pinecone/core-2020-05-10-deduplication huggingface dataset:
On the complexity of Submap Isomorphism

International audienceGeneralized maps describe the subdivision of objects in cells, and incidence and adjacency relations between cells, and they are widely used to model 2D and 3D images. Recently, we have defined submap isomorphism, which involves deciding if a copy of a pattern map may be found in a target map, and we have described a polynomial time algorithm for solving this problem when the pattern map is connected. In this paper, we show that submap isomorphism becomes NP-complete when the pattern map is not connected, by reducing the NP-complete problem Planar-4 3-SAT to it
Traffic engineering approaches in P2P environments

Nowadays, P2P applications proliferate in the Internet with distinct utilization contexts, being also an attractive model for the deployment of advanced Internet services. However, there are several undesirable effects that are caused by such applications, raising coexistence problems with Internet Service Providers (ISPs). In this context, using as case study BitTorrent like applications, this work explores a collaborative framework allowing that advanced efforts could be carried on between P2P applications and network level entities. In order to illustrate such framework, several Traffic Engineering (TE) mechanisms are devised in order to align some P2P dynamics with particular objectives pursued by network administrators. The simulation results show that both the proposed framework and corresponding illustrative mechanisms are viable and can effectively foster future research efforts within this field
Reconfiguration mechanisms for service coordination

Serie : Lecture notes in computer science, ISSN 0302-9743, vol. 7843Models for exogenous coordination provide powerful glue- code, in the form of software connectors, to express interaction protocols between services in distributed applications. Connector reconfiguration mechanisms play, in this setting, a major role to deal with change and adaptation of interaction protocols. This paper introduces a model for connector reconfiguration, based on a collection of primitives as well as a language to specify connectors and their reconfigurations.Fundação para a Ciência e a Tecnologia (FCT
Approximation algorithms for disjoint st-paths with minimum activation cost

In network activation problems we are given a directed or undirected graph G = (V,E) with a family {f (x, x) : (u,v) ∈ E} of monotone non-decreasing activation functions from D to {0,1}, where D is a constant-size domain. The goal is to find activation values x for all v ∈ V of minimum total cost Σ x such that the activated set of edges satisfies some connectivity requirements. Network activation problems generalize several problems studied in the network literature such as power optimization problems. We devise an approximation algorithm for the fundamental problem of finding the Minimum Activation Cost Pair of Node-Disjoint st-Paths (MA2NDP). The algorithm achieves approximation ratio 1.5 for both directed and undirected graphs. We show that a ρ-approximation algorithm for MA2NDP with fixed activation values for s and t yields a ρ-approximation algorithm for the Minimum Activation Cost Pair of Edge-Disjoint st-Paths (MA2EDP) problem. We also study the MA2NDP and MA2EDP problems for the special case |D| = 2.Peer-reviewedPost-print8th International Conference, CIAC 2013, Barcelona, Spain, May 22-24, 2013
List coloring in the absence of two subgraphs.

list assignment of a graph G = (V;E) is a function L\ud
that assigns a list L(u) of so-called admissible colors to each u 2 V .\ud
The List Coloring problem is that of testing whether a given graph\ud
G = (V;E) has a coloring c that respects a given list assignment L, i.e.,\ud
whether G has a mapping c : V ! f1; 2; : : :g such that (i) c(u) 6= c(v)\ud
whenever uv 2 E and (ii) c(u) 2 L(u) for all u 2 V . If a graph G has\ud
no induced subgraph isomorphic to some graph of a pair fH1;H2g, then\ud
G is called (H1;H2)-free. We completely characterize the complexity of\ud
List Coloring for (H1;H2)-free graphs
Turing machines can be efficiently simulated by the General Purpose
  Analog Computer

The Church-Turing thesis states that any sufficiently powerful computational
model which captures the notion of algorithm is computationally equivalent to
the Turing machine. This equivalence usually holds both at a computability
level and at a computational complexity level modulo polynomial reductions.
However, the situation is less clear in what concerns models of computation
using real numbers, and no analog of the Church-Turing thesis exists for this
case. Recently it was shown that some models of computation with real numbers
were equivalent from a computability perspective. In particular it was shown
that Shannon's General Purpose Analog Computer (GPAC) is equivalent to
Computable Analysis. However, little is known about what happens at a
computational complexity level. In this paper we shed some light on the
connections between this two models, from a computational complexity level, by
showing that, modulo polynomial reductions, computations of Turing machines can
be simulated by GPACs, without the need of using more (space) resources than
those used in the original Turing computation, as long as we are talking about
bounded computations. In other words, computations done by the GPAC are as
space-efficient as computations done in the context of Computable Analysis
Efficient Estimation of Human Upper Body Pose in Static Depth Images

Automatic estimation of human pose has long been a goal of computer vision, to which a solution would have a wide range of applications. In this paper we formulate the pose estimation task within a regression and Hough voting framework to predict 2D joint locations from depth data captured by a consumer depth camera. In our approach the offset from each pixel to the location of each joint is predicted directly using random regression forests. The predictions are accumulated in Hough images which are treated as likelihood distributions where maxima correspond to joint location hypotheses. Our approach is evaluated on a publicly available dataset with good results. © Springer-Verlag Berlin Heidelberg 2013
Decoupling the Eye: A Key toward a Robust Hovering for Sighted Aerial Robots

International audienceInspired by natural visual systems where gaze stabilization is at a premium, we simulated an aerial robot with a decoupled eye to achieve more robust hovering above a ground target despite strong lateral and rotational disturbances. In this paper, two different robots are compared for the same disturbances and displacements. The first robot is equipped with a fixed eye featuring a large field-of-view (FOV) and the second robot is endowed with a decoupled eye featuring a small FOV (about ±5°). Even if this mechanical decoupling increases the mechanical complexity of the robot, this study demonstrates that disturbances are rejected faster and the computational complexity is clearly decreased. Thanks to bio-inspired visuo-motor reflexes, the decoupled eye robot is able to hold its gaze locked onto a distant target and to reject strong disturbances by profiting of the small inertia of the decoupled eye
A Frequency-Limited H2 Model Approximation Method with Application to a Medium-Scale Flexible Aircraft

In this paper, the problem of approximating a medium-scale MIMO LTI dynamical system over a bounded frequency range is addressed. A new method based on the SVD-Tangential model order reduction framework is proposed. Grounded on the frequency-limited gramians defined in [5], the contribution of this paper is to propose a frequency-limited iterative SVD-Tangential interpolation algorithm (FL-ISTIA) to achieve frequency-limited model approximation without involving weighting filters. The efficiency of the approach is addressed both on standard benchmark and on an industrial flexible aircraft model
Toward an Autonomous Lunar Landing Based on Low-Speed Optic Flow Sensors

International audienceFor the last few decades, growing interest has returned to the quite chal-lenging task of the autonomous lunar landing. Soft landing of payloads on the lu-nar surface requires the development of new means of ensuring safe descent with strong final conditions and aerospace-related constraints in terms of mass, cost and computational resources. In this paper, a two-phase approach is presented: first a biomimetic method inspired from the neuronal and sensory system of flying insects is presented as a solution to perform safe lunar landing. In order to design an au-topilot relying only on optic flow (OF) and inertial measurements, an estimation method based on a two-sensor setup is introduced: these sensors allow us to accu-rately estimate the orientation of the velocity vector which is mandatory to control the lander's pitch in a quasi-optimal way with respect to the fuel consumption. Sec-ondly a new low-speed Visual Motion Sensor (VMS) inspired by insects' visual systems performing local angular 1-D speed measurements ranging from 1.5 • /s to 25 • /s and weighing only 2.8 g is presented. It was tested under free-flying outdoor conditions over various fields onboard an 80 kg unmanned helicopter. These pre-liminary results show that the optic flow measured despite the complex disturbances encountered closely matched the ground-truth optic flow
Solving the Uncalibrated Photometric Stereo Problem using Total Variation

In this paper we propose a new method to solve the problem of uncalibrated photometric stereo, making very weak assumptions on the properties of the scene to be reconstructed. Our goal is to solve the generalized bas-relief ambiguity (GBR) by performing a total variation regularization of both the estimated normal field and albedo. Unlike most of the previous attempts to solve this ambiguity, our approach does not rely on any prior information about the shape or the albedo, apart from its piecewise smoothness. We test our method on real images and obtain results comparable to the state-of-the-art algorithms
Scale Space Operators on Hierarchies of Segmentations

International audienceA hierarchy of segmentations(partitions) is a multiscale set representation of the image. This paper introduces a new set of scale space operators or transformations on the space of hierarchies of partitions. An ordering of hierarchies is proposed which is endowed by an !-ordering based on a global energy over the classes of the hierarchy. A class of Matheron semigroups are shown to exists in this ordering of hierarchies. A second contribution is the saliency transformation which fuses a saliency function corresponding to a hierarchy, with an external function, rendering a new or transformed saliency function. The results are demonstrated on the Berkeley dataset
Blind Deblurring Using a Simplified Sharpness Index

It was shown recently that the phase of the Fourier Transform of an image could lead to interesting no-reference image quality measures. The Global Phase Coherence, and its recent Gaussian variant called Sharpness Index, rate the sharpness of an image in contrast not only with blur, but also noise, ringing, etc. In this work, we introduce a new variant of these indices, that can be computed with one Fourier Transform only, hence four times quicker than the Sharpness Index. We use this new index S to build an image restoration algorithm that, in a stochastic framework, selects a radial-unimodal deconvolution kernel for which the S-value of the restored image is optimal. Experiments are discussed, and comparison is made with a radial oracle deconvolution filter and the recent blind deconvolution algorithm of Levin et al
A simulation study regarding different aircraft boarding strategies

The airline industry is constantly subject to the search of new\ud
methods in order to increase efficiency, profitability, and customer satisfaction.\ud
Since airlines only generate revenue when their airplanes are on the air, the time\ud
they spend at the airports should be the shortest possible. Hence, the airplane\ud
turnaround time becomes a process which airlines pay special attention on. The\ud
boarding process has a very important role, since it is one of the significant\ud
elements of the turnaround time, and a slow boarding process might lead to\ud
many kinds of problems to the airline, from financial issues to customer\ud
complaints. This paper analyzes the major interferences among the passengers\ud
that cause delays in boarding times, and after comparing the different aircraft\ud
boarding strategies, it proposes the most efficient strategy.Peer ReviewedPostprint (published version
Combining a co-occurrence-based and a semantic measure for entity linking

One key feature of the Semantic Web lies in the ability to link related Web resources. However, while relations within particular datasets are often well-defined, links between disparate datasets and corpora of Web resources are rare. The increasingly widespread use of cross-domain reference datasets, such as Freebase and DBpedia for annotating and enriching datasets as well as documents, opens up opportunities to exploit their inherent semantic relationships to align disparate Web resources. In this paper, we present a combined approach to uncover relationships between disparate entities which exploits (a) graph analysis of reference datasets together with (b) entity co-occurrence on the Web with the help of search engines. In (a), we introduce a novel approach adopted and applied from social network theory to measure the connectivity between given entities in reference datasets. The connectivity measures are used to identify connected Web resources. Finally, we present a thorough evaluation of our approach using a publicly available dataset and introduce a comparison with established measures in the field. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38288-8_37
Constructing a focused taxonomy from a document collection

We describe a new method for constructing custom taxonomies from document collections. It involves identifying relevant concepts and entities in text; linking them to knowledge sources like Wikipedia, DBpedia, Freebase, and any supplied taxonomies from related domains; disambiguating conflicting concept mappings; and selecting semantic relations that best group them hierarchically. An RDF model supports interoperability of these steps, and also provides a flexible way of including existing NLP tools and further knowledge sources. From 2000 news articles we construct a custom taxonomy with 10,000 concepts and 12,700 relations, similar in structure to manually created counterparts. Evaluation by 15 human judges shows the precision to be 89% and 90% for concepts and relations respectively; recall was 75% with respect to a manually generated taxonomy for the same domain
Ground truth energies for hierarchies of segmentations

International audienceIn evaluating a hierarchy of segmentations H of an image by ground truth G, which can be partitions of the space or sets, we look for the optimal partition in H that " fits" G best. Two energies on partial partitions express the proximity from H to G, and G to H. They derive from a local version of the Hausdor distance. Then the problem amounts to nding the cut of the hierarchy which minimizes the said energy. This cuts provide global similarity measures of precision and recall. This allows to contrast two input hierarchies with respect to the G, and also to describe how to compose energies from di erent ground truths. Results are demonstrated over the Berkeley database
Attribute Controlled Reconstruction and Adaptive Mathematical Morphology

ISBN : 978-3-642-38293-2International audienceIn this paper we present a reconstruction method controlled by the evolution of attributes. The process begins from a marker, propagated over increasing quasi-flat zones. The evolution of several increasing and non-increasing attributes is studied in order to select the appropriate region. Additionally, the combination of attributes can be used in a straightforward way. To demonstrate the performance of our method, three applications are presented. Firstly, our method successfully segments connected objects in range images. Secondly, input-adaptive structuring elements (SE) are defined computing the controlled propagation for each pixel on a pilot image. Finally, input-adaptive SE are used to assess shape features on the image. Our approach is multi-scale and auto-dual. Compared with other methods, it is based on a given attribute but does not require a size parameter in order to determine appropriate regions. It is useful to extract objects of a given shape. Additionally, our reconstruction is a connected operator since quasi-flat zones do not create new contours on the image
On Nonlocal Mathematical Morphology

ISBN : 978-3-642-38293-2International audienceIn this paper, nonlocal mathematical morphology operators are introduced as a natural extension of nonlocal-means in the max-plus algebra. Firstly, we show that nonlocal morphology is a particular case of adaptive morphology. Secondly, we present the necessary properties to have algebraic properties on the associated pair of transformations. Finally, we recommend a sparse version to introduce an efficient algorithm that computes these operators in reasonable computational time
Inf-structuring functions and self-dual marked flattenings in bi-Heyting algebra

International audienceThis paper introduces a generalization of self-dual marked flattenings defined in the lattice of mappings. This definition provides a way to associate a self-dual operator to every mapping that decomposes an element into sub-elements (i.e. gives a cover). Contrary to classical flattenings whose definition relies on the complemented structure of the powerset lattices, our approach uses the pseudo relative complement and supplement of the bi-Heyting algebra and a new notion of \textit{inf-structuring functions} that provides a very general way to structure the space. We show that using an inf-structuring function based on connections allows to recover the original definition of marked flattenings and we provide, as an example, a simple inf-structuring function whose derived self-dual operator better preserves contrasts and does not introduce new pixel values
Efficient 1D and 2D barcode detection using mathematical morphology

Barcode technology is essential in automatic identification,
and is used in a wide range of real-time applications. Different 
code types and applications impose special problems, so there is 
a continuous need for solutions with improved performance. 
Several methods exist for code localization, that are well 
characterized by accuracy and speed. Particularly, high-speed 
processing places need reliable automatic barcode localization, 
e.g. conveyor belts and automated production, where missed 
detections cause loss of profit. Our goal is to detect 
automatically, rapidly and accurately the barcode location with 
the help of extracted image features. We propose a new algorithm 
variant, that outperforms in both accuracy and efficiency other 
detectors found in the literature using similar ideas, and also 
improves on the detection performance in detecting 2D codes 
compared to our previous algorithm
Network-aware evaluation environment for reputation systems

Parties of reputation systems rate each other and use ratings to compute reputation scores that drive their interactions. When deciding which reputation model to deploy in a network environment, it is important to find the\ud
most suitable model and to determine its right initial configuration. This calls for an engineering approach for describing, implementing and evaluating reputation systems while taking into account specific aspects of both the reputation systems and the networked environment where they will run. We present a software tool (NEVER) for network-aware evaluation of reputation systems and their rapid prototyping through experiments performed according to user-specified parameter
Biomedical Knowledge Extraction Using Fuzzy Differential Profiles and Semantic Ranking

International audienceRecently, technologies such as DNA microarrays allow to generate big scale of transcriptomic data used to the aim of exploring background of genes. The analysis and the interpretation of such data requires important databases and efficient mining methods, in order to extract specific biological functions belonging to a group of genes of an expression profile. To this aim, we propose here a new approach for mining transcriptomic data combining domain knowledge and classification methods. Firstly, we propose the definition of Fuzzy Differential Gene Expression Profiles (FG-DEP) based on fuzzy classification and a differential definition between the considered biological situations. Secondly, we will use our previously defined efficient semantic similarity measure (called IntelliGO), that is applied on Gene Ontology (GO) annotation terms, for computing semantic and functional similarities between genes of resulting FG-DEP and well known genetic markers involved in the development of cancers. After that, the similarity matrices will be used to introduce a novel Functional Spectral Representation (FSR) calculated through a semantic ranking of genes regarding their similarities with the tumoral markers. The FSR representation should help expert to interpret by a new way transcriptomic data and infer new genes having similar biological functions regarding well known diseases
Enhancing random forests performance in microarray data classification

Random forests are receiving increasing attention for classification of microarray datasets. We evaluate the effects of a feature selection process on the performance of a random forest classifier as well as on the choice of two critical parameters, i.e. the forest size and the number of features chosen at each split in growing trees. Results of our experiments suggest that parameters lower than popular default values can lead to effective and more parsimonious classification models. Growing few trees on small subsets of selected features, while randomly choosing a single variable at each split, results in classification performance that compares well with state-of-art studies
Characterizing Health-Related Information Needs of Domain Experts

In information retrieval literature, understanding the users’ intents behind the queries is critically important to gain a better insight of how to select relevant results. While many studies investigated how users in general carry out exploratory health searches in digital environments, a few focused on how are the queries formulated, specifically by domain expert users. This study intends to fill this gap by studying 173 health expert queries issued from 3 medical information retrieval tasks within 2 different evaluation compaigns. A statistical analysis has been carried out to study both variation and correlation of health-query attributes such as length, clarity and specificity of either clinical or non clinical queries. The knowledge gained from the study has an immediate impact on the design of future health information seeking systems
Improved Key Recovery Attacks on Reduced-Round AES in the Single-Key Setting

International audienceIn this paper, we revisit meet-in-the-middle attacks on AES in the single-key model and improve on Dunkelman, Keller and Shamir attacks at Asiacrypt 2010. We present the best attack on 7 rounds of AES-128 where data/time/memory complexities are below 2 100 . Moreover, we are able to extend the number of rounds to reach attacks on 8 rounds for both AES-192 and AES-256. This gives the best attacks on those two versions with a data complexity of 2 107 chosen-plaintexts, a memory complexity of 2 96 and a time complexity of 2 172 for AES-192 and 2 196 for AES-256. Finally, we also describe the best attack on 9 rounds of AES-256 with 2 120 chosen plaintexts and time and memory complexities of 2 203 . All these attacks have been found by carefully studying the number of reachable multisets in Dunkelman et al. attacks