pinecone/core-2020-05-10-deduplication huggingface dataset:
Process discovery for industrial control system cyber attack detection

<i>Industrial Control Systems</i> (ICSs) are moving from dedicated\ud
communications to Ethernet-based interconnected networks, placing them at risk of cyber attack. ICS networks are typically monitored by an <i>Intrusion Detection System</i> (IDS), however traditional IDSs do not detect attacks which disrupt the control ow of an ICS. ICSs are unique in the repetition and restricted number of tasks that are undertaken. Thus there is the opportunity to use Process Mining, a series of\ud
techniques focused on discovering, monitoring and improving business processes, to detect ICS control fow anomalies. In this paper we investigate the suitability of various process mining discovery algorithms for the task of detecting cyber attacks on ICSs by examining logs from control devices. Firstly, we identify the requirements of this unique environment, and then evaluate the appropriateness of several commonly used process discovery algorithms to satisfy these requirements. Secondly, the comparison was performed and validated using ICS logs derived from a case study, containing successful attacks on industrial control systems. Our research shows that the Inductive Miner process discovery method, without the use of noise filtering, is the most suitable for discovering a process model that is effective in detecting cyber-attacks on industrial control systems, both in processing time and accuracy
Politics of nanotechnologies in food and agriculture

The chapter discusses the reasons for the delay in the regulatory intervention\ud
concerning nanotechnologies used in the agriculture and food sectors. The\ud
main finding is that unregulated introduction of nanoinnovation into the food system\ud
is due to the current neoliberal food policy and to the power struggles that\ud
characterize the economic, social and political dynamics within the global supply\ud
chain. Therefore, it is necessary to put the ‘question concerning technology’ at the\ud
center of the regulatory debate in order to implement a regulatory system able to\ud
face nanorisks. Which means looking at the way in which technology controls\ud
power relationships within society. Attention should be shifted from efficiency to\ud
power issues, and new technologies should be assessed from a political rather than\ud
an economic or ethical perspective
The Quality of MOOCs: How to improve the design of open education and online courses for learners?

This paper presents the current status of Open Education and MOOCs and discusses their quality following the main question: How can we introduce new design and evaluation methods and personalization strategies to improve the learning quality of Open Education? First, the dimensions of Open Education are differentiated. Then the dimensions of holistic quality development are transferred to Open Education and discussed for the design of MOOCs leading to recommendations for personalization. A new quality indicator for evaluating the quality of MOOCs is introduced: It is proposed not to measure the traditional drop-out rates but the completion of individual goals and intentions by the MOOC learner. It is concluded that Open Education and MOOCs have got the potential for the next revolution in learning experiences
The positive and negative impact of an intergenerational digital technology education programme on younger people’s perceptions of older adults

In order to meet the technological needs of older adults, and ensure digital inclusion, it is important for digital technology designers to accurately assess and understand older adults’ needs and requirements, free from the influence of societal assumptions of their capabilities. This study evaluated the impact of an intergenerational digital technology education programme on younger adults’ stereotypes of older people. Using an experimental design, results show that compared to a control group, students taking part in the programme subsequently rated older adults as more friendly but less competent. Practical implications for developing intergenerational education programmes are discussed
Multimodal, intermodal and terminals

The chapter looks at rail freight terminals, rail--sea interfaces, in particular, as part of a multimodal, or integrated transportation network. Terminals are key infrastructure for linking individual transport modes and governing and managing their interchange in a manner that creates a seamless and sustainable transportation system. Therefore, their performance is critical for maximising transport efficiency and modes integration. This chapter focused on how to measure the operational performance of rail freight terminals in a framework of integrated transportation network. In an increasingly competitive and commercialised world, there is an increasing demand to be able to rank transport options and routes in some way. Drawing on new material, this talk attempts to outline possible methods for how to measure the performance of rail terminals. It focuses on the identification of suitable methods to assess performance by key indicators. Intermodality demands for going beyond safeguarding the individual modes to ensuring the security of the intermodal inter-faces (terminals), the nodes that link and integrate passenger and freight flows. That demands for an integrated holistic approach built on the collaboration between international, national organisations and operators. The study put emphasis on the security challenges and threats to freight transport generally and in rail-sea interfaces more specifically. It moves onto the regulations already governing security in rail-sea interfaces. Finally, it focus on the role that infrastructure planning can play in improving security and offer some conclusions and recommendations for the futur
gearshifft - The FFT Benchmark Suite for Heterogeneous Platforms

Fast Fourier Transforms (FFTs) are exploited in a wide variety of fields
ranging from computer science to natural sciences and engineering. With the
rising data production bandwidths of modern FFT applications, judging best
which algorithmic tool to apply, can be vital to any scientific endeavor. As
tailored FFT implementations exist for an ever increasing variety of high
performance computer hardware, choosing the best performing FFT implementation
has strong implications for future hardware purchase decisions, for resources
FFTs consume and for possibly decisive financial and time savings ahead of the
competition. This paper therefor presents gearshifft, which is an open-source
and vendor agnostic benchmark suite to process a wide variety of problem sizes
and types with state-of-the-art FFT implementations (fftw, clfft and cufft).
gearshifft provides a reproducible, unbiased and fair comparison on a wide
variety of hardware to explore which FFT variant is best for a given problem
size
Semantic Integration of Geospatial Data from Earth Observations

We propose an approach to semantically enrich metadata  records of satellite imagery with external data. As a result we are able the identify relevant images using a larger set of matching criteria. Conventional methods for annotating data sets are usually based on metadata records (with attributes such as title, provider, access mode, and spatio-temporal characteristics), which other a narrow view of the world. Enriching metadata with contextual information (i.e., the region depicted in the image has been recently affected by extreme weather) requires formalizing spatio-temporal relationships between metadata records and external data sources. Semantic technologies play a key role in such scenarios by providing an infrastructure based on RDF and ontologies
Interpretable feature maps for robot attention

Attention is crucial for autonomous agents interacting with complex environments. In a real scenario, our expectations drive attention, as we look for crucial objects to complete our understanding of the scene. But most visual attention models to date are designed to drive attention in a bottom-up fashion, without context, and the features they use are not always suitable for driving top-down attention. In this paper, we present an attentional mechanism based on semantically meaningful, interpretable features. We show how to generate a low-level semantic representation of the scene in real time, which can be used to search for objects based on specific features such as colour, shape, orientation, speed, and texture.Postprin
"DIY" Prototyping of Teaching Materials for Visually Impaired Children: Usage and Satisfaction of Professionals

Professionals working with visually impaired children (i.e. specialist teachers and educators, Orientation and Mobility trainers, psychologists, etc.) have to create their own teaching materials. Indeed, only few adapted materials exist, and do not fully meet their needs. Thus, rapid prototyping tools and methods could help them to design and make materials adapted to teaching to visually impaired students. In this study, we first designed a blog enabling professionals to create their own teaching materials. Then, we set up a challenge with five teams including one professional of visual impairment and students in computer science. The aim of each team was to design and make a teaching material, based on handcrafting, 3D printing tools and cheap micro-controllers, fitting the needs of the professional. After they have used their material with visually impaired students, we interviewed the professionals in order to evaluate usage and satisfaction. The professionals reported that the materials were easy to make, and valuable for teaching to visually impaired students. They also reported that DIY prototyping, based on 3D printing and cheap microcontrollers, enables them to create their own teaching materials, and hence accurately meet unanswered needs. Importantly, they would advise their colleagues to use this method and new tools. However, they consider that they would need assistance to create new materials on their own
Surjective H-Colouring : new hardness results.

A homomorphism from a graph G to a graph H is a vertex mapping f from the vertex set of G to the vertex set of H such that there is an edge between vertices f(u) and f(v) of H whenever there is an edge between vertices u and v of G. The H-Colouring problem is to decide whether or not a graph G allows a homomorphism to a fixed graph H. We continue a study on a variant of this problem, namely the Surjective HH -Colouring problem, which imposes the homomorphism to be vertex-surjective. We build upon previous results and show that this problem is NP-complete for every connected graph H that has exactly two vertices with a self-loop as long as these two vertices are not adjacent. As a result, we can classify the computational complexity of Surjective HH -Colouring for every graph H on at most four vertices
A Novel Convex Relaxation for Non-Binary Discrete Tomography

We present a novel convex relaxation and a corresponding inference algorithm
for the non-binary discrete tomography problem, that is, reconstructing
discrete-valued images from few linear measurements. In contrast to state of
the art approaches that split the problem into a continuous reconstruction
problem for the linear measurement constraints and a discrete labeling problem
to enforce discrete-valued reconstructions, we propose a joint formulation that
addresses both problems simultaneously, resulting in a tighter convex
relaxation. For this purpose a constrained graphical model is set up and
evaluated using a novel relaxation optimized by dual decomposition. We evaluate
our approach experimentally and show superior solutions both mathematically
(tighter relaxation) and experimentally in comparison to previously proposed
relaxations
Subspace Least Squares Multidimensional Scaling

Multidimensional Scaling (MDS) is one of the most popular methods for
dimensionality reduction and visualization of high dimensional data. Apart from
these tasks, it also found applications in the field of geometry processing for
the analysis and reconstruction of non-rigid shapes. In this regard, MDS can be
thought of as a \textit{shape from metric} algorithm, consisting of finding a
configuration of points in the Euclidean space that realize, as isometrically
as possible, some given distance structure. In the present work we cast the
least squares variant of MDS (LS-MDS) in the spectral domain. This uncovers a
multiresolution property of distance scaling which speeds up the optimization
by a significant amount, while producing comparable, and sometimes even better,
embeddings.Comment: Scale Space and Variational Methods in Computer Vision: 6th
  International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 201
Beyond Multi-view Stereo: Shading-Reflectance Decomposition

We introduce a variational framework for separating shading and reflectance from a series of images acquired under different angles, when the geometry has already been estimated by multi-view stereo. Our formulation uses an l1-TV variational framework, where a robust photometric-based data term enforces adequation to the images, total variation ensures piecewise-smoothness of the reflectance, and an additional multi-view consistency term is introduced for resolving the arising ambiguities. Optimisation is carried out using an alternating optimisation strategy building upon iteratively reweighted least-squares. Preliminary results on both a synthetic dataset, using various lighting and reflectance scenarios, and a real dataset, confirm the potential of the proposed approach
Reduced-order semi-implicit schemes for fluid-structure interaction
  problems

POD--Galerkin reduced-order models (ROMs) for fluid-structure interaction
problems (incompressible fluid and thin structure) are proposed in this paper.
Both the high-fidelity and reduced-order methods are based on a Chorin-Temam
operator-splitting approach. Two different reduced-order methods are proposed,
which differ on velocity continuity condition, imposed weakly or strongly,
respectively. The resulting ROMs are tested and compared on a representative
haemodynamics test case characterized by wave propagation, in order to assess
the capabilities of the proposed strategies
True Error Control for the Localized Reduced Basis Method for Parabolic
  Problems

We present an abstract framework for a posteriori error estimation for
approximations of scalar parabolic evolution equations, based on elliptic
reconstruction techniques [10, 9, 3, 5]. In addition to its original
application (to derive error estimates on the discretization error), we extend
the scope of this framework to derive offline/online decomposable a posteriori
estimates on the model reduction error in the context of Reduced Basis (RB)
methods. In addition, we present offline/online decomposable a posteriori error
estimates on the full approximation error (including discretization as well as
model reduction error) in the context of the localized RB method [14]. Hence,
this work generalizes the localized RB method with true error certification to
parabolic problems. Numerical experiments are given to demonstrate the
applicability of the approach
Interpolatory methods for $\mathcal{H}_\infty$ model reduction of
  multi-input/multi-output systems

We develop here a computationally effective approach for producing
high-quality $\mathcal{H}_\infty$-approximations to large scale linear
dynamical systems having multiple inputs and multiple outputs (MIMO). We extend
an approach for $\mathcal{H}_\infty$ model reduction introduced by Flagg,
Beattie, and Gugercin for the single-input/single-output (SISO) setting, which
combined ideas originating in interpolatory $\mathcal{H}_2$-optimal model
reduction with complex Chebyshev approximation. Retaining this framework, our
approach to the MIMO problem has its principal computational cost dominated by
(sparse) linear solves, and so it can remain an effective strategy in many
large-scale settings. We are able to avoid computationally demanding
$\mathcal{H}_\infty$ norm calculations that are normally required to monitor
progress within each optimization cycle through the use of "data-driven"
rational approximations that are built upon previously computed function
samples. Numerical examples are included that illustrate our approach. We
produce high fidelity reduced models having consistently better
$\mathcal{H}_\infty$ performance than models produced via balanced truncation;
these models often are as good as (and occasionally better than) models
produced using optimal Hankel norm approximation as well. In all cases
considered, the method described here produces reduced models at far lower cost
than is possible with either balanced truncation or optimal Hankel norm
approximation
Energy stable model order reduction for the Allen-Cahn equation

The Allen-Cahn equation is a gradient system, where the free-energy
functional decreases monotonically in time. We develop an energy stable reduced
order model (ROM) for a gradient system, which inherits the energy decreasing
property of the full order model (FOM). For the space discretization we apply a
discontinuous Galerkin (dG) method and for time discretization the energy
stable average vector field (AVF) method. We construct ROMs with proper
orthogonal decomposition (POD)-greedy adaptive sampling of the snapshots in
time and evaluating the nonlinear function with greedy discrete empirical
interpolation method (DEIM). The computational efficiency and accuracy of the
reduced solutions are demonstrated numerically for the parametrized Allen-Cahn
equation with Neumann and periodic boundary conditions
ArbiLoMod: Local Solution Spaces by Random Training in Electrodynamics

The simulation method ArbiLoMod has the goal to provide users of Finite
Element based simulation software with quick re-simulation after localized
changes to the model under consideration. It generates a Reduced Order Model
(ROM) for the full model without ever solving the full model. To this end, a
localized variant of the Reduced Basis method is employed, solving only small
localized problems in the generation of the reduced basis. The key to quick
re-simulation lies in recycling most of the localized basis vectors after a
localized model change. In this publication, ArbiLoMod's local training
algorithm is analyzed numerically for the non-coercive problem of time harmonic
Maxwell's equations in 2D, formulated in H(curl)
ASARI: a new adaptive oversegmentation method

Using superpixels instead of pixels has become a popular pre-processing step in computer vision. However, there are few adaptive methods able to automatically find the best comprise between boundary adherence and superpixel number. Moreover, no algorithm producing color and texture homogeneous superpixels keeps competitive execution time. In this article we suggest a new graph-based region merging method, called Adaptive Superpixel Algorithm with Rich Information (ASARI) to solve these two difficulties. We will show that ASARI achieves results similar to the state-of-the-art methods on the existing benchmarks and outperforms these methods when dealing with big images
Body shape-based biometric person recognition from mmW images

A growing interest has arisen in the security community for the use of millimeter waves in order to detect weapons and concealed objects. Also, the use of millimetre wave images has been proposed recently for biometric person recognition to overcome certain limitations of images acquired at visible frequencies. This paper proposes a biometric person recognition system based on shape information extracted from millimetre wave images. To this aim, we report experimental results using millimeter wave images with different body shape-based feature approaches: contour coordinates, shape contexts, Fourier descriptors and row and column profiles, using Dynamic Time Warping for matching. Results suggest the potential of performing person recognition through millimetre waves using only shape information, a functionality that could be easily integrated in the security scanners deployed in airportsThis work has been partially supported by project CogniMetrics TEC2015-70627-R
(MINECO/FEDER), and the SPATEK network (TEC2015-68766-REDC
Skinhealth, A Mobile Application for Supporting Teledermatology: A Case Study in a Rural Area in Colombia

Background: The use of mobile applications in dermatology to support remote diagnosis is becoming more important each day, particularly in rural areas where dermatology services are commonly managed by healthcare personnel with no speciality training. Objective: The aim of this study is to assess the reliability of mobile applications to support remote dermatological diagnosis, when used together with a dermatological ontology in underprivileged areas. Methods: A mobile application that allows characterization of skin lesions was developed. The experiment was conducted in a remote area without access to a dermatologist. A total of 64 dermatological queries were recorded in the mobile application. Results: The results showed that the probability of obtaining a correct diagnosis was between 64.4% and 85.6% and a confidence interval of 95%. Conclusions: This study demonstrates the implementation of a Teledermatology strategy based on mobile applications and domain ontology-driven knowledge base to provide timely assistance to healthcare professionals. This approach was found to be pertinent in the Colombian rural context, particularly in forest regions where dermatology specialists are not available
Chern and Fu-Kane-Mele invariants as topological obstructions

The use of topological invariants to describe geometric phases of quantum
matter has become an essential tool in modern solid state physics. The first
instance of this paradigmatic trend can be traced to the study of the quantum
Hall effect, in which the Chern number underlies the quantization of the
transverse Hall conductivity. More recently, in the framework of time-reversal
symmetric topological insulators and quantum spin Hall systems, a new
topological classification has been proposed by Fu, Kane and Mele, where the
label takes value in $\mathbb Z_2$.
  We illustrate how both the Chern number $c \in \mathbb Z$ and the
Fu-Kane-Mele invariant $\delta \in \mathbb Z_2$ of 2-dimensional topological
insulators can be characterized as topological obstructions. Indeed, $c$
quantifies the obstruction to the existence of a frame of Bloch states for the
crystal which is both continuous and periodic with respect to the crystal
momentum. Instead, $\delta$ measures the possibility to impose a further
time-reversal symmetry constraint on the Bloch frame.Comment: 20 pages, 2 figures. Contribution to the proceedings of the INdAM
  meeting "Contemporary Trends in the Mathematics of Quantum Mechanics", July
  4-8, 2016, Rome (Italy
Self-Adjoint Extensions of Dirac Operator with Coulomb Potential

In this note we give a concise review of the present state-of-art for the
problem of self-adjoint realisations for the Dirac operator with a Coulomb-like
singular scalar potential $V(\vec x)=\phi(\vec x) I_4$. We try to follow the
historical and conceptual path that leads to the present understanding of the
problem and to highlight the techniques employed and the main ideas. In the
final part we outline a few major open questions that concern the topical
problem of the multiplicity of self-adjoint realisations of the model, and
which are worth addressing in the future.Comment: 17 page
Correlation inequalities for classical and quantum XY models

We review correlation inequalities of truncated functions for the classical
and quantum XY models. A consequence is that the critical temperature of the XY
model is necessarily smaller than that of the Ising model, in both the
classical and quantum cases. We also discuss an explicit lower bound on the
critical temperature of the quantum XY model.Comment: 13 pages. Submitted to the volume "Advances in Quantum Mechanics:
  contemporary trends and open problems" of the INdAM-Springer series,
  proceedings of the INdAM meeting "Contemporary Trends in the Mathematics of
  Quantum Mechanics" (4-8 July 2016) organised by G. Dell'Antonio and A.
  Michelangel