pinecone/core-2020-05-10-deduplication huggingface dataset:
Application of a Mamdani-type fuzzy rule-based system to segment periventricular cerebral veins in susceptibility-weighted images

This paper presents an algorithm designed to segment veins in the periventricular region of the brain in susceptibility-weighted magnetic resonance images. The proposed algorithm is based on a Mamdani-type fuzzy rule-based system that enables enhancement of veins within periventricular regions of interest as the first step. Segmentation is achieved after determining the cut-off value providing the best trade-off between sensitivity and specificity to establish the suitability of each pixel to belong to a cerebral vein. Performance of the algorithm in\ud
susceptibility-weighted images acquired in healthy volunteers showed very good segmentation, with a small number of false positives. The results were not affected by small changes in the size and location of the regions of interest. The\ud
algorithm also enabled detection of differences in the visibility of periventricular veins between healthy subjects and multiple sclerosis patients. © Springer International Publishing Switzerland 2016.Postprint (author's final draft
A framework for outdoor mobile augmented reality and its application to mountain peak detection

Outdoor augmented reality applications project information of interest onto views of the world in real-time. Their core challenge is recognizing the meaningful objects present in the current view and retrieving and overlaying pertinent information onto such objects. In this paper we report on the development of a framework for mobile outdoor augmented reality application, applied to the overlay of peak information onto views of mountain landscapes. The resulting app operates by estimating the virtual panorama visible from the viewpoint of the user, using an online Digital Terrain Model (DEM), and by matching such panorama to the actual image framed by the camera. When a good match is found, meta-data from the DEM (e.g., peak name, altitude, distance) are projected in real time onto the view. The application, besides providing a nice experience to the user, can be employed to crowdsource the collection of annotated mountain images for environmental applications
Augmented Reality in the Control Tower: a Rendering Pipeline for Multiple Head-Tracked Head-Up Displays

The purpose of the air traffic management system is to accomplish the safe and efficient flow of air traffic. However, the primary goals of safety and efficiency are to some extent conflicting. In fact, to deliver a greater level of safety, separation between aircrafts would have to be greater than it currently is, but this would negatively impact the efficiency. In an attempt to avoid the trade- off between these goals, the long-range vision for the Single European Sky in- cludes objectives for operating as safely and efficiently in Visual Meteorological Conditions as in Instrument Meteorological Conditions. In this respect, a wide set of virtual/augmented reality tools has been developed and effectively used in both civil and military aviation for piloting and training purposes (e.g., Head-Up Displays, Enhanced Vision Systems, Synthetic Vision Systems, Combined Vi- sion Systems, etc.). These concepts could be transferred to air traffic control with a relatively low effort and substantial benefits for controllers’ situation aware- ness. Therefore, this study focuses on the see-through, head-tracked, head-up dis- play that may help controllers dealing with zero/low visibility conditions and in- creased traffic density at the airport. However, there are several open issues as- sociated with the use of this technology. One is the difficulty of obtaining a con- stant overlap between the scene-linked symbols and the background view based on the user’s viewpoint, which is known as ‘registration’. Another one is the presence of multiple, arbitrary oriented Head-Up Displays (HUDs) in the control tower, which further complicates the generation of the Augmented Reality (AR) content. In this paper, we propose a modified rendering pipeline for a HUD sys- tem that can be made out of several, arbitrary oriented, head-tracked, AR dis- plays. Our algorithm is capable of generating a constant and coherent overplay between the AR layer and the outside view from the control tower. However a 3D model of the airport and the airport’s surroundings is needed, which must be populated with all the necessary AR overlays (both static and dynamic). We plan to use this concept as a basis for further research in the field of see-through HUDs for the control tower
Assisted coverage closure

Malfunction of safety-critical systems may cause damage to people and the environment.  Software within those systems is rigorously designed and verified according to domain specific guidance, such as ISO26262 for automotive safety.  This paper describes academic and industrial co-operation in tool development to support one of the most stringent of the requirements --- achieving full code coverage in requirements-driven testing.\ud
\ud
We present a verification workflow supported by a tool that integrates the coverage measurement tool RapiCover with the test-vector generator FShell. The tool assists closing the coverage gap by providing the engineer with test vectors that help in debugging coverage-related code quality issues and creating new test cases, as well as justifying the presence of unreachable parts of the code in order to finally achieve full effective coverage according to the required criteria. We illustrate the tool's practical utility on automotive industry benchmarks. It generates 8 times more MC/DC coverage than random search
An investigation of interregional trade network structures

We provide empirical evidence on the network structure of trade flows between European regions and discuss the theoretical underpinning of such a structure. First, we analyze EU regional trade data using Social Network Analysis. We describe the topology of this network and compute local and global centrality measures. Finally, we consider the distribution of higher order statistics, through the analysis of local clustering and main triadic structures in the triad census of interregional trade flows. In the theoretical part, we explore the relationship between trade costs and trade links. As shown by Behrens (2004, 2005a, 2005b) in a two-region linear new economic geography (NEG) model, trade costs and the local market size determine, even with finite trade costs, unconditional autarky and unilateral trade, that is, a one-directional flow from one region to the other. Following these contributions and guided by the empirical evidence, we clarify the relationship between market competition, trade costs and the patterns of trade in a three-region NEG model. We identify a larger set of trade network configurations other the three elementary ones that occur at the dyadic level between two regions (no trade, one-way trade, reciprocated two-way trade), and relate the model with the triad census
Experiments with Synchronizing Automata

We have improved an algorithm generating synchronizing automata with a large
length of the shortest reset words. This has been done by refining some known
results concerning bounds on the reset length. Our improvements make possible
to consider a number of conjectures and open questions concerning synchronizing
automata, checking them for automata with a small number of states and
discussing the results. In particular, we have verified the \v{C}ern\'y
conjecture for all binary automata with at most 12 states, and all ternary
automata with at most 8 states.Comment: CIAA 2016. The final publication available at
  http://link.springer.com/chapter/10.1007/978-3-319-40946-7_1
Computing the Expected Edit Distance from a String to a PFA

In a number of fields one is to compare a witness string with a distribution. One possibility is to compute the probability of the string for that distribution. Another, giving a more global view, is to compute the expected edit distance from a string randomly drawn to the witness string. This number is often used to measure the performance of a prediction, the goal then being to return the median string, or the string with smallest expected distance. To be able to measure this, computing the distance between a hypothesis and that distribution is necessary. This paper proposes two solutions for computing this value, when the distribution is defined with a probabilistic finite state automaton. The first is exact but has a cost which can be exponential in the length of the input string, whereas the second is a FPRAS.Spanish Ministerio de Educación, Cultura y Deporte through a FPU grant (Ref. AP2012-0939) and the Spanish Ministerio de Economía y Competitividad through Project No. TIN2013-48152-C2-1-R (supported by UE FEDER funds). This work was partly done while the second author was supported by the University of Kyoto
Learner autonomy and awareness through distance collaborative group work in English for Academic Purposes

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-40956-6_13Learner autonomy is considered to be both an important skill and attitude of learners, which involves responsibility for and control of the learning process. A key notion in autonomy is interdependence, developed through collaboration and which results in heightened awareness. Precisely, this concept lies at the core of technology applications, which facilitate interaction and collaboration at a distance. With a growing number of online ESP situations, more attention needs to be paid to virtual classrooms and the development of learner autonomy through collaboration.\ud
In the context of a distance EAP course, this chapter examines how students carry out a collaborative language awareness task, considering that peer interaction can be an appropriate setting to develop language awareness, whether in face-to-face or online situations. Based on the framework of 'community of inquiry' (Garrison et al. 2000), this study looks at how group members interact through forum posts and wiki edits, showing how students initiate, manage and carry out the task, together with the social, cognitive, and meta-cognitive processes that are generated. Given the nature of the task, creating a language learning activity, special attention is paid to students’ focus on and discussion of topics related to language and learning. From these observations we can derive implications for online language teaching and materials design.Peer ReviewedPreprin
Improved static symmetry breaking for SAT

An effective SAT preprocessing technique is the construction of symmetry breaking formulas: auxiliary clauses that guide a SAT solver away from needless exploration of symmetric subproblems. However, during the past decade, state-of-the-art SAT solvers rarely incorporated symmetry breaking. This suggests that the reduction of the search space does not outweigh the overhead incurred by detecting symmetry and constructing symmetry breaking formulas. We investigate three methods to construct more effective symmetry breaking formulas. The first method simply improves the encoding of symmetry breaking formulas. The second detects special symmetry subgroups, for which complete symmetry breaking formulas exist. The third infers binary symmetry breaking clauses for a symmetry group as a whole rather than longer clauses for individual symmetries. We implement these methods in a symmetry breaking preprocessor, and verify their effectiveness on both hand-picked problems as well as the 2014 SAT competition benchmark set. Our experiments indicate that our symmetry breaking preprocessor improves the current state-of-the-art in static symmetry breaking for SAT and has a sufficiently low overhead to improve the performance of modern SAT solvers on hard combinatorial instances.status: publishe
Trade-offs between time and memory in a tighter model of CDCL SAT solvers

"The final publication is available at http://link.springer.com/chapter/10.1007/978-3-319-40970-2_11A long line of research has studied the power of conflict- driven clause learning (CDCL) and how it compares to the resolution proof system in which it searches for proofs. It has been shown that CDCL can polynomially simulate resolution even with an adversarially chosen learning scheme as long as it is asserting. However, the simulation only works under the assumption that no learned clauses are ever forgot- ten, and the polynomial blow-up is significant. Moreover, the simulation requires very frequent restarts, whereas the power of CDCL with less frequent or entirely without restarts remains poorly understood. With a view towards obtaining results with tighter relations between CDCL and resolution, we introduce a more fine-grained model of CDCL that cap- tures not only time but also memory usage and number of restarts. We show how previously established strong size-space trade-offs for resolution can be transformed into equally strong trade-offs between time and memory usage for CDCL, where the upper bounds hold for CDCL with- out any restarts using the standard 1UIP clause learning scheme, and the (in some cases tightly matching) lower bounds hold for arbitrarily frequent restarts and arbitrary clause learning schemes.Peer ReviewedPostprint (author's final draft
Solving and Verifying the boolean Pythagorean Triples problem via
  Cube-and-Conquer

The boolean Pythagorean Triples problem has been a longstanding open problem
in Ramsey Theory: Can the set N = $\{1, 2, ...\}$ of natural numbers be divided
into two parts, such that no part contains a triple $(a,b,c)$ with $a^2 + b^2 =
c^2$ ? A prize for the solution was offered by Ronald Graham over two decades
ago.
  We solve this problem, proving in fact the impossibility, by using the
Cube-and-Conquer paradigm, a hybrid SAT method for hard problems, employing
both look-ahead and CDCL solvers. An important role is played by dedicated
look-ahead heuristics, which indeed allowed to solve the problem on a cluster
with 800 cores in about 2 days.
  Due to the general interest in this mathematical problem, our result requires
a formal proof. Exploiting recent progress in unsatisfiability proofs of SAT
solvers, we produced and verified a proof in the DRAT format, which is almost
200 terabytes in size. From this we extracted and made available a compressed
certificate of 68 gigabytes, that allows anyone to reconstruct the DRAT proof
for checking
Speeding up the constraint-based method in difference logic

"The final publication is available at http://link.springer.com/chapter/10.1007%2F978-3-319-40970-2_18"Over the years the constraint-based method has been successfully applied to a wide range of problems in program analysis, from invariant generation to termination and non-termination proving. Quite often the semantics of the program under study as well as the properties to be generated belong to difference logic, i.e., the fragment of linear arithmetic where atoms are inequalities of the form u v = k. However, so far constraint-based techniques have not exploited this fact: in general, Farkas’ Lemma is used to produce the constraints over template unknowns, which leads to non-linear SMT problems. Based on classical results of graph theory, in this paper we propose new encodings for generating these constraints when program semantics and templates belong to difference logic. Thanks to this approach, instead of a heavyweight non-linear arithmetic solver, a much cheaper SMT solver for difference logic or linear integer arithmetic can be employed for solving the resulting constraints. We present encouraging experimental results that show the high impact of the proposed techniques on the performance of the VeryMax verification systemPeer ReviewedPostprint (author's final draft
Q-Resolution with Generalized Axioms

Q-resolution is a proof system for quantified Boolean formulas (QBFs) in
prenex conjunctive normal form (PCNF) which underlies search-based QBF solvers
with clause and cube learning (QCDCL). With the aim to derive and learn
stronger clauses and cubes earlier in the search, we generalize the axioms of
the Q-resolution calculus resulting in an exponentially more powerful proof
system. The generalized axioms introduce an interface of Q-resolution to any
other QBF proof system allowing for the direct combination of orthogonal
solving techniques. We implemented a variant of the Q-resolution calculus with
generalized axioms in the QBF solver DepQBF. As two case studies, we apply
integrated SAT solving and resource-bounded QBF preprocessing during the search
to heuristically detect potential axiom applications. Experiments with
application benchmarks indicate a substantial performance improvement.Comment: (minor fixes) camera-ready version + appendix; to appear in the
  proceedings of SAT 2016, LNCS, Springe
HordeQBF: A Modular and Massively Parallel QBF Solver

The recently developed massively parallel satisfiability (SAT) solver
HordeSAT was designed in a modular way to allow the integration of any
sequential CDCL-based SAT solver in its core. We integrated the QCDCL-based
quantified Boolean formula (QBF) solver DepQBF in HordeSAT to obtain a
massively parallel QBF solver---HordeQBF. In this paper we describe the details
of this integration and report on results of the experimental evaluation of
HordeQBF's performance. HordeQBF achieves superlinear average and median
speedup on the hard application instances of the 2014 QBF Gallery.Comment: camera-ready version, 6-page tool paper, to appear in the proceedings
  of SAT 2016, LNCS, Springe
Utilising the Cross Industry Standard Process for Data Mining to reduce uncertainty in the Measurement and Verification of energy savings

This paper investigates the application of Data Mining (DM) to predict baseline energy consumption for the improvement of energy savings estimation accuracy in Measurement and Verification (M&V). M&V is a requirement of a certified energy management system (EnMS). A critical stage of the M&V process is the normalisation of data post Energy Conservation Measure (ECM) to pre-ECM conditions. Traditional M&V approaches utilise simplistic modelling techniques, which dilute the power of the available data. DM enables the true power of the available energy data to be harnessed with complex modelling techniques. The methodology proposed incorporates DM into the M&V process to improve prediction accuracy. The application of multi-variate regression and artificial neural networks to predict compressed air energy consumption in a manufacturing facility is presented. Predictions made using DM were consistently more accurate than those found using traditional approaches when the training period was greater than two months
Knowledge Engineering Method Based on Consensual Knowledge and Trust Computation: The MUSCKA System

We propose a method for building a knowledge base addressing  specific issues such as covering an end-users' need and reuse  non-ontological sources such as thesauri or classifications. After designing  an ontology module representing the knowledge needed by end-users,  we enrich and populate it automatically with knowledge extracted from  existing sources. The originality of our proposition is to propose ontological  object candidates from existing sources according to both their  relatedness to the ontological module and to computed measures of trust.  This paper describes the trust measures we propose which are obtained  by analysing the consensus found in existing sources. Thus we consider  that knowledge are more reliable if it has been extracted from several  sources. The use of these measures has been evaluated on a real case  study with experts from the agriculture domai
Dealing with Incompatibilities During a Knowledge Bases Fusion Process

More and more data sets are published on the linked open data. Reusing these data is a challenging task as for a given domain, several data sets built for specific usage may exist. In this article we present an approach for existing knowledge bases fusion by taking into account incompatibilities that may appear in their representations. Equivalence mappings established by an alignment tool are considered in order to generate a subset of compatible candidates. The approach has been evaluated by domain experts on datasets dealing with agriculture
Dense orthogonal initialization for deterministic PSO: ORTHOinit+

This paper describes a novel initialization for Deterministic Particle Swarm Optimization (DPSO), based on choosing specific dense initial positions and velocities for particles. This choice tends to induce orthogonality of particles’ trajectories, in the early iterations, in order to better explore the search space. Our proposal represents an improvement, by the same authors, of the theoretical analysis on a previously proposed PSO reformulation, namely the initialization ORTHOinit. A preliminary experience on constrained Portfolio Selection problems confirms our expectations
Operations on weakly recognizing morphisms

This is a pre-copyedited version of a contribution published in Campeanu, C., Manea, F. Shallit, J. (eds.) Descriptional Complexity of Formal Systems,\ud
18th IFIP WG 1.2 International Conference, DCFS 2016 published by Springer. The definitive authenticated version is available online via https://doi.org/10.1007/978-3-319-41114-9_10© IFIP International Federation for Information Processing 2016. Weakly recognizing morphisms from free semigroups onto finite semigroups are a classical way for defining the class of ω-regular languages, i.e., a set of infinite words is weakly recognizable by such a morphism if and only if it is accepted by some Büchi automaton. We consider the descriptional complexity of various constructions for weakly recognizing morphisms. This includes the conversion from and to Büchi automata, the conversion into strongly recognizing morphisms, and complementation. For some problems, we are able to give more precise bounds in the case of binary alphabets or simple semigroups
Minimal and Reduced Reversible Automata

A condition characterizing the class of regular languages which have several
nonisomorphic minimal reversible automata is presented. The condition concerns
the structure of the minimum automaton accepting the language under
consideration. It is also observed that there exist reduced reversible automata
which are not minimal, in the sense that all the automata obtained by merging
some of their equivalent states are irreversible. Furthermore, a sufficient
condition for the existence of infinitely many reduced reversible automata
accepting a same language is given. It is also proved that, when the language
is accepted by a unique minimal reversible automaton (that does not necessarily
coincide with the minimum deterministic automaton), then no other reduced
reversible automata accepting it can exist.Comment: Preliminary version presented at DCFS 2016 --- Descriptional
  Complexity of Formal Systems, Bucharest, Romania, Jul 5-8, 201
On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection

Extended regular expressions (with complement and intersection) are used in many applications due to their succinctness. In particular, regular expressions extended with intersection only (also called semi-extended) can already be exponentially smaller than standard regular expressions or equivalent nondeterministic finite automata (NFA). For practical purposes it is important to study the average behaviour of conversions between these models. In this paper, we focus on the conversion of regular expressions with intersection to nondeterministic finite automata, using partial derivatives and the notion of support. First, we give a tight upper bound of 2O(n) for the worst-case number of states of the resulting partial derivative automaton, where n is the size of the expression. Using the framework of analytic combinatorics, we then establish an upper bound of (1.056 + o(1))n for its asymptotic average-state complexity, which is significantly smaller than the one for the worst case. © IFIP International Federation for Information Processing 2016