pinecone/core-2020-05-10-deduplication huggingface dataset:
Action Recognition with a Bio--Inspired Feedforward Motion Processing Model: The Richness of Center-Surround Interactions

International audienceHere we show that reproducing the functional properties of MT cells with various center--surround interactions enriches motion representation and improves the action recognition performance. To do so, we propose a simplified bio--inspired model of the motion pathway in primates: It is a feedforward model restricted to V1-MT cortical layers, cortical cells cover the visual space with a foveated structure, and more importantly, we reproduce some of the richness of center-surround interactions of MT cells. Interestingly, as observed in neurophysiology, our MT cells not only behave like simple velocity detectors, but also respond to several kinds of motion contrasts. Results show that this diversity of motion representation at the MT level is a major advantage for an action recognition task. Defining motion maps as our feature vectors, we used a standard classification method on the Weizmann database: We obtained an average recognition rate of 98.9%, which is superior to the recent results by Jhuang et al. (2007). These promising results encourage us to further develop bio--inspired models incorporating other brain mechanisms and cortical layers in order to deal with more complex videos
A Multi-scale Vector Spline Method for Estimating the Fluids Motion on Satellite Images

International audienceSatellite image sequences visualize important patterns of the atmospheric and oceanographic circulation. Assessing motion from these data thus has a strong potential for improving the performances of the forecast models. Representing a vector field by a vector spline has been proven efficient for fluid motion assessment: the vector spline formulation makes it possible to initially select the locations where the conservation equation has to be taken into account; it efficiently implements the 2nd order div-curl regularity, advocated for turbulent fluids. The scientific contribution of this article is to formulate vector splines in a multiscale scheme, with the double objective of assessing motion even in the case of large displacements and capturing the spectrum of spatial scales associated to turbulent flows. The proposed method only requires the inversion of a band matrix, which is performed by an efficient numerical scheme making the method tractable for large satellite image sequences
A Property-Driven Approach to Formal Verification of Process Models

Enterprise Information Systems, 9th International Conference, ICEIS 2007, Funchal, Madeira, June 12-16, 2007, Revised Selected PapersInternational audienceMore and more, models, through Domain Specific Languages (DSL), tend to be the solution to define complex systems. Expressing properties specific to these metamodels, and checking them, appear as an urgent need. Until now, the only complete industrial solutions that are available consider structural properties such as the ones that could be expressed in OCL. There are although some attempts on behavioural properties for DSL. This paper addresses a method to specify and then check temporal properties over models. The case study is SimplePDL, a process metamodel. We propose a way to use a temporal extension of OCL, TOCL, to express properties. We specify a models transformation to Petri Nets and LTL formulae for both the process model and its associated temporal properties. We check these properties using a model checker and enrich the model with the analysis results. This work is a first step towards a generic framework to specify and effectively check temporal properties over arbitrary models
Solving airline operations problems using specialized agents in a distributed multi-agent system

An airline schedule very rarely operates as planned. Problems related with aircrafts, crew members and passengers are common and the actions towards the solution of these problems are usually known as operations recovery. The Airline Operations Control Center (AOCC) tries to solve these problems with the minimum cost and satisfying all the required rules. In this paper we present the implementation of a Distributed Multi-Agent System (MAS) representing the existing roles in an AOCC, This MAS deals with several operational bases and for each type of operation problems it has several specialized software agents that implement different algorithms (heuristic, AI, OR, etc.), competing to find the best solution for each problem. We present a real case study taken from an AOCC where a crew recovery problem is solved. Computational results using a real airline schedule are presented, including a comparison with a solution for the same problem found by the human operators in the AOCC. We show that, even in simple problems and when comparing with solutions found by human operators, it is possible to find valid solutions, in less time and with a smaller cost
On Revenue-Optimal Dynamic Auctions for Bidders with Interdependent Values

In a dynamic market, being able to update one’s value based on information available to other bidders currently in the market can be critical to having profitable transactions. This is nicely captured by the model of interdependent values (IDV): a bidder’s value can explicitly depend on the private information of other bidders. In this paper we present preliminary results about the revenue properties of dynamic auctions for IDV bidders. We adopt a computational approach to design single-item revenue-optimal dynamic auctions with known arrivals and departures but (private) signals that arrive online. In leveraging a characterization of truthful auctions, we present a mixed-integer programming formulation of the design problem. Although a discretization is imposed on bidder signals the solution is a mechanism applicable to continuous signals. The formulation size grows exponentially in the dependence of bidders’ values on other bidders’ signals. We highlight general properties of revenue-optimal dynamic auctions in a simple parametrized example and study the sensitivity of prices and revenue to model parameters.Engineering and Applied Science
Taming Existence in RDF Querying

We introduce the recursive, rule-based RDF query language
RDFLog. RDFLog extends previous RDF query languages by arbitrary
quantifier alternation: blank nodes may occur in the scope of all, some,
or none of the universal variables of a rule. In addition RDFLog is aware
of important RDF features such as the distinction between blank nodes,
literals and URIs or the RDFS vocabulary. The semantics of RDFLog is
closed (every answer is an RDF graph), but lifts RDF’s restrictions on
literal and blank node occurrences for intermediary data. We show how
to define a sound and complete operational semantics that can be implemented
using existing logic programming techniques. Using RDFLog
we classify previous approaches to RDF querying along their support for
blank node construction and show equivalence between languages with
full quantifier alternation and languages with only ∀∃ rules.
Simulation Subsumption or Déjà vu on the Web

Simulation unification is a special kind of unification adapted to retrieving semi-structured data on the Web. This article introduces simulation subsumption, or containment, that is, query subsumption under simulation unification. Simulation subsumption is crucial in general for query optimization, in particular for optimizing pattern-based search engines, and for the termination of recursive rule-based web languages such as the XML and RDF query language Xcerpt. This paper first motivates and formalizes simulation subsumption. Then, it establishes decidability of simulation subsumption for advanced query patterns featuring descendant constructs, regular expressions, negative subterms (or subterm exclusions), and multiple variable occurrences. Finally, we show that subsumption between two query terms can be decided in O(n!n) where n is the sum of the sizes of both query terms.
Programmability of chemical reaction networks

Motivated by the intriguing complexity of biochemical circuitry within individual cells we study Stochastic Chemical Reaction Networks (SCRNs), a formal model that considers a set of chemical reactions acting on a finite number of molecules in a well-stirred solution according to standard chemical kinetics equations. SCRNs have been widely used for describing naturally occurring (bio)chemical systems, and with the advent of synthetic biology they become a promising language for the design of artificial biochemical circuits. Our interest here is the computational power of SCRNs and how they relate to more conventional models of computation. We survey known connections and give new connections between SCRNs and Boolean Logic Circuits, Vector Addition Systems, Petri Nets, Gate Implementability, Primitive Recursive Functions, Register Machines, Fractran, and Turing Machines. A theme to these investigations is the thin line between decidable and undecidable questions about SCRN behavior
AKARA: A flexible clustering protocol for demanding transactional workloads

Shared-nothing clusters are a well known and cost-effective approach to database server scalability, in particular, with highly intensive read-only workloads typical of many 3-tier web-based applications. The common reliance on a centralized component and a simplistic propagation strategy employed by mainstream solutions however conduct to poor scalability with traditional on-line transaction processing (OLTP), where the update ratio is high. Such approaches also pose an additional obstacle to high availability while introducing a single point of failure.
More recently, database replication protocols based on group communication have been shown to overcome such limitations, expanding the applicability of shared-nothing clusters to more demanding transactional workloads. These take simultaneous advantage of total order multicast and transactional semantics to improve on mainstream solutions. However, none has already been widely deployed in a general purpose database management system.
In this paper, we argue that a major hurdle for their acceptance is that these proposals have disappointing performance with specific subsets of real-world workloads. Such limitations are deep-rooted and working around them requires in-depth understanding of protocols and changes to applications. We address this issue with a novel protocol that combines multiple transaction execution mechanisms and replication techniques and then show how it avoids the identified pitfalls. Experimental results are obtained with a workload based on the industry standard TPC-C benchmark
Q-Strategy: A Bidding Strategy for Market-Based Allocation of Grid Services

The application of autonomous agents by the provisioning and usage of computational services is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic service provisioning and usage of Grid services, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems.\ud
The contributions of the paper are threefold. First, we present a bidding agent framework for implementing artificial bidding agents, supporting consumers and providers in technical and economic preference elicitation as well as automated bid generation by the requesting and provisioning of Grid services. Secondly, we introduce a novel consumer-side bidding strategy, which enables a goal-oriented and strategic behavior by the generation and submission of consumer service requests and selection of provider offers. Thirdly, we evaluate and compare the Q-strategy, implemented within the presented framework, against the Truth-Telling bidding strategy in three mechanisms – a centralized CDA, a decentralized on-line machine scheduling and a FIFO-scheduling mechanisms
Information hiding through variance of the parametric orientation underlying a B-rep face

Watermarking technologies have been proposed for many different,types of digital media. However, to this date, no viable watermarking techniques have yet emerged for the high value B-rep (i.e. Boundary Representation) models used in 3D mechanical CAD systems. In this paper, the authors propose a new approach (PO-Watermarking) that subtly changes a model's geometric representation to incorporate a 'transparent' signature. This scheme enables software applications to create fragile, or robust watermarks without changing the size of the file, or shape of the CAD model. Also discussed is the amount of information the proposed method could transparently embed into a B-rep model. The results presented demonstrate the embedding and retrieval of text strings and investigate the robustness of the approach after a variety of transformation and modifications have been carried out on the data
Using Concrete Syntax in Graph-based Model Transformations

The emergence of large and complex software systems increases the interest in model-driven engineering, as a way to lower the cost of development and maintenance of software. Models allow us to hide irrelevant details, provide different model viewpoints, and isolate and modularize models of cross-cutting concerns of a system. The emerging technologies for aspectoriented modeling and weaving provide a systematic way to handle cross-cutting concerns at the modeling level. The success of model-driven engineering relies heavily on model transformations. This thesis describes how aspect-oriented modeling and many typical model transformations can be defined as aspects/rules that: (1) use the concrete syntax of the involved modeling languages, and (2) use graph transformation principles as its foundation. The thesis presents two main results. The first main result is an aspect language for UML 2 sequence diagrams. The language takes advantage of a formal model for sequence diagrams, which makes the matching and weaving process semantics-based. For this language we provide a confluence theory. The second main result is an approach to define many typical model transformations as graph transformations, where the transformation designer uses the concrete syntax of the involved modeling languages. Some typical model transformation examples are illustrated in this thesis, i.e. transformation from feature models to BPMN, UML activity diagram aspects, UML activity diagram refactoring, UML state machine refactoring, transformation from sequence diagrams to state machines, and transformations involving Petri nets. A collection operator has been introduced as a means to match and transform collections of similar subgraphs in graph transformations, using either concrete or abstract syntax. This allows for improved usability in transformations that would otherwise be complex or impractical to specify
Real-time software for mobile robot simulation and experimentation in cooperative environments

Trabajo presentado al 1st SIMPAR celebrado en Venecia del 3 al 6 de noviembre de 2008.This paper presents the software being developed at IRI (Institut de Robotica i Informatica Industrial) for mobile robot autonomous navigation in the context of the European project URUS (Ubiquitous Robots in Urban Settings). In order that a deployed sensor network and robots operating in the environment cooperate in terms of information sharing, main requirements are real-time performance and the integration of information coming from remote machines not onboard the robot. Moreover, the project involves a group of eleven industrial and academic partners, therefore software integration issues are critical. The proposed software framework is based on the YARP middleware and has been tested in real and simulated experiments.This work was supported by projects: 'Ubiquitous networking robotics in urban settings' (E-00938), 'CONSOLIDER-INGENIO 2010 Multimodal interaction in pattern recognition and computer vision' (V-00069), 'Robotica ubicua para entornos urbanos' (J-01225).  Partially supported by Consolider Ingenio 2010, project CSD2007-00018,\ud
CICYT project DPI2007-61452, and IST-045062 of the European Community Union.Peer Reviewe
Finite Elements for a Beam System With Nonlinear Contact Under Periodic
  Excitation

Solar arrays are structures which are connected to satellites; during launch,
they are in a folded position and submitted to high vibrations. In order to
save mass, the flexibility of the panels is not negligible and they may strike
each other; this may damage the structure. To prevent this, rubber snubbers are
mounted at well chosen points of the structure; a prestress is applied to the
snubber; but it is quite difficult to check the amount of prestress and the
snubber may act only on one side; they will be modeled as one sided springs
(see figure 2). In this article, some analysis for responses (displacements) in
both time and frequency domains for a clamped-clamped Euler-Bernoulli beam
model with a spring are presented. This spring can be unilateral or bilateral
fixed at a point. The mounting (beam +spring) is fixed on a rigid support which
has a sinusoidal motion of constant frequency. The system is also studied in
the frequency domain by sweeping frequencies between two fixed values, in order
to save the maximum of displacements corresponding to each frequency. Numerical
results are compared with exact solutions in particular cases which already
exist in the literature. On the other hand, a numerical and theoretical
investigation of nonlinear normal mode (NNM) can be a new method to describe
nonlinear behaviors, this work is in progress
The causal differential scattering approach to calculating the effective properties of random composite materials with a particle size distribution

An implementation of the Causal Differential Method (CDM) for modelling the effective properties of a random two-phase composite material is presented. Such materials are commonly used as ultrasonic transducer matching layersor backing layers. The method is extended to incorporate a particle size distribution in the inclusion phase. Numerical issues regarding the implementation and convergence of the method are discussed. It is found that, for a given frequency of excitation, the calculated velocity for the composite has a distribution whose variance increases as the volume fraction of inclusions increases. The model predictions would suggest that to reliably and repeatedly manufacture these composites, with a desired mechanical impedance, a low volume fraction of inclusions should be used
Evaluation of a cooperative ARQ protocol for delay-tolerant vehicular networks

This paper evaluates a Cooperative ARQ protocol to be used in delay-tolerant vehicular networks. The scenario consists in cars downloading information from Access Points along a road. The key difference between proposed Cooperative ARQ protocols is when the cooperation takes place. Simply C-ARQ cooperation occurs in a packet-by-packet basis. In this proposal, that we call DC-ARQ (Delayed Cooperative ARQ), the cooperation is delayed until cars are out of the coverage area of the Access Point. The scheme has been evaluated through simulations. A comparison of DC-ARQ with a\ud
baseline case in which no cooperation is used has been performed under different vehicle densities scenarios.Peer ReviewedPostprint (author’s final draft
Using Cost Distributions to Guide Weight Decay in Local Search for SAT

Although clause weighting local search algorithms have produced some of the best results on a range of challenging satisfiability (SAT) benchmarks, this performance is dependent on the careful hand-tuning of sensitive parameters. When such hand-tuning is not possible, clause weighting algorithms are generally outperformed by self-tuning WalkSAT-based algorithms such as AdaptNovelty+ and AdaptG2WSAT. In this paper we investigate tuning the weight decay parameter of two clause weighting algorithms using the statistical properties of cost distributions that are dynamically accumulated as the search progresses. This method selects a parameter setting both according to the speed of descent in the cost space and according to the shape of the accumulated cost distribution, where we take the shape to be a predictor of future performance. In a wide ranging empirical study we show that this automated approach to parameter tuning can outperform the default settings for two state-of-the-art algorithms that employ clause weighting (PAWS and gNovelty+). We also show that these self-tuning algorithms are competitive with three of the best-known self-tuning SAT local search techniques: RSAPS, AdaptNovelty+ and AdaptG2WSAT.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Learning from the past with experiment databases

Thousands of Machine Learning research papers contain experimental comparisons that usually have been conducted with a single focus of interest, and detailed results are usually lost after publication. Once past experiments are collected in experiment databases they allow for additional and possibly much broader investigation. In this paper, we show how to use such a repository to answer various interesting research questions about learning algorithms and to verify a number of recent studies. Alongside performing elaborate comparisons and rankings of algorithms, we also investigate the effects of algorithm parameters and data properties, and study the learning curves and bias-variance proﬁles of algorithms to gain deeper insights into their behavior.status: publishe
Wireless capsule endoscopic frame classification scheme based on higher order statistics of multi-scale texture  descriptors

The gastrointestinal (GI) tract is a long tube, prone to all kind of lesions. The traditional endoscopic methods do not reach the entire GI tract. Wireless capsule endoscopy is a diagnostic procedure that allows the visualization of the whole GI tract, acquiring video frames, at a rate of two frames per second, while travels through the GI tract, propelled by peristalsis. These frames possess rich information about the condition of the stomach and intestine mucosa, expressed by color and texture in these images. These vital characteristics of each frame can be extracted by color texture analysis. Since texture information is present as middle and high frequency content in the original image, two new images are synthesized from the discrete wavelet coefficients at the lowest and middle scale of a two level Discrete Wavelet Transform of the original frame. These new synthesized images contain essential texture information, at different scales, which can be extracted from statistical descriptors of the coocurrence matrices, which are second-order representations of the synthesized images that encode color and spatial relationships within the pixels of these new images. Since the human perception of texture is complex, a multi-scale and multicolor process based in the analysis of the spatial color variations relationships, is proposed, as classification features. The multicolor texture information is modeled by the third order moments of the texture descriptors sampled at the different color channels. HSV color space is more related to the perceptive human characteristics, therefore it was used in the ambit of this paper. The multi-scale texture information is modeled by covariance of the texture descriptors within the same color channel of the two synthesized images, which contain texture information at different scales. The features are used in a classification scheme using a multilayer perceptron neural network. The proposed method has been applied in real data taken from several capsule endoscopic exams and reaches 94.6% of sensitivity and 93.7% specificity. These results support the feasibility of the proposed algorithm.Center Algoritm