pinecone/core-2020-05-10-deduplication huggingface dataset:
Apparatus: Reasoning About Security Requirements in the Internet of Things

Internet of Things (IoT) can be seen as the main driver towards an era of ubiquitous computing. Taking into account the scale of IoT, the number of security issues that emerge are unprecedented, therefore the need for proposing new methodologies for elaborating about security in IoT systems is undoubtedly crucial and this is recognised by both academia and the industry alike. In this work we present Apparatus, a conceptual model for reasoning about security in IoT systems through the lens of Security Requirements Engineering. Apparatus is architecture-oriented and describes an IoT system as a cluster of nodes that share network connections. The information of the system is documented in a textual manner, using Javascript Notation Object (JSON) format, in order to elicit security requirements. To demonstrate its usage the security requirements of a temperature monitor system are identified and a first application of Apparatus is exhibited
Choreographies in Practice

Choreographic Programming is a development methodology for concurrent
software that guarantees correctness by construction. The key to this paradigm
is to disallow mismatched I/O operations in programs, called choreographies,
and then mechanically synthesise distributed implementations in terms of
standard process models via a mechanism known as EndPoint Projection (EPP).
  Despite the promise of choreographic programming, there is still a lack of
practical evaluations that illustrate the applicability of choreographies to
concrete computational problems with standard concurrent solutions. In this
work, we explore the potential of choreographies by using Procedural
Choreographies (PC), a model that we recently proposed, to write distributed
algorithms for sorting (Quicksort), solving linear equations (Gaussian
elimination), and computing Fast Fourier Transform. We discuss the lessons
learned from this experiment, giving possible directions for the usage and
future improvements of choreography languages
An implementation architecture for scenario-based simulations

The past years have witnessed an increased use of applied games for developing and evaluating communication skills. These skills benefit from in-terpersonal interactions. Providing feedback to students practicing communica-tion skills is difficult in a traditional class setting with one teacher and many students. This logistic challenge may be partly overcome by providing training using a simulation in which a student practices with communication scenarios. A scenario is a description of a series of interactions, where at each step the player is faced with a choice. We have developed a scenario editor that enables teachers to develop scenarios for practicing communication skills. A teacher can develop a scenario without knowledge of the implementation. This paper presents the implementation architecture for such a scenario-based simulation.This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187.  This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains
Stealth Assessment in ITS - A Study for Developmental Dyscalculia

Intelligent tutoring systems are adapting the curriculum to the needs of the student. The integration of stealth assessments of student traits into tutoring systems, i.e. the automatic detection of student characteristics has the potential to re?ne this adaptation. We present a pipeline for integrating automatic assessment seamlessly into a tutoring system and apply the method to the case of developmental dyscalculia (DD). The proposed classi?er is based on user inputs only, allowing non-intrusive and unsupervised, universal screening of children. We demonstrate that interaction logs provide enough information to identify children at risk of DD with high accuracy and validity and reliability comparable to traditional assessments. Our model is able to adapt the duration of the screening test to the individual child and can classify a child at risk of DD with an accuracy of 91% after 11 minutes on average
Validation of hardware events for successful performance pattern
  identification in High Performance Computing

Hardware performance monitoring (HPM) is a crucial ingredient of performance
analysis tools. While there are interfaces like LIKWID, PAPI or the kernel
interface perf\_event which provide HPM access with some additional features,
many higher level tools combine event counts with results retrieved from other
sources like function call traces to derive (semi-)automatic performance
advice. However, although HPM is available for x86 systems since the early 90s,
only a small subset of the HPM features is used in practice. Performance
patterns provide a more comprehensive approach, enabling the identification of
various performance-limiting effects. Patterns address issues like bandwidth
saturation, load imbalance, non-local data access in ccNUMA systems, or false
sharing of cache lines. This work defines HPM event sets that are best suited
to identify a selection of performance patterns on the Intel Haswell processor.
We validate the chosen event sets for accuracy in order to arrive at a reliable
pattern detection mechanism and point out shortcomings that cannot be easily
circumvented due to bugs or limitations in the hardware
An ICT-Based Reference Model for E-grocery in Smart Cities

E-grocery is a new emerging and challenging business channel for the food and beverage market, enabling consumers to purchase grocery products online. It combines the issues of last mile distribution with those related to the perishability of foods, affecting the success and profitability of several e-grocery companies. The Local Food Supply Chain (LFSC) concerns the local production and delivery to food consumers, in a more economically and environmentally efficient way, but it remains a less explored business. The paper discusses whether a new LFSC model for e-grocery is useful and proposes an innovative solution based on ICT and mobile application
Post-test perceptions of digital tools by the elderly in an ambient environment

This article presents the first results about the perception of 33 elderly people on interaction tools in a digital ambient environment. The evaluation of this study is based on interviews and filling a short questionnaire after a presentation of the different possible technologies and the use of a digital automated living lab by the volunteers on a life scenario. The first results show a significant interest of the elderly the voice interaction mode compared with touch screen or switches as well as a good opinion of technological tools presented in real situation that they would use in the future if their health required it
Hybridization as Cooperative Parallelism for the Quadratic Assignment Problem

International audienceThe Quadratic Assignment Problem is at the core of several real-life applications. Finding an optimal assignment is computationally very difficult, for many useful instances. The best results are obtained with hybrid heuristics, which result in complex solvers. We propose an alternate solution where hybridization is obtain by means of parallelism and cooperation between simple single-heuristic solvers. We present experimental evidence that this approach is very efficient and can effectively solve a wide variety of hard problems, often surpassing state-of-the-art systems
Stochastic Runge-Kutta Software Package for Stochastic Differential
  Equations

As a result of the application of a technique of multistep processes
stochastic models construction the range of models, implemented as a
self-consistent differential equations, was obtained. These are partial
differential equations (master equation, the Fokker--Planck equation) and
stochastic differential equations (Langevin equation). However, analytical
methods do not always allow to research these equations adequately. It is
proposed to use the combined analytical and numerical approach studying these
equations. For this purpose the numerical part is realized within the framework
of symbolic computation. It is recommended to apply stochastic Runge--Kutta
methods for numerical study of stochastic differential equations in the form of
the Langevin. Under this approach, a program complex on the basis of analytical
calculations metasystem Sage is developed. For model verification logarithmic
walks and Black--Scholes two-dimensional model are used. To illustrate the
stochastic "predator--prey" type model is used. The utility of the combined
numerical-analytical approach is demonstrated.Comment: in English, in Russian. M.N. Gevorkyan, T.R. Velieva, A.V. Korolkova,
  D.S. Kulyabov, L.A. Sevastyanov, Stochastic Runge-Kutta Software Package for
  Stochastic Differential Equations, in Dependability Engineering and Complex
  Systems, Vol. 470, 2016, pp. 169-17
Business process performance mining with staged process flows

Existing process mining techniques provide summary views of the overall process performance over a period of time, allowing analysts to identify bottlenecks and associated performance issues. However, these tools are not de- signed to help analysts understand how bottlenecks form and dissolve over time nor how the formation and dissolution of bottlenecks – and associated fluctua- tions in demand and capacity – affect the overall process performance. This paper presents an approach to analyze the evolution of process performance via a notion of Staged Process Flow (SPF). An SPF abstracts a business process as a series of queues corresponding to stages. The paper defines a number of stage character- istics and visualizations that collectively allow process performance evolution to be analyzed from multiple perspectives. The approach has been implemented in the ProM process mining framework. The paper demonstrates the advantages of the SPF approach over state-of-the-art process performance mining tools using two real-life event logs publicly available
Minimizing overprocessing waste in business processes via predictive activity ordering

Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead
Optimizing monitorability of multi-cloud applications

When adopting a multi-cloud strategy, the selection of cloud providers where to deploy VMs is a crucial task for ensuring a good behaviour for the developed application. This selection is usually focused on the general information about performances and capabilities offered by the cloud providers. Less attention has been paid to the monitoring services although, for the application developer, is fundamental to understand how the application behaves while it is running. In this paper we propose an approach based on a multi-objective mixed integer linear optimization problem for supporting the selection of the cloud providers able to satisfy constraints on monitoring dimensions associated to VMs. The balance between the quality of data monitored and the cost for obtaining these data is considered, as well as the possibility for the cloud provider to enrich the set of monitored metrics through data analysis
OSSAP: A situational method for defining open source software adoption processes

Organizations are increasingly becoming Open Source Software (OSS) adopters, either as a result of a strategic decision or just as a consequence of technological choices. The strategy followed to adopt OSS shapes organizations’ businesses; therefore methods to assess such impact are needed. In this paper, we propose OSSAP, a method for defining OSS Adoption business Processes, built using a Situational Method Engineering (SME) approach. We use SME to combine two well-known modelling methods, namely goal-oriented models (using i*) and business process models (using BPMN), with a pre-existing catalogue of goal-oriented OSS adoption strategy models. First, we\ud
define a repository of reusable method chunks, including the guidelines to apply them. Then, we define OSSAP as a composition of those method chunks to help organizations to improve their business processes in order to integrate the best fitting OSS adoption strategy. We illustrate it with an example of application in a telecommunications company.Peer ReviewedPostprint (author's final draft
Improving understandability of declarative process models by revealing hidden dependencies

Declarative process models have become a mature alternative to procedural ones. Instead of focusing on what has to happen, they rather follow an outside-in approach based on a rule base containing different types of constraints. The models are well-capable of representing flexible behavior, as everything that is not allowed by the constraints in the model is possible during execution. These models, however, are more difficult to comprehend and require a higher mental effort of both the modeler and the reader. Since constraints can be added freely to the model, it is often overseen what impact the combination of them has. This is often referred to as hidden dependencies.
This paper proposes a methodology to make these dependencies explicit for the declarative process modeling language Declare by considering a Declare model as a graph and relying on the constraints' characteristics. Moreover, this paper also contributes by empirically confirming that a tool that can visualize hidden dependency information on top of a Declare model has a significant positive impact on the understandability of Declare models.status: publishe
Tectonic Reconstructions of the Southernmost Andes and the Scotia Sea During the Opening of the Drake Passage

Study of the tectonic development of the Scotia Sea region started with basic lithological and structural studies of outcrop geology in Tierra del Fuego and the Antarctic Peninsula. To nineteenth- and early twentieth-century geologists, the results of these studies suggested the presence of a submerged orocline running around the margins of the Scotia Sea. Subsequent increases in detailed knowledge about the fragmentary outcrop geology from islands distributed around the margins of the Scotia Sea, and later their interpretation in the light of the plate tectonic paradigm led to large modifications in the hypothesis such that by the present day the concept of oroclinal bending in the region persists only in vestigial form. Of the early comparative lithostratigraphic work in the region, only the likenesses between Jurassic–Cretaceous basin floor and fill sequences in South Georgia and Tierra del Fuego are regarded as strong enough to be useful in plate kinematic reconstruction by permitting the interpretation of those regions’ contiguity in mid-Mesozoic times. Marine and satellite geophysical data sets reveal features of the remaining, submerged, 98 % of the Scotia Sea region between the outcrops. These data enable a more detailed and quantitative approach to the region’s plate kinematics. In contrast to long-used interpretations of the outcrop geology, these data do not prescribe the proximity of South Georgia to Tierra del Fuego in any past period. It is, however, possible to reinterpret the geology of those two regions in terms of the plate kinematic history that the seafloor has preserved
Adaptive optics in high-contrast imaging

The development of adaptive optics (AO) played a major role in modern
astronomy over the last three decades. By compensating for the atmospheric
turbulence, these systems enable to reach the diffraction limit on large
telescopes. In this review, we will focus on high contrast applications of
adaptive optics, namely, imaging the close vicinity of bright stellar objects
and revealing regions otherwise hidden within the turbulent halo of the
atmosphere to look for objects with a contrast ratio lower than 10^-4 with
respect to the central star. Such high-contrast AO-corrected observations have
led to fundamental results in our current understanding of planetary formation
and evolution as well as stellar evolution. AO systems equipped three
generations of instruments, from the first pioneering experiments in the
nineties, to the first wave of instruments on 8m-class telescopes in the years
2000, and finally to the extreme AO systems that have recently started
operations. Along with high-contrast techniques, AO enables to reveal the
circumstellar environment: massive protoplanetary disks featuring spiral arms,
gaps or other asymmetries hinting at on-going planet formation, young giant
planets shining in thermal emission, or tenuous debris disks and micron-sized
dust leftover from collisions in massive asteroid-belt analogs. After
introducing the science case and technical requirements, we will review the
architecture of standard and extreme AO systems, before presenting a few
selected science highlights obtained with recent AO instruments.Comment: 24 pages, 14 figure
North Sea Region Climate Change Assessment

This book offers an up-to-date review of our current understanding of climate change in the North Sea and adjacent areas, as well as its impact on ecosystems and socio-economic sectors. It provides a detailed assessment of climate change based on published scientific work compiled by independent international experts from climate-related disciplines such as oceanography, atmospheric sciences, marine and terrestrial ecology, using a regional evaluation and review process similar to that of the Intergovernmental Panel on Climate Change (IPCC). It provides a comprehensive overview of all aspects of our changing climate, discussing a wide range of topics including past, current and future climate change, and climate-related changes in marine, terrestrial and freshwater ecosystems. It also explores the impact of climate change on socio-economic sectors such as fisheries, agriculture, coastal zone management, coastal protection, urban climate, recreation/tourism, offshore activities/energy, and air pollution.\u
Socio-economic Impacts—Fisheries

Fishers and scientists have known for over 100 years that the status of fish stocks can be greatly influenced by prevailing climatic conditions. Based on historical sea surface temperature data, the North Sea has been identified as one of 20 ‘hot spots’ of climate change globally and projections for the next 100 years suggest that the region will continue to warm. The consequences of this rapid temperature rise are already being seen in shifts in species distribution and variability in stock recruitment. This chapter reviews current evidence for climate change effects on fisheries in the North Sea—one of the most important fishing grounds in the world—as well as available projections for North Sea fisheries in the future. Discussion focuses on biological, operational and wider market concerns, as well as on possible economic consequences. It is clear that fish communities and the fisheries that target them will be very different in 50 or 100 years’ time and that management and governance will need to adapt accordingly
Gaggle on the Gavel:  Designing an Interactive Website to Create a Community of Lawyers

Law is behind other industries and professions in its implementation of technolo-gy that could make the practice of law and the delivery of legal services more ef-fective and satisfying.  Although there has been considerable development in le-gal technology over the past few years, research identified the need for an interac-tive LinkedIn-style online community for lawyers to communicate other lawyers.  Such a community would be particularly beneficial for solo practitioners, lawyers in small firms and lawyers in rural communities and would also provide a con-venient way to connect with lawyers for referrals and recommendations, for spe-cialized expertise and to develop contacts in different geographic locations.  Ten-tatively titled Gaggle on the Gavel is an attempt to create such a community that would gather a number of attractive features and functionality under one umbrella and be compliant with the rules of professional conduct with respect to client con-fidentiality, security, advertising and solicitation.  A system has been designed, prototyped and revised based on feedback from a focus group of lawyers
Stable discontinuous Galerkin FEM without penalty parameters

We propose a modified local discontinuous Galerkin (LDG) method for
second--order elliptic problems that does not require extrinsic penalization to
ensure stability. Stability is instead achieved by showing a discrete
Poincar\'e--Friedrichs inequality for the discrete gradient that employs a
lifting of the jumps with one polynomial degree higher than the scalar
approximation space. Our analysis covers rather general simplicial meshes with
the possibility of hanging nodes.Comment: Accepted for publication in the conference proceedings of Numerical
  Mathematics and Advanced Applications ENUMATH 2015. Typo correcte
Model Order Reduction for Pattern Formation in FitzHugh-Nagumo Equation

We developed a reduced order model (ROM) using the proper orthogonal
decomposition (POD) to compute efficiently the labyrinth and spot like patterns
of the FitzHugh-Nagumo (FNH) equation. The FHN equation is discretized in space
by the discontinuous Galerkin (dG) method and in time by the backward Euler
method. Applying POD-DEIM (discrete empirical interpolation method) to the full
order model (FOM) for different values of the parameter in the bistable
nonlinearity, we show that using few POD and DEIM modes, the patterns can be
computed accurately. Due to the local nature of the dG discretization, the
POD-DEIM requires less number of connected nodes than continuous finite element
for the nonlinear terms, which leads to a significant reduction of the
computational cost for dG POD-DEIM
The Role of Reciprocity and Directionality of Friendship Ties in
  Promoting Behavioral Change

Friendship is a fundamental characteristic of human beings and usually
assumed to be reciprocal in nature. Despite this common expectation, in
reality, not all friendships by default are reciprocal nor created equal. Here,
we show that reciprocated friendships are more intimate and they are
substantially different from those that are not. We examine the role of
reciprocal ties in inducing more effective peer pressure in a cooperative
arrangements setting and find that the directionality of friendship ties can
significantly limit the ability to persuade others to act. Specifically, we
observe a higher behavioral change and more effective peer-influence when
subjects shared reciprocal ties with their peers compared to sharing unilateral
ones. Moreover, through spreading process simulation, we find that although
unilateral ties diffuse behaviors across communities, reciprocal ties play more
important role at the early stages of the diffusion process.Comment: The 9th International Conference on Social, Cultural, and Behavioral
  Modeling & Prediction and Behavior Representation in Modeling and Simulation,
  SBP-BRiMS 201