pinecone/core-2020-05-10-deduplication huggingface dataset:
Towards the use of sequential patterns for detection and characterization of natural and agricultural areas

Nowadays, a huge amount of high resolution satellite images are freely available. Such images allow researchers in environmental sciences to study the different natural habitats and farming practices in a remote way. However, satellite images content strongly depends on the season of the acquisition. Due to the periodicity of natural and agricultural dynamics throughout seasons, sequential patterns arise as a new opportunity to model the behaviour of these environments. In this paper, we describe some preliminary results obtained with a new framework for studying spatiotemporal evolutions over natural and agricultural areas using k-partite graphs and sequential patterns extracted from segmented Landsat images.Postprint (author’s final draft
On the Informational Comparison of Qualitative Fuzzy Measures

Fuzzy measures or capacities are the most general representation of uncertainty functions. However, this general class has been little explored from the point of view of its information content, when degrees of uncertainty are not supposed to be numerical, and belong to a finite qualitative scale, except in the case of possibility or necessity measures. The thrust of the paper is to define an ordering relation on the set of qualitative capacities expressing the idea that one is more informative than another, in agreement with the possibilistic notion of relative specificity. To this aim, we show that the class of qualitative capacities can be partitioned into equivalence classes of functions containing the same amount of information. They only differ by the underlying epistemic attitude such as pessimism or optimism. A meaningful information ordering between capacities can be defined on the basis of the most pessimistic (resp. optimistic) representatives of their equivalence classes. It is shown that, while qualitative capacities bear strong similarities to belief functions, such an analogy can be misleading when it comes to information content
β-robust solutions for the fuzzy open shop scheduling

International Conference, IPMU 2014, (15th. 2014. Montpellier, France)The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-08795-5_46We consider the open shop scheduling problem with uncertain durations modelled as fuzzy numbers. We define the concepts of necessary and possible β-robustness of schedules and set as our goal to maximise them. Additionally, we propose to assess solution robustness by means of Monte Carlo simulations. Experimental results using a genetic algorithm illustrate the proposal
Stable non-standard imprecise probabilities

Stability arises as the consistency criterion in a betting interpretation for hyperreal imprecise previsions, that is imprecise previsions (and probabilities) which may take infinitesimal values. The purpose of this work is to extend the notion of stable coherence introduced in [8] to conditional hyperreal imprecise probabilities. Our investigation extends the de Finetti-Walley operational characterisation of (imprecise) prevision to conditioning on events which are considered "practically impossible" but not "logically impossible"
A propositional CONEstrip algorithm

We present a variant of the CONEstrip algorithm for checking whether the origin lies in a finitely generated convex cone that can be open, closed, or neither. This variant is designed to deal efficiently with problems where the rays defining the cone are specified as linear combinations of propositional sentences. The variant differs from the original algorithm in that we apply row generation techniques. The generator problem is WPMaxSAT, an optimization variant of SAT; both can be solved with specialized solvers or integer linear programming techniques. We additionally show how optimization problems over the cone can be solved by using our propositional CONEstrip algorithm as a preprocessor. The algorithm is designed to support consistency and inference computations within the theory of sets of desirable gambles. We also make a link to similar computations in probabilistic logic, conditional probability assessments, and imprecise probability theory
Model reference gain scheduling control of a PEM fuel cell using Takagi-Sugeno modelling

In this paper, a solution for the oxygen stoichiometry control problem for Proton Exchange Membrane (PEM) fuel cells is presented. The solution relies on the use of a reference model, where the resulting nonlinear error model is brought to a Takagi-Sugeno (TS) form using the nonlinear sector approach. The TS model is suitable for designing a controller using Linear Matrix Inequalities (LMI)-based techniques, such that the resulting closed-loop error system is stable with poles placed in some desired region of the complex plane. Simulation results are used to show the effectiveness of the proposed approach. In particular, the PEM fuel cell can reach asymptotically the oxygen stoichiometry set-point despite all the considered stack current changes.Peer ReviewedPostprint (author’s final draft
Analogical Classification: A Rule-Based View

Analogical proportion-based classification methods have been introduced a few years ago. They look in the training set for suitable triples of examples that are in an analogical proportion with the item to be classified, on a maximal set of attributes. This can be viewed as a lazy classification technique since, like k-nn algorithms, there is no static model built from the set of examples. The amazing results (at least in terms of accuracy) that have been obtained from such techniques are not easy to justify from a theoretical viewpoint. In this paper, we show that there exists an alternative method to build analogical proportion-based learners by statically building a set of inference rules during a preliminary training step. This gives birth to a new classification algorithm that deals with pairs rather than with triples of examples. Experiments on classical benchmarks of the UC Irvine repository are reported, showing that we get comparable results
A Bacterial-Based Algorithm to Simulate Complex Adaptative Systems

Paper presented at the 13th International Conference on Simulation of Adaptive Behavior which took place at Castellón, Spain in 2014, July 22-25.Bacteria have demonstrated an amazing capacity to overcome envi-ronmental changes by collective adaptation through genetic exchanges. Using a distributed communication system and sharing individual strategies, bacteria propagate mutations as innovations that allow them to survive in different envi-ronments. In this paper we present an agent-based model which is inspired by bacterial conjugation of DNA plasmids. In our approach, agents with bounded rationality interact in a common environment guided by local rules, leading to Complex Adaptive Systems that are named 'artificial societies'. We have demonstrated that in a model based on free interactions among autonomous agents, optimal results emerge by incrementing heterogeneity levels and decentralizing communication structures, leading to a global adaptation of the system. This organic approach to model peertopeer dynamics in Complex Adaptive Systems is what we have named ‘bacterial-based algorithms’ because agents exchange strategic information in the same way that bacteria use conjugation and share genome
Regression-free Synthesis for Concurrency

While fixing concurrency bugs, program repair algorithms may introduce new
concurrency bugs. We present an algorithm that avoids such regressions. The
solution space is given by a set of program transformations we consider in for
repair process. These include reordering of instructions within a thread and
inserting atomic sections. The new algorithm learns a constraint on the space
of candidate solutions, from both positive examples (error-free traces) and
counterexamples (error traces). From each counterexample, the algorithm learns
a constraint necessary to remove the errors. From each positive examples, it
learns a constraint that is necessary in order to prevent the repair from
turning the trace into an error trace. We implemented the algorithm and
evaluated it on simplified Linux device drivers with known bugs.Comment: for source code see https://github.com/thorstent/ConRepai
Proving non-termination using max-SMT

We show how Max-SMT-based invariant generation can be exploited for proving non-termination of programs. The construction of the proof of non-termination is guided by the generation of quasi-invariants - properties such that if they hold at a location during execution once, then they will continue to hold at that location from then onwards. The check that quasi-invariants can indeed be reached is then performed separately. Our technique considers strongly connected subgraphs of a program's control flow graph for analysis and thus produces more generic witnesses of non-termination than existing methods. Moreover, it can handle programs with unbounded non-determinism and is more likely to converge than previous approaches.Peer ReviewedPostprint (author’s final draft
Unification and Logarithmic Space

We present an algebraic characterization of the complexity classes Logspace
and NLogspace, using an algebra with a composition law based on unification.
This new bridge between unification and complexity classes is inspired from
proof theory and more specifically linear logic and Geometry of Interaction.
  We show how unification can be used to build a model of computation by means
of specific subalgebras associated to finite permutations groups. We then prove
that whether an observation (the algebraic counterpart of a program) accepts a
word can be decided within logarithmic space. We also show that the
construction can naturally represent pointer machines, an intuitive way of
understanding logarithmic space computing
Pattern Mining for Named Entity Recognition

Revised selected paper of the LTC'2011 conferenceInternational audienceMany evaluation campaigns have shown that knowledge-based and data-driven approaches remain equally competitive for Named Entity Recognition. Our research team has developed CasEN, a symbolic system based on finite state tranducers, which achieved promising results during the Ester2 French-speaking evaluation campaign. Despite these encouraging results, manually extending the coverage of such a hand-crafted system is a difficult task. In this paper, we present a novel approach based on pattern mining for NER and to supplement our system's knowledge base. The system, mXS, exhaustively searches for hierarchical sequential patterns, that aim at detecting Named Entity boundaries. We assess their efficiency by using such patterns in a standalone mode and in combination with our existing system
Pattern Mining for Named Entity Recognition

International audienceMany evaluation campaigns have shown that knowledge-based and data-driven approaches remain equally competitive for Named Entity Recognition. Our re-search team has developed CasEN, a symbolic system based on finite state tran-ducers, which achieved promising results during the Ester2 French-speaking eval-uation campaign. Despite these encouraging results, manually extending the cov-erage of such a hand-crafted system is a difficult task. In this paper, we present a novel approach based on pattern mining for NER and to supplement our sys-tem's knowledge base. The system, mXS, exhaustively searches for hierarchical sequential patterns, that aim at detecting Named Entity boundaries. We assess their efficiency by using such patterns in a standalone mode and in combination with our existing system
Crowdsourcing for Language Resource Development: Criticisms About Amazon Mechanical Turk Overpowering Use

International audienceThis article is a position paper about Amazon Mechanical Turk, the use of which has been steadily growing in language processing in the past few years. According to the mainstream opinion expressed in articles of the domain, this type of on-line working platforms allows to develop quickly all sorts of quality language resources, at a very low price, by people doing that as a hobby. We shall demonstrate here that the situation is far from being that ideal. Our goal here is manifold: 1- to inform researchers, so that they can make their own choices, 2- to develop alternatives with the help of funding agencies and scientific associations, 3- to propose practical and organizational solutions in order to improve language resources development, while limiting the risks of ethical and legal issues without letting go price or quality, 4- to introduce an Ethics and Big Data Charter for the documentation of language resourc
Showing invariance compositionally for a process algebra for network
  protocols

This paper presents the mechanization of a process algebra for Mobile Ad hoc
Networks and Wireless Mesh Networks, and the development of a compositional
framework for proving invariant properties. Mechanizing the core process
algebra in Isabelle/HOL is relatively standard, but its layered structure
necessitates special treatment. The control states of reactive processes, such
as nodes in a network, are modelled by terms of the process algebra. We propose
a technique based on these terms to streamline proofs of inductive invariance.
This is not sufficient, however, to state and prove invariants that relate
states across multiple processes (entire networks). To this end, we propose a
novel compositional technique for lifting global invariants stated at the level
of individual nodes to networks of nodes.Comment: The Isabelle/HOL source files, and a full proof document, are
  available in the Archive of Formal Proofs, at
  http://afp.sourceforge.net/entries/AWN.shtm
Experience Implementing a Performant Category-Theory Library in Coq

We describe our experience implementing a broad category-theory library in Coq. Category theory and computational performance are not usually mentioned in the same breath, but we have needed substantial engineering effort to teach Coq to cope with large categorical constructions without slowing proof script processing unacceptably. In this paper, we share the lessons we have learned about how to represent very abstract mathematical objects and arguments in Coq and how future proof assistants might be designed to better support such reasoning. One particular encoding trick to which we draw attention allows category-theoretic arguments involving duality to be internalized in Coq’s logic with definitional equality. Ours may be the largest Coq development to date that uses the relatively new Coq version developed by homotopy type theorists, and we reflect on which new features were especially helpful.Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Big-Data@CSAIL Initiative)National Science Foundation (U.S.) (Grant CCF-1253229)United States. Office of Naval Research (Grant N000141310260)United States. Air Force Office of Scientific Research (Grant FA9550-14-1-0031
Verified Abstract Interpretation Techniques for Disassembling Low-level Self-modifying Code

International audienceStatic analysis of binary code is challenging for several reasons. In particular, standard static analysis techniques operate over control flow graphs, which are not available when dealing with self-modifying programs which can modify their own code at runtime. We formalize in the Coq proof assistant some key abstract interpretation techniques that automatically extract memory safety properties from binary code. Our analyzer is formally proved correct and has been run on several self-modifying challenges, provided by Cai et al. in their PLDI 2007 paper
Risk factors and identifiers for Alzheimer's disease: a data mining analysis

The topic of this paper is the Alzheimer’s Disease (AD), with the goal being the analysis of risk factors and identifying tests that can help diagnose AD. While there exists multiple studies that analyze the factors that can help diagnose or predict AD, this is the first study that considers only non-image data, while using a multitude of techniques from machine learning and data mining. The applied methods include classification tree analysis, cluster analysis, data visualization, and classification analysis. All the analysis, except classification analysis, resulted in insights that eventually lead to the construction of a risk table for AD. The study contributes to the literature not only with new insights, but also by demonstrating a framework for analysis of such data. The insights obtained in this study can be used by individuals and health professionals to assess possible risks, and take preventive measures
Automated Classification of Airborne Laser Scanning Point Clouds

Making sense of the physical world has always been at the core of mapping. Up
until recently, this has always dependent on using the human eye. Using
airborne lasers, it has become possible to quickly "see" more of the world in
many more dimensions. The resulting enormous point clouds serve as data sources
for applications far beyond the original mapping purposes ranging from flooding
protection and forestry to threat mitigation. In order to process these large
quantities of data, novel methods are required. In this contribution, we
develop models to automatically classify ground cover and soil types. Using the
logic of machine learning, we critically review the advantages of supervised
and unsupervised methods. Focusing on decision trees, we improve accuracy by
including beam vector components and using a genetic algorithm. We find that
our approach delivers consistently high quality classifications, surpassing
classical methods
BioCloud Search EnGene: Surfing Biological Data on the Cloud

The massive production and spread of biomedical data around the web introduces new challenges related to identify computational approaches for providing quality search and browsing of web resources. This papers presents BioCloud Search EnGene (BSE), a cloud application that facilitates searching and integration of the many layers of biological information offered by public large-scale genomic repositories. Grounding on the concept of dataspace, BSE is built on top of a cloud platform that severely curtails issues associated with scalability and performance. Like popular online gene portals, BSE adopts a gene-centric approach: researchers can find their information of interest by means of a simple “Google-like” query interface that accepts standard gene identification as keywords. We present BSE architecture and functionality and discuss how our strategies contribute to successfully tackle big data problems in querying gene-based web resources. BSE is publically available at: http://biocloud-unica.appspot.com/
The development of linked databases and environmental modelling systems for decision-making in London

A basic requirement for a city's growth is the availability of land, raw material and water. For continued and sustainable development of today’s cities we must be able to meet these basic requirements whilst being mindful of the environment and its relationship with anthropogenic activity. The heterogeneous and complex nature of urban systems where there are obvious environmental and anthropogenic inter-dependencies necessitates a more holistic approach to decision-making. New developments such as linked databases of environmental data and integrated environmental modelling systems provide new ways of organising cross-disciplinary information and a means to apply this to explain, explore and predict the urban systems response to environmental change. In this paper we show how, accessibility to linked databases, detailed understanding of the geology and integrated environmental modelling solutions has the potential to provide decision-makers and policy developers with the science based information needed to understand and address these challenges
Urban engineering geological maps for Bradford, UK

An applied geological study of the City of Bradford Metropolitan District, UK, was the last of a series of British Government-funded projects to provide background applied geological information for land-use planning and development. This study included a range of engineering geological maps. As well as providing a general engineering geological overview, the maps show foundation conditions, suitability of deposits as engineered fill, excavatability, the thickness of superficial deposits and landslide distribution and slope steepness. The paper briefly describes the content of the maps and how they were produced
Interactions Between Tunnels and Unstable Slopes: Role of Excavation

International audienceBack analysis of old tunnels in an unstable slope context leads to consider several situations of tunnel entering a slope: cross-cutting tunnel to slope, sloped tunnel, or shallow tunnel following the slope. Identified pathologies of structures vary depending on these situations. This research focuses on different slope mechanisms of instability, especially on creep processes and on damages affecting the structure of tunnels parallel to the slopes. The analysis of the Geotechnical Influenced Zone of these tunnel structures in slope context is a significant point of this study. Through numerical simulations, the different aging and damage processes related to structures have been taken into account. Factors associated with geological and geomorphogical conditions of the slope along with their changes over time can be distinguished from factors corresponding to tunnel's excavations and construction methods. The influence of the first factors on the kinetics of movements and on the emergence of pathologies on structures can be revealed through the study of different geological, geomorphogical, hydrological and seismic contexts. This study focuses on the impact of building methods' parameters (excavation, reinforcement structures, supports and linings). The excavation of a tunnel leads to a slope destabilization due to a more or less important deconfinement of the surrounding massif. Construction techniques influence, on one hand, slope destabilization with the development of shear strips and, on the other hand, structural damages in the tunnel lining. The relative influence of the deconfinement level when setting out the lining, the morphology of the transverse section of the tunnel, its dimensions and the characteristics of the lining structure are studied through several parametric studies. As a conclusion, lessons are drawn about analysis methodologies of tunnel and the corresponding monitoring
Superficial Hollows and Rockhead anomalies in the London Basin, UK: origins, distribution and risk implications for subsurface infrastructure and water resources

Recent findings in London show that the subsurface is much more complex than expected,with a number of apparently anomalous features that present a direct hazard to infrastructure development and a risk to ground water management. Of these features, one of the least understood are the large superficial hollows which occur in the rockhead—in much of the London Basin, this is the top of the London Clay Formation—and which are infilled by a\ud
range of Quaternary deposits, principally alluvial sands and gravels deposited by the River Thames and its tributaries. The hollows range in size and shape. Several are a few hundred metres across and can be up to 40–50 m deep, though determining their exact form is problematic. The soil and sediment infill of the hollows differs substantially from the surrounding ground in terms of strength and drainage, as well as some differences in\ud
chemistry. This presents a real hazard to infrastructure as there is a potential for vertical and horizontal movement, flooding, as well as increasing the risk of contamination of the deeper aquifer. In the paper, the locations and characteristics of known hollows and deformed strata\ud
are reviewed and evidence for how they formed is reassessed, systematically considering different hypotheses (scour, ground ice, karst subsidence, seismo-tectonic). From this we consider the implications for continued development of subsurface infrastructure development,\ud
and for water resources