pinecone/core-2020-05-10-deduplication huggingface dataset:
Timing interactions in social simulations: The voter model

The recent availability of huge high resolution datasets on human activities
has revealed the heavy-tailed nature of the interevent time distributions. In
social simulations of interacting agents the standard approach has been to use
Poisson processes to update the state of the agents, which gives rise to very
homogeneous activity patterns with a well defined characteristic interevent
time. As a paradigmatic opinion model we investigate the voter model and review
the standard update rules and propose two new update rules which are able to
account for heterogeneous activity patterns. For the new update rules each node
gets updated with a probability that depends on the time since the last event
of the node, where an event can be an update attempt (exogenous update) or a
change of state (endogenous update). We find that both update rules can give
rise to power law interevent time distributions, although the endogenous one
more robustly. Apart from that for the exogenous update rule and the standard
update rules the voter model does not reach consensus in the infinite size
limit, while for the endogenous update there exist a coarsening process that
drives the system toward consensus configurations.Comment: Book Chapter, 23 pages, 9 figures, 5 table
Graph Metrics for Temporal Networks

Temporal networks, i.e., networks in which the interactions among a set of
elementary units change over time, can be modelled in terms of time-varying
graphs, which are time-ordered sequences of graphs over a set of nodes. In such
graphs, the concepts of node adjacency and reachability crucially depend on the
exact temporal ordering of the links. Consequently, all the concepts and
metrics proposed and used for the characterisation of static complex networks
have to be redefined or appropriately extended to time-varying graphs, in order
to take into account the effects of time ordering on causality. In this chapter
we discuss how to represent temporal networks and we review the definitions of
walks, paths, connectedness and connected components valid for graphs in which
the links fluctuate over time. We then focus on temporal node-node distance,
and we discuss how to characterise link persistence and the temporal
small-world behaviour in this class of networks. Finally, we discuss the
extension of classic centrality measures, including closeness, betweenness and
spectral centrality, to the case of time-varying graphs, and we review the work
on temporal motifs analysis and the definition of modularity for temporal
graphs.Comment: 26 pages, 5 figures, Chapter in Temporal Networks (Petter Holme and
  Jari Saram\"aki editors). Springer. Berlin, Heidelberg 201
Models, Entropy and Information of Temporal Social Networks

Temporal social networks are characterized by {heterogeneous} duration of
contacts, which can either follow a power-law distribution, such as in
face-to-face interactions, or a Weibull distribution, such as in mobile-phone
communication. Here we model the dynamics of face-to-face interaction and
mobile phone communication by a reinforcement dynamics, which explains the data
observed in these different types of social interactions. We quantify the
information encoded in the dynamics of these networks by the entropy of
temporal networks. Finally, we show evidence that human dynamics is able to
modulate the information present in social network dynamics when it follows
circadian rhythms and when it is interfacing with a new technology such as the
mobile-phone communication technology.Comment: 21 pages, 9 figures; Temporal Networks, P. Holme, and J. Saram\"aki
  (Eds.) Understanding Complex Systems Series, Springer (2013
Applications of Temporal Graph Metrics to Real-World Networks

Real world networks exhibit rich temporal information: friends are added and
removed over time in online social networks; the seasons dictate the
predator-prey relationship in food webs; and the propagation of a virus depends
on the network of human contacts throughout the day. Recent studies have
demonstrated that static network analysis is perhaps unsuitable in the study of
real world network since static paths ignore time order, which, in turn,
results in static shortest paths overestimating available links and
underestimating their true corresponding lengths. Temporal extensions to
centrality and efficiency metrics based on temporal shortest paths have also
been proposed. Firstly, we analyse the roles of key individuals of a corporate
network ranked according to temporal centrality within the context of a
bankruptcy scandal; secondly, we present how such temporal metrics can be used
to study the robustness of temporal networks in presence of random errors and
intelligent attacks; thirdly, we study containment schemes for mobile phone
malware which can spread via short range radio, similar to biological viruses;
finally, we study how the temporal network structure of human interactions can
be exploited to effectively immunise human populations. Through these
applications we demonstrate that temporal metrics provide a more accurate and
effective analysis of real-world networks compared to their static
counterparts.Comment: 25 page
Time allocation in social networks: correlation between social structure
  and human communication dynamics

Recent research has shown the deep impact of the dynamics of human
interactions (or temporal social networks) on the spreading of information,
opinion formation, etc. In general, the bursty nature of human interactions
lowers the interaction between people to the extent that both the speed and
reach of information diffusion are diminished. Using a large database of 20
million users of mobile phone calls we show evidence this effect is not
homogeneous in the social network but in fact, there is a large correlation
between this effect and the social topological structure around a given
individual. In particular, we show that social relations of hubs in a network
are relatively weaker from the dynamical point than those that are poorer
connected in the information diffusion process. Our results show the importance
of the temporal patterns of communication when analyzing and modeling dynamical
process on social networks.Comment: 16 pages, 7 figures, Chapter of the book "Temporal Networks",
  Springer, 2013. Series: Understanding Complex Systems. Holme, Petter;
  Saramaki, Jari (Eds.
Heavy Metal Levels in Dog Liver and Kidney in Naples (Campania, Italy)

The aim of the current study was to carry out a retrospective analysis of heavy metal (Pb, Cd, and Hg) levels in liver and kidney of 38 dogs living in an urban habitat (city of Naples). Tissues were homogenized, digested in a microwave digestion system, and analyzed by atomic absorption spectrometry. The results of\ud
this study showed generally low levels of heavy metals in tissues of all examined dogs; only mercury concentrations in kidneys of pet dogs were higher than in stray dogs, and no signiﬁcant age-dependent differences in metal levels were shown between the two groups. In conclusion, these results suggest the involvement of ad hoc-formulated pet food exposure to heavy metals in domestic animals
Ensemble of Diversely Trained Support Vector Machines for Protein Fold Recognition

Protein Fold Recognition (PFR) is defined as assigning a given protein to a fold based on its major secondary structure. PFR is considered as an important step toward protein structure prediction and drug design. However, it still remains as an unsolved problem for biological science and bioinformatics. In this study, we explore the impact of two novel feature extraction methods namely overlapped segmented distribution and overlapped segmented autocorrelation to provide more local discriminatory information for the PFR compared to previously proposed methods found in the literature. We study the impact of our proposed feature extraction methods using 15 promising physicochemical attributes of the amino acids. Afterwards, by proposing an ensemble Support Vector Machines (SVM) which are diversely trained using features extracted from different physicochemical-based attributes, we enhance the protein fold prediction accuracy for up to 5% better than similar studies found in the literature.Griffith Sciences, Griffith School of EngineeringFull Tex
Protein fold recognition using segmentation-based feature extraction model

Protein Fold recognition (PFR) is considered as an important step towards protein structure prediction. It also provides significant information about general functionality of a given protein. Despite all the efforts have been made, PFR still remains unsolved. It is shown that appropriately extracted features from the physicochemical-based attributes of the amino acids plays crucial role to address this problem. In this study, we explore 55 different physicochemical-based attributes using two novel feature extraction methods namely segmented distribution and segmented density. Then, by proposing an ensemble of different classifiers based on the AdaBoost.M1 and Support Vector Machine (SVM) classifiers which are diversely trained on different combinations of features extracted from these attributes, we outperform similar studies found in the literature for over 2% for the PFR task.Griffith Sciences, Griffith School of EngineeringFull Tex
Assisting Inhabitants of Residential Homes with Management of Their Energy Consumption

Although there are already a range of energy monitoring and automation systems available in the market that target residential homes, mostly with the aim of reducing their total energy consumption, very few of these systems are directly concerned with how those energy savings are actually made. As such, these systems do not provide tools that would allow users to make intelligent decisions about their energy usage strategies, and encourage them to change their energy use behaviour. In this paper we describe a system designed to facilitate planning and control of energy usage activities in residential homes. We also report on a user study of this system which demonstrates its potential for making energy savings possible
An investigation into the practical application of residential energy certificates

The Energy Performance of Buildings Directive (EPBD) 2002/91/EC introduced various obligatory requirements intended to achieve the reduction of use of energy resources in buildings and consequentially the reduction of the impact of energy use in buildings. Article 7 of the directive formally specified the current European requirement for the energy certification of buildings. In order to implement this requirement, a general framework for establishing a methodology of calculation of the total energy performance of buildings became necessary. The Maltese methodology for the issuance of energy performance certificates for residential property was developed and introduced by the Ministry of Resources and Rural Affairs in 2010. This methodology differs from that of most other European countries since the energy used for cooling in summer is taken into consideration when carrying out the calculation. Most states only consider the energy for heating in winter for residential energy certificates. A study of the results produced by the Maltese certification process is being used to identify whether the methodology implemented is an accurate tool for environmental monitoring of energy use in Maltese residential property. The analysis is utilised to establish a benchmark for energy use in different residential property typologies. This analysis is developed further to highlight the strengths and weaknesses of the certification procedure as a design tool, and to understand whether the procedure can be effectively applied in the cost optimisation of residential construction or refurbishment projects.peer-reviewe
Statistical relational learning

Relational learning refers to learning from data that have a complex structure.  This structure may be either internal (a data instance may itself have a complex structure) or external (relationships between this instance and other data elements).  Statistical relational learning refers to the use of statistical learning methods in a relational learning context, and the challenges involved in that.   In this chapter we give an overview of statistical relational learning. We start with some motivating problems, and continue with a general description of the task of (statistical) relational learning and some of its more concrete forms (learning from graphs, learning from logical interpretations, learning from relational databases).  Next, we discuss a number of approaches to relational learning, starting with symbolic (non-probabilistic) approaches, and moving on to numerical and probabilistic methods. Methods discussed include inductive logic programming, relational neural networks, and probabilistic logical or relational models.status: publishe
A Soft Handover for Service Delivery in Intermittently Connected Hybrid Networks

International audienceToday, handheld devices equipped with Wi-Fi interfaces are used intensively by a huge number of people every day. These devices can form intermittently connected mobile ad hoc networks spontaneously. These networks appear as a relevant solution to extend a pre-existing infrastructure-based network composed of several access points in view of providing nomadic people with application services in a wide area. In such hybrid networks, intermittent connections are prevalent, and end-to-end paths between clients and providers cannot be maintained all the time. Thus, the communications must be achieved following a "store, carry and forward" principle. In this paper, we present a new soft handover mechanism dedicated to service delivery in such hybrid networks. This handover solution exploits several pieces of information, such as the message propagation time, the path stability, and the mobility degree of intermediate nodes in order to select the most appropriate access point(s) to forward a response to a given mobile client
Advances on Matroid Secretary Problems: Free Order Model and Laminar Case

The best-known conjecture in the context of matroid secretary problems claims the existence of an O(1)-approximation applicable to any matroid. Whereas this conjecture remains open, modified forms of it were shown to be true, when assuming that the assignment of weights to the secretaries is not adversarial but uniformly at random [20,18]. However, so far, no variant of the matroid secretary problem with adversarial weight assignment is known that admits an O(1)-approximation. We address this point by presenting a 9-approximation for the free order model, a model suggested shortly after the introduction of the matroid secretary problem, and for which no O(1)-approximation was known so far. The free order model is a relaxed version of the original matroid secretary problem, with the only difference that one can choose the order in which secretaries are interviewed.
Furthermore, we consider the classical matroid secretary problem for the special case of laminar matroids. Only recently, a O(1)-approximation has been found for this case, using a clever but rather involved method and analysis [12] that leads to a 16000/3-approximation. This is arguably the most involved special case of the matroid secretary problem for which an O(1)-approximation is known. We present a considerably simpler and stronger 3√3e ≈ 14.12 -approximation, based on reducing the problem to a matroid secretary problem on a partition matroid.National Science Foundation (U.S.) (Grant 1029603)United States. Office of Naval Research (Grant N00014-12-1-0033)United States. Office of Naval Research (Grant N00014-09-1-0326
Eight-Fifth Approximation for TSP Paths

We prove the approximation ratio 8/5 for the metric $\{s,t\}$-path-TSP
problem, and more generally for shortest connected $T$-joins.
  The algorithm that achieves this ratio is the simple "Best of Many" version
of Christofides' algorithm (1976), suggested by An, Kleinberg and Shmoys
(2012), which consists in determining the best Christofides $\{s,t\}$-tour out
of those constructed from a family $\Fscr_{>0}$ of trees having a convex
combination dominated by an optimal solution $x^*$ of the fractional
relaxation. They give the approximation guarantee $\frac{\sqrt{5}+1}{2}$ for
such an $\{s,t\}$-tour, which is the first improvement after the 5/3 guarantee
of Hoogeveen's Christofides type algorithm (1991). Cheriyan, Friggstad and Gao
(2012) extended this result to a 13/8-approximation of shortest connected
$T$-joins, for $|T|\ge 4$.
  The ratio 8/5 is proved by simplifying and improving the approach of An,
Kleinberg and Shmoys that consists in completing $x^*/2$ in order to dominate
the cost of "parity correction" for spanning trees. We partition the edge-set
of each spanning tree in $\Fscr_{>0}$ into an $\{s,t\}$-path (or more
generally, into a $T$-join) and its complement, which induces a decomposition
of $x^*$. This decomposition can be refined and then efficiently used to
complete $x^*/2$ without using linear programming or particular properties of
$T$, but by adding to each cut deficient for $x^*/2$ an individually tailored
explicitly given vector, inherent in $x^*$.
  A simple example shows that the Best of Many Christofides algorithm may not
find a shorter $\{s,t\}$-tour than 3/2 times the incidentally common optima of
the problem and of its fractional relaxation.Comment: 15 pages, corrected typos in citations, minor change
The visible perimeter of an arrangement of disks

Given a collection of n opaque unit disks in the plane, we want to find a stacking order for them that maximizes their visible perimeter, the total length of all pieces of their boundaries visible from above. We prove that if the centers of the disks form a dense point set, i.e., the ratio of their maximum to their minimum distance is O(n1/2), then there is a stacking order for which the visible perimeter is Ω(n2/3). We also show that this bound cannot be improved in the case of the n1/2 × n 1/2 piece of a sufficiently small square grid. On the other hand, if the set of centers is dense and the maximum distance between them is small, then the visible perimeter is O(n3/4) with respect to any stacking order. This latter bound cannot be improved either. These results partially answer some questions of Cabello, Haverkort, van Kreveld, and Speckmann. © 2013 Springer-Verlag
Canonical Ordering for Triangulations on the Cylinder, with Applications to Periodic Straight-line Drawings

International audienceWe extend the notion of canonical orderings to cylindric triangulations. This allows us to extend the incremental straight-line drawing algorithm of de Fraysseix, Pach and Pollack to this setting. Our algorithm yields in linear time a crossing-free straight-line drawing of a cylindric triangulation $G$ with $n$ vertices on a regular grid $\mZ/w\mZ\times[0..h]$, with $w\leq 2n$ and $h\leq n(2d+1)$, where $d$ is the (graph-) distance between the two boundaries. As a by-product, we can also obtain in linear time a crossing-free straight-line drawing of a toroidal triangulation with $n$ vertices on a periodic regular grid $\mZ/w\mZ\times\mZ/h\mZ$, with $w\leq 2n$ and $h\leq 1+n(2c+1)$, where $c$ is the length of a shortest non-contractible cycle. Since $c\leq\sqrt{2n}$, the grid area is $O(n^{5/2})$. Our algorithms apply to any triangulation (whether on the cylinder or on the torus) that have no loops nor multiple edges in the periodic representation
High-performance network traffic processing systems using commodity hardware

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-36784-7_1The Internet has opened new avenues for information ac-
cessing and sharing in a variety of media formats. Such popularity has
resulted in an increase of the amount of resources consumed in backbone
links, whose capacities have witnessed numerous upgrades to cope with
the ever-increasing demand for bandwidth. Consequently, network tra c
processing at today's data transmission rates is a very demanding task,
which has been traditionally accomplished by means of specialized hard-
ware tailored to speci c tasks. However, such approaches lack either of

exibility or extensibility|or both. As an alternative, the research com-
munity has pointed to the utilization of commodity hardware, which may
provide 
exible and extensible cost-aware solutions, ergo entailing large
reductions of the operational and capital expenditure investments. In
this chapter, we provide a survey-like introduction to high-performance
network tra c processing using commodity hardware. We present the
required background to understand the di erent solutions proposed in
the literature to achieve high-speed lossless packet capture, which are
reviewed and compared
Reviewing Traffic ClassificationData Traffic Monitoring and Analysis

Traffic classification has received increasing attention in the last years. It aims at offering the ability to automatically recognize the application that has generated a given stream of packets from the direct and passive observation of the individual packets, or stream of packets, flowing in the network. This ability is instrumental to a number of activities that are of extreme interest to carriers, Internet service providers and network administrators in general. Indeed, traffic classification is the basic block that is required to enable any traffic management operations, from differentiating traffic pricing and treatment (e.g., policing, shaping, etc.), to security operations (e.g., firewalling, filtering, anomaly detection, etc.). Up to few years ago, almost any Internet application was using well-known transport layer protocol ports that easily allowed its identification. More recently, the number of applications using random or non-standard ports has dramatically increased (e.g. Skype, BitTorrent, VPNs, etc.). Moreover, often network applications are configured to use well-known protocol ports assigned to other applications (e.g. TCP port 80 originally reserved for Web traffic) attempting to disguise their presence. For these reasons, and for the importance of correctly classifying traffic flows, novel approaches based respectively on packet inspection, statistical and machine learning techniques, and behavioral methods have been investigated and are becoming standard practice. In this chapter, we discuss the main trend in the field of traffic classification and we describe some of the main proposals of the research community. We complete this chapter by developing two examples of behavioral classifiers: both use supervised machine learning algorithms for classifications, but each is based on different features to describe the traffic. After presenting them, we compare their performance using a large dataset, showing the benefits and drawback of each approac
Providing Authentication in Delay/Disruption Tolerant Networking (DTN) Environment

DTN environment is characterized by intermittent connectivity, high/variable delay, heterogeneity, high error rate and asymmetric data rate amongst others. These characteristics accounts for the poor behavior of Internet protocols in this environment. To address these problems, DTN was conceived and designed together with specialized protocols to carry out its services. Its emergence called for a new concept in security that was considered at the design stage. The main aim of this paper is to propose a traditional cryptography based authentication scheme that does not depend on network administrator’s availability during post network authentication communication and facilitates bundle processing by the recipient in the absence of connectivity. In this paper, we present and discuss the system model, the proposed credential and the propose authentication scheme. A simulation framework is developed for the implementation of the proposed and referenced schemes. From the simulation results, the proposed scheme was observed to be independent of network administrator’s availability during post network authentication communication and facilitates bundle processing in the absence of connectivity