Ambient intelligence and ergonomics in Asia
Toly Chen
0
1
2
Chu-Chai Chan
0
1
2
Hsin-Chieh Wu
0
1
2
Yu-Cheng Lin
0
1
2
0
Y.-C. Lin Department of Industrial Engineering and Management, Overseas Chinese University
,
Xitun
,
Taiwan
1
C.-C. Chan H.-C. Wu Department of Industrial Engineering and Management, Chaoyang University of Technology
,
Taichung
,
Taiwan
2
T. Chen (&) Department of Industrial Engineering and Systems Management, Feng Chia University
,
Taichung
,
Taiwan
-
Ambient intelligence (AmI) is one of the most important
advances in computer technology in the mobile era. By
being aware and applying knowledge of ergonomics
(human factors), AmI system users will be in better shape
and health, become more effective and find using AmI
system a more pleasant and enjoyable experience.
This special issue contains selected papers from the 1st
international conference on ambient intelligence and
ergonomics in Asia (AmIE 2013), which was held at
Taichung city, Taiwan, July 35, 2013. The conference
attracted a large number of scientific papers that
contributed to the state-of-the-art in the fields of ambient
intelligence and ergonomics. After a strict review, five articles
from researchers around the world were finally accepted.
To determine an understandable algorithm that could be
used by designers to create novel concept designs,
M.T. Wang and C.C. Yang selected the popular motor
scooter as a sample product, and used the most distinctive
front handle cover as a design target. Their method
included three phases: preparation, construction of conceptual
creativity, and semantic analysis. After comparing random
idea sketches with designs available on the market, they
observed that certain concept designs obtained using this
method were exceptionally innovative, and could be easily
redesigned for an actual product.
A.M. Otebolaku and M.T. Andrade investigated
context-aware recommendation techniques for implicit
delivery of contextually relevant online media items. The
proposed recommendation service identifies a users
dynamic contextual situation from the devices built-in
sensors, and uses case-based reasoning to determine the
users current contextual preferences. The effectiveness of
the proposed recommendation service was evaluated with a
case study.
Gripping and pinching are frequently used hand strength
in various occupational activities and in clinical evaluation
of the hand. Therefore, formulating grip and pinch
prediction models with easily obtainable personal parameters
will help facilitate the design and evaluation of workplace
environments or facilitate the hand impairment or
progression assessments. P.C. Sung, C.C. Hsu, C.L. Lee,
Y.-S.P. Chiu, and H.L. Chen developed maximum
voluntary contraction (MVC) grip and key pinch strength
prediction models using regression method and artificial
neural networks (ANN).
An ANN is a prevalent humanized computing method
that imitates the central nervous system of a human. To
estimate the cycle time of a job in a wafer fabrication
factory, H.C. Wu and T. Chen proposed a joint use of a
classification and regression tree (CART) and back
propagation network (BPN). In their method, a BPN is
constructed to estimate the cycle times of jobs of a branch. A
real case was used to evaluate the effectiveness of the
proposed methodology.
C.T. Tseng, Y.L. Lee, and C.C. Chou designed an
AmIbased decision support system that combined an
electromagnetism-like mechanism (EM) and sensory data to aid
human operators in making decisions regarding the
management of cascade hydropower systems. The
AmIbased system proposed in their study was used to determine
the periodic water release at each plant in the Dajia
hydropower system, thereby maximizing the Taiwan power
companys power-generation profit.
We would like to thank to the JAIHC Editor-in-Chief
Vincenzo Loia for providing full support in bringing out
this special issue. We are thankful to the paper contributors
who shared their research as well as the reviewers who
spared their valuable time in paper review. We would also
like to thank the journal staff. Without their support and
professional assistance, the pre-publication process would
not been possible.
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