[1]
Checksum gestures: continuous gestures as an out-of-band channel for secure
pairing
Secruity tricks
/
Ahmed, Imtiaj
/
Ye, Yina
/
Bhattacharya, Sourav
/
Asokan, N.
/
Jacucci, Giulio
/
Nurmi, Petteri
/
Tarkoma, Sasu
Proceedings of the 2015 International Conference on Ubiquitous Computing
2015-09-07
p.391-401
© Copyright 2015 ACM
Summary: We propose the use of a single continuous gesture as a novel, intuitive, and
efficient mechanism to authenticate a secure communication channel. Our
approach builds on a novel algorithm for encoding (at least 20-bits)
authentication information as a single continuous gesture, referred to as a
checksum gesture. By asking the user to perform the generated gesture, a secure
channel can be authenticated. Results from a controlled user experiment (N = 13
participants, 1022 trials) demonstrate the feasibility of our technique,
showing over 90% success rate in establishing a secure communication channel
despite relying on complex gesture patterns. The authentication times of our
method are over three-folds faster than with previous gesture-based solutions.
The average execution time of a gesture is 5:7 seconds in our study, which is
comparable to the input time of conventional text input based PIN
authentication. Our approach is particularly well-suited for scenarios
involving wearable devices that lack conventional input capabilities, e.g.,
pairing a smartwatch with an interactive display.
[2]
Predicting Viewer Perceived Emotions in Animated GIFs
Multimedia Grand Challenge
/
Jou, Brendan
/
Bhattacharya, Subhabrata
/
Chang, Shih-Fu
Proceedings of the 2014 ACM International Conference on Multimedia
2014-11-03
p.213-216
© Copyright 2014 ACM
Summary: Animated GIFs are everywhere on the Web. Our work focuses on the
computational prediction of emotions perceived by viewers after they are shown
animated GIF images. We evaluate our results on a dataset of over 3,800
animated GIFs gathered from MIT's GIFGIF platform, each with scores for 17
discrete emotions aggregated from over 2.5M user annotations -- the first
computational evaluation of its kind for content-based prediction on animated
GIFs to our knowledge. In addition, we advocate a conceptual paradigm in
emotion prediction that shows delineating distinct types of emotion is
important and is useful to be concrete about the emotion target. One of our
objectives is to systematically compare different types of content features for
emotion prediction, including low-level, aesthetics, semantic and face
features. We also formulate a multi-task regression problem to evaluate whether
viewer perceived emotion prediction can benefit from jointly learning across
emotion classes compared to disjoint, independent learning.
[3]
Learning a Linear Influence Model from Transient Opinion Dynamics
KM Session 4: Social Networks & Social Media II
/
De, Abir
/
Bhattacharya, Sourangshu
/
Bhattacharya, Parantapa
/
Ganguly, Niloy
/
Chakrabarti, Soumen
Proceedings of the 2014 ACM Conference on Information and Knowledge
Management
2014-11-03
p.401-410
© Copyright 2014 ACM
Summary: Many social networks are characterized by actors (nodes) holding
quantitative opinions about movies, songs, sports, people, colleges,
politicians, and so on. These opinions are influenced by network neighbors.
Many models have been proposed for such opinion dynamics, but they have some
limitations. Most consider the strength of edge influence as fixed. Some model
a discrete decision or action on part of each actor, and an edge as causing an
"infection" (that is often permanent or self-resolving). Others model edge
influence as a stochastic matrix to reuse the mathematics of eigensystems.
Actors' opinions are usually observed globally and synchronously. Analysis
usually skirts transient effects and focuses on steady-state behavior. There is
very little direct experimental validation of estimated influence models. Here
we initiate an investigation into new models that seek to remove these
limitations. Our main goal is to estimate, not assume, edge influence strengths
from an observed series of opinion values at nodes. We adopt a linear (but not
stochastic) influence model. We make no assumptions about system stability or
convergence. Further, actors' opinions may be observed in an asynchronous and
incomplete fashion, after missing several time steps when an actor changed its
opinion based on neighbors' influence. We present novel algorithms to estimate
edge influence strengths while tackling these aggressively realistic
assumptions. Experiments with Reddit, Twitter, and three social games we
conducted on volunteers establish the promise of our algorithms. Our opinion
estimation errors are dramatically smaller than strong baselines like the
DeGroot, flocking, voter, and biased voter models. Our experiments also lend
qualitative insights into asynchronous opinion updates and aggregation.
[4]
The company you keep: mobile malware infection rates and inexpensive risk
indicators
Security 1
/
Truong, Hien Thi Thu
/
Lagerspetz, Eemil
/
Nurmi, Petteri
/
Oliner, Adam J.
/
Tarkoma, Sasu
/
Asokan, N.
/
Bhattacharya, Sourav
Proceedings of the 2014 International Conference on the World Wide Web
2014-04-07
v.1
p.39-50
© Copyright 2014 ACM
Summary: There is little information from independent sources in the public domain
about mobile malware infection rates. The only previous independent estimate
(0.0009%) [11], was based on indirect measurements obtained from domain-name
resolution traces. In this paper, we present the first independent study of
malware infection rates and associated risk factors using data collected
directly from over 55,000 Android devices. We find that the malware infection
rates in Android devices estimated using two malware datasets (0.28% and
0.26%), though small, are significantly higher than the previous independent
estimate. Based on the hypothesis that some application stores have a greater
density of malicious applications and that advertising within applications and
cross-promotional deals may act as infection vectors, we investigate whether
the set of applications used on a device can serve as an indicator for
infection of that device. Our analysis indicates that, while not an accurate
indicator of infection by itself, the application set does serve as an
inexpensive method for identifying the pool of devices on which more expensive
monitoring and analysis mechanisms should be deployed. Using our two malware
datasets we show that this indicator performs up to about five times better at
identifying infected devices than the baseline of random checks. Such
indicators can be used, for example, in the search for new or previously
undetected malware. It is therefore a technique that can complement standard
malware scanning. Our analysis also demonstrates a marginally significant
difference in battery use between infected and clean devices.
[5]
Bengali text input interface design for mobile devices
Accessibility aspects in UIDLs
/
Bhattacharya, Samit
/
Laha, Subrata
Universal Access in the Information Society
2013-11
v.12
n.4
p.441-451
Keywords: Bengali; Virtual keyboard; Two-level design; Frequency-based organization;
Static and adaptive; Page replacement algorithm
Copyright © 2013 Springer
Summary: Text entry has become one of the most frequent activities performed using
mobile devices such as PDAs. Virtual keyboards (VK), which allow text to be
entered by tapping keys displayed on the screen, are among the predominant mode
of text input for such devices. It is important to design VK layouts in a way
such that the users can achieve high text entry speed with high accuracy.
Several layouts, primarily in English and also in some other languages, have
been proposed to achieve the twin objectives. However, no such work has been
reported for Bengali, the second and fifth most popular language of India and
the world, respectively. The existing methods cannot be applied directly to
Bengali VK design due to the problem of accommodating the large Bengali
alphabet (more than 60 characters) on a small display area. In order to resolve
the resulting usability-performance trade-off, this paper proposes a two-level
design. Five two-level VKs representing three design paradigms (alphabetic,
frequency-based and adaptive) have been designed and compared in an empirical
study. The study results show that for mobile devices, the two-level adaptive
design is expected to give best performance in terms of text entry rate and
accuracy. The layouts as well as the procedure and results of the study are
discussed in this paper.
[6]
Towards a comprehensive computational model for aesthetic assessment of
videos
Multimedia grand challenge
/
Bhattacharya, Subhabrata
/
Nojavanasghari, Behnaz
/
Chen, Tao
/
Liu, Dong
/
Chang, Shih-Fu
/
Shah, Mubarak
Proceedings of the 2013 ACM International Conference on Multimedia
2013-10-21
p.361-364
© Copyright 2013 ACM
Summary: In this paper we propose a novel aesthetic model emphasizing psycho-visual
statistics extracted from multiple levels in contrast to earlier approaches
that rely only on descriptors suited for image recognition or based on
photographic principles. At the lowest level, we determine dark-channel,
sharpness and eye-sensitivity statistics over rectangular cells within a frame.
At the next level, we extract Sentibank features (1,200 pre-trained visual
classifiers) on a given frame, that invoke specific sentiments such as
"colorful clouds", "smiling face" etc. and collect the classifier responses as
frame-level statistics. At the topmost level, we extract trajectories from
video shots. Using viewer's fixation priors, the trajectories are labeled as
foreground, and background/camera on which statistics are computed.
Additionally, spatio-temporal local binary patterns are computed that capture
texture variations in a given shot. Classifiers are trained on individual
feature representations independently. On thorough evaluation of 9 different
types of features, we select the best features from each level -- dark channel,
affect and camera motion statistics. Next, corresponding classifier scores are
integrated in a sophisticated low-rank fusion framework to improve the final
prediction scores. Our approach demonstrates strong correlation with human
prediction on 1,000 broadcast quality videos released by NHK as an aesthetic
evaluation dataset.
[7]
Recognition of complex events in open-source web-scale videos: a bottom up
approach
Doctoral symposium
/
Bhattacharya, Subhabrata
Proceedings of the 2013 ACM International Conference on Multimedia
2013-10-21
p.1035-1038
© Copyright 2013 ACM
Summary: Recognition of complex events in unconstrained Internet videos is a
challenging research problem. In this symposium proposal, we present a
systematic decomposition of complex events into hierarchical components and
make an in-depth analysis of how existing research are being used to cater to
various levels of this hierarchy. We also identify three key stages where we
make novel contributions which are necessary to not only improve the overall
recognition performance, but also develop richer understanding of these events.
At the lowest level, our contributions include (a) compact covariance
descriptors of appearance and motion features used in sparse coding framework
to recognize realistic actions and gestures, and (b) a Lie-algebra based
representation of dominant camera motion present in video shots which can be
used as a complementary feature for video analysis. In the next level, we
propose an (c) efficient maximum likelihood estimate based representation from
low-level features computed from videos which demonstrates state of the art
performance in large scale visual concept detection, and finally, we propose to
(d) model temporal interactions between concepts detected in video shots
through two new discriminative feature spaces derived from Linear dynamical
systems which eventually boosts event recognition performance. In all cases, we
conduct thorough experiments to demonstrate promising performance gains over
some of the prominent approaches.
[8]
A study of the impact of task complexity and interface design on e-learning
task adaptations
APCHI 2013: full papers
/
Deshpande, Yogesh
/
Bhattacharya, Samit
/
Yammiyavar, Pradeep
Proceedings of the 2013 Asia Pacific Conference on Computer Human
Interaction
2013-09-24
p.19-27
© Copyright 2013 ACM
Summary: E-learners use different strategies of learning and interactions in
different learning situations. The learning task's complexity and the design of
user interface used together influences learner's adaptations in their
interaction tasks. This research studies influence of task's complexity and
interface design, on learner's adaptations in interaction tasks. The study
reveals learner's interaction behavior in situations of changing cognitive
demands of learning tasks.
The participants of the study solved learning tests using an e-learning web
application with two distinct types of graphical user interfaces (GUI-1 and
GUI-2). GUI-1 had hierarchical navigation design while GUI-2 had
non-hierarchical design. Different sample groups (K, C and A) were administered
learning tests having different complexities such as knowledge based (K),
comprehension based (C) and application based (A). The interaction tasks such
as total pages visited (Tpv) and total operations done (Top) during the
learning tests were recorded for computing task adaptation score (TAS). The
adaptation scores for GUI-1 and GUI-2 in various sample groups (K, C and A)
were compared and analyzed. The study concludes that the hierarchical or
non-hierarchical navigation designs have no significant effect on learner's
adaptations in Tpv and Top. However learning test complexity (knowledge,
comprehension and application) significantly affects task adaptation scores.
[9]
Automatic correction of annotation boundaries in activity datasets by class
separation maximization
Workshop: international workshop on human activity sensing corpus and its
application (HASCA2013)
/
Kirkham, Reuben
/
Khan, Aftab
/
Bhattacharya, Sourav
/
Hammerla, Nils
/
Mellor, Sebastian
/
Roggen, Daniel
/
Ploetz, Thomas
Adjunct Proceedings of the 2013 International Joint Conference on Pervasive
and Ubiquitous Computing
2013-09-08
v.2
p.673-678
© Copyright 2013 ACM
Summary: t is challenging to precisely identify the boundary of activities in order
to annotate the activity datasets required to train activity recognition
systems. This is the case for experts, as well as non-experts who may be
recruited for crowd-sourcing paradigms to reduce the annotation effort or speed
up the process by distributing the task over multiple annotators. We present a
method to automatically adjust annotation boundaries, presuming a correct
annotation label, but imprecise boundaries, otherwise known as "label jitter".
The approach maximizes the Fukunaga Class-Separability, applied to time series.
Evaluations on a standard benchmark dataset showed statistically significant
improvements from the initial jittery annotations.
[10]
Gaussian process-based predictive modeling for bus ridership
Workshop: PURBA 2013: workshop on pervasive urban applications
/
Bhattacharya, Sourav
/
Phithakkitnukoon, Santi
/
Nurmi, Petteri
/
Klami, Arto
/
Veloso, Marco
/
Bento, Carlos
Adjunct Proceedings of the 2013 International Joint Conference on Pervasive
and Ubiquitous Computing
2013-09-08
v.2
p.1189-1198
© Copyright 2013 ACM
Summary: The dynamics of a city are characterized, among others, by the traveling
patterns of its dwellers. Accurate knowledge of human mobility patterns would
have applications, e.g., in urban design, in the optimization of public
transportation operating costs, and in the improvement of public transportation
services. The present paper combines a large scale bus transportation dataset
with publicly available data sources to predict bus usage. We propose a
Gaussian process-based approach for modeling and predicting bus ridership. To
validate our approach we perform experiments on data collected from Lisbon,
Portugal. The results demonstrate significant improvements in prediction
accuracy compared to a probabilistic baseline predictor.
[11]
Semi-supervised Learning Based Aesthetic Classifier for Short Animations
Embedded in Web Pages
Display Manipulations
/
Bansal, Dipak
/
Bhattacharya, Samit
Proceedings of IFIP INTERACT'13: Human-Computer Interaction-1
2013
v.1
p.728-745
Keywords: Aesthetics; web page; short video; classification; semi-supervised learning;
Co-training
© Copyright 2013 IFIP
Summary: We propose a semi-supervised learning based computational model for
aesthetic classification of short animation videos, which are nowadays part of
many web pages. The proposed model is expected to be useful in developing an
overall aesthetic model of web pages, leading to better evaluation of web page
usability. We identified two feature sets describing aesthetics of an animated
video. Based on the feature sets, we developed a Naïve-Bayes classifier by
applying Co-training, a semi-supervised machine learning technique. The model
classifies the videos as good, average or bad in terms of their aesthetic
quality. We designed 18 videos and got those rated by 17 participants for use
as the initial training set. Another set of 24 videos were designed and labeled
using Co-training. We conducted an empirical study with 16 videos and 23
participants to ascertain the efficacy of the proposed model. The study results
show 75% model accuracy.
[12]
Igwana: a text-free search interface
/
Bhattacharya, Shourov
/
Feldman, Luke
Proceedings of the 2012 Australian Computer-Human Interaction Conference
2012-11-26
p.34-37
© Copyright 2012 CHISIG and authors
Summary: Keyword-driven search has become an important way for people to find content
on the World Wide Web. However, it is estimated that more than 700 million
adults (Warrilow, 2009) lack sufficient literacy in either English or another
major language to use existing search interfaces. As a result, these users are
to a large extent 'locked out' from the Web. We seek to address this challenge
through the development of a user interface ('igwana') to navigate effectively
through large sets of content by using pictograms in place of text. This paper
describes some of our preliminary research and ideas and a proposed design for
the igwana system.
[13]
Segmenting web-domains and hashtags using length specific models
KM track: information extraction
/
Srinivasan, Sriram
/
Bhattacharya, Sourangshu
/
Chakraborty, Rudrasis
Proceedings of the 2012 ACM Conference on Information and Knowledge
Management
2012-10-29
p.1113-1122
© Copyright 2012 ACM
Summary: Segmentation of a string of English language characters into a sequence of
words has many applications. Here, we study two applications in the internet
domain. First application is the web domain segmentation which is crucial for
monetization of broken URLs. Secondly, we propose and study a novel application
of twitter hashtag segmentation for increasing recall on twitter searches.
Existing methods for word segmentation use unsupervised language models. We
find that when using multiple corpora, the joint probability model from
multiple corpora performs significantly better than the individual corpora.
Motivated by this, we propose weighted joint probability model, with weights
specific to each corpus. We propose to train the weights in a supervised manner
using max-margin methods. The supervised probability models improve
segmentation accuracy over joint probability models. Finally, we observe that
length of segments is an important parameter for word segmentation, and
incorporate length-specific weights into our model. The length specific models
further improve segmentation accuracy over supervised probability models. For
all models proposed here, inference problem can be solved using the dynamic
programming algorithm. We test our methods on five different datasets, two from
web domains data, and three from news headlines data from an LDC dataset. The
supervised length specific models show significant improvements over
unsupervised single corpus and joint probability models. Cross-testing between
the datasets confirm that supervised probability models trained on all
datasets, and length specific models trained on news headlines data, generalize
well. Segmentation of hashtags result in significant improvement in recall on
searches for twitter trends.
[14]
Enriching location information: an energy-efficient approach
Doctoral colloquia abstracts
/
Bhattacharya, Sourav
Proceedings of the 2011 International Conference on Ubiquitous Computing
2011-09-17
p.519-522
© Copyright 2011 ACM
Summary: Off-the-shelf modern mobile devices come with a number of inbuilt sensors,
e.g., GPS, WiFi, GSM, accelerometer, compass, gyroscope, NFC and Bluetooth.
Equipped with all these sensors and internet connectivity, modern mobile phones
are enabling continuous sensing and increasingly many emergent mobile
applications are using sensed context on the phone to understand users' needs
and improve usability. However, limited battery power is a big hindrance to the
deployment of continuous sensing on mobile devices and without any intelligent
sensor management, the battery lasts only few hours. In this research, we
emphasize on location-awareness and address the challenges in developing
ubiquitous positioning solutions, cross-device indoor localization, position
and trajectory tracking and inferring high-level contexts using
machine-learning techniques on sensor data in an energy-efficient way.
[15]
Predictive error behavior model of on-screen keyboard users
Works-in-progress
/
Jain, Siddharth
/
Bhattacharya, Samit
Proceedings of ACM CHI 2011 Conference on Human Factors in Computing Systems
2011-05-07
v.2
p.1435-1440
© Copyright 2011 ACM
Summary: On-screen keyboards are becoming ubiquitous with increasing use in mobile
devices and touch-screens. In this work, we present a novel predictive error
model which relates accuracy of an on-screen keyboard user to a given layout
using the distance between keys. The model is developed from empirical data
with the aim to predict the error rate of a user from the layout specification
alone. Our proposed model can be combined with the existing quantitative design
approaches for designing keyboards having high text-entry speed and accuracy.
[16]
Consideration set generation in commerce search
E-commerce
/
Bhattacharya, Sayan
/
Gollapudi, Sreenivas
/
Munagala, Kamesh
Proceedings of the 2011 International Conference on the World Wide Web
2011-03-28
v.1
p.317-326
© Copyright 2011 ACM
Summary: In commerce search, the set of products returned by a search engine often
forms the basis for all user interactions leading up to a potential transaction
on the web. Such a set of products is known as the consideration set. In this
study, we consider the problem of generating consideration set of products in
commerce search so as to maximize user satisfaction. One of the key features of
commerce search that we exploit in our study is the association of a set of
important attributes with the products and a set of specified attributes with
the user queries. Those important attributes not used in the query are treated
as unspecified. The attribute space admits a natural definition of user
satisfaction via user preferences on the attributes and their values, viz.
require that the surfaced products be close to the specified attribute values
in the query, and diverse with respect to the unspecified attributes. We model
this as a general Max-Sum Dispersion problem wherein we are given a set of n
nodes in a metric space and the objective is to select a subset of nodes with
total cost at most a given budget, and maximize the sum of the pairwise
distances between the selected nodes. In our setting, each node denotes a
product, the cost of a node being inversely proportional to its relevance with
respect to specified attributes. The distance between two nodes quantifies the
diversity with respect to the unspecified attributes. The problem is NP-hard
and a 2-approximation was previously known only when all the nodes have unit
cost.
In our setting, we do not make any assumptions on the cost. We label this
problem as the General Max-Sum Dispersion problem. We give the first constant
factor approximation algorithm for this problem, achieving an approximation
ratio of 2. Further, we perform extensive empirical analysis on real-world data
to show the effectiveness of our algorithm.
[17]
Influence of landmark-based navigation instructions on user attention in
indoor smart spaces
Handheld devices
/
Nurmi, Petteri
/
Salovaara, Antti
/
Bhattacharya, Sourav
/
Pulkkinen, Teemu
/
Kahl, Gerrit
Proceedings of the 2011 International Conference on Intelligent User
Interfaces
2011-02-13
p.33-42
© Copyright 2011 ACM
Summary: Using landmark-based navigation instructions is widely considered to be the
most effective strategy for presenting navigation instructions. Among other
things, landmark-based instructions can reduce the user's cognitive load,
increase confidence in navigation decisions and reduce the number of
navigational errors. Their main disadvantage is that the user typically focuses
considerable amount of attention on searching for landmark points, which easily
results in poor awareness of the user's surroundings. In indoor spaces, this
implies that landmark-based instructions can reduce the attention the user pays
on advertisements and commercial displays, thus rendering the assistance
commercially inviable. To better understand how landmark-based instructions
influence the user's awareness of her surroundings, we conducted a user study
with $20$ participants in a large national supermarket that investigated how
the attention the user pays on her surroundings varies across two types of
landmark-based instructions that vary in terms of their visual demand. The
results indicate that an increase in the visual demand of landmark-based
instructions does not necessarily improve the participant's recall of their
surrounding environment and that this increase can cause a decrease in
navigation efficiency. The results also indicate that participants generally
pay little attention to their surroundings and are more likely to rationalize
than to actually remember much from their surroundings. Implications of the
findings on navigation assistants are discussed.
[18]
A GA-based approach to improve web page aesthetics
/
Singh, Nahar
/
Bhattacharya, Samit
Proceedings of the 2010 International Conference on Intelligent Interactive
Technologies and Multimedia
2010-12-28
p.29-32
© Copyright 2010 ACM
Summary: The field of human-computer interaction traditionally deals with the problem
of improving usability of interactive systems. The concept of usability is
defined in terms of user's task performance. While task is undoubtedly one
important factor in "usable" interface design, recent research shows that form
(aesthetics) performs an equally important role in shaping the overall user
experience of an interactive system, which in turn leads to increased
usability. Keeping the form factor in focus, in this paper we present an
approach to improve aesthetics of web interfaces using a genetic algorithm
(GA). An existing computational model of aesthetics has been used to develop
the fitness function of the GA. In order to ascertain the efficacy of the
approach, an empirical study with 30 web pages and 10 subjects was carried out.
Results of the study show that in certain situations, the proposed approach is
able to improve perceived interface aesthetics.
[19]
A grid-based algorithm for on-device GSM positioning
Localization
/
Nurmi, Petteri
/
Bhattacharya, Sourav
/
Kukkonen, Joonas
Proceedings of the 2010 International Conference on Ubiquitous Computing
2010-09-26
p.227-236
Keywords: GSM, energy efficiency, fingerprinting, mobile computing, particle
filtering, positioning
© Copyright 2010 ACM
Summary: We propose a grid-based GSM positioning algorithm that can be deployed
entirely on mobile devices. The algorithm uses Gaussian distributions to model
signal intensity variations within each grid cell. Position estimates are
calculated by combining a probabilistic centroid algorithm with particle
filtering. In addition to presenting the positioning algorithm, we describe
methods that can be used to create, update and maintain radio maps on a mobile
device. We have implemented the positioning algorithm on Nokia S60 and Nokia
N900 devices and we evaluate the algorithm using a combination of offline and
real world tests. The results indicate that the accuracy of our method is
comparable to state-of-the-art methods, while at the same time having
significantly smaller storage requirements.
[20]
Jog Falls: A Pervasive Healthcare Platform for Diabetes Management
Applications
/
Nachman, Lama
/
Baxi, Amit
/
Bhattacharya, Sangeeta
/
Darera, Vivek
/
Deshpande, Piyush
/
Kodalapura, Nagaraju
/
Mageshkumar, Vincent
/
Rath, Satish
/
Shahabdeen, Junaith
/
Acharya, Raviraja
Proceedings of Pervasive 2010: International Conference on Pervasive
Computing
2010-05-17
p.94-111
Keywords: Personal Health Monitoring; Diabetes Management; Energy Expenditure
Analysis; Activity monitoring
© Copyright 2010 Springer-Verlag
Summary: This paper presents Jog Falls, an end to end system to manage diabetes that
blends activity and energy expenditure monitoring, diet-logging, and analysis
of health data for patients and physicians. It describes the architectural
details, sensing modalities, user interface and the physician's backend portal.
We show that the body wearable sensors accurately estimate the energy
expenditure across a varied set of active and sedentary states through the
fusion of heart rate and accelerometer data. The GUI ensures continuous
engagement with the patient by showing the activity goals, current and past
activity states and dietary records along with its nutritional values. The
system also provides a comprehensive and unbiased view of the patient's
activity and food intake trends to the physician, hence increasing his/her
effectiveness in coaching the patient. We conducted a user study using Jog
Falls at Manipal University, a leading medical school in India. The study
involved 15 participants, who used the system for 63 days. The results indicate
a strong positive correlation between weight reduction and hours of use of the
system.
[21]
Identifying Meaningful Places: The Non-parametric Way
Location in Pervasive Systems
/
Nurmi, Petteri
/
Bhattacharya, Sourav
Proceedings of Pervasive 2008: International Conference on Pervasive
Computing
2008-05-19
p.111-127
© Copyright 2008 Springer-Verlag
Summary: Gathering and analyzing location data is an important part of many
ubiquitous computing applications. The most common way to represent location
information is to use numerical coordinates, e.g., latitudes and longitudes. A
problem with this approach is that numerical coordinates are usually
meaningless to a user and they contrast with the way humans refer to locations
in daily communication. Instead of using coordinates, humans tend to use
descriptive statements about their location; for example, "I'm home" or "I'm at
Starbucks." Locations, to which a user can attach meaningful and descriptive
semantics, are often called places. In this paper we focus on the automatic
extraction of places from discontinuous GPS measurements. We describe and
evaluate a non-parametric Bayesian approach for identifying places from this
kind of data. The main novelty of our approach is that the algorithm is fully
automated and does not require any parameter tuning. Another novel aspect of
our algorithm is that it can accurately identify places without temporal
information. We evaluate our approach using data that has been gathered from
different users and different geographic areas. The traces that we use exhibit
different characteristics and contain data from daily life as well as from
traveling abroad. We also compare our algorithm against the popular k-means
algorithm. The results indicate that our method can accurately identify
meaningful places from a variety of location traces and that the algorithm is
robust against noise.
[22]
Study and modeling of user errors for virtual scanning keyboard design
Works in progress
/
Bhattacharya, Samit
/
Samanta, Debasis
/
Basu, Anupam
Proceedings of ACM CHI 2008 Conference on Human Factors in Computing Systems
2008-04-05
v.2
p.3399-3404
© Copyright 2008 ACM
Summary: Virtual scanning keyboards are text entry systems used by individuals with
severe speech and motion impairments. In this paper, we present results of our
empirical study on user errors for such keyboards. We also propose a
computational error model and a method for evaluation of such keyboards taking
errors into account. The work is aimed to help designers make appropriate
choice from a large number of design alternatives with minimum user
involvement.
[23]
User errors on scanning keyboards: Empirical study, model and design
principles
/
Bhattacharya, Samit
/
Samanta, Debasis
/
Basu, Anupam
Interacting with Computers
2008
v.20
n.3
p.406-418
Keywords: Augmentative communication; Soft keyboards; Scanning input methods; Focus
distance; Timing errors; Selection errors
© Copyright 2008 Elsevier B.V.
1. Introduction
2. Details of the empirical study
2.1. Interfaces and access switches
2.2. Subjects
2.3. Method
3. Data analysis
3.1. Calculation of error free text entry time
3.2. Calculation of text entry time increase due to SE
3.3. Calculation of text entry time increase due to TE
3.4. Results
4. Modeling of user behavior
5. Prediction of error behavior from the user model
5.1. Focus distance
5.2. Model prediction
5.3. Observed error behavior
6. Development of design principles
7. Discussion
8. Conclusions
Acknowledgements
Appendix A. Texts used in the study
References
Summary: Scanning keyboards are used as augmentative communication aids by persons
with severe speech and motion impairments. Literature reports two approaches
for the design of scanning keyboards; design based on the experience and
intuition of designers and user model based design methods. None of these
approaches, however, considers user errors in the design process, potentially
limiting the practical usefulness of the designs. We have performed experiments
in order to study user errors on scanning keyboards. We have found that two
types of errors affect performance of scanning keyboard users significantly,
namely (a) timing error that occurs when a user fails to select a key at the
appropriate time and (b) selection error that occurs when the user selects a
wrong key. These errors have been found to increase users' text entry time by
as high as 65% and 35%, respectively. Based on empirical observations, we have
developed a state transition model of user behavior during user-keyboard
interaction. The model comprises of four states, each of which represents the
physical and cognitive state of the user at particular instant of the
interaction. The transitions are caused by users' physical, cognitive and
perceptual activities. We have found that the errors could be explained as
caused due to the problems in making the transitions properly. In addition to
explaining errors, the model has helped us to predict distribution of error
probabilities with respect to the distance between keys. We have used the model
predicted error distributions to develop principles for scanning keyboard
design that aim to reduce user errors. The principles state that the frequently
used key pairs should be placed apart by a minimum distance, which has been
obtained from the error distributions, in order to reduce errors. The method
and results of the study, the user model and the design principles are
presented in this paper.
