that impede users from successfully re-finding the information they need. Our hypothesis is that by learning more about memory lapses in non-computing contexts and how people cope and recover from these lapses, we can better inform the design of PIM tools and improve the user's ability to re-access and re-use objects. We describe a diary study that investigates the everyday memory problems of 25 people from a wide range of backgrounds. Based on the findings, we present a series of principles that we hypothesize will improve the design of personal information management tools. This hypothesis is validated by an evaluation of a tool for managing personal photographs, which was designed with respect to our findings. The evaluation suggests that users' performance when re-finding objects can be improved by building personal information management tools to support characteristics of human memory

Mobile Informal Language Learning: Exploring Welsh Learners’ Practices

Mobile devices have great potential in supporting language learning, through providing access to vocabulary, lessons and resources, and supporting interactions with other speakers. There may be particular advantages, however, in using such technologies for learning minority languages. Welsh is a minority UK language spoken by around 611,000 people in Wales and there is considerable interest among adults in Wales and from Welsh families in learning Welsh. However the small numbers of speakers and their uneven distribution make it difficult for learners outside Welsh speaking “hotspots” to hear and practice Welsh. Mobile learning therefore has great potential for Welsh learners by providing resources wherever the learner is and by supporting web-based learning communities. The study reported here investigates whether this potential is being exploited in practice. It employed interviews and a small survey to study the practices of Welsh learners at all levels. It was found that learners used mobile technologies widely, to access a wide range of resources, although not always on-the-move, and also that many were using courses, in particular one online course. Learners’ practices in using digital technologies for their Welsh language learning are discussed, and also the implications for both learning other minority languages and for informal mobile learning more generally

Managed Forgetting to Support Information Management and Knowledge Work

Trends like digital transformation even intensify the already overwhelming mass of information knowledge workers face in their daily life. To counter this, we have been investigating knowledge work and information management support measures inspired by human forgetting. In this paper, we give an overview of solutions we have found during the last five years as well as challenges that still need to be tackled. Additionally, we share experiences gained with the prototype of a first forgetful information system used 24/7 in our daily work for the last three years. We also address the untapped potential of more explicated user context as well as features inspired by Memory Inhibition, which is our current focus of research.Comment: 10 pages, 2 figures, preprint, final version to appear in KI - K\"unstliche Intelligenz, Special Issue: Intentional Forgettin

Code In The Air: Simplifying Sensing and Coordination Tasks on Smartphones

A growing class of smartphone applications are tasking applications that run continuously, process data from sensors to determine the user's context (such as location) and activity, and optionally trigger certain actions when the right conditions occur. Many such tasking applications also involve coordination between multiple users or devices. Example tasking applications include location-based reminders, changing the ring-mode of a phone automatically depending on location, notifying when friends are nearby, disabling WiFi in favor of cellular data when moving at more than a certain speed outdoors, automatically tracking and storing movement tracks when driving, and inferring the number of steps walked each day. Today, these applications are non-trivial to develop, although they are often trivial for end users to state. Additionally, simple implementations can consume excessive amounts of energy. This paper proposes Code in the Air (CITA), a system which simplifies the rapid development of tasking applications. It enables non-expert end users to easily express simple tasks on their phone, and more sophisticated developers to write code for complex tasks by writing purely server-side scripts. CITA provides a task execution framework to automatically distribute and coordinate tasks, energy-efficient modules to infer user activities and compose them, and a push communication service for mobile devices that overcomes some shortcomings in existing push services.National Science Foundation (U.S.) (Grant 0931550

The Innovative Use of Personal Smart Devices by Students to Support their Learning

Research into the autonomous use of MP3 audio recorders by students in UK Higher Education demonstrated that students were innovative in their autonomous use of the devices. They used them to capture learning conversations from formal and informal situations to personalise and enhance their learning. However, today smartphones and other smart devices have replaced the necessity for students to carry multiply mobile devices including MP3 recorders. This chapter builds upon the earlier work and presents a small qualitative study into how students are autonomously using their smart devices to support their learning. The research explores the hypothesis that students are being innovative in the ways in which they are use their smart devices to support their formal and informal learning. The study involved five students who own smart devices who were invited to discuss their ownership of smartphone and tablet technologies and the ways they used them in their studies. The students first completed a short questionnaire and were then interviewed in small groups. The results agree with previous research into the student use of smart devices and describe autonomous engagement facilitated by personally owned smart technologies. The study identifies continuous patterns of pervasive engagement by students and concludes that more thought should be given to disruptive innovation, digital literacy and employability

Real-time human action recognition on an embedded, reconfigurable video processing architecture

Copyright @ 2008 Springer-Verlag.In recent years, automatic human motion recognition has been widely researched within the computer vision and image processing communities. Here we propose a real-time embedded vision solution for human motion recognition implemented on a ubiquitous device. There are three main contributions in this paper. Firstly, we have developed a fast human motion recognition system with simple motion features and a linear Support Vector Machine (SVM) classifier. The method has been tested on a large, public human action dataset and achieved competitive performance for the temporal template (eg. “motion history image”) class of approaches. Secondly, we have developed a reconfigurable, FPGA based video processing architecture. One advantage of this architecture is that the system processing performance can be reconfiured for a particular application, with the addition of new or replicated processing cores. Finally, we have successfully implemented a human motion recognition system on this reconfigurable architecture. With a small number of human actions (hand gestures), this stand-alone system is performing reliably, with an 80% average recognition rate using limited training data. This type of system has applications in security systems, man-machine communications and intelligent environments.DTI and Broadcom Ltd

FPGA implementation of real-time human motion recognition on a reconfigurable video processing architecture

In recent years, automatic human motion recognition has been widely researched within the computer vision and image processing communities. Here we propose a real-time embedded vision solution for human motion recognition implemented on a ubiquitous device. There are three main contributions in this paper. Firstly, we have developed a fast human motion recognition system with simple motion features and a linear Support Vector Machine(SVM) classifier. The method has been tested on a large, public human action dataset and achieved competitive performance for the temporal template (eg. ``motion history image") class of approaches. Secondly, we have developed a reconfigurable, FPGA based video processing architecture. One advantage of this architecture is that the system processing performance can be reconfigured for a particular application, with the addition of new or replicated processing cores. Finally, we have successfully implemented a human motion recognition system on this reconfigurable architecture. With a small number of human actions (hand gestures), this stand-alone system is performing reliably, with an 80% average recognition rate using limited training data. This type of system has applications in security systems, man-machine communications and intelligent environments