1,856 research outputs found
Custom Dual Transportation Mode Detection by Smartphone Devices Exploiting Sensor Diversity
Making applications aware of the mobility experienced by the user can open
the door to a wide range of novel services in different use-cases, from smart
parking to vehicular traffic monitoring. In the literature, there are many
different studies demonstrating the theoretical possibility of performing
Transportation Mode Detection (TMD) by mining smart-phones embedded sensors
data. However, very few of them provide details on the benchmarking process and
on how to implement the detection process in practice. In this study, we
provide guidelines and fundamental results that can be useful for both
researcher and practitioners aiming at implementing a working TMD system. These
guidelines consist of three main contributions. First, we detail the
construction of a training dataset, gathered by heterogeneous users and
including five different transportation modes; the dataset is made available to
the research community as reference benchmark. Second, we provide an in-depth
analysis of the sensor-relevance for the case of Dual TDM, which is required by
most of mobility-aware applications. Third, we investigate the possibility to
perform TMD of unknown users/instances not present in the training set and we
compare with state-of-the-art Android APIs for activity recognition.Comment: Pre-print of the accepted version for the 14th Workshop on Context
and Activity Modeling and Recognition (IEEE COMOREA 2018), Athens, Greece,
March 19-23, 201
Understanding customer satisfaction with services by leveraging big data: the role of services attributes and consumers’ cultural background
User-generated content and online reviews are becoming an increasingly relevant source of
information for online customers that use them for purchasing decisions. This study examines the impact
of services attributes and consumers’ cultural background on customer satisfaction with services in an
online setting using big data. First, almost half a million Expedia.com hotel online reviews related to hotel
properties located in five different countries (United States, United Kingdom, Italy, Spain, Russia) were
retrieved. Second, the resulting dataset was used to investigate if and to what extent the overall customer
satisfaction with a service is affected by the evaluation of specific hotel services attributes (operationalized
based on an established typology of attributes) and by the consumers’ cultural background (operationalized
by means of Hoftstede’s framework). A comprehensive multivariate regression analysis is carried out to test
the literature-driven hypotheses formulated. In particular, the analysis reveals that critical service attributes
such as hotel condition, room comfort, service and staff, and cleanliness positively affect the overall online
satisfaction ratings. The cultural dimensions of power distance, individualism and uncertainty avoidance
negatively affect overall online satisfaction, while long-term orientation and indulgence positively affect
online satisfaction. Masculinity seem not to play a significant role. We also observe that reviews’ text length
exerts a negative impact on online ratings. Theoretical and practical implications are discussed
Context-Aware Android Applications through Transportation Mode Detection Techniques
In this paper, we study the problem of how to detect the current transportation mode of the user from the smartphone sensors data, because this issue is considered crucial for the deployment of a multitude of mobility-aware systems, ranging from trace collectors to health monitoring and urban sensing systems. Although some feasibility studies have been performed in the literature, most of the proposed systems rely on the utilization of the GPS and on computational expensive algorithms that do not take into account the limited resources of mobile phones. On the opposite, this paper focuses on the design and implementation of a feasible and efficient detection system that takes into account both the issues of accuracy of classification and of energy consumption. To this purpose, we propose the utilization of embedded sensor data (accelerometer/gyroscope) with a novel meta-classifier based on a cascading technique, and we show that our combined approach can provide similar performance than a GPS-based classifier, but introducing also the possibility to control the computational load based on requested confidence. We describe the implementation of the proposed system into an Android framework that can be leveraged by third-part mobile applications to access context-aware information in a transparent way
The determinants of Facebook social engagement for National Tourism Organisations’ Facebook pages: a quantitative approach
This work explores how the National Tourism Organizations (NTOs) of the top 10 most visited countries by international tourists strategically employ Facebook to promote and market their destinations. Based on big data retrieved from the NTOs’ Facebook pages, and leveraging advanced metrics for capturing user engagement, the study sheds light on the factors contributing to superior level of social activity. The findings indicate that the way Facebook is tactically employed varies significantly across sampled NTOs. The panel data regression analyses suggest that engagement is positively affected by posting visual content (namely photos), and posting during the weekends, and negatively affected by evening posting. Post frequency displays no statistically significant effect on social engagement. The study also shows that most of the NTOs (except for Italy, Spain, Turkey and the UK) deploy Facebook with a top-down approach, and spontaneous user generated content (UGC) is allowed to a very little extent
Cross-layer optimizations in multi-hop ad hoc networks
Unlike traditional wireless networks, characterized by the presence of last-mile, static and
reliable infrastructures, Mobile ad Hoc Networks (MANETs) are dynamically formed by
collections of mobile and static terminals that exchange data by enabling each other's
communication. Supporting multi-hop communication in a MANET is a challenging
research area because it requires cooperation between different protocol layers (MAC,
routing, transport). In particular, MAC and routing protocols could be considered
mutually cooperative protocol layers. When a route is established, the exposed and
hidden terminal problems at MAC layer may decrease the end-to-end performance
proportionally with the length of each route. Conversely, the contention at MAC layer
may cause a routing protocol to respond by initiating new routes queries and routing table
updates.
Multi-hop communication may also benefit the presence of pseudo-centralized virtual
infrastructures obtained by grouping nodes into clusters. Clustering structures may
facilitate the spatial reuse of resources by increasing the system capacity: at the same
time, the clustering hierarchy may be used to coordinate transmissions events inside the
network and to support intra-cluster routing schemes. Again, MAC and clustering
protocols could be considered mutually cooperative protocol layers: the clustering
scheme could support MAC layer coordination among nodes, by shifting the distributed
MAC paradigm towards a pseudo-centralized MAC paradigm. On the other hand, the
system benefits of the clustering scheme could be emphasized by the pseudo-centralized
MAC layer with the support for differentiated access priorities and controlled contention.
In this thesis, we propose cross-layer solutions involving joint design of MAC, clustering
and routing protocols in MANETs.
As main contribution, we study and analyze the integration of MAC and clustering
schemes to support multi-hop communication in large-scale ad hoc networks. A novel
clustering protocol, named Availability Clustering (AC), is defined under general nodes'
heterogeneity assumptions in terms of connectivity, available energy and relative
mobility. On this basis, we design and analyze a distributed and adaptive MAC protocol,
named Differentiated Distributed Coordination Function (DDCF), whose focus is to
implement adaptive access differentiation based on the node roles, which have been
assigned by the upper-layer's clustering scheme. We extensively simulate the proposed
clustering scheme by showing its effectiveness in dominating the network dynamics,
under some stressing mobility models and different mobility rates. Based on these results,
we propose a possible application of the cross-layer MAC+Clustering scheme to support
the fast propagation of alert messages in a vehicular environment.
At the same time, we investigate the integration of MAC and routing protocols in large
scale multi-hop ad-hoc networks. A novel multipath routing scheme is proposed, by
extending the AOMDV protocol with a novel load-balancing approach to concurrently
distribute the traffic among the multiple paths. We also study the composition effect of a
IEEE 802.11-based enhanced MAC forwarding mechanism called Fast Forward (FF),
used to reduce the effects of self-contention among frames at the MAC layer. The
protocol framework is modelled and extensively simulated for a large set of metrics and
scenarios.
For both the schemes, the simulation results reveal the benefits of the cross-layer
MAC+routing and MAC+clustering approaches over single-layer solutions
Vacancies in graphene: an application of adiabatic quantum optimization
Quantum annealers have grown in complexity to the point that quantum
computations involving few thousands of qubits are now possible. In this paper,
\textcolor{black}{with the intentions to show the feasibility of quantum
annealing to tackle problems of physical relevance, we used a simple model,
compatible with the capability of current quantum annealers, to study} the
relative stability of graphene vacancy defects. By mapping the crucial
interactions that dominate carbon-vacancy interchange onto a quadratic
unconstrained binary optimization problem, our approach exploits
\textcolor{black}{the ground state as well the excited states found by} the
quantum annealer to extract all the possible arrangements of multiple defects
on the graphene sheet together with their relative formation energies. This
approach reproduces known results and provides a stepping stone towards
applications of quantum annealing to problems of physical-chemical interest
6G to Take the Digital Divide by Storm: Key Technologies and Trends to Bridge the Gap
The pandemic caused by COVID-19 has shed light on the urgency of bridging the digital
divide to guarantee equity in the fruition of different services by all citizens. The inability to access
the digital world may be due to a lack of network infrastructure, which we refer to as service-delivery
divide, or to the physical conditions, handicaps, age, or digital illiteracy of the citizens, that is
mentioned as service-fruition divide. In this paper, we discuss the way how future sixth-generation
(6G) systems can remedy actual limitations in the realization of a truly digital world. Hence, we
introduce the key technologies for bridging the digital gap and show how they can work in two
use cases of particular importance, namely eHealth and education, where digital inequalities have
been dramatically augmented by the pandemic. Finally, considerations about the socio-economical
impacts of future 6G solutions are drawn
Blockchain and Web of Things for Structural Health Monitoring Applications: A Proof of Concept
Interoperable and secure data management techniques are fundamental for most of large-scale Structural Health Monitoring (SHM) systems. Indeed, given the relevance of SHM critical measurements, data integrity must be protected against tampering or falsifications. In this paper, we propose a four-layer SHM architecture that allows to build an effective data pipeline from sensors to consumer applications, passing through the cloud. The architecture is built on top of the MODRON platform and exploits the recent advances of the W3C Web of Things (WoT) standard for interoperability. We then discuss how third-party services can take benefit of the W3C WoT architecture to retrieve the SHM critical data and to publish them on the Ethereum Blockchain through an SHM-specific Smart Contract, for data protection and traceability purposes. We test the effectiveness of the Smart Contract implementation in terms of latency and costs under simulated workload
Unraveling the Mechanism of Tip-Enhanced Molecular Energy Transfer
Electronic Energy Transfer (EET) between chromophores is fundamental in many
natural light-harvesting complexes, serving as a critical step for solar energy
funneling in photosynthetic plants and bacteria. The complicated role of the
environment in mediating this process in natural architectures has been
addressed by recent scanning tunneling microscope (STM) experiments involving
EET between two molecules supported on a solid substrate [Cao, S. et al., Nat.
Chem. 2021, 13, 766-770]. These measurements demonstrated that EET in such
conditions has peculiar features, such as a steep dependence on the
donor-acceptor distance, reminiscent of a short-range mechanism more than of a
Forster-like process. By using state of the art hybrid ab initio
electromagnetic modeling, here we provide a comprehensive theoretical analysis
of tip-enhanced EET. In particular, we show that this process can be understood
as a complex interplay of electromagnetic-based molecular plasmonic processes,
whose result may effectively mimic short range effects. Therefore, the
established identification of an exponential decay with Dexter-like effects
does not hold for tip-enhanced EET, and accurate electromagnetic modeling is
needed to identify the EET mechanism
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