Ambient intelligence and ergonomics in Asia
J Ambient Intell Human Comput
Ambient intelligence and ergonomics in Asia
Hsin-Chieh Wu 0 1 2
Toly Chen 0 1 2
Peng-Cheng Sung 0 1 2
Yu-Cheng Lin 0 1 2
0 Department of Industrial Engineering and Systems Management, Feng Chia University , Taichung , Taiwan
1 Department of Industrial Engineering and Management, Chaoyang University of Technology , Taichung , Taiwan
2 Department of Computer-aided Industrial Design, Overseas Chinese University , Taichung , Taiwan
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This special issue is based on selected papers from the 2nd
international conference on ambient intelligence and
Ergonomics in Asia held on January 21–23, 2015, in
Taoyuan, Taiwan. 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. All of
the papers selected for this special issue were extended
from their original versions and underwent two or three
rounds of rigorous peer-reviewed process. The accepted
papers cover interesting works on the interaction between
ambient intelligence and ergonomics.
Virtual environment (VE) technology for online
shopping can provide a 3D perspective to customers for a more
realistic sense of the goods and the shopping environment.
Cheng-Li Liu and Shiaw-Tsyr Uang found that the elderly
who browsed in a 3D virtual store with high-quality depth
perception cues benefitted from binocular disparity within
a 3D display and were able to experience a good sense
of presence. Although the 3D displays provided a
stereopsis environment, the cyber sickness side-effect from
exposure in a VE can be serious when the depth
perception cues are poor, especially within a stereoscopic display.
Rung-Ching Chen, Chia-Fen Hsieh and Wei-Lun Chang
established an intrusion detection system, the patrol
intrusion detection system (PIDS), to protect the confidentiality
and integrity of sensor data. In the proposed methodology a
fraction of the sensor nodes were used as roaming patrol
nodes to detect malicious sensor nodes. A revised artificial
bee colony (ABC) algorithm was designed to find a path
with lower power consumption to transmit attack feature
packets in the PIDS.
Estimating the cycle time for each job is a critical
concern in managing a factory. To address this concern,
classification approaches in which jobs are classified before
or after forecasting their cycle times have recently been
proposed. However, none of these approaches can
guarantee the compatibility of the job classifier with the
forecasting mechanism. To overcome this difficulty Toly Chen
proposed a new classification approach, in which the
forecasting mechanism training was embedded into the job
classifier iterations. Consequently, the classification and
forecasting stages interweaved with each other, improving
their compatibility.
A. AL-Refaie, Toly Chen, R. Al-Athamneh and
HsinChieh Wu proposed a fuzzy neural network approach to
optimize the performance of a process with multiple
responses. In their method each quality characteristic was
transformed into a signal-to-noise ratio, and all ratios were
then provided as inputs to a fuzzy model to obtain a single
comprehensive output measure (COM). The radial basis
function neural networks were used to generate a full
factorial design. The average COM values were then
calculated for different factor levels, where for each factor, the
level that maximizes the COM value was identified as the
optimal level.
Mobile advertising researchers have suggested that the
advertising effect is caused by the advertising features.
Kuo-Wei Su, Po-Hsin Huang, Po-Hung Chen and Ya-Ting
Li tried to identify what mobile application advertising
formats users really liked and accepted. They found that
rich media showed higher advertising effectiveness than
the dynamic banner. Further, the playfulness interactive
mode was better than user control and connectedness for
advertising effectiveness.
Hsin-Chieh Wu, Min-Chi Chiu and Chia-Wei Peng used
an ergonomic perspective to measure eyestrain occurrence
time while watching different display types and stimulation
scenarios. Notably, both display type and stimulation
scenario have significant effects on the eyestrain occurrence
time. They suggested that hand-held intelligent devices
should intelligently remind users to rest according to the time
spent viewing from the AMOLED (active matrix organic
light emitting diode) or TFT-LCD (thin film transistor-liquid
crystal display) screen, as well as while watching static text
or dynamic images. Their findings can be applied to
developing an ambient intelligent system that can intelligently
remind the user to take a rest before visual fatigue occurs.
The growth of LED (light-emitting diodes) lighting
applications has accelerated along with LED lighting
efficiency and characteristics enhancements. Energy issue and
policy formulation considerations are concerns among
governments all over the world. Chien-Chun Lu, Chinmei
Chou, Akira Yasukouchi, Tomoaki Koz (...truncated)