SPLASH: Smart-Phone Logging App for Sustaining Hydration Enabled by NFC
Late-Breaking Works: Engineering of Interactive Systems
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Luo, Xu
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Woznowski, Przemyslaw
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Burrows, Alison
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Haghighi, Mo
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Craddock, Ian
Extended Abstracts of the ACM CHI'16 Conference on Human Factors in
Computing Systems
2016-05-07
v.2
p.1526-1532
© Copyright 2016 ACM
Summary: Maintaining good hydration is crucial for adequate physical and mental
performance for all human beings. In this paper we present SPLASH, an Android
app that enables users to set daily goals and to keep track of their liquid
intake through a combination of smart-phone NFC technology and NFC-tagged cups.
We conducted several experiments to verify the robustness of the technology,
which indicated that the selected NFC tags had acceptable robustness,
operational distance and good penetration ability to meet the intended
requirements for monitoring hydration. To further assess the feasibility of our
concept, we evaluated SPLASH with ten users who gave feedback on its usability.
We discuss the current prototype's advantages and limitations, as well as
possible improvements and potential capabilities. At the end of this paper, we
propose additional healthcare application scenarios for our concept.
Measuring Photoplethysmogram-Based Stress-Induced Vascular Response Index to
Assess Cognitive Load and Stress
Health Sensors & Monitoring
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Lyu, Yongqiang
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Luo, Xiaomin
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Zhou, Jun
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Yu, Chun
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Miao, Congcong
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Wang, Tong
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Shi, Yuanchun
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Kameyama, Ken-ichi
Proceedings of the ACM CHI'15 Conference on Human Factors in Computing
Systems
2015-04-18
v.1
p.857-866
© Copyright 2015 ACM
Summary: Quantitative assessment for cognitive load and mental stress is very
important in optimizing human-computer system designs to improve performance
and efficiency. Traditional physiological measures, such as heart rate
variation (HRV), blood pressure and electrodermal activity (EDA), are widely
used but still have limitations in sensitivity, reliability and usability. In
this study, we propose a novel photoplethysmogram-based stress induced vascular
index (sVRI) to measure cognitive load and stress. We also provide the basic
methodology and detailed algorithm framework. We employed a classic experiment
with three levels of task difficulty and three stages of testing period to
verify the new measure. Compared with the blood pressure, heart rate and HRV
components recorded simultaneously, the sVRI reached the same level of
significance on the effect of task difficulty/period as the most significant
other measure. Our findings showed sVRI's potential as a sensitive, reliable
and usable parameter.
BAP: Bimodal Attribute Prediction for Zero-Shot Image Categorization
Posters 2
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Li, Hanhui
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Li, Donghui
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Luo, Xiaonan
Proceedings of the 2014 ACM International Conference on Multimedia
2014-11-03
p.1013-1016
© Copyright 2014 ACM
Summary: Recent advances in attribute-based methods provide the zero-shot learning
problem with practical solutions. In attribute-based methods, visual attributes
are introduced to fill the gap between low-level image features and high-level
semantic information. This paper proposes a novel bimodal attribute prediction
model called BAP, which can better predict visual attributes in images. BAP
fuses advantages of the conventional direct attribute prediction (DAP) and
indirect attribute prediction (IAP) on the level of attribute prediction. It
contains an attribute-classifier pooling process that generates a large amount
of base classifiers and a combination strategy that integrates these
classifiers. We explore and propose four BAP models with different combination
strategies in this paper, and experimentally show that our BAP outperforms the
conventional models both in offline and online zero-shot image categorization.
A comparison of order picking assisted by head-up display (HUD),
cart-mounted display (CMD), light, and paper pick list
Eyewear computing
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Guo, Anhong
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Raghu, Shashank
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Xie, Xuwen
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Ismail, Saad
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Luo, Xiaohui
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Simoneau, Joseph
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Gilliland, Scott
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Baumann, Hannes
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Southern, Caleb
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Starner, Thad
Proceedings of the 2014 International Symposium on Wearable Computers
2014-09-13
v.1
p.71-78
© Copyright 2014 ACM
Summary: Wearable and contextually aware technologies have great applicability in
task guidance systems. Order picking is the task of collecting items from
inventory in a warehouse and sorting them for distribution; this process
accounts for about 60% of the total operational costs of these warehouses.
Current practice in industry includes paper pick lists and pick-by-light
systems. We evaluated order picking assisted by four approaches: head-up
display (HUD); cart-mounted display (CMD); pick-by-light; and paper pick list.
We report accuracy, error types, task time, subjective task load and user
preferences for all four approaches. The findings suggest that pick-by-HUD and
pick-by-CMD are superior on all metrics to the current practices of
pick-by-paper and pick-by-light.
Oris: enhance social self-awareness for visually impaired people
Student design competition
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Luo, Xuan
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Xu, Yu
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Mullen, Clark
Proceedings of ACM CHI 2014 Conference on Human Factors in Computing Systems
2014-04-26
v.2
p.197-202
© Copyright 2014 ACM
Summary: People with visual impairments rely on various technologies to alleviate
daily physiological and psychological challenges. In order to introduce our
design focus, we first describe our contextual inquiry with target users who
are visually impaired. We then study existing technologies that help people
with visual impairment to overcome physical limitations. Finally, we propose a
potential solution (Fig. 1) to help people who are visually impaired gain
self-awareness in social contexts by using body data (facial and gesture)
recognition technologies. We also describe future strategies in developing a
collaborative platform to help this community further.
Website Interaction Network
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Luo, Xiangfeng
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Liu, Huimin
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Xuan, Junyu
Journal of Organizational Computing and Electronic Commerce
2014-04-03
v.24
n.2/3
p.215-235
© Copyright 2014 Taylor and Francis
Summary: The websites-based social network, as a social media, provides and shares
abundant information via organizing users' content and contacts, whereby users'
activities in the real world can be imaged to the websites. However, users'
content and contacts in real-world social networks cannot be detected easily.
Herein, we construct a website interaction network to reflect the online social
network, based on mapping relationships among websites, webpages, and
attributes of a social event. This network reflects the social association
relationships between websites of an event, which can be mapped to the users'
relationships in the real-world social network. In this article, we study the
structural features of a website interaction network and, then, mapping of
these features to the real-world social network. Further, we discuss
implications for human behaviors, human relationships, and structure of human
society. Experimental results show that the website interaction networks
concerning popular social events have power-law scaling in degree distribution
and exhibit small-world properties.
Competence-based song recommendation
Multimedia
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Shou, Lidan
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Mao, Kuang
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Luo, Xinyuan
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Chen, Ke
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Chen, Gang
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Hu, Tianlei
Proceedings of the 2013 Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2013-07-28
p.423-432
© Copyright 2013 ACM
Summary: Singing is a popular social activity and a good way of expressing one's
feelings. One important reason for unsuccessful singing performance is because
the singer fails to choose a suitable song. In this paper, we propose a novel
singing competence-based song recommendation framework. It is distinguished
from most existing music recommendation systems which rely on the computation
of listeners' interests or similarity. We model a singer's vocal competence as
singer profile, which takes voice pitch, intensity, and quality into
consideration. Then we propose techniques to acquire singer profiles. We also
present a song profile model which is used to construct a human annotated song
database. Finally, we propose a learning-to-rank scheme for recommending songs
by singer profile. The experimental study on real singers demonstrates the
effectiveness of our approach and its advantages over two baseline methods. To
the best of our knowledge, our work is the first to study competence-based song
recommendation.
Distilling and exploring nuggets from a corpus
Demonstrations
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Castelli, Vittorio
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Raghavan, Hema
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Florian, Radu
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Han, Ding-Jung
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Luo, Xiaoqiang
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Roukos, Salim
Proceedings of the 35th Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2012-08-12
p.1006
© Copyright 2012 ACM
Summary: This paper describes a live and scalable system that automatically extracts
information nuggets for entities/topics from a continuously updated corpus for
effective exploration and analysis. A nugget is a piece of semantic information
that (1) must be mapped semantically to the transitive closure of a pre-defined
ontology, (2) is explicitly supported by text, and (3) has a natural language
description that completely conveys its semantic to a user. Fig. 1 shows a type
of nugget "involvement in events" for a person entity (Leon Panetta): each
nugget has a short description ("meeting", "news conference") with a list of
supporting passages.
Our key contributions are (1) We extract nuggets and remove redundancy to
produce a summary of salient information with supporting clusters of passages.
(2) We present an entity/topic centric exploration interface that also allows
users to navigate to other entities involved in a nugget. (3) We use the
statistical NLP technologies developed over the years in the ACE, GALE and
TAC-KBP programs, including parsing, mention detection, within and cross
document coreference resolution, relation detection and slot filler extraction.
(4) Our system is flexible and easily adaptable across domains as demonstrated
on two corpora: generic news and scientific papers. Search engines such as
Google News and Scholar do not retrieve nuggets, and only remove redundancy at
document level. News aggregation applications such as Evri categorize news
articles based on the entities of topics but do not extract nuggets. Other
systems extract richer information, but not all of it has clear semantics;
e.g., Silobreaker presents results as "the relationship between X and Y in the
context of [keyphrase]", leaving users with the task of interpreting the
semantics as it is not tied to a clear ontology. In contrast we remove
redundancy, summarize results and present nuggets that have clear semantics.
myDJ: recommending karaoke songs from one's own voice
Demonstrations
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Mao, Kuang
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Luo, Xinyuan
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Chen, Ke
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Chen, Gang
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Shou, Lidan
Proceedings of the 35th Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2012-08-12
p.1009
© Copyright 2012 ACM
Summary: In this demo, we present myDJ, a karaoke recommendation system which
recommends the songs people are capable to sing. Different from the existing
song recommendation systems which recommend songs people like to listen, myDJ
can recommend proper songs according to a subject's physical phonation area. It
consists of a singer profiler to analyze the subject's phonation characters. In
addition, the song profile for each song in database is extracted. To learn a
ranking function, the learning to rank algorithm Listnet is applied under a
list of predefined features extracted from each singer-song profile pair. In
the results, proper songs which are suitable but challenging for the subject
are recommended.
A developing framework for interactive temporal data visualization
New concept and framework
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Luo, Xiongfei
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Teng, Dongxing
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Liu, Wei
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Tian, Feng
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Dai, Guozhong
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Wang, Hongan
Proceedings of the 2010 International Symposium on Visual Information
Communication and Interaction
2010-09-28
p.14
© Copyright 2010 ACM
Summary: This article presents UCFM, a user-centered developing framework for
interactive temporal data visualization. UCFM is comprised mainly by software
architecture and software development methods. The software architecture
describes modules in interactive temporal data visualization system and their
relationships. And based on the software architecture and development practice,
the software development methods summarize these specific steps to design and
develop interactive temporal data visualization system. To demonstrate UCFM's
validity, the development process of an interactive temporal data visualization
application is illustrated.
Understanding the Determinants of User Acceptance of Enterprise Instant
Messaging: An Empirical Study
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Luo, Xin
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Gurung, Anil
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Shim, J. P.
Journal of Organizational Computing and Electronic Commerce
2010
v.20
n.2
p.155-181
© Copyright 2010 Taylor and Francis
Summary: As modern organizations increasingly depend on information systems (IS) to
enhance work productivity and seek new business opportunities, communication
effectiveness has become one of the key factors that underlie the effective
performance of IS implementations and applications. Instant Messaging (IM)
presents a revolution in enterprise communication. As more organizations are
findings ways to utilize this near-synchronous computing communication
technology to enhance communication effectiveness in the workplace, there is a
compelling need to understand the factors that are important for the adoption
of enterprise IM. We have developed an integrative model based on constructs of
the existing IT adoption models as well as theories on motivation, innovation
diffusion, and critical mass. Using responses from 140 intended subjects, we
have found the results of survey data support the contentions that perceived
usefulness, compatibility, enjoyment, and security are significant predictors
of intention to use enterprise IM. Although perceived connectivity did not
predict the intention directly, it did indirectly through perceived usefulness
and perceived ease of use. Implications and future research are discussed.
Modeling and Analysis for Grid Service Cooperative Scheduling Based on Petri
Nets
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Han, Yaojun
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Jiang, Changjun
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Luo, Xuemei
CDVE 2007: International Conference on Cooperative Design, Visualization,
and Engineering
2007-09-16
p.104-112
Keywords: grid service; composition; dynamic timed Petri net; performance analysis
© Copyright 2007 Springer-Verlag
Summary: As the complexity of application system for enterprises, an important
challenge is to dynamically schedule and integrate the heterogeneous and
distributed services or activities to work cooperatively and efficiently. An
effective technology to resolve the problem is grid service. A grid service
built on both grid computing and web services technologies is an extended Web
service. An application system for enterprises is a grid service composition
that consists of a collection of grid services related by data and control
flow. Therefore, there is a need for modeling and analyzing techniques and
tools for reliable and effective grid service composition. The Petri net based
method is an idea approach. In this paper, we use a colored dynamic timed Petri
net (CDTPN) to model the grid service composition. The definition of CDTPN for
grid service and an algorithm to construct a composite service are proposed. We
give a definition of reachable service graph and an algorithm for constructing
the reachable service graph of CDTPN. Finally, we discuss the correctness and
effectiveness of the grid service composition by analyzing the reachable
service graph.
Interactive Browsing of Large Images on Multi-projector Display Wall System
Part 4: Ubiquitous Interaction
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Jiang, Zhongding
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Luo, Xuan
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Mao, Yandong
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Zang, Binyu
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Lin, Hai
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Bao, Hujun
HCI International 2007: 12th International Conference on Human-Computer
Interaction, Part II: Interaction Platforms and Techniques
2007-07-22
v.2
p.827-836
Copyright © 2007 Springer-Verlag
Summary: With the precision of data acquisition increases, large images that may
occupy terabytes, become common in research and industry fields. Since
multi-projector display wall systems can provide higher resolution, they
becomes paramount to display the large images. In this paper, we present one
large image viewing system designed for display wall system. Our system need
not totally downloading the whole image data to each rendering node. It enables
users to browse the out-of-core images in real time using data streaming
techniques. In the system, the original out-of-core raw image is compressed and
represented using one hierarchical structure in multi-resolution manner. We
design one proxy architecture that interactive streams data from remote data
server to all rendering nodes. Our system allows users to interactively pan,
and zoom the large images with versatile graphical user interface.
Piloting Team Training at Duke University Health System
HEALTH CARE: Teams, Communication, and Culture in Medical Care
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Wright, Melanie C.
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Luo, Xuemei
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Richardson, William J.
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Leonard, Michael M.
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Hohenhaus, Susan M.
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Taekman, Jeffrey M.
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Frush, Karen S.
Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting
2006-10-16
v.50
p.949-953
© Copyright 2006 HFES
Summary: Good team communication and coordination are critical to the safe delivery
of health care. Efforts at training students, clinicians, and support staff in
team coordination skills are beginning to be implemented across the country.
However, there is limited data validating the effectiveness of such programs or
highlighting the features that make one program more effective than another. In
this paper we present the results of a pilot project to evaluate a team
training program at the Ambulatory Surgery Center in the Duke University Health
System. Our experiences suggest that (1) initial data collection regarding team
coordination attitudes and skills and (2) close follow-up coordination with the
clinical organization to implement applicable practice changes are essential
components to a teamwork coordination program.
Acquiring user tradeoff strategies and preferences for negotiating agents: A
default-then-adjust method
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Luo, Xudong
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Jennings, Nicholas R.
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Shadbolt, Nigel
International Journal of Human-Computer Studies
2006
v.64
n.4
p.304-321
Keywords: Tradeoff strategy and preference; Knowledge acquisition; Preference
acquisition; Automated negotiation; Software agents
© Copyright 2006 Elsevier B.V.
Summary: A wide range of algorithms have been developed for various types of
negotiating agents. In developing such algorithms the main focus has been on
their efficiency and their effectiveness. However, this is only a part of the
picture. Typically, agents negotiate on behalf of their owners and for this to
be effective the agents must be able to adequately represent their owners'
strategies and preferences for negotiation. However, the process by which such
knowledge is acquired is typically left unspecified. To address this problem,
we undertook a study of how user information about negotiation tradeoff
strategies and preferences can be captured. Specifically, we devised a novel
default-then-adjust acquisition technique. In this, the system firstly does a
structured interview with the user to suggest the attributes that the tradeoff
could be made between, then it asks the user to adjust the suggested default
tradeoff strategy by improving some attribute to see how much worse the
attribute being traded off can be made while still being acceptable, and,
finally, it asks the user to adjust the default preference on the tradeoff
alternatives. This method is consistent with the principles of standard
negotiation theory and to demonstrate its effectiveness we implemented a
prototype system and performed an empirical evaluation in an accommodation
renting scenario. The result of this evaluation indicates the proposed
technique is helpful and efficient in accurately acquiring the users' tradeoff
strategies and preferences.
Acquiring domain knowledge for negotiating agents: a case of study
ARTICLE
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Castro-Schez, Jose J.
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Jennings, Nicholas R.
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Luo, Xudong
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Shadbolt, Nigel R.
International Journal of Human-Computer Studies
2004
v.61
n.1
p.3-31
© Copyright 2004 Elsevier B.V.
Summary: In this paper, we employ the fuzzy repertory table technique to acquire the
necessary domain knowledge for software agents to act as sellers and buyers
using a bilateral, multi-issue negotiation model that can achieve optimal
results in semi-competitive environments. In this context, the seller's domain
knowledge that needs to be acquired is the rewards associated with the products
and restrictions attached to their purchase. The buyer's domain knowledge that
is acquired is their requirements and preferences on the desired products. The
knowledge acquisition methods we develop involve constructing three fuzzy
repertory tables and their associated distinctions matrixes. The first two are
employed to acquire the seller agent's domain knowledge; and the third one is
used, together with an inductive machine learning algorithm, to acquire the
domain knowledge for the buyer agent.
