Email-Set Visualization: Facilitating Re-Finding in Email Archives

In this paper we describe ESVT – EmailSet Visualization Tool, an email archive tool that provides users a visualization to re-find and discover information in their email archive. ESVT is an end-to-end email archive tool that can be used from archiving a user’s email messages to visualizing queries on the email archive. We address email archiving by allowing import of email messages from an email server or from a standard existing email client. The central idea in ESVT’s visualization, an “email-set”, is the set of emails that are the result of a query on a user’s email archive. ESVT provides a multiple email-set view - visualization of multiple email-sets on a time axis. In addition, each email set can be individually visualized based on person and time axis, using the single email-set view. Query logs, individual email visualization, multiple email set visualization provide rich contextual cues, thus enabling end users to deal with email overload and re-find past email which otherwise wouldn’t be discovered easily

The role of human-centred design in implementing ICT solutions in WASH projects

Over the past decade in many parts of Sub-Saharan Africa, there has been a continual rise in the advancement of telecommunications, as well as a continual rise in urbanisation. Within this context, a number of sector professionals have acknowledged the potential for the rapid growth in information and communication technologies (ICT) to offer new opportunities to water providers to address some of their enduring challenges. Desille and Faggianelli (2013) emphasise the importance of those both collecting and analysing information to ensure data collected is relevant and regularly updated. Unfortunately, little attention is initially given to catering these systems towards those collecting data. This paper uses lessons learned regarding appropriate and inappropriate design approaches in ICT projects in the WASH sector to showcase two case studies implemented by the social enterprise, SeeSaw. Despite SeeSaw’s attempt to incorporate the personalities, incentivise, and motivations of the reporters at the onset of the project, some challenges still remain. These results suggest both the challenges avoided when design considerations incorporate those collecting information, but also the challenges that still remain – and that future research can help clarify

Orthogonal Gradient Descent for Continual Learning

Neural networks are achieving state of the art and sometimes super-human performance on learning tasks across a variety of domains. Whenever these problems require learning in a continual or sequential manner, however, neural networks suffer from the problem of catastrophic forgetting; they forget how to solve previous tasks after being trained on a new task, despite having the essential capacity to solve both tasks if they were trained on both simultaneously. In this paper, we propose to address this issue from a parameter space perspective and study an approach to restrict the direction of the gradient updates to avoid forgetting previously-learned data. We present the Orthogonal Gradient Descent (OGD) method, which accomplishes this goal by projecting the gradients from new tasks onto a subspace in which the neural network output on previous task does not change and the projected gradient is still in a useful direction for learning the new task. Our approach utilizes the high capacity of a neural network more efficiently and does not require storing the previously learned data that might raise privacy concerns. Experiments on common benchmarks reveal the effectiveness of the proposed OGD method

Ambient Assistive Technologies (AAT): socio-technology as a powerful tool for facing the inevitable sociodemographic challenges?

Due to the socio-demographic change in most developed western countries, elderly populations have been continuously increasing. Therefore, preventive and assistive systems that allow elderly people to independently live in their own homes as long as possible will become an economical if not ethical necessity. These respective technologies are being developed under the term "Ambient Assistive Technologies" (AAT). The EU-funded AAT-project Ambient Lighting Assistance for an Ageing Population (ALADIN) has established the long-term goal to create an adaptive system capable of improving the residential lighting conditions of single living elderly persons also aiming at supporting the preservation of their independence

The best way to conduct intervention research: methodological considerations

This article is a theoretical contribution to the debate about which qualitative interventionmethodology is best suited to building stronger partnerships between researchers and practitioners in educational research. In the first part of this article, two types of intervention methodologies gaining impact in the field are contrasted in light of Yrjö Engeström’s criticism. This discussion lays the groundwork for the main claim in the second part of this article that dialogical work between researchers and practitioners focusing on ‘contradictions’ and the ‘object of activity,’ can provide analytical tools to improve understanding of challenges in intervention research

Orthogonal Gradient Descent for Continual Learning

Neural networks are achieving state of the art and sometimes super-human performance on learning tasks across a variety of domains. Whenever these problems require learning in a continual or sequential manner, however, neural networks suffer from the problem of catastrophic forgetting; they forget how to solve previous tasks after being trained on a new task, despite having the essential capacity to solve both tasks if they were trained on both simultaneously. In this paper, we propose to address this issue from a parameter space perspective and study an approach to restrict the direction of the gradient updates to avoid forgetting previously-learned data. We present the Orthogonal Gradient Descent (OGD) method, which accomplishes this goal by projecting the gradients from new tasks onto a subspace in which the neural network output on previous task does not change and the projected gradient is still in a useful direction for learning the new task. Our approach utilizes the high capacity of a neural network more efficiently and does not require storing the previously learned data that might raise privacy concerns. Experiments on common benchmarks reveal the effectiveness of the proposed OGD method

Exploring the adaptive capacity of emergency management using agent based modelling

This project aimed to explore the suitability of Agent Based Modelling and Simulation (ABMS) technology in assisting planners and policy makers to better understand complex situations with multiple interacting aspects. The technology supports exploration of the impact of different factors on potential outcomes of a scenario, thus building understanding to inform decision making. To concretise this exploration a specific simulation tool was developed to explore response capacity around flash flooding in an inner Melbourne suburb, with a focus on sandbag depots as an option to be considered.The three types of activities delivered by this project to achieve its objectives were the development of an agent-based simulation, data collection to inform the development of the simulation and communication and engagement activities to progress the work. Climate change is an area full of uncertainties, and yet sectors such as Emergency Management and many others need to develop plans and policy responses regarding adaptation to these uncertain futures. Agent Based Modelling and Simulation is a technology which supports modelling of a complex situation from the bottom up, by modelling the behaviours of individual agents (often representing humans) in various scenarios. By running simulations with different configurations it is possible to explore and analyse a very broad range of potential options, providing a detailed understanding of potential risks and outcomes, given particular alternatives. This project explored the suitability of this technology for use in assessing and developing the capacity of the emergency response sector, as it adapts to climate change. A simulation system was developed to explore a particular issue regarding protection of property in a suburb prone to flash flooding. In particular the option of providing sandbag depots was explored. Simulations indicated that sandbag depots provided by CoPP or VicSES were at this time not a viable option. The simulation tool was deemed to be very useful for demonstrating this to community members as well as to decision makers. An interactive game was also developed to assist in raising awareness of community members about how to sandbag their property using on-site sandbags. The technology was deemed to be of great potential benefit to the sector and areas for further work inorder to realise this benefit were identified. In addition to developing awareness of useful technology, this project also demonstrated the critical importance of interdisciplinary team work, and close engagement with stakeholders and end users, if valuable technology uptake is to be realised. &nbsp