Gamer Style: Performance Factors in Gamified Simulation
Gamification
/
Gupta, Surabhi
/
Coles, Tim
/
Dumas, Cedric
/
McBride, Simon J.
/
Bradford, DanaKai
Proceedings of the ACM CHI'16 Conference on Human Factors in Computing
Systems
2016-05-07
v.1
p.2014-2025
© Copyright 2016 ACM
Summary: Serious games and gamified simulations are increasingly being used to aid
instruction in technical disciplines including the medical field. Assessments
of player performance are important in understanding user profiles in order to
establish serious games as a reliable, consistent method for increasing skills
and competence in all trainees. In this study we used questionnaires, game
characteristic metrics and EEG analysis to explore players' performance in a
bronchoscopy simulator. We found that players who performed better were
younger, made fewer errors, were quicker and differed in spectral profile
during game play. Our findings, while speculative, have implications for
training regimes in which gamified simulations are employed. We make
suggestions for game design and for tailoring training regimes to suit
individual learning styles to enhance knowledge acquisition and retention.
EGDE, A Soft Keyboard for Fast Typing for the Visually Challenged
Student Design Competition
/
Rajendran, Chandni
/
Parab, Chinmay
/
Gupta, Shreya
Extended Abstracts of the ACM CHI'16 Conference on Human Factors in
Computing Systems
2016-05-07
v.2
p.50-55
© Copyright 2016 ACM
Summary: EDGE is an accessible text-input overlay on touch screen phones that is
designed specifically to enable speedier typing by users with vision
impairment. The model uses the edges of the phone because all the tactile
references available on a touch screen are concentrated along the edges. The
characters are laid out along the edges in the same grouping as a 3x4
International Standard Key Pad, building on users' familiarity [1]. It can be
initiated in the same manner as any keyboard service on a smart phone. However,
it occupies the full extent of the screen as an overlay and can be dismissed by
an on-screen gesture. The model has the ability to switch between single-tap
and multi-tap mode and features that provide context awareness while typing.
Along with text prediction as an added feature, EDGE could be a very effective
text input method that visually impaired users will be able to use with
confidence even without audio feedback.
Tackling User Research Challenges within the Finance Industry
Case Study: User Research
/
Wehbe, Rina R.
/
Wahid, Shahtab
/
Gupta, Siddharth
/
Ishak, Edward W.
Extended Abstracts of the ACM CHI'16 Conference on Human Factors in
Computing Systems
2016-05-07
v.2
p.796-803
© Copyright 2016 ACM
Summary: We present a case study illustrating how a user experience (UX) team
performs user research in the finance industry. In particular, we focus on the
impact of salespeople and financial professionals on how the research is
conducted. Challenges stemming from this -- such as recruitment, time
constraints, and conflicting expectations -- and potential ways to mitigate
them are discussed. Our work contributes to an understanding of how to do
research in time-sensitive, high pressure environments while also working with
gatekeepers to accessing users.
SCEPTRE: A Pervasive, Non-Invasive, and Programmable Gesture Recognition
Technology
Wearable and Mobile IUI 1
/
Paudyal, Prajwal
/
Banerjee, Ayan
/
Gupta, Sandeep K. S.
Proceedings of the 2016 International Conference on Intelligent User
Interfaces
2016-03-07
v.1
p.282-293
© Copyright 2016 ACM
Summary: Communication and collaboration between deaf people and hearing people is
hindered by lack of a common language. Although there has been a lot of
research in this domain, there is room for work towards a system that is
ubiquitous, non-invasive, works in real-time and can be trained interactively
by the user. Such a system will be powerful enough to translate gestures
performed in real-time, while also being flexible enough to be fully
personalized to be used as a platform for gesture based HCI. We propose SCEPTRE
which utilizes two non-invasive wrist-worn devices to decipher gesture-based
communication. The system uses a multi-tiered template based comparison system
for classification on input data from accelerometer, gyroscope and
electromyography (EMG) sensors. This work demonstrates that the system is very
easily trained using just one to three training instances each for twenty
randomly chosen signs from the American Sign Language (ASL) dictionary and also
for user-generated custom gestures. The system is able to achieve an accuracy
of 97.72% for ASL gestures.
MagnifiSense: inferring device interaction using wrist-worn passive
magneto-inductive sensors
Novel sensing techniques
/
Wang, Edward J.
/
Lee, Tien-Jui
/
Mariakakis, Alex
/
Goel, Mayank
/
Gupta, Sidhant
/
Patel, Shwetak N.
Proceedings of the 2015 International Conference on Ubiquitous Computing
2015-09-07
p.15-26
© Copyright 2015 ACM
Summary: The different electronic devices we use on a daily basis produce distinct
electromagnetic radiation due to differences in their underlying electrical
components. We present MagnifiSense, a low-power wearable system that uses
three passive magneto-inductive sensors and a minimal ADC setup to identify the
device a person is operating. MagnifiSense achieves this by analyzing
near-field electromagnetic radiation from common components such as the motors,
rectifiers, and modulators. We conducted a staged, in-the-wild evaluation where
an instrumented participant used a set of devices in a variety of settings in
the home such as cooking and outdoors such as commuting in a vehicle.
MagnifiSense achieves a classification accuracy of 82.6% using a model-agnostic
classifier and 94.0% using a model-specific classifier. In a 24-hour
naturalistic deployment, MagnifiSense correctly identified 25 of the total 29
events, while achieving a low false positive rate of 0.65% during 20.5 hours of
non-activity.
EVHomeShifter: evaluating intelligent techniques for using electrical
vehicle batteries to shift when homes draw energy from the grid
Smarter homes and vehicles
/
Brush, A. J. Bernheim
/
Krumm, John
/
Gupta, Sidhant
/
Patel, Shwetak
Proceedings of the 2015 International Conference on Ubiquitous Computing
2015-09-07
p.1077-1088
© Copyright 2015 ACM
Summary: Time of use tiered pricing schedules encourage shifting electricity demand
from peak to off-peak hours. Charging times for electric vehicles (EV) can be
shifted into overnight hours, which are usually off-peak. EVs can also be used
as energy storage devices, available during certain peak hours to power a house
with electricity stored during off-peak hours. Studies suggest both techniques
are practical, but were based on simulated demand patterns or large commercial
fleets. To investigate feasibility on a per home basis, we collected data from
15 EV homes using the Lab of Things sensing infrastructure. We evaluate a
scheme that powers homes with their car battery during expensive electricity
periods and then charges the battery during cheaper periods. We show an average
potential savings of $10.91/month for shifting charging times, and an
additional $13.58/month for powering the home from the EV, even accounting for
the inefficiencies of electric conversion.
Identifying Successful Investors in the Startup Ecosystem
Posters
/
Gupta, Srishti
/
Pienta, Robert
/
Tamersoy, Acar
/
Chau, Duen Horng
/
Basole, Rahul C.
Companion Proceedings of the 2015 International Conference on the World Wide
Web
2015-05-18
v.2
p.39-40
© Copyright 2015 ACM
Summary: Who can spot the next Google, Facebook, or Twitter? Who can discover the
next billion-dollar startups? Measuring investor success is a challenging task,
as investment strategies can vary widely. We propose InvestorRank, a novel
method for identifying successful investors by analyzing how an investor's
collaboration network change over time. InvestorRank captures the intuition
that a successful investor achieves increasingly success in spotting great
startups, or is able to keep doing so persistently. Our results show potential
in discovering relatively unknown investors that may be the success stories of
tomorrow.
Constructing Secure Audio CAPTCHAs by Exploiting Differences between Humans
and Machines
Enhanced Security with Passwords & CAPTCHAs
/
Meutzner, Hendrik
/
Gupta, Santosh
/
Kolossa, Dorothea
Proceedings of the ACM CHI'15 Conference on Human Factors in Computing
Systems
2015-04-18
v.1
p.2335-2338
© Copyright 2015 ACM
Summary: To prevent abuses of Internet services, CAPTCHAs are used to distinguish
humans from programs where an audio-based scheme is beneficial to support
visually impaired people. Previous studies show that most audio CAPTCHAs,
albeit hard to solve for humans, are lacking security strength. In this work we
propose an audio CAPTCHA that is far more robust against automated attacks than
it is reported for current CAPTCHA schemes. The CAPTCHA exhibits a good
trade-off between human usability and security. This is achieved by exploiting
the fact that the human capabilities of language understanding and speech
recognition are clearly superior compared to current machines. We evaluate the
CAPTCHA security by using a state-of-the-art attack and assess the
intelligibility by means of a large-scale listening experiment.
Forum77: An Analysis of an Online Health Forum Dedicated to Addiction
Recovery
Managing Chronic Illness through Collaboration
/
MacLean, Diana
/
Gupta, Sonal
/
Lembke, Anna
/
Manning, Christopher
/
Heer, Jeffrey
Proceedings of ACM CSCW 2015 Conference on Computer-Supported Cooperative
Work and Social Computing
2015-02-28
v.1
p.1511-1526
© Copyright 2015 ACM
Summary: Prescription drug abuse is a pressing public health issue, and people who
misuse prescription drugs are turning to online forums for help. Are such
forums effective? We analyze the process of opioid withdrawal, recovery and
relapse on Forum77, MedHelp.org's online health forum for substance abuse
recovery. Applying Prochashka's Transtheoretical Model for behavior change, we
develop a taxonomy describing phases of addiction expressed by Forum77 members.
We examine activity and linguistic features across the phases USING,
WITHDRAWING and RECOVERING. We train statistical classifiers to identify
addiction phase, relapse and whether a user was RECOVERING at the time of her
last post. Applying our classifiers to 2,848 users, we find that while almost
50% relapse, the prognosis for ending in RECOVERING is favorable. Supplementing
our results with users' own accounts of their experiences, we discuss Forum77's
efficacy and shortcomings, and implications for future technologies.
Stemming the Flow of Information in a Social Network
News, Credibility, and Opinion Formation
/
Srinivasan, Balaji Vasan
/
Kumar, Akshay
/
Gupta, Shubham
/
Gupta, Khushi
Proceedings of the 2014 International Conference on Social Informatics
2014-11-11
p.326-335
Keywords: social network; rumor source; rumor stemming; targeted influence
© Copyright 2014 Springer
Summary: Social media has changed the way people interact with each other and has
contributed greatly towards bringing people together. It has become an ideal
platform for people to share their opinions. However, due to the volatility of
social networks, a negative campaign or a rumor can go viral resulting in
severe impact to the community. In this paper, we aim to solve this problem of
stemming the flow of a negative campaign in a network by observing only parts
of the network. Given a negative campaign and information about the status of
its spread through a few candidate nodes, our algorithm estimates the
information flow in the network and based on this estimated flow, finds a set
of nodes which would be instrumental in stemming the information flow. The
proposed algorithm is tested on real-world networks and its effectiveness is
compared against other existing works.
How heterogeneous community engage newcomers? The effect of community
diversity on newcomers' perception of inclusion: An empirical study in social
media service
/
Pan, Zhao
/
Lu, Yaobin
/
Gupta, Sumeet
Computers in Human Behavior
2014-10
v.39
n.0
p.100-111
Keywords: Community diversity
Keywords: Perceived inclusion
Keywords: Social identification
Keywords: Perceived uniqueness
Keywords: Newcomers
Keywords: Engagement
© Copyright 2014 Elsevier Ltd.
Summary: Online communities that provide social media services need to engage
newcomers so as to not lose them to competitors. This study examines the role
of community diversity (in terms of perceived visible dissimilarity, perceived
informational dissimilarity and perceived value dissimilarity) in influencing
perceived inclusion of newcomers in the online community and the influence of
such perception on newcomers' engagement intention. The theoretical background
on perceived inclusion is obtained from the optimal distinctiveness theory,
which comprises of two dimensions, namely, social identification and perceived
uniqueness. The results support the multiple roles of community diversity on a
newcomer's perceived inclusion. The findings of this study contribute to a
better understanding of the effect of community diversity on newcomers'
engagement behavior, and provide recommendations on designing a personalized
community diversity environment.
A self-calibrating approach to whole-home contactless power consumption
sensing
Sensing in the home
/
Aumi, Md Tanvir Islam
/
Gupta, Sidhant
/
Pickett, Cameron
/
Reynolds, Matt
/
Patel, Shwetak
Proceedings of the 2014 International Joint Conference on Pervasive and
Ubiquitous Computing
2014-09-13
v.1
p.361-371
© Copyright 2014 ACM
Summary: In this paper, we present a significant improvement over past work on
non-contact end-user deployable sensor for real time whole home power
consumption. The technique allows users to place a single device consisting of
magnetic pickups on the outside of a power or breaker panel to infer whole home
power consumption without the need for professional installation of current
transformers (CTs). The new approach does not require precise placement on the
breaker panel, a key requirement in previous approaches. This is enabled
through a self-calibration technique using a neural network that dynamically
learns the transfer function despite the placement of the sensor and the
construction of the breaker panel itself. We also demonstrate the ability to
actually infer true power using this technique, unlike past solutions that have
only been able to capture apparent power. We have evaluated our technique in
six homes and one industrial building, including one seven-day deployment. Our
results show we can estimate true power consumption with an average accuracy of
95.0% during naturalistic energy use in the home.
Data mapping framework in a digital library with computational epidemiology
datasets
Other
/
Hasan, S. M. Shamimul
/
Gupta, Sandeep
/
Fox, Edward A.
/
Bisset, Keith
/
Marathe, Madhav V.
JCDL'14: Proceedings of the 2014 ACM/IEEE-CS Joint Conference on Digital
Libraries
2014-09-08
p.449-450
Keywords: Computational modeling
Keywords: Data models
Keywords: Diseases
Keywords: Libraries
Keywords: Resource description framework
Keywords: Sociology
Keywords: Statistics
Keywords: Digital library
Keywords: Epidemiology
Keywords: Simulation
© Copyright 2014 IEEE
Summary: Computational epidemiology employs computer models and informatics tools to
reason about the spatio-temporal spread of diseases. The diversity of models,
data sources, data representations, and modalities that are collected, used,
and modified motivate the development of a digital library (DL) framework to
support computational epidemiology. The heterogeneous content includes
metadata, text, tables, spreadsheets, experimental descriptions, and large
result files. There is no accepted framework that allows unified access to such
content. We propose a framework for a digital library system tailored to such
datasets to support computational network epidemiology.
SCQAM: a scalable structured code quality assessment method for industrial
software
Software Quality
/
Gupta, Shrinath
/
Singh, Himanshu Kumar
/
Venkatasubramanyam, Radhika D.
/
Uppili, Umesh
Proceedings of the 2014 International Conference on Program Comprehension
2014-06-02
p.244-252
© Copyright 2014 ACM
Summary: Siemens, Corporate Technology, Development Center, Asia Australia (CT DC AA)
has been developing and maintaining several software projects for the Industry,
Energy, Healthcare, and Infrastructure & Cities sectors of Siemens. The
critical nature of these projects necessitates a high level of software code
quality. As part of the code quality program at CT DC AA the strategy is to
have a scalable method towards identification of issues affecting code quality
of projects across the organization. Traditionally, code quality experts in
Siemens used EMISQ method to assess code quality. EMISQ requires about three
person months (two experts for six weeks) for 50-100 kLoC, making it effort
intensive and time consuming. Thus, scaling this assessment method to include
the hundreds of projects in CT DC AA poses many challenges. To address this, we
have developed a lightweight assessment method called SCQAM (Structured Code
Quality Assessment Method). SCQAM is an expert-based method wherein manual
assessment of code quality by experts is directed by the systematic application
of code analysis tools. In this paper, we describe the SCQAM method,
experiences in applying it to projects in CT DC AA, challenges faced and
initiatives taken to enable fixing of systemic issues reported by assessments.
The insights from our SCQAM experience can provide useful pointers to other
organizations and practitioners interested in assessment and improvement of
software code quality.
A semiautomated method for classifying program analysis rules into a quality
model
Software Quality
/
Gupta, Shrinath
/
Singh, Himanshu Kumar
Proceedings of the 2014 International Conference on Program Comprehension
2014-06-02
p.266-270
© Copyright 2014 ACM
Summary: Most of the software code quality assessment and monitoring methods uses
Quality Model (QM) as an aid to capture quality requirements of the software.
An important aspect concerning use of QM is classification of Program Analysis
(PA) rules into QM according to their relevance to quality attributes such as
maintainability, reliability etc. Currently such classification is performed
manually by experts and most of the PA tools (such as FxCop for C#, FindBugs
for Java, PC-Lint for C/C++) support hundreds of PA rules. Hence performing
classification manually can be very effort intensive and time consuming and can
lead to concerns like subjectivity and inconsistency. Hence we propose a light
weight semiautomated method to expedite classification and make classification
activity less effort intensive. Proposed classifier is based on natural
language processing (NLP) techniques and uses a keyword matching algorithm. We
have computed precision and recall for such a classifier. We have also shown
results from applying technique on classifying rules from FxCop, PC-Lint, and
FindBugs into the EMISQ QM. We believe that proposed approach will
significantly help in reducing the time required to perform classification and
hence also to incorporate newer PA tools and rules into QM based methods.
PuppetX: a framework for gestural interactions with user constructed
playthings
Tangibles
/
Gupta, Saikat
/
Jang, Sujin
/
Ramani, Karthik
Proceedings of the 2014 International Conference on Advanced Visual
Interfaces
2014-05-27
p.73-80
© Copyright 2014 ACM
Summary: We present PuppetX, a framework for both constructing playthings and playing
with them using spatial body and hand gestures. This framework allows users to
construct various playthings similar to puppets with modular components
representing basic geometric shapes. It is topologically-aware, i.e. depending
on its configuration; PuppetX automatically determines its own topological
construct. Once the plaything is made the users can interact with them
naturally via body and hand gestures as detected by depth-sensing cameras. This
gives users the freedom to create playthings using our components and the
ability to control them using full body interactions. Our framework creates
affordances for a new variety of gestural interactions with physically
constructed objects. As its by-product, a virtual 3D model is created, which
can be animated as a proxy to the physical construct. Our algorithms can
recognize hand and body gestures in various configurations of the playthings.
Through our work, we push the boundaries of interaction with user-constructed
objects using large gestures involving the whole body or fine gestures
involving the fingers. We discuss the results of a study to understand how
users interact with the playthings and conclude with a demonstration of the
abilities of gestural interactions with PuppetX by exploring a variety of
interaction scenarios.
Emotion recognition using facial and audio features
Emotion recognition in the wild challenge and workshop
/
Krishna, Tarun
/
Rai, Ayush
/
Bansal, Shubham
/
Khandelwal, Shubham
/
Gupta, Shubham
/
Goel, Dushyant
Proceedings of the 2013 International Conference on Multimodal Interaction
2013-12-09
p.557-564
© Copyright 2013 ACM
Summary: Human Computer Interaction is an upcoming scientific field which aims at
inter-communication between humans and computers. A major element of this field
is Human Emotion Recognition. The most expressive way humans display emotions
is through facial expressions. Traditionally, emotion recognition has been
performed on laboratory controlled data. While undoubtedly worthwhile at the
time, such lab controlled data poorly represents the environment and conditions
faced in real-world situations. With the increase in the number of video clips
online, it is worthwhile to explore the performance of emotion recognition
methods that work 'in the wild'. This work mainly focuses on automatic emotion
recognition in a wild video sample. In this task, we have worked on the problem
of human emotion recognition using a combination of video features and audio
features. The technique that we have utilized for emotion detection involves a
blend of Optical flow, Gabor Filtering, few other facial features and audio
features. Training and Classification is performed using Support Vector
Machine-Hidden Markov Model (HMM). The unique thing about our methodology is
that it produces better results for some particular class of emotions as
compared to the baseline score in the case of wild emotion dataset with an
overall accuracy of 20.51% on the test set.
Flexible and dynamic compromises for effective recommendations
Poster session: IR track
/
Gupta, Saurabh
/
Chakraborti, Sutanu
Proceedings of the 2013 ACM Conference on Information and Knowledge
Management
2013-10-27
p.1909-1912
© Copyright 2013 ACM
Summary: Conversational Recommendation mimics the kind of dialog that takes between a
customer and a shopkeeper involving multiple interactions where the user can
give feedback at every interaction as opposed to Single Shot Retrieval, which
corresponds to a scheme where the system retrieves a set of items in response
to a user query in a single interaction. Compromise refers to a particular user
preference which the recommender system failed to satisfy. But in the context
of conversational systems, where the user's preferences keep on evolving as she
interacts with the system, what constitutes as a compromise for her also keeps
on changing. Typically, in Single Shot retrieval, the notion of compromise is
characterized by the assignment of a particular feature to a particular
dominance group such as MIB (higher value is better) or LIB (lower value is
better) and this assignment remains true for all the users who use the system.
In this paper, we propose a way to realize the notion of compromise in a
conversational setting. Our approach, Flexi-Comp, introduces the notion of
dynamically assigning a feature to two dominance groups simultaneously which is
then used to redefine the notion of compromise. We show experimentally that a
utility function based on this notion of compromise outperforms the existing
conversational recommenders in terms of recommendation efficiency.
Knowledge sharing in information system development teams: examining the
impact of shared mental model from a social capital theory perspective
Article
/
Xiang, Chunjie
/
Lu, Yaobin
/
Gupta, Sumeet
Behaviour and Information Technology
2013-10-01
v.32
n.10
p.1024-1040
© Copyright 2013 Taylor and Francis
Summary: Shared mental model (SMM), a concept from psychology, is defined as a common
thinking style developed when individuals perform similar tasks in a cohesive
manner. In this article, we investigate the relationship between the three
dimensions of social capital and SMM. We also examine whether SMM mediates the
impact of social capital on knowledge sharing (KS) behaviour in information
system development (ISD) teams. Social capital is defined as the resource of
social relationships owned by individuals. It is useful for explaining human
behaviour in social networks. The data collected represent 492 ISD
professionals in 118 teams from 18 middle-sized enterprises. The results of
this study indicate that social capital theory is useful for explaining the
antecedents of SMM, and SMM is positively related to KS and team performance.
This research also emphasises the importance of developing SMM in a team.
Glassbeam search: big data analytics & object oriented UX framework
APCHI 2013: industrial case studies
/
Mahapatra, Jyotirmaya
/
Rathore, Porus
/
Gupta, Swati
/
Sridharamurthy, Pramod
Proceedings of the 2013 Asia Pacific Conference on Computer Human
Interaction
2013-09-24
p.237-241
© Copyright 2013 ACM
Summary: Glassbeam Support is a cloud based Machine log data analytics and search
application. It allows Data centers, Networking servers, OEMs and IT
Enterprises to quickly search for data sources and insights related to any
machine.
Due to the complexity of data within log files, the existing interface
supported a lot of features, which were not aligned to actual user behavior.
This made the product complex and various features were left unexplored. The
existing system presented itself with inefficient navigation and performance
latency issues. Glassbeam required a complete re-design of 'Search', which
could be intuitive and scalable to different kinds of log files across domains.
To achieve this, an 'Object Oriented' user experience design framework was
used where a 'Central Object' around which the entire application and
functionalities could be aligned.
The redesigned application reduced the time to narrow down to problems and
troubleshoot issues in minutes instead of days. The overall usability of the
system was enhanced and it supported a broader number of use cases. It
empowered enterprises with end-to-end log data analytics, support their
support, RnD and Sales forecasting activities.
AirWave: non-contact haptic feedback using air vortex rings
Novel interfaces
/
Gupta, Sidhant
/
Morris, Dan
/
Patel, Shwetak N.
/
Tan, Desney
Proceedings of the 2013 International Joint Conference on Pervasive and
Ubiquitous Computing
2013-09-08
v.1
p.419-428
© Copyright 2013 ACM
Summary: Input modalities such as speech and gesture allow users to interact with
computers without holding or touching a physical device, thus enabling
at-a-distance interaction. It remains an open problem, however, to incorporate
haptic feedback into such interaction. In this work, we explore the use of air
vortex rings for this purpose. Unlike standard jets of air, which are turbulent
and dissipate quickly, vortex rings can be focused to travel several meters and
impart perceptible feedback. In this paper, we review vortex formation theory
and explore specific design parameters that allow us to generate vortices
capable of imparting haptic feedback. Applying this theory, we developed a
prototype system called AirWave. We show through objective measurements that
AirWave can achieve spatial resolution of less than 10 cm at a distance of 2.5
meters. We further demonstrate through a user study that this can be used to
direct tactile stimuli to different regions of the human body.
DopLink: using the Doppler effect for multi-device interaction
Mobile devices
/
Aumi, Md Tanvir Islam
/
Gupta, Sidhant
/
Goel, Mayank
/
Larson, Eric
/
Patel, Shwetak
Proceedings of the 2013 International Joint Conference on Pervasive and
Ubiquitous Computing
2013-09-08
v.1
p.583-586
© Copyright 2013 ACM
Summary: Mobile and embedded electronics are pervasive in today's environment. As
such, it is necessary to have a natural and intuitive way for users to indicate
the intent to connect to these devices from a distance. We present DopLink, an
ultrasonic-based device selection approach. It utilizes the already embedded
audio hardware in smart devices to determine if a particular device is being
pointed at by another device (i.e., the user waves their mobile phone at a
target in a pointing motion). We evaluate the accuracy of DopLink in a
controlled user study, showing that, within 3 meters, it has an average
accuracy of 95% for device selection and 97% for finding relative device
position. Finally, we show three applications of DopLink: rapid device pairing,
home automation, and multi-display synchronization.
DysWebxia 2.0!: more accessible text for people with dyslexia
The Paciello group challenge
/
Rello, Luz
/
Bayarri, Clara
/
Gòrriz, Azuki
/
Baeza-Yates, Ricardo
/
Gupta, Saurabh
/
Kanvinde, Gaurang
/
Saggion, Horacio
/
Bott, Stefan
/
Carlini, Roberto
/
Topac, Vasile
Proceedings of the 2013 International Cross-Disciplinary Conference on Web
Accessibility (W4A)
2013-05-13
p.25
© Copyright 2013 ACM
Summary: Even if dyslexia is neurological in origin, certain text modifications could
make texts more accessible for people with dyslexia. We introduce DysWebxia
2.0, a model that integrates our findings from research conducted with this
target group. It alters content and presentation of the text to make it more
readable. We also present the current integrations of DysWebxia in different
reading software applications.
uTouch: sensing touch gestures on unmodified LCDs
Papers: haptics
/
Chen, Ke-Yu
/
Cohn, Gabe A.
/
Gupta, Sidhant
/
Patel, Shwetak N.
Proceedings of ACM CHI 2013 Conference on Human Factors in Computing Systems
2013-04-27
v.1
p.2581-2584
© Copyright 2013 ACM
Summary: Current solutions for enabling touch interaction on existing non-touch LCD
screens require adding additional sensors to the interaction surface. We
present uTouch, a system that detects and classifies touches and hovers without
any modification to the display, and without adding any sensors to the user.
Our approach utilizes existing signals in an LCD that are amplified when a user
brings their hand near or touches the LCD's front panel. These signals are
coupled onto the power lines, where they appear as electromagnetic interference
(EMI) which can be sensed using a single device connected elsewhere on the
power line infrastructure. We validate our approach with an 11 user, 8 LCD
study, and demonstrate a real-time system.
Dynamic Spatial Positioning: Physical Collaboration around Interactive Table
by Children in India
Tabletop Computing
/
Jamil, Izdihar
/
O'Hara, Kenton
/
Perry, Mark
/
Karnik, Abhijit
/
Marshall, Mark T.
/
Jha, Swathi
/
Gupta, Sanjay
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Subramanian, Sriram
Proceedings of IFIP INTERACT'13: Human-Computer Interaction-4
2013
v.4
p.141-158
Keywords: Interaction techniques; tabletop; spatial formation; dynamic spatial
position; collaborative learning; children and India
© Copyright 2013 IFIP
Summary: We present a study of how children demonstrate physicality during
collaboration around interactive tables at school. Our results show that
children tend to dynamically position themselves around the tabletop area to
effect particular social outcomes. These movements around the tabletop allow
them to enact coordination strategies in their social interactions with each
other to manage their learning and task-based activities. Our analysis
indicates the importance of understanding physical strategies and behaviours
when designing and deploying interactive tables in classrooms. We discuss how
the design of tabletops in school can embrace the extensibility of this
technology, providing access for children to shape their own collaboration
strategies during learning.
