36,829 research outputs found
Dynamic Influence Networks for Rule-based Models
We introduce the Dynamic Influence Network (DIN), a novel visual analytics
technique for representing and analyzing rule-based models of protein-protein
interaction networks. Rule-based modeling has proved instrumental in developing
biological models that are concise, comprehensible, easily extensible, and that
mitigate the combinatorial complexity of multi-state and multi-component
biological molecules. Our technique visualizes the dynamics of these rules as
they evolve over time. Using the data produced by KaSim, an open source
stochastic simulator of rule-based models written in the Kappa language, DINs
provide a node-link diagram that represents the influence that each rule has on
the other rules. That is, rather than representing individual biological
components or types, we instead represent the rules about them (as nodes) and
the current influence of these rules (as links). Using our interactive DIN-Viz
software tool, researchers are able to query this dynamic network to find
meaningful patterns about biological processes, and to identify salient aspects
of complex rule-based models. To evaluate the effectiveness of our approach, we
investigate a simulation of a circadian clock model that illustrates the
oscillatory behavior of the KaiC protein phosphorylation cycle.Comment: Accepted to TVCG, in pres
Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention
Deep neural networks, including recurrent networks, have been successfully
applied to human activity recognition. Unfortunately, the final representation
learned by recurrent networks might encode some noise (irrelevant signal
components, unimportant sensor modalities, etc.). Besides, it is difficult to
interpret the recurrent networks to gain insight into the models' behavior. To
address these issues, we propose two attention models for human activity
recognition: temporal attention and sensor attention. These two mechanisms
adaptively focus on important signals and sensor modalities. To further improve
the understandability and mean F1 score, we add continuity constraints,
considering that continuous sensor signals are more robust than discrete ones.
We evaluate the approaches on three datasets and obtain state-of-the-art
results. Furthermore, qualitative analysis shows that the attention learned by
the models agree well with human intuition.Comment: 8 pages. published in The International Symposium on Wearable
Computers (ISWC) 201
WEST: A Web Browser for Small Terminals
We describe WEST, a WEb browser for Small Terminals, that aims to solve some of the problems associated with accessing web pages on hand-held devices. Through a novel combination of text reduction and focus+context visualization, users can access web pages from a very limited display environment, since the system will provide an overview of the contents of a web page even when it is too large to be displayed in its entirety. To make maximum use of the limited resources available on a typical hand-held terminal, much of the most demanding work is done by a proxy server, allowing the terminal to concentrate on the task of providing responsive user interaction. The system makes use of some interaction concepts reminiscent of those defined in the Wireless Application Protocol (WAP), making it possible to utilize the techniques described here for WAP-compliant devices and services that may become available in the near future
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Visualizing pain data for wheelchair users: A ubiquitous approach
Copyright @ 2005 Rinton PressWe describe a wireless enabled solution for the vizualisation of pain data. Our approach uses pain drawings to record spatial location and type of pain and enables data collection with appropriate time stamping, thus providing a means for the seldom-recorded (but often attested) time-varying nature of pain, with consequential impact on monitoring the effectiveness of patient treatment regimes. Moreover, since the implementation platform of our solution is that of a Personal Digital Assistant (PDA), data collection takes place ubiquitously, providing back pain sufferers with mobility problems (such as wheelchair users) with a convenient means of logging their pain data and of seamlessly uploading it to a hospital server using WiFi technology. Stakeholder results show that, notwithstanding problems related to PDA data input, our approach is generally perceived to be an easy to use and convenient solution to the challenges of
anywhere/anytime data collection
Visualizing practical knowledge: The Haughton-Mars Project
To improve how we envision knowledge, we must improve our ability to see knowledge in everyday life. That is, visualization is concerned not only with displaying facts and theories, but also with finding ways to express and relate tacit understanding. Such knowledge, although often referred to as "common," is not necessarily shared and may be distributed socially in choreographies for working togetherÂin the manner that a chef and a maitre dÂhĂŽtel, who obviously possess very different skills, coordinate their work. Furthermore, non-verbal concepts cannot in principle be inventoried. Reifying practical knowledge is not a process of converting the implicit into the explicit, but pointing to what we know, showing its manifestations in our everyday life. To this end, I illustrate the study and reification of practical knowledge by examining the activities of a scientific expedition in the Canadian ArcticÂa group of scientists preparing for a mission to Mar
Pervasive Displays Research: What's Next?
Reports on the 7th ACM International Symposium on Pervasive Displays that took place from June 6-8 in Munich, Germany
Emotions in context: examining pervasive affective sensing systems, applications, and analyses
Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; âsensingâ, âanalysisâ, and âapplicationâ. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing
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