pinecone/core-2020-05-10-deduplication huggingface dataset:
Structure Preserving Bisimilarity, Supporting an Operational Petri Net
  Semantics of CCSP

In 1987 Ernst-R\"udiger Olderog provided an operational Petri net semantics
for a subset of CCSP, the union of Milner's CCS and Hoare's CSP. It assigns to
each process term in the subset a labelled, safe place/transition net. To
demonstrate the correctness of the approach, Olderog established agreement (1)
with the standard interleaving semantics of CCSP up to strong bisimulation
equivalence, and (2) with standard denotational interpretations of CCSP
operators in terms of Petri nets up to a suitable semantic equivalence that
fully respects the causal structure of nets. For the latter he employed a
linear-time semantic equivalence, namely having the same causal nets.
  This paper strengthens (2), employing a novel branching-time version of this
semantics---structure preserving bisimilarity---that moreover preserves
inevitability. I establish that it is a congruence for the operators of CCSP
Logics of Finite Hankel Rank

We discuss the Feferman-Vaught Theorem in the setting of abstract model
theory for finite structures. We look at sum-like and product-like binary
operations on finite structures and their Hankel matrices. We show the
connection between Hankel matrices and the Feferman-Vaught Theorem. The largest
logic known to satisfy a Feferman-Vaught Theorem for product-like operations is
CFOL, first order logic with modular counting quantifiers. For sum-like
operations it is CMSOL, the corresponding monadic second order logic. We
discuss whether there are maximal logics satisfying Feferman-Vaught Theorems
for finite structures.Comment: Appeared in YuriFest 2015, held in honor of Yuri Gurevich's 75th
  birthday. The final publication is available at Springer via
  http://dx.doi.org/10.1007/978-3-319-23534-9_1
On the unpredictability of individual quantum measurement outcomes

We develop a general, non-probabilistic model of prediction which is suitable
for assessing the (un)predictability of individual physical events. We use this
model to provide, for the first time, a rigorous proof of the unpredictability
of a class of individual quantum measurement outcomes, a well-known quantum
attribute postulated or claimed for a long time.
  We prove that quantum indeterminism - formally modelled as value
indefiniteness - is incompatible with the supposition of predictability:
measurements of value indefinite observables are unpredictable. The proof makes
essential use of a strengthened form of the Kochen-Specker theorem proven
previously to identify value indefinite observables. This form of quantum
unpredictability, like the Kochen-Specker theorem, relies on three assumptions:
compatibility with quantum mechanical predictions, non-contextuality, and the
value definiteness of observables corresponding to the preparation basis of a
quantum state.
  We explore the relation between unpredictability and incomputability and show
that the unpredictability of individual measurements of a value indefinite
quantum observable complements, and is independent of, the global strong
incomputability of any sequence of outcomes of this particular quantum
experiment.
  Finally, we discuss a real model of hypercomputation whose computational
power has yet to be determined, as well as further open problems.Comment: 19 page
Undercutting in argumentation systems

Rule-based argumentation systems are developed for reasoning about defeasible information. They take as input a theory made of a set of strict rules, which encode strict information, and a set of defeasible rules which describe general behaviour with exceptional cases. They build arguments by chaining such rules, define attacks between them, use a semantics for evaluating the arguments, and finally identify the plausible conclusions that follow from the rules. One of the main attack relations of such systems is the so-called undercutting which blocks the application of defeasible rules in some contexts. In this paper, we show that this relation is powerful enough to capture alone all the different conflicts in a theory. We present the first argumentation system that uses only undercutting and fully characterize both its extensions and its plausible conclusions under various acceptability semantics
Towards a dual process cognitive model for argument evaluation

In this paper we are interested in the computational and formal analysis of the persuasive impact that an argument can produce on a human agent. We propose a dual process cognitive computational model based on the highly influential work of Kahneman and investigate its reasoning mechanisms in the context of argument evaluation. This formal model is a first attempt to take a greater account of human reasoning and is a first step to a better understanding of persuasion processes as well as human argumentative strategies, which is crucial in collective decision making domain
A Possibilistic Analysis of Inconsistency

Central in standard possibilistic logic (where propositional logic formulas are associated with lower bounds of their necessity measures), is the notion of inconsistency level of a possibilistic logic base. Formulas whose level is strictly above this inconsistency level constitute a sub-base free of any inconsistency. Some extensions, based on the notions of paraconsistent completion of a possibilistic logic base, and of safely supported formulas, have been proposed for handling formulas below the level of inconsistency. In this paper we further explore these ideas, and show the interest of considering the minimal inconsistent subsets in this setting. Lines for further research are also outlined
Using rules of thumb for repairing inconsistent answer set programs

Answer set programming is a form of declarative programming that can be used to elegantly model various systems. When the available knowledge about these systems is imperfect, however, the resulting programs can be inconsistent. In such cases, it is of interest to find plausible repairs, i.e.~plausible modifications to the original program that ensure the existence of at least one answer set. Although several approaches to this end have already been proposed, most of them merely find a repair which is in some sense minimal. In many applications, however, expert knowledge is available which could allow us to identify better repairs. In this paper, we analyze the potential of using expert knowledge in this way, by focusing on a specific case study: gene regulatory networks. We show how we can identify the repairs that best agree with insights about such networks that have been reported in the literature, and experimentally compare this strategy against the baseline strategy of identifying minimal repairs
Liberation or anarchy? The Janus nature of groundwater use on North Africa's new irrigation frontiers

Two contrasting views prevail on groundwater use in situations of predominantly state-led irrigation development. The first considers "groundwater as liberation", i.e., how, by capturing the irrigation initiative, farmers liberated themselves from "state" water, enabling more intensive and productive agriculture. The second view – "groundwater as anarchy" – considers groundwater as a declining resource, overexploited by millions of individualistic farmers in the absence of effective groundwater governance with mounting inequalities in groundwater use. We analyse the Janus nature of groundwater in the expanding groundwater economy in Morocco, Algeria and Tunisia. Groundwater has redesigned irrigation frontiers, and caters to over 60 % of the total irrigated area, supplying more than 500,000 farms with irrigation water. However, more than half of the aquifers are overexploited, and typically only 40–50 % of farmers in a given area access groundwater. We conclude that groundwater use in North Africa cannot be qualified as anarchy, but rather as a negotiated disorder where the interests of farmers, the private sector, and the state, are continuously realigned. Groundwater "liberated" farmers only partially from "state" water, as the state has remained present in groundwater economies. Moreover, groundwater concerned a minority of farmers, who are often keen to get state support when facing resource depletion or harsh agricultural markets. Breaking the current conundrum will require creating space for change, by making visible the current and future effects of groundwater dynamics to local actors, and supporting the building of coalitions of actors towards a sustainable agricultural use of groundwater. (Résumé d'auteur
The most probable explanation for probabilistic logic programs with annotated disjunctions

Probabilistic logic languages, such as ProbLog and CP-logic,
are probabilistic generalizations of logic programming that allow one to model probability distributions over complex, structured domains. Their key probabilistic constructs are probabilistic facts and annotated disjunctions to represent binary and mutli-valued random variables, respectively. ProbLog allows the use of annotated disjunctions by translating them into probabilistic facts and rules. This encoding is tailored towards the task of computing the marginal probability of a query given evidence (MARG), but is not correct for the task of finding the most probable explanation (MPE) with important applications eg., diagnostics and scheduling. 
In this work, we propose a new encoding of annotated disjunctions which allows correct MARG and MPE. We explore from both theoretical and experimental perspective the trade-off between the encoding suitable only for MARG inference and the newly proposed (general) approach.status: publishe
Complex aggregates over clusters of elements

Complex aggregates have been proposed as a way to bridge the gap between approaches that handle sets by imposing conditions on specific elements, and approaches that handle them by imposing conditions on aggregated values. A complex aggregate summarises a subset of the elements in a set, where this subset is defined by conditions on the attribute values. In this paper, we present a new type of complex aggregate, where this subset is defined to be a cluster of the set. This is useful if subsets that are relevant for the task at hand are difficult to describe in terms of attribute conditions. This work is motivated from the analysis of flow cytometry data, where the sets are cells, and the subsets are cell populations. We describe two approaches to aggregate over clusters on an abstract level, and validate one of them empirically, motivating future research in this direction
The Layered Architecture Recovery as a Quadratic Assignment Problem

Software architecture recovery is a bottom-up process that aims at building high-level views that support the understanding of existing software applications. Many approaches have been proposed to support architecture recovery using various techniques. However, very few approaches are driven by the architectural styles that were used to build the systems under analysis. In this paper, we address the problem of recovering layered views of existing software systems. We re-examine the layered style to extract a set of fundamental principles which encompass a set of constraints that a layered system must conform to at design time and during its evolution. These constraints are used to guide the recovery process of layered architectures. In particular, we translate the problem of recovering the layered architecture into a quadratic assignment problem (QAP) based on these constraints, and we solve the QAP using a heuristic search algorithm. In this paper, we introduce the QAP formulation of the layering recovery and we present and discuss the results of the experimentation with the approach on four open source software systems
Redundancy resolution in human-robot co-manipulation with cartesian impedance control

In this paper the role of redundancy in Cartesian impedance control of a robotic arm for the execution of tasks in co-manipulation with humans is considered. In particular, the problem of stability is experimentally investigated. When a human operator guides the robot through direct physical interaction, it is desirable to have a compliant behaviour at the end effector according to a decoupled impedance dynamics. In order to achieve a desired impedance behaviour, the robot’s dynamics has to be suitably reshaped by the controller. Moreover, the stability of the coupled human-robot system should be guaranteed for any value of the impedance parameters within a prescribed region. If the robot is kinematically or functionally redundant, also the redundant degrees of freedom can be used to modify the robot dynamics. Through an extensive experimental study on a 7-DOF KUKA LWR4 arm, we compare two different strategies to solve redundancy and we show that, when redundancy is exploited to ensure a decoupled apparent inertia at the end effector, the stability region in the parameter space becomes larger. Thus, better performance can be achieved by using, e.g., variable impedance control laws tuned to human intentions
Monitoring for a decidable fragment of MTL-∫

Temporal logics targeting real-time systems are traditionally undecidable. Based on a restricted fragment of MTL-R, we propose a new approach for the runtime veriﬁcation of hard real-time systems. The novelty of our technique is that it is based on incremental evaluation, allowing us to e↵ectively treat duration properties (which play a crucial role in real-time systems). We describe the two levels of operation of our approach: offline simpliﬁcation by quantiﬁer removal techniques; and online evaluation of a three-valued interpretation for formulas of our fragment. Our experiments show the applicability of this mechanism as well as the validity of the provided complexity results
Qualitative and quantitative monitoring of spatio-temporal properties

We address the specification and verification of spatio-temporal behaviours of complex systems, extending Signal Spatio-Temporal Logic (SSTL) with a spatial operator capable of specifying topological properties in a discrete space. The latter is modelled as a weighted graph, and provided with a boolean and a quantitative semantics. Furthermore, we define efficient monitoring algorithms for both the boolean and the quantitative semantics. These are implemented in a Java tool available online. We illustrate the expressiveness of SSTL and the effectiveness of the monitoring procedures on the formation of patterns in a Turing reaction-diffusion system
Machine Learning Methods in Statistical Model Checking and System Design – Tutorial

Recent research has seen an increasingly fertile convergence of ideas from machine learning and formal modelling. Here we review some recently introduced methodologies for model checking and system design/parameter synthesis for logical properties against stochastic dynamical models. The crucial insight is a regularity result which states that the satisfaction probability of a logical formula is a smooth function of the parameters of a CTMC. This enables us to select an appropriate class of functional priors for Bayesian model checking and system design. We give a tutorial introduction to the statistical concepts, as well as an illustrative case study which demonstrates the usage of a newly-released software tool, U-check, which implements these methodologies
RV-Android: Efficient Parametric Android Runtime Verification, a Brief Tutorial

International audienceRV-Android is a new freely available open source runtime library for monitoring formal safety properties on Android. RV-Android uses the commercial RV-Monitor technology as its core monitoring library generation technology, allowing for the verification of safety properties during execution and operating entirely in userspace with no kernel or operating system modifications required. RV-Android improves on previous Android monitoring work by replacing the JavaMOP framework with RV-Monitor, a more advanced monitoring library generation tool with core algorithmic improvements that greatly improve resource consumption , e and battery life considerations. We demonstrate the developer usage of RV-Android with the standard Android build process, using instrumentation mechanisms e↵ective on both Android binaries and source code. Our method allows for both property development and advanced application testing through runtime verification. We showcase the user frontend of RV-Monitor, which is available for public demo use and requires no knowledge of RV concepts. We explore the extra expres-siveness the MOP paradigm provides over simply writing properties as aspects through two sample security properties, and show an example of a real security violation mitigated by RV-Android on-device. Lastly, we propose RV as an extension to the next-generation Android permissions system debuting in Android M
Second International Competition on Runtime Verification
 : 
CRV 2015

International audienceWe report on the Second International Competition on Run-time Verification (CRV-2015). The competition was held as a satellite event of the 15th International Conference on Runtime Verification (RV'15). The competition consisted of three tracks: o✏ine monitoring, online monitoring of C programs, and online monitoring of Java programs. This report describes the format of the competition, the participating teams and submitted benchmarks. We give an example illustrating the two main inputs expected from the participating teams, namely a benchmark (i.e., a program and a property on this program) and a monitor for this benchmark. We also propose some reflection based on the lessons learned
Algorithms for Order-Preserving Matching

String matching is a widely studied problem in Computer Science. There have been many recent developments in this field. One fascinating problem considered lately is the order-preserving matching (OPM) problem. The task is to find all the substrings in the text which have the same length and relative order as the pattern, where the relative order is the numerical order of the numbers in a string. The problem finds its applications in the areas involving time series or series of numbers. More specifically, it is useful for those who are interested in the relative order of the pattern and not in the pattern itself. For example, it can be used by analysts in a stock market to study movements of prices.  In addition to the OPM problem, we also studied its approximate variation. In approximate order-preserving matching, we search for those substrings in the text which have relative order similar to the pattern, i.e., relative order of the pattern matches with at most k mismatches. With respect to applications of order-preserving matching, approximate search is more meaningful than exact search. We developed various advanced solutions for the problem and its variant. Special emphasis was laid on the practical efficiency of the solutions. Particularly, we introduced a simple solution for the OPM problem using filtration. We proved experimentally that our method was effective and faster than the previous solutions for the problem. In addition, we combined the Single Instruction Multiple Data (SIMD) instruction set architecture with filtration to develop competent solutions which were faster than our previous solution. Moreover, we proposed another efficient solution without filtration using the SIMD architecture. We also presented an offline solution based on the FM-index scheme. Furthermore, we proposed practical solutions for the approximate order-preserving matching problem and one of the solutions was the first sublinear solution on average for the problem
Computing the Longest Unbordered Substring

International audienceA substring of a string is unbordered if its only border is the empty string. The study of unbordered substrings goes back to the paper of Ehrenfeucht and Silberger [7]. The main focus of [7] and of subsequent papers was to elucidate the relationship between the longest unbordered substring and the minimal period of strings. In this paper, we consider the algorithmic problem of computing the longest unbordered substring of a string. The problem was introduced recently in [12], where the authors showed that the average-case running time of the simple, border-array based algorithm can be bounded by O(n 2 /σ 4) for σ being the size of the alphabet. (The worst-case running time remained O(n 2).) Here we propose two algorithms, both presenting substantial theoretical improvements to the result of [12]. The first algorithm has O(n log n) average-case running time and O(n 2) worst-case running time, and the second algorithm has O(n 1.5) worst-case running time
Evaluating geographical knowledge re-ranking, linguistic processing and query expansion techniques for geographical information retrieval

This paper describes and evaluates the use of Geographical Knowledge Re-Ranking, Linguistic Processing, and Query Expansion techniques to improve Geographical Information Retrieval effectiveness. Geographical Knowledge Re-Ranking is performed with Geographical Gazetteers and conservative Toponym Disambiguation techniques that boost the ranking of the geographically relevant documents retrieved by standard state-of-the-art Information Retrieval algorithms. Linguistic Processing is performed in two ways: 1) Part-of-Speech tagging and Named Entity Recognition and Classification are applied to analyze the text collections and topics to detect toponyms, 2) Stemming (Porter’s algorithm) and Lemmatization are also applied in combination with default stopwords filtering. The Query Expansion methods tested are the Bose-Einstein (Bo1) and Kullback-Leibler term weighting models. The experiments have been performed with the English Monolingual test collections of the GeoCLEF evaluations (from years 2005, 2006, 2007, and 2008) using the TF-IDF, BM25, and InL2 Information Retrieval algorithms over unprocessed texts as baselines. The experiments have been performed with each GeoCLEF test collection (25 topics per evaluation) separately and with the fusion of all these collections (100 topics). The results of evaluating separately Geographical Knowledge Re-Ranking, Linguistic Processing (lemmatization, stemming, and the combination of both), and Query Expansion with the fusion of all the topics show that all these processes improve the Mean Average Precision (MAP) and RPrecision effectiveness measures in all the experiments and show statistical significance over the baselines in most of them. The best results in MAP and RPrecision are obtained with the InL2 algorithm using the following techniques: Geographical Knowledge Re-Ranking, Lemmatization with Stemming, and Kullback-Leibler Query Expansion. Some configurations with Geographical Knowledge Re-Ranking, Linguistic Processing and Query Expansion have improved the MAP of the best official results at GeoCLEF evaluations of 2005, 2006, and 2007.Peer ReviewedPostprint (published version
Improved Practical Compact Dynamic Tries

We consider the problem of implementing a dynamic trie with an emphasis on good practical performance. For a trie with n nodes with an alphabet of size σ, the information-theoretic lower bound is nlogσ+O(n) bits. The Bonsai data structure [1] supports trie operations in O(1) expected time (based on assumptions about the behaviour of hash functions). While its practical speed performance is excellent, its space usage of (1+ϵ)n(logσ+O(loglogn)) bits, where ϵ is any constant >0, is not asymptotically optimal. We propose an alternative, m-Bonsai, that uses (1+ϵ)n(logσ+O(1)) bits in expectation, and supports operations in O(1) expected time (again based on assumptions about the behaviour of hash functions). We give a heuristic implementation of m-Bonsai which uses considerably less memory and is slightly faster than the original Bonsai.Peer-reviewedPost-print22nd International Symposium on String Processing and Information Retrieva