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Individual behavior towards mobile services acceptance in the airline sector: A survey in Saudi Arabia
A survey on Human Mobility and its applications
Human Mobility has attracted attentions from different fields of studies such
as epidemic modeling, traffic engineering, traffic prediction and urban
planning. In this survey we review major characteristics of human mobility
studies including from trajectory-based studies to studies using graph and
network theory. In trajectory-based studies statistical measures such as jump
length distribution and radius of gyration are analyzed in order to investigate
how people move in their daily life, and if it is possible to model this
individual movements and make prediction based on them. Using graph in mobility
studies, helps to investigate the dynamic behavior of the system, such as
diffusion and flow in the network and makes it easier to estimate how much one
part of the network influences another by using metrics like centrality
measures. We aim to study population flow in transportation networks using
mobility data to derive models and patterns, and to develop new applications in
predicting phenomena such as congestion. Human Mobility studies with the new
generation of mobility data provided by cellular phone networks, arise new
challenges such as data storing, data representation, data analysis and
computation complexity. A comparative review of different data types used in
current tools and applications of Human Mobility studies leads us to new
approaches for dealing with mentioned challenges
Sybil attacks against mobile users: friends and foes to the rescue
Collaborative applications for co-located mobile
users can be severely disrupted by a sybil attack to the point of
being unusable. Existing decentralized defences have largely been
designed for peer-to-peer networks but not for mobile networks.
That is why we propose a new decentralized defence for portable
devices and call it MobID. The idea is that a device manages two
small networks in which it stores information about the devices
it meets: its network of friends contains honest devices, and its
network of foes contains suspicious devices. By reasoning on these
two networks, the device is then able to determine whether
an unknown individual is carrying out a sybil attack or not.
We evaluate the extent to which MobID reduces the number
of interactions with sybil attackers and consequently enables
collaborative applications.We do so using real mobility and social
network data. We also assess computational and communication
costs of MobID on mobile phones
Entropic measures of individual mobility patterns
Understanding human mobility from a microscopic point of view may represent a
fundamental breakthrough for the development of a statistical physics for
cognitive systems and it can shed light on the applicability of macroscopic
statistical laws for social systems. Even if the complexity of individual
behaviors prevents a true microscopic approach, the introduction of mesoscopic
models allows the study of the dynamical properties for the non-stationary
states of the considered system. We propose to compute various entropy measures
of the individual mobility patterns obtained from GPS data that record the
movements of private vehicles in the Florence district, in order to point out
new features of human mobility related to the use of time and space and to
define the dynamical properties of a stochastic model that could generate
similar patterns. Moreover, we can relate the predictability properties of
human mobility to the distribution of time passed between two successive trips.
Our analysis suggests the existence of a hierarchical structure in the mobility
patterns which divides the performed activities into three different
categories, according to the time cost, with different information contents. We
show that a Markov process defined by using the individual mobility network is
not able to reproduce this hierarchy, which seems the consequence of different
strategies in the activity choice. Our results could contribute to the
development of governance policies for a sustainable mobility in modern cities
Smartphones
Many of the research approaches to smartphones actually regard them as more or less transparent points of access to other kinds of communication experiences. That is, rather than considering the smartphone as something in itself, the researchers look at how individuals use the smartphone for their communicative purposes, whether these be talking, surfing the web, using on-line data access for off-site data sources, downloading or uploading materials, or any kind of interaction with social media. They focus not so much on the smartphone itself but on the activities that people engage in with their smartphones
Innovation in Mobile Learning: A European Perspective
In the evolving landscape of mobile learning, European researchers have conducted significant mobile learning projects, representing a distinct perspective on mobile learning research and development. Our paper aims to explore how these projects have arisen, showing the driving forces of European innovation in mobile learning. We propose context as a central construct in mobile learning and examine theories of learning for the mobile world, based on physical, technological, conceptual, social and temporal mobility. We also examine the impacts of mobile learning research on educational practices and the implications for policy. Throughout, we identify lessons learnt from European experiences to date
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