A Scheduling Method for
Switching Playback Speed in Selective Contents Broadcasting (181-196)
Daichi Fukui and Yusuke Gotoh
In selective contents broadcasting,
i.e. watching contents users selected themselves, the server can deliver
several contents to many users. However, when users watch the data
continuously, waiting time occurs by decreasing the available bandwidth
and increasing the number of contents. Therefore, many researchers have
proposed scheduling methods to reduce the waiting time. Although the
conventional method reduces waiting time by producing the broadcast
schedule in fast-forwarding, that for playing contents in normal
playback becomes lengthened. In this paper, we propose a scheduling
method for switching the playback speed in selective contents
broadcasting. Our proposed method can make the broadcast schedule based
on the configuration of the program and the available bandwidth. In
addition, waiting time can be reduced by dividing each content into two
types of data for fast-forwarding and normal playback and scheduling
them.
Intelligent Personal Health
Devices Converged with Internet of Things Networks (197-212)
James J. Kang and Henry Larkin
Smartphone technology has become more
popular and innovative over the last few years, and has led to the
prevalence of wearable devices embedded with body sensors for fitness
tracking and various smartphone features. Internet of Things (IoT),
which can interact with wearables and personal sensor devices (PSDs), is
emerging with technologies such as mobile health (mHealth), the cloud,
big data and smart environments like smart homes. It may also provide
enhanced services utilising health data obtained from physiological
sensors. When these sensors are converged with IoT devices, the volume
of transactions and traffic are expected to increase immensely due to
the increased demand of health data from the IoT network. These
additional demands will affect the existing mHealth services. Health
service providers may also demand more data to enhance their services
such as real-time monitoring and actuation of sensors alongside the
existing monitoring of traffic. Both of these situations can cause rapid
battery consumption and consume significant bandwidth. Some PSDs are
implanted on or inside the body, and may require invasive surgical
operations to replace batteries, such as for a heart pacemaker. It is
therefore crucial to save and conserve power consumption in order to
reduce the frequency of such procedures as well as health data
transmission when needed. There has not yet been any research into
managing and controlling data processing and transmission to reduce
transactions by applying intelligence onto body sensors. This paper
provides a novel approach and solution to reduce data transactions in
sensors and allow for the transfer of critical data without failure to
medical practitioners over IoT traffic. This can be done via an
inference system to transfer health data collected by body sensors
efficiently and effectively to mHealth and IoT networks. The results
from the experiments to reduce bandwidth and battery resources with
heart rate sensors show a possible savings in resource usage of between
66% and 99.5%. Battery power can be saved by 3.14 Watts in the
experiments if the transmission of a single 1KB data point is reduced,
and by 7.47 Watts if the transmission of 628 data points totalling the
size of 120KB is reduced. The accuracy of data inference between the
originally sensed data and the data transmitted after inference can be
maintained by up to 99% or more. Such savings have the potential of
making always-on mHealth devices a practical reality. This research
contributes a low-overhead approach to mHealth sensors by inferring the
processing and transferring of data.
When Game Theories Meets Security and Privacy Related Risk
Assessment of Vehicular Networks (VANET) (213-224)
Sara Bahamou, Driss El Ouadghiri, and Jean-Marie
Bonnin
Vehicular ad-hoc
networks faces numerous challenges, in particular Security and Privacy
issues. Here, security assessment, risk evaluation and many other
security features/ calculations are based generally on theoretical
ideas, that may project in different level real life conditions. Hence,
the existing of an important risk that these analysis may not work
properly. We shouldn't forget that the important goal of
VANET
applications deployment is to reduce accident rate, which means the
reduction of the human deaths and injuries number. Hence, our focus on
the importance of strengthening the security aspect of different
VANET
applications and services, Which could be achieved by relying on
security requirements. We found many research approaches covering a
significant part of
VANETs
security and risk assessment challenges. This article is dedicated to
the most crucial challenges in every security analysis methodology which
is the study of different attack scenarios. These scenarios are
generally in accordance with the most feared threats. So our goal here,
is to determine the most probably attack scenario and how we can deploy
the appropriate countermeasures in such a way some risks are acceptable.
Therefore, our approach to
VANET
defense applies attack tree- defense tree for advanced vulnerabilities
assessment and intrusion detection. Attack tree processing shows how
attackers can penetrate a
VANET,
so by identifying critical vulnerabilities we can provide strategies for
protecting the critical network assets. Thus, attack-tree leads us to
the optimal intrusion detection and attack response. A strong link is
existed between attacker and defender assets, which can be modeled by a
mathematical analysis, called game theory analysis. This game approach
has demonstrated the interaction in the attack-tree processing.
Comparing the Placement of Two Arm-Worn Devices for
Recognizing Dynamic Hand Gestures (225-242)
Kathrin Kefer, Clemens
Holzmann, and Rainhard Dieter Findling
Dynamic hand gestures become
increasingly popular as touch-free input
modality
for interactive systems. There exists a variety of arm-worn devices for
recognition of hand gestures, which differ not only in their
capabilities, but also in their positioning on users' arms. These
differences in positioning might influence how well gestures are
recognized, leading to different gesture recognition
accuracies.
In this paper we therefore investigate the effect of device placement on
dynamic hand gesture recognition accuracy. We consider devices being
strapped to the forearm on two positions: the wrist and below the elbow.
These positions represent smart watches being worn on the wrist and
devices with
EMG
sensors for the detection of static hand gestures (e.g\
spreading the fingers) being worn right below the elbow. Our initial
hypothesis is that wrist-worn devices will have better recognition
accuracy, caused by higher acceleration values of a bigger action radius
with dynamic hand gestures on the wrist. We conduct a comparative study
using an LG G Watch and
Thalmic
Labs'
Myo armband, for which we record a
total of 12960 gesture samples of eight simple dynamic gestures in three
different variants with eight participants. We evaluate a
potential difference in gesture recognition
accuracies
using different feature sets and classifiers. Although recognition
accuracies for wrist-worn devices
seem higher, the difference is not statistically significant due to
substantial variations in accuracy across participants. We thus cannot
conclude that different positions of gesture recording devices on the
lower arm have significant influence or correctly recognizing arm
gestures.
A Comparison of Techniques
for Cross-Device Interaction from Mobile Devices to Large
Displays (243-264)
Jeni
Paay, Dimitrios Raptis, Jesper Kjeldskov, Bjarke M. Lauridsen, Ivan S.
Penchev, Elias
Ringhauge, and Eric V. Ruder
In recent years there has been an
increasing interest in cross-device interaction research involving
mobile computing. We contribute to this research with a comparative
study of four interaction techniques for moving information from a
mobile device to a large display. The four techniques (Pinch, Swipe,
Throw, and Tilt) were compared through a laboratory experiment with 53
participants, measuring their effectiveness, efficiency and error size.
Findings from the experiment revealed that the Swipe technique performed
best on all measures. In terms of effectiveness, the Tilt technique
performed the worst, and especially so with small targets. In terms of
efficiency and error size, the Pinch technique was the slowest and also
the most imprecise. We also found that target size mattered considerably
for all techniques, confirming previous research. Based on our findings
we discuss why the individual techniques performed as observed, and
discuss implications for using mobile devices in cross-device
interaction design.
Sparse Canonicial Correlation Analysis for Mobile Media Recognition on the Cloud
(265-276)
Yangjiang Wang, Bin Zhou,
Weifeng Liu, and Huimin Zhang
With the rapid development of the
Internet technology and smartphone, people can easily capture and upload
media information including text, audio, photos, and video. And then it
becomes one critical demand to effectively and efficiently manage these
personal multimedia that are often presented in multiple modalities.
Canonical correlation analysis (CCA) has been widely employed for
multi-modal data in many applications because of its promising
performance in feature extraction and subspace learning for multivariate
vectors. However, the traditional CCA may be difficult to interpret
especially when the original variables are expected to involve only a
few components. In this paper, we develop a mobile media recognition
method on the cloud. Particularly, we propose sparse canonical
correlation analysis (SCCA) on the cloud. SCCA can find a reasonable
trade-off between statistical fidelity and interpretability.
Furthermore, we employ a generalised power method to optimise the SCCA
algorithm. Finally, we conduct extensive experiments for recognition on
several popular databases including UCI datasets and USAA dataset.
Experimental results demonstrate that the proposed SCCA algorithm
outperforms the traditional CCA algorithm.
A Variance
Distortion Rate Control Scheme for combined Spatial-Temporal Scalable Video
Coding (277-290)
L. Balaji, A. Dhanalakshmi, and C.
Chellaswamy
Rate Control plays an important role in
video compression for transportation over heterogeneous network
bandwidth varying conditions. A combined spatial-temporal rate control
scheme is proposed for scalable video coding. Introductory quantization
parameter estimation is determined based on complete variance distortion
method for I frame of first GOP and estimates buffer occupancy level.
With the estimated buffer level, target bits are determined considering
the coding complexity is proposed in the rate control scheme. In
addition, a proportional integral and derivative (PID) controller that
calculates the error and minimize fluctuation between the actual buffer
fullness and target buffer fullness for competent buffer utilization. As
a result, the proposed scheme exploits entire buffer exclusive of
crossing overflow and underflow level. The investigational results are
compared with other two benchmark schemes and the proposed scheme can
able to achieve better target bit adjustment with condensed fluctuations
and competent buffer utilization.
Analysis and Evaluation of Feature Detection and Tracking Techniques
Using Open
CV with Focus on Markerless Augmented Reality Applications (291-302)
Gustavo Maglhaes Moura and Rodrigo Luis de Souza da Silva
Augmented Reality (AR) is a
technology able to extend human interactions with the real world. One
field of study in AR is the use of real objects as markers. To perform
this task, feature recognition of the real world by computer systems
must be performed. This work consists in the analysis and evaluation of
several algorithms available in
OpenCV
library that allow the detection of
pre-established
patterns in images and videos. The main contribution of this work is to
present the most appropriate combination of algorithms to help the
development of
markerless
AR applications.