pinecone/core-2020-05-10-deduplication huggingface dataset:
Studying Emergent Behaviours in Morphogenesis Using Signal Spatio-Temporal Logic

Pattern formation is an important spatio-temporal emergent behaviour in biology. Mathematical models of pattern formation in the stochastic setting are extremely challenging to execute and analyse. Here we propose a formal analysis of the emergent behaviour of stochastic reaction diffusion systems in terms of Signal Spatio-Temporal Logic, a recently proposed logic for reasoning on spatio-temporal systems. We present a formal analysis of the spatio-temporal dynamics of the Bicoid morphogen in Drosophila melanogaster, one of the most important proteins in the formation of the horizontal segmentation in the development of the fly embryo. We use a recently proposed framework for statistical model checking of stochastic systems with uncertainty on parameters to characterise the parametric dependence and robustness of the French Flag pattern, highlighting non-trivial correlations between the parameter values and the emergence of the patterning
Radio-aware service-level scheduling to minimize downlink traffic delay through Mobile Edge Computing

One of the most challenging problems in mobile broadband networks is how to assign the available radio resources among the different mobile users. Traditionally, research proposals are either speci c to some type of traffic or deal with computationally intensive algorithms aimed at optimizing the delivery of general purpose traffic. Consequently, commercial networks do not incorporate these mechanisms due to the limited hardware resources at the mobile edge. Emerging 5G architectures introduce cloud computing principles to add flexible computational
resources to Radio Access Networks. This paper makes use of the Mobile Edge Computing concepts to introduce a new element, denoted as Mobile Edge Scheduler, aimed at minimizing the mean delay of general traffic flows in the LTE downlink. This element runs close to the eNodeB
element and implements a novel flow-aware and channel-aware scheduling policy in order to accommodate the transmissions to the available channel quality of end users.The research leading to these results has received funding from the European Union's H2020 Research and Innovation Project SESAME, under the Grant Agreement H2020-ICT-671596, and from the Spanish Ministerio de Economia y Competitividad (MINECO) under grant TEC2013-46766-R:
QoEverage - QoE- aware optimization mechanisms for next generation networks
and services
The three 'W' of the World Wide Web callfor the three 'M'of a Massively Multidisciplinary Methodology

International audienceThis position paper defends the idea that the development of the Web to its full potential requires addressing the challenge of massive multidisciplinarity. It was triggered by the topic of a joint panel at the conferences CLOSER and WEBIST 2014.The topic of the panel was: " social, political and economic implications of the cloud and the Web ". I focused on the Web and the position that I defended during the panel, and that I report here, is that, while implications of the Web can be identified in social, political and economic domains, the global challenge raised by the Web is the need for massive multidisciplinarity to lead it to its full potential that goes beyond any individual prediction. This article starts with three sections respectively confirming the social, political and economic impacts of the Web. The fourth section shows that in fact many other domains are impacted and the fifth section proposes that this spreading is in fact due to several existential characteristic of the Web. The sixth section concludes insisting on the importance of preserving this open nature of the Web, of assisting it and of addressing the challenge of a massive multidisciplinary approach for developing the Web
Reliability modelling for electricity transmission networks using maintenance records

Maintenance decisions for transmission network assets (TNAs) require accurate reliability prediction of complex repairable systems. There are a number of factors influencing the reliability prediction for TNAs, which includes structure characteristics (e.g. conductor type), voltage, load, and the operating environment (mechanical loading, wind, temperature, pollutants and humidity). The reliability analysis and prediction is complicated by the fact that TNAs are linear assets (as opposed to discrete assets) which require specific modelling approaches for reliability prediction. This paper details a new reliability prediction model for TNAs. Another challenge is that transmission network is hardly fail. Instead of using outage data, where most reliability model used, failure times were identified through extracting significant unplanned maintenance events for critical failure modes. A regression tree based grouping analysis was utilized to analyse the influences by variety of factors on future unplanned maintenance. These results were then used to build the reliability prediction model allowing a decision maker to have an estimate of future unplanned maintenance requirements. A case study using real industry data was conducted to test the proposed reliability prediction model. The results demonstrate the feasibility of using this approach for TNA maintenance decision support
Enhancing information about sustainability features for sustainable housing delivery

Sustainability practices in government regulations and within the society influence the delivery of sustainable housing. The actual delivery rate of Australian sustain-able housing is not as high as other countries. There is an absence of engagement by stakeholders in adopting sustainable housing practices. This may be due, in the current Australian property market, to confusion as to what sustainability features should be considered, given the large range of environmental, economic and social sustainability options possible. One of the main problems appears to be that information demanders, especially real estate agents, valuers, insurance agents and mortgage lenders do not include sustainability perspectives in their advice or in their decision processes. Information distribution in the Australian property market is flawed, resulting in a lack of return-on-investment value of ‘green’ features implemented by some stakeholders. This paper reviewed the global sustainable development concept and Australian sustainable assessment methods. This review identified the possibility of a research project which aimed at identifying and integrating different perceptions and priority needs of the information demanders, for developing a model for the potential implementation of sustainability features distribution in the property industry. This research will reduce confusion on the sustainability-related information which can influence the decision making of stakeholders in the supply and demand of sustainable housing
Comparison of the sensitivity of different sensor technologies to imbalance severity in low speed wind turbines

Imbalance is not only a direct major cause of downtime in wind turbines, but also accelerates the degradation of neighbouring and downstream components (e.g. main bearing, generator). Along with detection, the imbalance quantification is also essential as some residual imbalance always exist even in a healthy turbine. Three different commonly used sensor technologies (vibration, acoustic emission and electrical measurements) are investigated in this work to verify their sensitivity to different imbalance grades. This study is based on data obtained by experimental tests performed on a small scale wind turbine drive train test-rig for different shaft speeds and imbalance levels. According to the analysis results, electrical measurements seem to be the most suitable for tracking the development of imbalance
Models of random sparse eigenmatrices matrices and Bayesian analysis of
  multivariate structure

We discuss probabilistic models of random covariance structures defined by
distributions over sparse eigenmatrices. The decomposition of orthogonal
matrices in terms of Givens rotations defines a natural, interpretable
framework for defining distributions on sparsity structure of random
eigenmatrices. We explore theoretical aspects and implications for conditional
independence structures arising in multivariate Gaussian models, and discuss
connections with sparse PCA, factor analysis and Gaussian graphical models.
Methodology includes model-based exploratory data analysis and Bayesian
analysis via reversible jump Markov chain Monte Carlo. A simulation study
examines the ability to identify sparse multivariate structures compared to the
benchmark graphical modelling approach. Extensions to multivariate normal
mixture models with additional measurement errors move into the framework of
latent structure analysis of broad practical interest. We explore the
implications and utility of the new models with summaries of a detailed applied
study of a 20-dimensional breast cancer genomics data set.Comment: 25 pages, 7 figures. 1 tabl
Availability and Network-Aware MapReduce Task Scheduling over the Internet

International audienceMapReduce offers an ease-of-use programming paradigm for processing large datasets. In our previous work, we have designed a MapReduce framework called BitDew-MapReduce for desktop grid and volunteer computing environment, that allows nonexpert users to run data-intensive MapReduce jobs on top of volunteer resources over the Internet. However, network distance and resource availability have great impact on MapReduce applications running over the Internet. To address this, an availability and network-aware MapReduce framework over the Internet is proposed. Simulation results show that the MapReduce job response time could be decreased by 27.15%, thanks to Naive Bayes Classifier-based availability prediction and landmark-based network estimation
Physics-based Motion Planning: Evaluation Criteria and Benchmarking

Motion planning has evolved from coping with simply geometric problems to
physics-based ones that incorporate the kinodynamic and the physical
constraints imposed by the robot and the physical world. Therefore, the
criteria for evaluating physics-based motion planners goes beyond the
computational complexity (e.g. in terms of planning time) usually used as a
measure for evaluating geometrical planners, in order to consider also the
quality of the solution in terms of dynamical parameters. This study proposes
an evaluation criteria and analyzes the performance of several kinodynamic
planners, which are at the core of physics-based motion planning, using
different scenarios with fixed and manipulatable objects. RRT, EST, KPIECE and
SyCLoP are used for the benchmarking. The results show that KPIECE computes the
time-optimal solution with heighest success rate, whereas, SyCLoP compute the
most power-optimal solution among the planners used.Comment: Robot2015 - Second Iberian Robotics Conferenc
User intention driven adaptive gait assistance using a wearable exoskeleton

A user intention based rehabilitation strategy for a lower-limb wearable robot is proposed and evaluated. The control strategy, which involves monitoring the human-orthosis interaction torques, determines the gait initiation instant and modifies orthosis operation for gait assistance, when needed. Orthosis operation is classified as assistive or resistive in function of its evolution with respect to a normal gait pattern. The control algorithm relies on the adaptation of the joints’ stiffness in function of their interaction torques and their deviation from the desired trajectories. An average of recorded gaits obtained from healthy subjects is used as reference input. The objective of this work is to develop a control strategy that can trigger the gait initiation from the user’s intention and maintain the dynamic stability, using an efficient real-time stiffness adaptation for multiple joints, simultaneously maintaining their synchronization. The algorithm has been tested with five healthy subjects showing its efficient behavior in initiating the gait and maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from incomplete Spinal cord injury and Stroke.Peer ReviewedPostprint (author's final draft
Design of a Realistic Robotic Head based on Action Coding System

Producción CientíficaIn this paper, the development of a robotic head able to move
and show di erent emotions is addressed. The movement and emotion
generation system has been designed following the human facial muscu-
lature. Starting from the Facial Action Coding System (FACS), we have
built a 26 actions units model that is able to produce the most relevant
movements and emotions of a real human head. The whole work has
been carried out in two steps. In the  rst step, a mechanical skeleton
has been designed and built, in which the di erent actuators have been
inserted. In the second step, a two-layered silicon skin has been manu-
factured, on which the di erent actuators have been inserted following
the real muscle-insertions, for performing the di erent movements and
gestures. The developed head has been integrated in a high level be-
havioural architecture, and pilot experiments with 10 users regarding
emotion recognition and mimicking have been carried out.Junta de Castilla y León (Programa de apoyo a proyectos de investigación-Ref. VA036U14)Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. VA013A12-2)Ministerio de Economía, Industria y Competitividad (Grant DPI2014-56500-R
Low cost, robust and real time system for detecting and tracking moving objects to automate cargo handling in port terminals

The presented paper addresses the problem of detecting and tracking moving objects for autonomous cargo handling in port terminals using a perception system which input data is a single layer laser scanner. A computationally low cost and robust Detection and Tracking Moving Objects (DATMO) algorithm is presented to be used in autonomous guided vehicles and autonomous trucks for efficient transportation of cargo in ports. The method first detects moving objects and then tracks them, taking into account that in port terminals the structure of the environment is formed by containers and that the moving objects can be trucks, AGV, cars, straddle carriers and people among others. Two approaches of the DATMO system have been tested, the first one is oriented to detect moving obstacles and focused on tracking and filtering those detections; and the second one is focused on keepking targets when no detections are provided. The system has been evaluated with real data obtained in the CTT port terminal in Hengelo, the Netherlands. Both methods have been tested in the dataset with good results in tracking moving objects.Peer ReviewedPostprint (author's final draft
Ball detection for robotic soccer: a real-time RGB-D approach

The robotic football competition has encouraged the participants to develop
new ways of solving different problems in order to succeed in the competition.
This article shows a different approach to the ball detection and recognition by the
robot using a Kinect System. It has enhanced the capabilities of the depth camera
in detecting and recognizing the ball during the football match. This is important
because it is possible to avoid the noise that the RGB cameras are subject to for
example lighting issues.info:eu-repo/semantics/publishedVersio
Real time people detection combining appearance and depth image spaces using boosted random ferns

This paper presents a robust and real-time method for people detection in urban and crowed environments. Unlike other conventional methods which either focus on single features or compute multiple and independent classifiers specialized in a particular feature space, the proposed approach creates a synergic combination of appearance and depth cues in a unique classifier. The core of our method is a Boosted Random Ferns classifier that selects automatically the most discriminative local binary features for both the appearance and depth image spaces. Based on this classifier, a fast and robust people detector which maintains high detection rates in spite of environmental changes is created. The proposed method has been validated in a challenging RGB-D database of people in urban scenarios and has shown that outperforms state-of-the-art approaches in spite of the difficult environment conditions. As a result, this method is of special interest for real-time robotic applications where people detection is a key matter, such as human-robot interaction or safe navigation of mobile robots for example.Peer ReviewedPostprint (author's final draft
Formal Support for Standardizing Protocols with State

Many cryptographic protocols are designed to achieve their goals using only
messages passed over an open network. Numerous tools, based on well-understood
foundations, exist for the design and analysis of protocols that rely purely on
message passing. However, these tools encounter difficulties when faced with
protocols that rely on non-local, mutable state to coordinate several local
sessions.
  We adapt one of these tools, {\cpsa}, to provide automated support for
reasoning about state. We use Ryan's Envelope Protocol as an example to
demonstrate how the message-passing reasoning can be integrated with state
reasoning to yield interesting and powerful results.
  Keywords: protocol analysis tools, stateful protocols, TPM, PKCS#11
STRATUS: Towards returning data control to cloud users

When we upload or create data into the cloud or the web, we immediately lose control of our data. Most of the time, we will not know where the data will be stored, or how many copies of our files are there. Worse, we are unable to know and stop malicious insiders from accessing the possibly sensitive data. Despite being transferred across and within clouds over encrypted channels, data often has to be decrypted within the database for it to be processed. Exposing the data at some point in the cloud to a few privileged users is undoubtedly a vendor-centric approach, and hinges on the trust relationships data owners have with their cloud service providers. A recent example of the abuse of the trust relationship is the high-profile Edward Snowden case. In this paper, we propose a user-centric approach which returns data control to the data owners – empowering users with data provenance, transparency and auditability, homomorphic encryption, situation awareness, revocation, attribution and data resilience. We also cover key elements of the concept of user data control. Finally, we introduce how we attempt to address these issues via the New Zealand Ministry of Business Innovation and Employment (MBIE)-funded STRATUS (Security Technologies Returning Accountability, Trust and User-centric Services in the Cloud) research project
Comparison of cube attacks over different vector spaces

The final publication is\ud
available at http://dx.doi.org/10.1007/978-3-319-27239-9_14We generalise the cube attack of Dinur and Shamir (and the similar AIDA attack of Vielhaber) to a more general higher order differentiation attack, by summing over an arbitrary subspace of the space of initialisation vectors. The Moebius transform can be used for efficiently examining all the subspaces of a big space, similar to the method used by Fouque and Vannet for the usual cube attack.\ud
\ud
Secondly we propose replacing the Generalised Linearity Test proposed by Dinur and Shamir with a test based on higher order differentiation/Moebius transform. We show that the proposed test provides all the information provided by the Generalised Linearity Test, at the same computational cost. In addition, for functions that do not pass the linearity test it also provides, at no extra cost, an estimate of the degree of the function. This is useful for guiding the heuristics for the cube/AIDA attacks
Continuous after-the-fact leakage-resilient eCK-secure key exchange

Security models for two-party authenticated key exchange (AKE) protocols have developed over time to capture the security of AKE protocols even when the adversary learns certain secret values. Increased granularity of security can be modelled by considering partial leakage of secrets in the manner of models for leakage-resilient cryptography, designed to capture side-channel attacks. In this work, we use the strongest known partial-leakage-based security model for key exchange protocols, namely continuous after-the-fact leakage eCK (CAFL-eCK) model. We resolve an open problem by constructing the first concrete two-pass leakage-resilient key exchange protocol that is secure in the CAFL-eCK model
Hidden attractors in fundamental problems and engineering models

Recently a concept of self-excited and hidden attractors was suggested: an
attractor is called a self-excited attractor if its basin of attraction
overlaps with neighborhood of an equilibrium, otherwise it is called a hidden
attractor. For example, hidden attractors are attractors in systems with no
equilibria or with only one stable equilibrium (a special case of
multistability and coexistence of attractors). While coexisting self-excited
attractors can be found using the standard computational procedure, there is no
standard way of predicting the existence or coexistence of hidden attractors in
a system. In this plenary survey lecture the concept of self-excited and hidden
attractors is discussed, and various corresponding examples of self-excited and
hidden attractors are considered
On Minimizing Crossings in Storyline Visualizations

In a storyline visualization, we visualize a collection of interacting
characters (e.g., in a movie, play, etc.) by $x$-monotone curves that converge
for each interaction, and diverge otherwise. Given a storyline with $n$
characters, we show tight lower and upper bounds on the number of crossings
required in any storyline visualization for a restricted case. In particular,
we show that if (1) each meeting consists of exactly two characters and (2) the
meetings can be modeled as a tree, then we can always find a storyline
visualization with $O(n\log n)$ crossings. Furthermore, we show that there
exist storylines in this restricted case that require $\Omega(n\log n)$
crossings. Lastly, we show that, in the general case, minimizing the number of
crossings in a storyline visualization is fixed-parameter tractable, when
parameterized on the number of characters $k$. Our algorithm runs in time
$O(k!^2k\log k + k!^2m)$, where $m$ is the number of meetings.Comment: 6 pages, 4 figures. To appear at the 23rd International Symposium on
  Graph Drawing and Network Visualization (GD 2015