23,507 research outputs found
Quality assessment technique for ubiquitous software and middleware
The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future
Objective assessment of region of interest-aware adaptive multimedia streaming quality
Adaptive multimedia streaming relies on controlled
adjustment of content bitrate and consequent video quality variation in order to meet the bandwidth constraints of the communication
link used for content delivery to the end-user. The values of the easy to measure network-related Quality of Service metrics have no direct relationship with the way moving images are
perceived by the human viewer. Consequently variations in the video stream bitrate are not clearly linked to similar variation in the user perceived quality. This is especially true if some human visual system-based adaptation techniques are employed. As research has shown, there are certain image regions in each frame of a video sequence on which the users are more interested than in the others. This paper presents the Region of Interest-based Adaptive Scheme (ROIAS) which adjusts differently the regions within each frame of the streamed multimedia content based on the user interest in them. ROIAS is presented and discussed in terms of the adjustment algorithms employed and their impact on the human perceived video quality. Comparisons with existing approaches, including a constant quality adaptation scheme across the whole frame area, are performed employing two objective metrics which estimate user perceived video quality
A Comparison of Spatial-based Targeted Disease Containment Strategies using Mobile Phone Data
Epidemic outbreaks are an important healthcare challenge, especially in
developing countries where they represent one of the major causes of mortality.
Approaches that can rapidly target subpopulations for surveillance and control
are critical for enhancing containment processes during epidemics.
Using a real-world dataset from Ivory Coast, this work presents an attempt to
unveil the socio-geographical heterogeneity of disease transmission dynamics.
By employing a spatially explicit meta-population epidemic model derived from
mobile phone Call Detail Records (CDRs), we investigate how the differences in
mobility patterns may affect the course of a realistic infectious disease
outbreak. We consider different existing measures of the spatial dimension of
human mobility and interactions, and we analyse their relevance in identifying
the highest risk sub-population of individuals, as the best candidates for
isolation countermeasures. The approaches presented in this paper provide
further evidence that mobile phone data can be effectively exploited to
facilitate our understanding of individuals' spatial behaviour and its
relationship with the risk of infectious diseases' contagion. In particular, we
show that CDRs-based indicators of individuals' spatial activities and
interactions hold promise for gaining insight of contagion heterogeneity and
thus for developing containment strategies to support decision-making during
country-level pandemics
EVEREST IST - 2002 - 00185 : D23 : final report
Deliverable públic del projecte europeu EVERESTThis deliverable constitutes the final report of the project IST-2002-001858 EVEREST. After its successful completion, the project presents this document that firstly summarizes the context, goal and the approach objective of the project. Then it presents a concise summary of the major goals and results, as well as highlights the most valuable lessons derived form the project work. A list of deliverables and publications is included in the annex.Postprint (published version
An Information-Theoretic Framework for Consistency Maintenance in Distributed Interactive Applications
Distributed Interactive Applications (DIAs) enable geographically dispersed users
to interact with each other in a virtual environment. A key factor to the success
of a DIA is the maintenance of a consistent view of the shared virtual world for
all the participants. However, maintaining consistent states in DIAs is difficult
under real networks. State changes communicated by messages over such networks
suffer latency leading to inconsistency across the application. Predictive Contract
Mechanisms (PCMs) combat this problem through reducing the number of messages
transmitted in return for perceptually tolerable inconsistency. This thesis examines
the operation of PCMs using concepts and methods derived from information theory.
This information theory perspective results in a novel information model of PCMs
that quantifies and analyzes the efficiency of such methods in communicating the
reduced state information, and a new adaptive multiple-model-based framework for
improving consistency in DIAs.
The first part of this thesis introduces information measurements of user behavior
in DIAs and formalizes the information model for PCM operation. In presenting the
information model, the statistical dependence in the entity state, which makes using
extrapolation models to predict future user behavior possible, is evaluated. The
efficiency of a PCM to exploit such predictability to reduce the amount of network
resources required to maintain consistency is also investigated. It is demonstrated
that from the information theory perspective, PCMs can be interpreted as a form
of information reduction and compression.
The second part of this thesis proposes an Information-Based Dynamic Extrapolation
Model for dynamically selecting between extrapolation algorithms based on
information evaluation and inferred network conditions. This model adapts PCM
configurations to both user behavior and network conditions, and makes the most
information-efficient use of the available network resources. In doing so, it improves
PCM performance and consistency in DIAs
Symbolic representation of scenarios in Bologna airport on virtual reality concept
This paper is a part of a big Project named Retina Project, which is focused in reduce the workload of an ATCO. It uses the last technological advances as Virtual Reality concept. The work has consisted in studying the different awareness situations that happens daily in Bologna Airport. It has been analysed one scenario with good visibility where the sun predominates and two other scenarios with poor visibility where the rain and the fog dominate. Due to the study of visibility in the three scenarios computed, the conclusion obtained is that the overlay must be shown with a constant dimension regardless the position of the aircraft to be readable by the ATC and also, the frame and the flight strip should be coloured in a showy colour (like red) for a better control by the ATCO
Layered evaluation of interactive adaptive systems : framework and formative methods
Peer reviewedPostprin
Context-aware multi-head self-attentional neural network model for next location prediction
Accurate activity location prediction is a crucial component of many mobility
applications and is particularly required to develop personalized, sustainable
transportation systems. Despite the widespread adoption of deep learning
models, next location prediction models lack a comprehensive discussion and
integration of mobility-related spatio-temporal contexts. Here, we utilize a
multi-head self-attentional (MHSA) neural network that learns location
transition patterns from historical location visits, their visit time and
activity duration, as well as their surrounding land use functions, to infer an
individual's next location. Specifically, we adopt point-of-interest data and
latent Dirichlet allocation for representing locations' land use contexts at
multiple spatial scales, generate embedding vectors of the spatio-temporal
features, and learn to predict the next location with an MHSA network. Through
experiments on two large-scale GNSS tracking datasets, we demonstrate that the
proposed model outperforms other state-of-the-art prediction models, and reveal
the contribution of various spatio-temporal contexts to the model's
performance. Moreover, we find that the model trained on population data
achieves higher prediction performance with fewer parameters than
individual-level models due to learning from collective movement patterns. We
also reveal mobility conducted in the recent past and one week before has the
largest influence on the current prediction, showing that learning from a
subset of the historical mobility is sufficient to obtain an accurate location
prediction result. We believe that the proposed model is vital for
context-aware mobility prediction. The gained insights will help to understand
location prediction models and promote their implementation for mobility
applications.Comment: updated Discussion section; accepted by Transportation Research Part
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