pinecone/core-2020-05-10-deduplication huggingface dataset:
On the State Complexity of the Shuffle of Regular Languages

We investigate the shuffle operation on regular languages represented by
complete deterministic finite automata. We prove that $f(m,n)=2^{mn-1} +
2^{(m-1)(n-1)}(2^{m-1}-1)(2^{n-1}-1)$ is an upper bound on the state complexity
of the shuffle of two regular languages having state complexities $m$ and $n$,
respectively. We also state partial results about the tightness of this bound.
We show that there exist witness languages meeting the bound if $2\le m\le 5$
and $n\ge2$, and also if $m=n=6$. Moreover, we prove that in the subset
automaton of the NFA accepting the shuffle, all $2^{mn}$ states can be
distinguishable, and an alphabet of size three suffices for that. It follows
that the bound can be met if all $f(m,n)$ states are reachable. We know that an
alphabet of size at least $mn$ is required provided that $m,n \ge 2$. The
question of reachability, and hence also of the tightness of the bound $f(m,n)$
in general, remains open.Comment: The final publication is available at Springer via
  http://dx.doi.org/10.1007/978-3-319-41114-9_
Automatic predicate testing in formal certification : you’ve only proven what you’ve said, not what you meant!

The use of formal methods and proof assistants helps to increase the confidence in critical software. However, a formal proof is only a guarantee relative to a formal specification, and not necessary about the real requirements. There is always a jump when going from an informal specification to a formal specification expressed in a logical theory. Thus, proving the correctness of a piece of software always makes the implicit assumption that there is adequacy between the formalised specification -written with logical statements and predicates- and the real requirements -often written in English-. Unfortunately, a huge part of the complexity lies precisely in the specification itself, and it is far from obvious that the formal specification says exactly and completely what it should say. Why should we trust more these predicates than the code that we’ve first refused to trust blindly, leading to these proofs? We show in this paper that the proving activity has not replaced the testing activity but has only changed the object which requires to be tested. Instead of testing code, we now need to test predicates.We present recent ideas about how to conduct these tests inside the proof assistant on a few examples, and how to automate them as far as possible.Postprin
Criticality and Energy Landscapes in Spin Glasses

Despite the extreme simplicity in their definition, spin glasses disclose a
wide variety of non-trivial behaviors that are not yet fully understood. In
this thesis we try to shed light on some of them, focusing on one hand on the
search of phase transitions under perturbations of the Hamiltonian, and on the
other hand on the zero-temperature properties and responses to external
stimuli. After introducing spin glasses through a historiographical review, and
useful concepts on phase transitions and numerics, the results of two massive
Monte Carlo campaigns on three-dimensional systems are shown. In the first one
the de Almeida-Thouless transition is studied, and a new finite-size scaling
ansatz is proposed, that accelerates the convergence to the thermodynamic
limit. In the second one the phase diagram of the Heisenberg spin glass with
random exchange anisotropy is reconstructed. In the following part of the
manuscript, surprising features of zero-temperature statics and dynamics of
several spin glass models are found. Among them, correlations between soft
spins that arise spontaneously during avalanches, and the discovery of
localized states that involve the presence of two-level systems.Comment: PhD thesis defended at the Universidad Complutense de Madrid on
  October 16th 2015. 286 pages, 70 figure
Characterization of programmers with dyslexia

Computer programmers with dyslexia can be found in a range of aca-demic and professional scenarios. Dyslexia may have the effect on a computer programmer of degrading the expected results during collaborative software de-velopment. These people may perform better using visual programming lan-guages. However, we need to understand what programmers with dyslexia expe-rience in order to be able to come up with possible solutions. We have con-ducted an analysis of existing literature and a survey on dyslexia and programming. This paper reports the preliminary results based on the data gathered so far and the key characteristics and needs of this group with the aim of defining the profile of computer programmers with dyslexia
Training a carbon-nanotube/liquid crystal data classifier using evolutionary algorithms.

Evolution-in-Materio uses evolutionary algorithms (EA) to exploit the physical properties of unconfigured, physically rich materials, in effect transforming them into information processors. The potential of this technique for machine learning problems is explored here. Results are obtained from a mixture of single walled carbon nanotubes and liquid crystals (SWCNT/LC). The complex nature of the voltage/current relationship of this material presents a potential for adaptation. Here, it is used as a computational medium evolved by two derivative-free, population-based stochastic search algorithms, particle swarm optimisation (PSO) and differential evolution (DE). The computational problem considered is data classification. A custom made electronic motherboard for interacting with the material has been developed, which allows the application of control signals on the material body. Starting with a simple binary classification problem of separable data, the material is trained with an error minimisation objective for both algorithms. Subsequently, the solution, defined as the combination of the material itself and optimal inputs, is verified and results are reported. The evolution process based on EAs has the capacity to evolve the material to a state where data classification can be performed. PSO outperforms DE in terms of results’ reproducibility due to the smoother, as opposed to more noisy, inputs applied on the material
Psychophysiology in games

Psychophysiology is the study of the relationship between psychology\ud
and its physiological manifestations. That relationship is of particular importance\ud
for both game design and ultimately gameplaying. Players’ psychophysiology offers\ud
a gateway towards a better understanding of playing behavior and experience.\ud
That knowledge can, in turn, be beneficial for the player as it allows designers to\ud
make better games for them; either explicitly by altering the game during play or\ud
implicitly during the game design process. This chapter argues for the importance\ud
of physiology for the investigation of player affect in games, reviews the current\ud
state of the art in sensor technology and outlines the key phases for the application\ud
of psychophysiology in games.The work is supported, in part, by the EU-funded FP7 ICT iLearnRWproject\ud
(project no: 318803).peer-reviewe
Formalizing Threat Models for Virtualized Systems

We propose a framework, called FATHoM (FormAlizing THreat Models), to define threat models for virtualized systems. For each component of a virtualized system, we specify a set of security properties that defines its control responsibility, its vulnerability and protection states. Relations are used to represent how assumptions made about a component’s security state restrict the assumptions that can be made on the other components. FATHoM includes a set of rules to compute the derived security states from the assumptions and the components’ relations. A further set of relations and rules is used to define how to protect the derived vulnerable components. The resulting system is then analysed, among others, for consistency of the threat model. We have developed a tool that implements FATHoM, and have validated it with use-cases adapted from the literature
A controlled natural language for tax fraud detection

Addressing tax fraud has been taken increasingly seriously, but most attempts to uncover it involve the use of human fraud experts to identify and audit suspicious cases. To identify such cases, they come up with patterns which an IT team then implements to extract matching instances. The process, starting from the communication of the patterns to the developers, the debugging of the implemented code, and the refining of the rules, results in a lengthy and error-prone iterative methodology. In this paper, we present a framework where the fraud expert is empowered to independently design tax fraud patterns through a controlled natural language implemented in GF, enabling immediate feedback reported back to the fraud expert. This allows multiple refinements of the rules until optimised, all within a timely manner. The approach has been evaluated by a number of fraud experts working with the Maltese Inland Revenue Department.peer-reviewe
Automatic Nonlinear Filtering and Segmentation for Breast Ultrasound Images

International audienceBreast cancer is one of the leading causes of cancer death among women worldwide. The proposed approach comprises three steps as follows. Firstly, the image is preprocessed to remove speckle noise while preserving important features of the image. Three methods are investigated, i.e., Frost Filter, Detail Preserving Anisotropic Diffusion, and Probabilistic Patch-Based Filter. Secondly, Normalized Cut or Quick Shift is used to provide an initial segmentation map for breast lesions. Thirdly, a postprocessing step is proposed to select the correct region from a set of candidate regions. This approach is implemented on a dataset containing 20 B-mode ultrasound images, acquired from UDIAT Diagnostic Center of Sabadell, Spain. The overall system performance is determined against the ground truth images. The best system performance is achieved through the following combinations: Frost Filter with Quick Shift, Detail Preserving Anisotropic Diffusion with Normalized Cut and Probabilistic Patch-Based with Normalized Cut
3D Structured Light Scanner on the Smartphone

In the recent years turning smartphones into 3D reconstruction devices has been greatly investigated. Different 3D reconstruction concepts have been proposed, and one of the most popular is based on IR projection of a pseudorandom dots (speckle) pattern. We demonstrate our idea how a pseudorandom dots pattern can be used and we also present an active approach applying a structured light (SL) scanning on the smartphone. SL has a number of advantages compared to other 3D reconstruction concepts and likewise our smartphone implementation inherits the same advantages compared to other smartphone based solutions. The shown qualitative and quantitative results demonstrate the comparable outcome with the standard type SL scanner
Morphological Separation of Clustered Nuclei in Histological Images

13th International Conference, ICIAR 2016, in Memory of Mohamed Kamel, Póvoa de Varzim, Portugal, July 13-15, 2016This is the final version of the article. Available from Springer Verlag via the DOI in this record.Automated nuclear segmentation is essential in the analysis of most microscopy images. This paper presents a novel concavity-based method for the separation of clusters of nuclei in binary images. A heuristic rule, based on object size, is used to infer the existence of merged regions. Concavity extrema detected along the merged-cluster boundary are used to guide the separation of overlapping regions. Inner split contours of multiple concavities along the nuclear boundary are estimated via a series of morphological procedures. The algorithm was evaluated on images of H400 cells in monolayer cultures and compares favourably with the state-of-art watershed method commonly used to separate overlapping nuclei.The research reported in this paper was supported by the Engineering and Physical Sciences Research Council (EPSRC), UK through funding under grant EP/M023869/1 “Novel context-based segmentation algorithms for intelligent microscopy
Synthesizing Probabilistic Invariants via Doob's Decomposition

When analyzing probabilistic computations, a powerful approach is to first
find a martingale---an expression on the program variables whose expectation
remains invariant---and then apply the optional stopping theorem in order to
infer properties at termination time. One of the main challenges, then, is to
systematically find martingales.
  We propose a novel procedure to synthesize martingale expressions from an
arbitrary initial expression. Contrary to state-of-the-art approaches, we do
not rely on constraint solving. Instead, we use a symbolic construction based
on Doob's decomposition. This procedure can produce very complex martingales,
expressed in terms of conditional expectations.
  We show how to automatically generate and simplify these martingales, as well
as how to apply the optional stopping theorem to infer properties at
termination time. This last step typically involves some simplification steps,
and is usually done manually in current approaches. We implement our techniques
in a prototype tool and demonstrate our process on several classical examples.
Some of them go beyond the capability of current semi-automatic approaches
Semantic Relation Extraction. Resources, Tools and Strategies

[Abstract] Relation extraction is a subtask of information extraction that aims at obtaining instances of semantic relations present in texts. This information can be arranged in machine-readable formats, useful for several applications that need structured semantic knowledge. The work presented in this paper explores different strategies to automate the extraction of semantic relations from texts in Portuguese, Galician and Spanish. Both machine learning (distant-supervised and supervised) and rule-based techniques are investigated, and the impact of the different levels of linguistic knowledge is analyzed for the various approaches. Regarding domains, the experiments are focused on the extraction of encyclopedic knowledge, by means of the development of biographical relations classifiers (in a closed domain) and the evaluation of an open information extraction tool. To implement the extraction systems, several natural language processing tools have been built for the three research languages: From sentence splitting and tokenization modules to part-of-speech taggers, named entity recognizers and coreference resolution systems. Furthermore, several lexica and corpora have been compiled and enriched with different levels of linguistic annotation, which are useful for both training and testing probabilistic and symbolic models. As a result of the performed work, new resources and tools are available for automated processing of texts in Portuguese, Galician and Spanish.Ministerio de Economía y Competitividad (MINECO); FFI2014-51978-C2-1-RMinisterio de Economía y Competitividad (MINECO); Ayudas Juan de la Cierva-Formación FJCI-2014-2285
Automatic Classification of the Complexity of Nonfiction Texts in
  Portuguese for Early School Years

Recent research shows that most Brazilian students have serious problems
regarding their reading skills. The full development of this skill is key for
the academic and professional future of every citizen. Tools for classifying
the complexity of reading materials for children aim to improve the quality of
the model of teaching reading and text comprehension. For English, Fengs work
[11] is considered the state-of-art in grade level prediction and achieved 74%
of accuracy in automatically classifying 4 levels of textual complexity for
close school grades. There are no classifiers for nonfiction texts for close
grades in Portuguese. In this article, we propose a scheme for manual
annotation of texts in 5 grade levels, which will be used for customized
reading to avoid the lack of interest by students who are more advanced in
reading and the blocking of those that still need to make further progress. We
obtained 52% of accuracy in classifying texts into 5 levels and 74% in 3
levels. The results prove to be promising when compared to the state-of-art
work.9Comment: PROPOR International Conference on the Computational Processing of
  Portuguese, 2016, 9 page
Automatic semantic role labeling on non-revised syntactic trees of
  journalistic texts

Semantic Role Labeling (SRL) is a Natural Language Processing task that
enables the detection of events described in sentences and the participants of
these events. For Brazilian Portuguese (BP), there are two studies recently
concluded that perform SRL in journalistic texts. [1] obtained F1-measure
scores of 79.6, using the PropBank.Br corpus, which has syntactic trees
manually revised, [8], without using a treebank for training, obtained
F1-measure scores of 68.0 for the same corpus. However, the use of manually
revised syntactic trees for this task does not represent a real scenario of
application. The goal of this paper is to evaluate the performance of SRL on
revised and non-revised syntactic trees using a larger and balanced corpus of
BP journalistic texts. First, we have shown that [1]'s system also performs
better than [8]'s system on the larger corpus. Second, the SRL system trained
on non-revised syntactic trees performs better over non-revised trees than a
system trained on gold-standard data.Comment: PROPOR International Conference on the Computational Processing of
  Portuguese, 2016, 8 page
Partial distance correlation with methods for dissimilarities\ud

Partial distance correlation measures association between two random vectors with respect to a third random vector, analogous to, but more general than (linear) partial correlation. Distance correlation characterizes independence of random vectors in arbitrary dimension. Motivation for the definition is discussed. We introduce a Hilbert space of U-centered distance matrices in which squared distance covariance is the inner product. Simple computation of the sample partial distance correlation and definitions of the population coefficients are presented. Power of the test for zero partial distance correlation is compared with power of the partial correlation test and the partial Mantel test. © Springer International Publishing Switzerland 2016
Operator splitting methods with error estimator and adaptive time-stepping. Application to the simulation of combustion phenomena

International audienceOperator splitting techniques were originally introduced with the main objective of saving computational costs. A multi-physics problem is thus split in subproblems of different nature with a significant reduction of the algorithmic complexity and computational requirements of the numerical solvers. Nevertheless, splitting errors are introduced in the numerical approximations due to the separate evolution of the split subproblems and can compromise a reliable reproduction of the coupled dynamics. In this chapter we present a numerical technique to estimate such splitting errors on the fly and dynamically adapt the splitting time steps according to a user-defined accuracy tolerance. The method applies to the numerical solution of time-dependent stiff PDEs, illustrated here by propagating laminar flames investigated in combustion applications
Stability-Based Adaptation of Asynchronously Communicating Software

International audienceSoftware Adaptation aims at composing incompatible black-box components or services (peers) whose individual functionality is as required for the new system. Adaptation techniques aim at automatically generating new components called adapters. An adapter works as an orchestrator and makes the involved peers work correctly together by receiving all messages exchanged in the system and by correcting mis-match between them. A challenging issue in this area is to consider that peers are described with (possibly cyclic) behavioural models and interact asynchronously, that is, exchanging messages via message buffers. The synthesis of adapters in this context is difficult because the composition of peers may result in infinite systems. In this paper, we propose new adaptation techniques, which rely on a property of communicating systems called stability. Stability aims at verifying whether a communicating system exhibits the same observational behaviour from a certain buffer bound on. We also provide adapter generation techniques using process algebra encodings and enumerative analysis techniques
A review of Hybrid High-Order methods: formulations, computational aspects, comparison with other methods

International audienceHybrid High-Order (HHO) methods are formulated in terms of discrete unknowns attached to mesh faces and cells (hence, the term hybrid), and these unknowns are polynomials of arbitrary order k>=0 (hence, the term high-order). HHO methods are devised from local reconstruction operators and a local stabilization term. The discrete problem is assembled cellwise, and cell-based unknowns can be eliminated locally by static condensation. HHO methods support general meshes, are locally conservative, and allow for a robust treatment of physical parameters in various situations, e.g., heterogeneous/anisotropic diffusion, quasi-incompressible linear elasticity, and advection-dominated transport. This paper reviews HHO methods for a variable-diffusion model problem with nonhomogeneous, mixed Dirichlet–Neumann boundary conditions, including both primal and mixed formulations. Links with other discretization methods from the literature are discussed
The AGI Containment Problem

There is considerable uncertainty about what properties, capabilities and
motivations future AGIs will have. In some plausible scenarios, AGIs may pose
security risks arising from accidents and defects. In order to mitigate these
risks, prudent early AGI research teams will perform significant testing on
their creations before use. Unfortunately, if an AGI has human-level or greater
intelligence, testing itself may not be safe; some natural AGI goal systems
create emergent incentives for AGIs to tamper with their test environments,
make copies of themselves on the internet, or convince developers and operators
to do dangerous things. In this paper, we survey the AGI containment problem -
the question of how to build a container in which tests can be conducted safely
and reliably, even on AGIs with unknown motivations and capabilities that could
be dangerous. We identify requirements for AGI containers, available
mechanisms, and weaknesses that need to be addressed
Analysis of Algorithms and Partial Algorithms

We present an alternative methodology for the analysis of algorithms, based
on the concept of expected discounted reward. This methodology naturally
handles algorithms that do not always terminate, so it can (theoretically) be
used with partial algorithms for undecidable problems, such as those found in
artificial general intelligence (AGI) and automated theorem proving. We mention
an approach to self-improving AGI enabled by this methodology.
  Aug 2017 addendum: This article was originally written with multiple
audiences in mind. It is really best put in the following terms. Goertzel,
Hutter, Legg, and others have developed a definition of an intelligence score
for a general abstract agent: expected lifetime reward in a random environment.
AIXI is generally the optimal agent according to this score, but there may be
reasons to analyze other agents and compare score values. If we want to use
this definition of intelligence in practice, perhaps we can start by analyzing
some simple agents. Common algorithms can be thought of as simple agents
(environment is input, reward is based on running time) so we take the goal of
applying the agent intelligence score to algorithms. That is, we want to find,
what are the IQ scores of algorithms? We can do some very simple analysis, but
the real answer is that even for simple algorithms, the intelligence score is
too difficult to work with in practice