pinecone/core-2020-05-10-deduplication huggingface dataset:
Tuning and optimization for a variety of many-core architectures without
  changing a single line of implementation code using the Alpaka library

We present an analysis on optimizing performance of a single C++11 source
code using the Alpaka hardware abstraction library. For this we use the general
matrix multiplication (GEMM) algorithm in order to show that compilers can
optimize Alpaka code effectively when tuning key parameters of the algorithm.
We do not intend to rival existing, highly optimized DGEMM versions, but merely
choose this example to prove that Alpaka allows for platform-specific tuning
with a single source code. In addition we analyze the optimization potential
available with vendor-specific compilers when confronted with the heavily
templated abstractions of Alpaka. We specifically test the code for bleeding
edge architectures such as Nvidia's Tesla P100, Intel's Knights Landing (KNL)
and Haswell architecture as well as IBM's Power8 system. On some of these we
are able to reach almost 50\% of the peak floating point operation performance
using the aforementioned means. When adding compiler-specific #pragmas we are
able to reach 5 TFLOPS/s on a P100 and over 1 TFLOPS/s on a KNL system.Comment: Accepted paper for the P\^{}3MA workshop at the ISC 2017 in Frankfur
HetFS: A heterogeneous file system for everyone

Storage devices have been getting more and more diverse during the last decade. The advent of SSDs made it painfully clear that rotating devices, such as HDDs or magnetic tapes, were lacking in regards to response time. However, SSDs currently have a limited number of write cycles and a significantly larger price per capacity, which has prevented rotational technologies from begin abandoned. Additionally, Non-Volatile Memories (NVMs) have been lately gaining traction, offering devices that typically outperform NAND-based SSDs but exhibit a full new set of idiosyncrasies.\ud
Therefore, in order to appropriately support this diversity, intelligent mechanisms will be needed in the near-future to balance the benefits and drawbacks of each storage technology available to a system. In this paper, we present a first step towards such a mechanism called HetFS, an extension to the ZFS file system that is capable of choosing the storage device a file should be kept in according to preprogrammed filters. We introduce the prototype and show some preliminary results of the effects obtained when placing specific files into different devices.The research leading to these results has received funding from the European\ud
Community under the BIGStorage ETN (Project 642963 of the H2020-MSCA-ITN-2014), by the Spanish Ministry of Economy and Competitiveness under\ud
the TIN2015-65316 grant and by the Catalan Government under the 2014-SGR-\ud
1051 grant. To learn more about the BigStorage project, please visit http:\ud
//bigstorage-project.eu/.Peer ReviewedPostprint (author's final draft
Object-Oriented Knowledge Representation and Data Storage Using
  Inhomogeneous Classes

This paper contains analysis of concept of a class within different
object-oriented knowledge representation models. The main attention is paid to
structure of the class and its efficiency in the context of data storage, using
object-relational mapping. The main achievement of the paper is extension of
concept of homogeneous class of objects by introducing concepts of single-core
and multi-core inhomogeneous classes of objects, which allow simultaneous
defining of a few different types within one class of objects, avoiding
duplication of properties and methods in representation of types, decreasing
sizes of program codes and providing more efficient information storage in the
databases. In addition, the paper contains results of experiment, which show
that data storage in relational database, using proposed extensions of the
class, in some cases is more efficient in contrast to usage of homogeneous
classes of objects.Comment: 2 figure
Burden and risk assessment of foodborne parasites

Burden and risk assessment play an increasingly important and accepted role in defining control policies for foodborne parasites (FBPs). Burden assessment is a top-down approach, starting from available epidemiological data, while risk assessment is a bottom-up or predictive approach, starting from exposure and dose-response data. Both methods however share a common goal of generating estimates of the health and economic impacts of the concerned hazards. These estimates can be used to generate an evidence-based ranking of the impact of FBPs (i.e. risk ranking) and a baseline against which the effects of interventions can be evaluated. Risk assessment further provides a scientific framework for evaluating the potential effects of intervention measures and, by combining with economic models, the expected efficiency of such measures
Optimisation of relay placement in wireless butterfly networks

As a typical model of multicast network, wireless butterfly networks (WBNs) have been studied for modelling the scenario when two source nodes wish to convey data to two destination nodes via an intermediary node namely relay node. In the context of wireless communications, when receiving two data packets from the two source nodes, the relay node can employ either physical-layer network coding or analogue network coding on the combined packet prior to forwarding to the two destination nodes. Evaluating the energy efficiency of these combination approaches, energy-delay trade-off (EDT) is worth to be investigated and the relay placement should be taken into account in the practical network design. This chapter will first investigate the EDT of network coding in the WBNs. Based on the derived EDT, algorithms that optimize the relay position will be developed to either minimize the transmission delay or minimize the energy consumption subject to constraints on power allocation and location of nodes. Furthermore, considering an extended model of the WBN, the relay placement will be studied for a general wireless multicast network with multiple source, relay and destination nodes
Prediction of the progression of subcortical brain structures in
  Alzheimer's disease from baseline

We propose a method to predict the subject-specific longitudinal progression
of brain structures extracted from baseline MRI, and evaluate its performance
on Alzheimer's disease data. The disease progression is modeled as a trajectory
on a group of diffeomorphisms in the context of large deformation diffeomorphic
metric mapping (LDDMM). We first exhibit the limited predictive abilities of
geodesic regression extrapolation on this group. Building on the recent concept
of parallel curves in shape manifolds, we then introduce a second predictive
protocol which personalizes previously learned trajectories to new subjects,
and investigate the relative performances of two parallel shifting paradigms.
This design only requires the baseline imaging data. Finally, coefficients
encoding the disease dynamics are obtained from longitudinal cognitive
measurements for each subject, and exploited to refine our methodology which is
demonstrated to successfully predict the follow-up visits
Multilevel Modeling with Structured Penalties for Classification from
  Imaging Genetics data

In this paper, we propose a framework for automatic classification of
patients from multimodal genetic and brain imaging data by optimally combining
them. Additive models with unadapted penalties (such as the classical group
lasso penalty or $L_1$-multiple kernel learning) treat all modalities in the
same manner and can result in undesirable elimination of specific modalities
when their contributions are unbalanced. To overcome this limitation, we
introduce a multilevel model that combines imaging and genetics and that
considers joint effects between these two modalities for diagnosis prediction.
Furthermore, we propose a framework allowing to combine several penalties
taking into account the structure of the different types of data, such as a
group lasso penalty over the genetic modality and a $L_2$-penalty on imaging
modalities. Finally , we propose a fast optimization algorithm, based on a
proximal gradient method. The model has been evaluated on genetic (single
nucleotide polymorphisms-SNP) and imaging (anatomical MRI measures) data from
the ADNI database, and compared to additive models. It exhibits good
performances in AD diagnosis; and at the same time, reveals relationships
between genes, brain regions and the disease status
Women in crisis situations: Empowering and supporting women through ICTs

Women are more likely to experience poverty than their male counter-parts, through negative life events that can potentially place women in a crisis situation. Past studies highlight that there is a need for a better understanding of the tools that could both support and empower women in crisis situations. We respond to this with a study that illustrates how we may be able to generate ideas for designing technologies that are both empowering and supportive. In collaboration with a non-profit community care center in Australia, we undertook a qualitative study of thirteen women in crisis situations to better understand the issues they faced. We took an in-situ approach, where we provided video and disposable cameras to these participants letting them record their experiences. Through an analysis of their videos and photos followed by semi-structured interviews, we show that while each participant had different life experiences that initially appear unrelated, there are three common challenges they face. These are: their living conditions, social isolation and stigma. As our findings are from an exclusively female perspective, through this research we contribute to the HCI literature on understanding the specific issues faced by women in crisis situations and aim to inform designs for technology that can support and empower women in challenging circumstances
MeViTa: Interactive visualizations to help older adults with their medication Intake using a camera-projector system

In this paper, we investigate whether augmented reality visualization techniques can empower older adults to explore and understand medication information in an effective and timely manner. Through a user-centered design process involving older adults and health professionals we developed an interactive camera-projector system called MeViTa (Medication Visualization Table) that projects medication information surrounding medication boxes laid on a table. Six designs were iteratively developed. In total 26 older adults, with a mean age of 71 (±7), participated in the user studies. Although no time benefits were observed, participants perceived MeViTa as an effective means to explore and understand medication information, and as more engaging than the traditional patient information leaflet. Furthermore, by visualizing medication information, our approach provides qualitative findings of the relative ease and difficulty for older adults to learn more about medication information.status: publishe
The Diffusion of Humans and Cultures in the Course of the Spread of
  Farming

The most profound change in the relationship between humans and their
environment was the introduction of agriculture and pastoralism. [....] For an
understanding of the expansion process, it appears appropriate to apply a
diffusive model. Broadly, these numerical modeling approaches can be catego-
rized in correlative, continuous and discrete. Common to all approaches is the
comparison to collections of radiocarbon data that show the apparent wave of
advance of the transition to farming. However, these data sets differ in entry
density and data quality. Often they disregard local and regional specifics and
research gaps, or dating uncertainties. Thus, most of these data bases may only
be used on a very general, broad scale. One of the pitfalls of using
irregularly spaced or irregularly documented radiocarbon data becomes evident
from the map generated by Fort (this volume, Chapter 16): while the general
east-west and south-north trends become evident, some areas appear as having
undergone anomalously early transitions to farming. This may be due to faulty
entries into the data base or regional problems with radiocarbon dating, if not
unnoticed or undocumented laboratory mistakes.Comment: 20 pages, 5 figures, submitted to Diffusive Spreading in Nature,
  Technology and Society, edited by Armin Bunde, J\"urgen Caro, J\"org
  K\"arger, Gero Vogl, Chapter 1
Order-randomized Laplacian mesh smoothing.

In this paper we compare three variants of the graph Laplacian smoothing. The first is the standard synchronous implementation, corresponding to multiplication by the graph Laplacian matrix. The second is a voter process inspired asynchronous implementation, assuming that every vertex is equipped with an independent exponential clock. The third is in-between the first two, with the vertices updated according to a random permutation of them. We review some well-known results on spectral graph theory and on voter processes, and we show that while the convergence of the synchronous Laplacian is graph dependent and, generally, does not converge on bipartite graphs, the asynchronous converges with high probability on all graphs. The differences in the properties of these three approaches are illustrated with examples including both regular grids and irregular meshes
Simplicial complex entropy.

We propose an entropy function for simplicial complices. Its value gives the expected cost of the optimal encoding of sequences of vertices of the complex, when any two vertices belonging to the same simplex are indistinguishable. We focus on the computational properties of the entropy function, showing that it can be computed efficiently. Several examples over complices consisting of hundreds of simplices show that the proposed entropy function can be used in the analysis of large sequences of simplicial complices that often appear in computational topology applications
The 3D Redeployment of Nodes in Wireless Sensor Networks with Real Testbed Prototyping

The use of real prototyping systems allows implementing real-world deployments which permit evaluating new protocols, algorithms and network solutions. This study covers the problem of 3D indoor redeployment of connected objects in DL-IoT collection networks. The objective is to choose the right positions in which connected objects are added to an initial configuration, while optimizing a set of objectives. The approach used to solve this problem is based on a new hybrid optimization algorithm that combines a strategy of incorporation of user preferences (PI-EMO-VF) with a recent variant of the genetic algorithms (NSGA-III). The obtained numerical results and the real experiments on our testbed prove the effectiveness of the proposed approach compared to another recent optimization algorithm (MOEA/DD)
A hybrid ant-genetic algorithm to solve a real deployment problem: a case study with experimental validation

In this paper, we investigate the problem of deploying 3D nodes in a wireless sensor network. The aim is to choose the ideal 3D locations to add new nodes to an initial configuration of nodes, while optimizing a set of objectives. In this regard, our study proposes a new hybrid algorithm which stems from the ant foraging behavior and the genetics. It is based on a recent variant of the genetic algorithms (NSGA-III) and the Ant Colony Optimization algorithm. The obtained numerical results and the simulations compared with experiments prove the effectiveness of the proposed approach
Mixed Variable Structural Optimization: Toward an Efficient Hybrid Algorithm

Designing a structure implies a selection of optimal concept and sizing, with the aim of minimizing the weight and/or production cost. In general, a structural optimization problem involves both continuous variables (e.g., geometrical variables, ...) and categorical ones (e.g., materials, stiffener types, ...). Such a problem belongs to the class of mixed-integer nonlinear programming (MINLP) problems. In this paper, we specifically consider a subclass of structural optimization problems where the categorical variables set is non-ordered. To facilitate categorical variables handling, design catalogs are introduced as a generalization of the stacking guide used for composite optimization. From these catalogs, a decomposition of the MINLP problem is proposed, and solved through a branch and bound method. This methodology is tested on a 10 bars truss optimization inspired from an aircraft design problem, consistent with the level of complexity faced in the industry
Gaussian Process for Aerodynamic Pressures Prediction in Fast Fluid Structure Interaction Simulations

The interaction between inertial, elastic and aerodynamic forces for structures subjected to a fluid flow may cause unstable coupled vibrations that can endanger the structure itself. Predicting these interactions is a time consuming but crucial task in an aircraft design process. In order to reduce the computational time surrogate reduced order models can be used in both structural and aerodynamic models. More over it is possible to avoid launching CFD computations at every time step. A database of aerodynamic pressure distribution on the structural component can be created conveniently sampling the space of the structural model DoF. Starting from the knowledge of the precomputed data-set a Gaussian Process can be applied to predict the pressure distribution on an unexplored point of the space of DoF. The knowledge of the standard deviation can be used to give indications on where to launch further CFD computations to enrich the database. This technique will be first applied to a database of pressures obtained using the software Xfoil®, later it will be applied to CFD simulations of type RANS launched with elsA® on one Flap track Fairing of an Airbus aircraft
Model-driven engineering of an openCypher engine: using graph queries to compile graph queries

Graph database systems are increasingly adapted for storing and processing heterogeneous network-like datasets. Many challenging applications with near real-time requirements - such as financial fraud detection, on-the-fly model validation and root cause analysis - can be formalised as graph problems and tackled with graph databases efficiently. However, as no standard graph query language has yet emerged, users are subjected to the possibility of vendor lock-in.\ud
\ud
The openCypher group aims to define an open specification for a declarative graph query language. However, creating an openCypher-compatible query engine requires significant research and engineering efforts. Meanwhile, model-driven language workbenches support the creation of domain-specific languages by providing high-level tools to create parsers, editors and compilers. In this paper, we present an approach to build a compiler and optimizer for openCypher using model-driven technologies, which allows developers to define declarative optimization rules
Correct composition of dephased behavioural models

Scenarios of execution are commonly used to specify partial behaviour and interactions between different objects and components in a system. To avoid overall inconsistency in specifications, various automated methods have emerged in the literature to compose (behavioural) models. In recent work, we have shown how the theorem prover Isabelle can be combined with the constraint solver Z3 to efficiently detect inconsistencies in two or more behavioural models and, in their absence, generate the composition. Here, we extend our approach further and show how to generate the correct composition (as a set of valid traces) of dephased models. This work has been inspired by a problem from a medical domain where different care pathways (for chronic conditions) may be applied to the same patient with different starting points.Postprin
A Component-oriented Framework for Autonomous Agents

The design of a complex system warrants a compositional methodology, i.e.,
composing simple components to obtain a larger system that exhibits their
collective behavior in a meaningful way. We propose an automaton-based paradigm
for compositional design of such systems where an action is accompanied by one
or more preferences. At run-time, these preferences provide a natural fallback
mechanism for the component, while at design-time they can be used to reason
about the behavior of the component in an uncertain physical world. Using
structures that tell us how to compose preferences and actions, we can compose
formal representations of individual components or agents to obtain a
representation of the composed system. We extend Linear Temporal Logic with two
unary connectives that reflect the compositional structure of the actions, and
show how it can be used to diagnose undesired behavior by tracing the
falsification of a specification back to one or more culpable components
Formal Analysis of V2X Revocation Protocols.

Research on vehicular networking (V2X) security has produced\ud
a range of security mechanisms and protocols tailored for this\ud
domain, addressing both security and privacy. Typically, the security\ud
analysis of these proposals has largely been informal. However, formal\ud
analysis can be used to expose flaws and ultimately provide a higher level\ud
of assurance in the protocols. This paper focusses on the formal analysis\ud
of a particular element of security mechanisms for V2X found in many\ud
proposals, that is the revocation of malicious or misbehaving vehicles\ud
from the V2X system by invalidating their credentials. This revocation\ud
needs to be performed in an unlinkable way for vehicle privacy even in\ud
the context of vehicles regularly changing their pseudonyms. The Rewire\ud
scheme by Förster et al. and its subschemes Plain and R-token aim\ud
to solve this challenge by means of cryptographic solutions and trusted\ud
hardware. Formal analysis using the Tamarin prover identifies two flaws:\ud
one previously reported in the literature concerned with functional correctness\ud
of the protocol, and one previously unknown flaw concerning an\ud
authentication property of the R-token scheme. In response to these\ud
flaws we propose Obscure Token (O-token), an extension of Rewire\ud
to enable revocation in a privacy preserving manner. Our approach addresses\ud
the functional and authentication properties by introducing an\ud
additional key-pair, which offers a stronger and verifiable guarantee of\ud
successful revocation of vehicles without resolving the long-term identity.\ud
Moreover O-token is the first V2X revocation protocol to be co-designed\ud
with a formal model
Quantitative Analysis of DoS Attacks and Client Puzzles in IoT Systems

Denial of Service (DoS) attacks constitute a major security threat to today's
Internet. This challenge is especially pertinent to the Internet of Things
(IoT) as devices have less computing power, memory and security mechanisms to
mitigate DoS attacks. This paper presents a model that mimics the unique
characteristics of a network of IoT devices, including components of the system
implementing `Crypto Puzzles' - a DoS mitigation technique. We created an
imitation of a DoS attack on the system, and conducted a quantitative analysis
to simulate the impact such an attack may potentially exert upon the system,
assessing the trade off between security and throughput in the IoT system. We
model this through stochastic model checking in PRISM and provide evidence that
supports this as a valuable method to compare the efficiency of different
implementations of IoT systems, exemplified by a case study