Find: Microsoft designs smart bra to combat emotional eating

Interesting work though I have to think bras are the wrong place for sensors. Really?
 
// published on Ars Technica // visit site
Microsoft designs smart bra to combat emotional eating

Microsoft researchers have developed a bra-mounted sensor system that measures boob sweat and heart activity in order to detect emotional triggers for overeating.

The research is based on the idea that people eat not just when they are hungry but also for a host of emotional and habitual reasons. The goal was to provide a system that could intervene before the person turns to food for emotional support.

Microsoft researchers teamed up with colleagues from the University of Rochester and the University of Southampton to develop a range of interventions that go a step further than activity trackers such as FitBit and Nike's Fuelband. In their paper, the researchers mention other systems that have been developed that include heart rate monitors, earpieces to track chewing and swallowing, and augmented reality glasses to capture the food consumed.

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Spotted: HierarchicalTopics - Visually Exploring Large Text Collections Using Topic Hierarchies


 
 // published on Visualization and Computer Graphics, IEEE Transactions on - new TOC // visit site

HierarchicalTopics: Visually Exploring Large Text Collections Using Topic Hierarchies

Analyzing large textual collections has become increasingly challenging given the size of the data available and the rate that more data is being generated. Topic-based text summarization methods coupled with interactive visualizations have presented promising approaches to address the challenge of analyzing large text corpora. As the text corpora and vocabulary grow larger, more topics need to be generated in order to capture the meaningful latent themes and nuances in the corpora. However, it is difficult for most of current topic-based visualizations to represent large number of topics without being cluttered or illegible. To facilitate the representation and navigation of a large number of topics, we propose a visual analytics system - HierarchicalTopic (HT). HT integrates a computational algorithm, Topic Rose Tree, with an interactive visual interface. The Topic Rose Tree constructs a topic hierarchy based on a list of topics. The interactive visual interface is designed to present the topic content as well as temporal evolution of topics in a hierarchical fashion. User interactions are provided for users to make changes to the topic hierarchy based on their mental model of the topic space. To qualitatively evaluate HT, we present a case study that showcases how HierarchicalTopics aid expert users in making sense of a large number of topics and discovering interesting patterns of topic groups. We have also conducted a user study to quantitatively evaluate the effect of hierarchical topic structure. The study results reveal that the HT leads to faster identification of large number of relevant topics. We have also solicited user feedback during the experiments and incorporated some suggestions into the current version of HierarchicalTopics.

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Spotted: User steered LDA

Like pca and mds, LDA often ids topics that don't make sense to people. Steering might help....

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 // published on Visualization and Computer Graphics, IEEE Transactions on - new TOC // visit site

UTOPIAN: User-Driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization

Topic modeling has been widely used for analyzing text document collections. Recently, there have been significant advancements in various topic modeling techniques, particularly in the form of probabilistic graphical modeling. State-of-the-art techniques such as Latent Dirichlet Allocation (LDA) have been successfully applied in visual text analytics. However, most of the widely-used methods based on probabilistic modeling have drawbacks in terms of consistency from multiple runs and empirical convergence. Furthermore, due to the complicatedness in the formulation and the algorithm, LDA cannot easily incorporate various types of user feedback. To tackle this problem, we propose a reliable and flexible visual analytics system for topic modeling called UTOPIAN (User-driven Topic modeling based on Interactive Nonnegative Matrix Factorization). Centered around its semi-supervised formulation, UTOPIAN enables users to interact with the topic modeling method and steer the result in a user-driven manner. We demonstrate the capability of UTOPIAN via several usage scenarios with real-world document corpuses such as InfoVis/VAST paper data set and product review data sets.

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Spotted: Using smartphones to sense too much smartphone use

But what do you do when you sense it's too much? We hate technology that nags. 
 
// published on Ubiquitous Computing-Latest Proceeding Volume // visit site

Automatically detecting problematic use of smartphones
Choonsung Shin, Anind K. Dey

Smartphone adoption has increased significantly and, with the increase in smartphone capabilities, this means that users can access the Internet, communicate, and entertain themselves anywhere and anytime. However, there is growing evidence of problematic use of smartphones that impacts both social and heath aspects of users' lives. Currently, assessment of overuse or problematic use depends on one-time, self-reported behavioral information about phone use. Due to the known issues with self-reports in such types of assessments, we explore an automated, objective and repeatable approach for assessing problematic usage. We collect a wide range of phone usage data from smartphones, identify a number of usage features that are relevant to this assessment, and build detection models based on Adaboost with machine learning algorithms automatically detecting problematic use.

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Spotted: Technology for finding those little things we've lost

But is this overkill? Maybe we should stop making things that disappear so easily. Certainly for remotes, a "find my remote" function is called for. 

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// published on Ubiquitous Computing-Latest Proceeding Volume // visit site

Find my stuff: supporting physical objects search with relative positioning
Jens Nickels, Pascal Knierim, Bastian Könings, Florian Schaub, Björn Wiedersheim, Steffen Musiol, Michael Weber

Searching for misplaced keys, phones, or wallets is a common nuisance. Find My Stuff (FiMS) provides search support for physical objects inside furniture, on room level, and in multiple locations, e.g., home and office. Stuff tags make objects searchable while all other localization components are integrated into furniture. FiMS requires minimal configuration and automatically adapts to the user's furniture arrangement. Object search is supported with relative position cues, such as "phone is inside top drawer" or "the wallet is between couch and table," which do not require exact object localization. Functional evaluation of our prototype shows the approach's practicality with sufficient accuracy in realistic environments and low energy consumption.

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Spotted: Exploring sustainability research in computing - where we are and where we go next


 
// published on Ubiquitous Computing-Latest Proceeding Volume // visit site

Exploring sustainability research in computing: where we are and where we go next
Bran Knowles, Lynne Blair, Mike Hazas, Stuart Walker

This paper develops a holistic framework of questions which seem to motivate sustainability research in computing in order to enable new opportunities for critique. Analysis of systematically selected corpora of computing publications demonstrates that several of these question areas are well covered, while others are ripe for further exploration. It also provides insight into which of these questions tend to be addressed by different communities within sustainable computing. The framework itself reveals discursive similarities between other existing environmental discourses, enabling reflection and participation with the broader sustainability debate. It is argued that the current computing discourse on sustainability is reformist and premised in a Triple Bottom Line construction of sustainability.

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Spotted: App stores as a source of data for analytics data


 
// published on Human Computer Interaction with Mobile Devices and Services-Latest Proceeding Volume // visit site

Informing future design via large-scale research methods and big data
Mattias Rost, Alistair Morrison, Henriette Cramer, Frank Bentley

With the launch of 'app stores' on several mobile platforms and the great uptake of smartphones among the general population, researchers have begun utilising these distribution channels to deploy research software to large numbers of users. Previous Research In The Large workshops have sought to establish base-line practice in this area. We have seen the use of app stores as being successful as a methodology for gathering large amounts of data, leading to design implications, but we have yet to explore the full potential for this data's use and interpretation. How is it possible to leverage the practices of large-scale research, beyond the current approaches, to more directly inform future designs?

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Spotted: Contextualise! personalise! persuade!: a mobile HCI framework for behaviour change support systems


 // published on Human Computer Interaction with Mobile Devices and Services-Proceeding Volume // visit site

Contextualise! personalise! persuade!: a mobile HCI framework for behaviour change support systems

Sebastian Prost, Johann Schrammel, Kathrin Röderer, Manfred Tscheligi

This paper presents a context-aware, personalised, persuasive (CPP) system design framework applicable to the sustainable transport field and other behaviour change support system domains. It operates on a situational, a user, and a target behaviour layer. Emphasis is placed on interlinking each layer's behaviour change factors for greater effectiveness. A prototype CPP system for more sustainable travel behaviour is introduced to demonstrate how the framework can be applied in practice.

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Find: the ingredients of a successful Redditt submission

Seems like other sites are ripe for this sort or analysis. And visualization too. 

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// published on The Verge - All Posts // visit site

Stanford researchers crack the math behind successful Reddit submissions

It's a social media marketer's dream: a formula for a successful Reddit submission. A team of statisticians at Stanford has spent the past few months analyzing 16,700 pictures on Reddit in order to analyze the impact of content, title, community to which it was submitted, and time of submission. Each picture was submitted an average of 7.9 times, which helped the researchers isolate each factor's impact.

What makes a popular submission to the link aggregator that drives more than 4.8 billion pageviews a month? The answer, of course, is "it depends." The interplay between factors turned out to be hugely important, and different strategies worked for different subreddits, the topic-centric communities on Reddit.

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