pinecone/core-2020-05-10-deduplication huggingface dataset:
A kilobit hidden SNFS discrete logarithm computation

We perform a special number field sieve discrete logarithm computation in a
1024-bit prime field. To our knowledge, this is the first kilobit-sized
discrete logarithm computation ever reported for prime fields. This computation
took a little over two months of calendar time on an academic cluster using the
open-source CADO-NFS software. Our chosen prime $p$ looks random, and $p--1$
has a 160-bit prime factor, in line with recommended parameters for the Digital
Signature Algorithm. However, our p has been trapdoored in such a way that the
special number field sieve can be used to compute discrete logarithms in
$\mathbb{F}\_p^*$ , yet detecting that p has this trapdoor seems out of reach.
Twenty-five years ago, there was considerable controversy around the
possibility of back-doored parameters for DSA. Our computations show that
trapdoored primes are entirely feasible with current computing technology. We
also describe special number field sieve discrete log computations carried out
for multiple weak primes found in use in the wild. As can be expected from a
trapdoor mechanism which we say is hard to detect, our research did not reveal
any trapdoored prime in wide use. The only way for a user to defend against a
hypothetical trapdoor of this kind is to require verifiably random primes
Discrete integrable systems, Darboux transformations, and Yang-Baxter
  maps

These lecture notes are devoted to the integrability of discrete systems and
their relation to the theory of Yang-Baxter (YB) maps. Lax pairs play a
significant role in the integrability of discrete systems. We introduce the
notion of Lax pair by considering the well-celebrated doubly-infinite Toda
lattice. In particular, we present solution of the Cauchy initial value problem
via the method of the inverse scattering transform, provide a review of
scattering theory of Jacobi matrices, and give the Riemann-Hilbert formulation
of the inverse scattering transform. On the other hand, the Lax-Darboux scheme
constitutes an important tool in the theory of integrable systems, as it
relates several concepts of integrability. We explain the role of Darboux and
B\"acklund trasformations in the theory of integrable systems, and we show how
they can be used to construct discrete integrable systems via the Lax-Darboux
scheme. Moreover, we give an introduction to the theory of Yang-Baxter maps and
we show its relation to discrete integrable systems. Finally, we demonstrate
the construction of Yang-Baxter maps via Darboux transformations, using the
nonlinear Schr\"odinger equation as illustrative example.Comment: 54 pages, 13 Figures. Book chapter, accepted for publication in CRM
  Springer Series, for the ASIDE 2016 summer school in Montreal, June 27 - July
  1, 201
Kerncraft: A Tool for Analytic Performance Modeling of Loop Kernels

Achieving optimal program performance requires deep insight into the
interaction between hardware and software. For software developers without an
in-depth background in computer architecture, understanding and fully utilizing
modern architectures is close to impossible. Analytic loop performance modeling
is a useful way to understand the relevant bottlenecks of code execution based
on simple machine models. The Roofline Model and the Execution-Cache-Memory
(ECM) model are proven approaches to performance modeling of loop nests. In
comparison to the Roofline model, the ECM model can also describes the
single-core performance and saturation behavior on a multicore chip. We give an
introduction to the Roofline and ECM models, and to stencil performance
modeling using layer conditions (LC). We then present Kerncraft, a tool that
can automatically construct Roofline and ECM models for loop nests by
performing the required code, data transfer, and LC analysis. The layer
condition analysis allows to predict optimal spatial blocking factors for loop
nests. Together with the models it enables an ab-initio estimate of the
potential benefits of loop blocking optimizations and of useful block sizes. In
cases where LC analysis is not easily possible, Kerncraft supports a cache
simulator as a fallback option. Using a 25-point long-range stencil we
demonstrate the usefulness and predictive power of the Kerncraft tool.Comment: 22 pages, 5 figure
Closure polynomials for strips of tetrahedra

The final publication is available at link.springer.comA tetrahedral strip is a tetrahedron-tetrahedron truss where any tetrahedron has two neighbors except those in the extremes which have only one. Unless any of the tetrahedra degenerate, such a truss is rigid. In this case, if the distance between the strip endpoints is imposed, any rod length in the truss is constrained by all the others to attain discrete values. In this paper, it is shown how to characterize these values as the roots of a closure polynomial whose derivation requires surprisingly no other tools than elementary algebraic manipulations. As an application of this result, the forward kinematics of two parallel platforms with closure polynomials of degree 16 and 12 is straightforwardly solved.Peer ReviewedPostprint (author's final draft
Refactoring Legacy JavaScript Code to Use Classes: The Good, The Bad and
  The Ugly

JavaScript systems are becoming increasingly complex and large. To tackle the
challenges involved in implementing these systems, the language is evolving to
include several constructions for programming- in-the-large. For example,
although the language is prototype-based, the latest JavaScript standard, named
ECMAScript 6 (ES6), provides native support for implementing classes. Even
though most modern web browsers support ES6, only a very few applications use
the class syntax. In this paper, we analyze the process of migrating structures
that emulate classes in legacy JavaScript code to adopt the new syntax for
classes introduced by ES6. We apply a set of migration rules on eight legacy
JavaScript systems. In our study, we document: (a) cases that are
straightforward to migrate (the good parts); (b) cases that require manual and
ad-hoc migration (the bad parts); and (c) cases that cannot be migrated due to
limitations and restrictions of ES6 (the ugly parts). Six out of eight systems
(75%) contain instances of bad and/or ugly cases. We also collect the
perceptions of JavaScript developers about migrating their code to use the new
syntax for classes.Comment: Paper accepted at 16th International Conference on Software Reuse
  (ICSR), 2017; 16 page
ITS-G5 Channel Models for High Speed Train-to-Train Communication

Train-to-train communication will be the key technology for future railway operation. An increase of safety and effciency can be achieved by exchanging data between trains via ad hoc networks. For this purpose intelligent transport systems (ITS-G5) was developed for road traffc. The usage of this technology for railways is hardly investigated. We investigate the performance of an ITS-G5 data link for train-to-train communication at high speed conditions. ITS-G5 units were installed on two high speed trains and train-to-train (T2T) measurements were performed between Naples and Rome during four nights to cover different maneuvers. We present the analysis of the measurements data and resulting path loss models for tunnel and open feld environments
Performance Assessment of a New Routing Protocol in AANET

Routing is a critical issue in mobile ad hoc networks. The routing algorithm must take into account the specific properties of the network such as its topology, the mobility of the nodes and their number. In this paper, we present a simulation-based study of the performances of our innovative routing protocol named NoDe-TBR (Node Density TBR) that takes into account the actual node density distribution. The considered ad hoc network is an Aeronautical Ad hoc NETwork (AANET), a future communication system enabling air↔air and air↔ground communications beyond the radio range of the sender. This context and the communication architecture have been modeled in a realistic way based on replayed aircraft trajectories, a realistic access layer, and application that should be deployed in the future
Improving Spectral Efficiency While Reducing PAPR Using Faster-Than-Nyquist Multicarrier Signaling

Multicarrier modulations are widely used in mobile radio applications due to their adaptability to the time-frequency characteristics of the channel, thus enabling low-complexity equalization. However, their intrinsically high peak-to-average power ratio (PAPR) is a major drawback with regard to implementation issues (e.g., power amplification efficiency, regulatory constraints...). In this paper, we confirm that the PAPR can be decreased as the signaling density (i.e., spectral efficiency at fixed constellation size) increases, even in the case where symbols cannot be perfectly reconstructed using a linear system. In such a two-dimensional generalization of faster-than-Nyquist (FTN) systems, PAPR distribution models from the literature are confirmed by simulation results. Furthermore, for a fixed number of subcarriers, we show that a sufficient condition to yield the optimal PAPR distribution at the output of a critically sampled transmitter is to specify pulse shapes as tight frames. Finally, simulation are performed in the more realistic case of an oversampled transmitted signal
Computing the Chern-Schwartz-MacPherson Class of Complete Simplical
  Toric Varieties

Topological invariants such as characteristic classes are an important tool
to aid in understanding and categorizing the structure and properties of
algebraic varieties. In this note we consider the problem of computing a
particular characteristic class, the Chern-Schwartz-MacPherson class, of a
complete simplicial toric variety X defined by a fan from the combinatorial
data contained in the fan. Specifically, we give an effective combinatorial
algorithm to compute the Chern-Schwartz-MacPherson class of X, in the Chow ring
(or rational Chow ring) of X. This method is formulated by combining, and when
necessary modifying, several known results from the literature and is
implemented in Macaulay2 for test purposes
Geometric and Computational Approach to Classical and Quantum Secret Sharing

Producción CientíficaLinear ramp secret sharing schemes are given by a pair of nested codes. In this work algebraic geometry codes are considered. We found sufficient conditions for qualified or forbidden sets by using geometric properties of the set of points. This article considers both classical schemes and quantum schemes.The authors gratefully acknowledge the support from Japan Society for the Promotion of Science (Grant Nos. 23246071 and 26289116), from the Spanish MINECO (Grant No. MTM2012-36917-C03-03), the Danish Council for Independent Research (Grant No. DFF-4002-00367) and from the "Program for Promoting the Enhancement of Research Universities'' at Tokyo Institute of Technology
States and channels in quantum mechanics without complex numbers

In the presented note we aim at exploring the possibility of abandoning
complex numbers in the representation of quantum states and operations. We
demonstrate a simplified version of quantum mechanics in which the states are
represented using real numbers only. The main advantage of this approach is
that the simulation of the $n$-dimensional quantum system requires $n^2$ real
numbers, in contrast to the standard case where $n^4$ real numbers are
required. The main disadvantage is the lack of hermicity in the representation
of quantum states. Using Mathematica computer algebra system we develop a set
of functions for manipulating real-only quantum states. With the help of this
tool we study the properties of the introduced representation and the induced
representation of quantum channels.Comment: 10 pages, 2 figures, presented at ACA2015, July 20-23, 2015,
  Kalamata, Greec
Event Abstraction for Process Mining using Supervised Learning
  Techniques

Process mining techniques focus on extracting insight in processes from event
logs. In many cases, events recorded in the event log are too fine-grained,
causing process discovery algorithms to discover incomprehensible process
models or process models that are not representative of the event log. We show
that when process discovery algorithms are only able to discover an
unrepresentative process model from a low-level event log, structure in the
process can in some cases still be discovered by first abstracting the event
log to a higher level of granularity. This gives rise to the challenge to
bridge the gap between an original low-level event log and a desired high-level
perspective on this log, such that a more structured or more comprehensible
process model can be discovered. We show that supervised learning can be
leveraged for the event abstraction task when annotations with high-level
interpretations of the low-level events are available for a subset of the
sequences (i.e., traces). We present a method to generate feature vector
representations of events based on XES extensions, and describe an approach to
abstract events in an event log with Condition Random Fields using these event
features. Furthermore, we propose a sequence-focused metric to evaluate
supervised event abstraction results that fits closely to the tasks of process
discovery and conformance checking. We conclude this paper by demonstrating the
usefulness of supervised event abstraction for obtaining more structured and/or
more comprehensible process models using both real life event data and
synthetic event data.Comment: paper to appear in the proceedings of the SAI Intelligent Systems
  Conference 201
Solving MaxSAT by Successive Calls to a SAT Solver

The Maximum Satisfiability (MaxSAT) problem is the problem of finding a truth
assignment that maximizes the number of satisfied clauses of a given Boolean
formula in Conjunctive Normal Form (CNF). Many exact solvers for MaxSAT have
been developed during recent years, and many of them were presented in the
well-known SAT conference. Algorithms for MaxSAT generally fall into two
categories: (1) branch and bound algorithms and (2) algorithms that use
successive calls to a SAT solver (SAT- based), which this paper in on. In
practical problems, SAT-based algorithms have been shown to be more efficient.
This paper provides an experimental investigation to compare the performance of
recent SAT-based and branch and bound algorithms on the benchmarks of the
MaxSAT Evaluations.Comment: Survey, 46 page
A tool to promote sustainability in casting processes: Development highlights

The validity of traditional manufacturing decision variables (i.e. cost, quality, flexibility and time) is questioned by some important challenges of our time: the scarcity of natural resources and environmental pollution. Increasing energy cost to extract and process natural resources, alongside regulatory pressures against pollution, pushes very mature and competitive processes like casting towards a holistic approach where sustainability contributes to strategic decisions together with the mentioned traditional manufacturing variables. As a contribution to this industrial necessity, a modular tool able to analyse material and energy flows in casting processes is under development. In particular, the ability to represent automatically Sankey diagrams of the flows recently implemented is described and validated
Virtual sector profiles for innovation sharing in process industry : sector 01: chemicals

Production data in process industry are proprietary to a company since they are key to the process design and technology expertise. However, data confidentiality restrains industry from sharing results and advancing developments in and across process sectors. Using virtual profiles that simulate the typical operating modes of a given process industry offers an elegant solution for a company to share information with the outside world. This paper proposes a generic methodology to create sector blueprints and applies it to the chemicals industry. It details the profile of a typical chemical site based on essential units and realistic data gathered from existing refineries and chemical plants
A unifying orchestration operating platform for 5G

5G will revolutionize the way ICT and Telecommunications infrastructures work. Indeed, businesses can greatly benefit from innovation introduced by 5G and exploit the new deep integration between ICT and networking capabilities to generate new value-added services. Although a plethora of solutions for virtual resources and infrastructures management and orchestration already exists (e.g., OpenDaylight, ONOS, OpenStack, Apache Mesos, Open Source MANO, Docker Swarm, LXD/LXC, etc.), they are still not properly integrated to match the 5G requirements. In this paper, we present the 5G Operating Platform (5G-OP) which has been conceived to fill in this gap and integrate management, control and orchestration of computing, storage and networking resources down to the end-user devices and terminals (e.g., smart phone, machines, robots, drones, autonomous vehicles, etc.). The 5G-OP is an overarching framework capable to provide agnostic interfaces and a universal set of abstractions in order to implement seamless 5G infrastructure control and orchestration. The functional structure of the 5G-OP, including the horizontal and vertical interworking of functions in it, has been designed to allow Network Operators and Service Providers to exploit diverse roles and business strategies. Moreover, the functional decoupling of the 5G-OP from the underneath management, control and orchestration solutions allows pursuing faster innovation cycles, being ready for the emergence of new service models
Double-sided probing by map of Asplund's distances using Logarithmic
  Image Processing in the framework of Mathematical Morphology

We establish the link between Mathematical Morphology and the map of
Asplund's distances between a probe and a grey scale function, using the
Logarithmic Image Processing scalar multiplication. We demonstrate that the map
is the logarithm of the ratio between a dilation and an erosion of the function
by a structuring function: the probe. The dilations and erosions are mappings
from the lattice of the images into the lattice of the positive functions.
Using a flat structuring element, the expression of the map of Asplund's
distances can be simplified with a dilation and an erosion of the image; these
mappings stays in the lattice of the images. We illustrate our approach by an
example of pattern matching with a non-flat structuring function.Comment: The final publication is available at link.springer.co
Large Networks of Diameter Two Based on Cayley Graphs

In this contribution we present a construction of large networks of diameter
two and of order $\frac{1}{2}d^2$ for every degree $d\geq 8$, based on Cayley
graphs with surprisingly simple underlying groups. For several small degrees we
construct Cayley graphs of diameter two and of order greater than $\frac23$ of
Moore bound and we show that Cayley graphs of degrees
$d\in\{16,17,18,23,24,31,\dots,35\}$ constructed in this paper are the largest
currently known vertex-transitive graphs of diameter two.Comment: 9 pages, Published in Cybernetics and Mathematics Applications in
  Intelligent System
Revisiting and extending the AONT-RS scheme: a robust computationally secure secret sharing scheme

In 2010, Resch and Plank proposed a computationally secure secret sharing scheme, called AONT-RS. We present a generalisation of their scheme and discuss two ways in which information is leaked if used to distribute small ciphertexts. We discuss how to prevent such leak- age and provide a proof of computational privacy in the random oracle model. Next, we extend the scheme to be robust and prove the robust AONT-RS achieves computational privacy in the random oracle model and computational recoverability under standard assumptions. Finally, we compare the security, share size and complexity of the AONT-RS scheme with Krawczyk's SSMS scheme
Raviart Thomas Petrov-Galerkin Finite Elements

The general theory of Babu\v{s}ka ensures necessary and sufficient conditions
for a mixed problem in classical or Petrov-Galerkin form to be well posed in
the sense of Hadamard. Moreover, the mixed method of Raviart-Thomas with
low-level elements can be interpreted as a finite volume method with a
non-local gradient. In this contribution, we propose a variant of type
Petrov-Galerkin to ensure a local computation of the gradient at the interfaces
of the elements. The in-depth study of stability leads to a specific choice of
the test functions. With this choice, we show on the one hand that the mixed
Petrov-Galerkin obtained is identical to the finite volumes scheme "volumes
finis \`a 4 points" ("VF4") of Faille, Gallo\"uet and Herbin and to the
condensation of mass approach developed by Baranger, Maitre and Oudin. On the
other hand, we show the stability via an inf-sup condition and finally the
convergence with the usual methods of mixed finite elements.Comment: arXiv admin note: text overlap with arXiv:1710.0439
Predicting Huntington’s Disease: Extreme Learning Machine with Missing Values

Problems with incomplete data and missing values are common and important in real-world machine learning scenarios, yet often underrepresented in the research field. Particularly data related to healthcare tends to feature missing values which must be handled properly, and ignoring any incomplete samples is not an acceptable solution. The Extreme Learning Machine has demonstrated excellent performance in a variety of machine learning tasks, including situations with missing values. In this paper, we present an application to predict the onset of Huntington’s disease several years in advance based on data from MRI brain scans. Experimental results show that such prediction is indeed realistic with reasonable accuracy, provided the missing values are handled with care. In particular, Multiple Imputation ELM achieves exceptional prediction accuracy
Double Ramp Loss Based Reject Option Classifier

We consider the problem of learning reject option classifiers. The goodness
of a reject option classifier is quantified using $0-d-1$ loss function wherein
a loss $d \in (0,.5)$ is assigned for rejection. In this paper, we propose {\em
double ramp loss} function which gives a continuous upper bound for $(0-d-1)$
loss. Our approach is based on minimizing regularized risk under the double
ramp loss using {\em difference of convex (DC) programming}. We show the
effectiveness of our approach through experiments on synthetic and benchmark
datasets. Our approach performs better than the state of the art reject option
classification approaches
Integrating Reviews into Personalized Ranking for Cold Start
  Recommendation

Item recommendation task predicts a personalized ranking over a set of items
for each individual user. One paradigm is the rating-based methods that
concentrate on explicit feedbacks and hence face the difficulties in collecting
them. Meanwhile, the ranking-based methods are presented with rated items and
then rank the rated above the unrated. This paradigm takes advantage of widely
available implicit feedback. It, however, usually ignores a kind of important
information: item reviews. Item reviews not only justify the preferences of
users, but also help alleviate the cold-start problem that fails the
collaborative filtering. In this paper, we propose two novel and simple models
to integrate item reviews into Bayesian personalized ranking. In each model, we
make use of text features extracted from item reviews using word embeddings. On
top of text features we uncover the review dimensions that explain the
variation in users' feedback and these review factors represent a prior
preference of users. Experiments on six real-world data sets show the benefits
of leveraging item reviews on ranking prediction. We also conduct analyses to
understand the proposed models.Comment: TextBP