pinecone/core-2020-05-10-deduplication huggingface dataset:
On the use of balking for estimation of the blocking probability for OBS routers with FDL lines

The final publication is available at Springer via http://dx.doi.org/10.1007/11919568_40This paper deals with estimation of blocking probabilities for OBS switches with Fiber Delay Lines (FDLs) and full wavelength conversion. An incoming burst that finds the wavelengths occupied is temporarily stored in a FDL. Hence, contention will be sorted out successfully if the residual life of the system is smaller than the maximum FDL delay. In order to derive the blocking probability, the most accurate methodology to date is the use of balking systems [1,2,3,4]. Even though the approach is accurate for very short lengths of the FDLs we identify the cases in which inaccuracy is detected. This happens precisely when the system works with low loss probabilities. Mainly for large number of wavelengths on the fibers and values of the FDL length at least in the vicinity of the burst service time.This work was funded by Spanish MEC (project CAPITAL subproject code:
TEC2004-05622-C04-04 and project PINTA
Feature correspondences From Multiple Views of Coplanar Ellipses

International audienceWe address the problem of feature correspondences in images of coplanar ellipses with objective to benefit of robust ellipse fitting algorithm. The main difficulty is the lack of projective invariant points immediately available. Therefore, our key idea is to construct virtual line and point features using the property of tangent invariance under perspective projection. The proposed method requires first a robust detection of ellipse edge points to fit a parametric model on each ellipse. The feature lines are then obtained by computing the 4 bitangents to each couple of ellipses. The points are derived by considering the tangent points and the intersection points between bitangents. Results of experimental studies are presented to demonstrate the reliability and robustness of the feature extraction process. Subpixel accuracy is easily achieved. A real application to camera self-calibration is also described
Geometric Invariant Domain for Image Watermarking

To enable copyright protection and authentication, robust digital watermark can be embedded into multimedia contents imperceptibly. However, geometric distortions pose a significant threat to robust image watermarking because it can desynchronize the watermark information while preserving the visual quality. To overcome this, we developed an invariant domain with three transforms; Fast Fourier Transform (FFT), Log-Polar Mapping (LPM), and Dual Tree-Complex Wavelet Transform (DT-CWT).  Shift invariance is obtained using FFT. Rotation and scaling invariance are achieved by taking the DT-CWT of a LPM output. Unlike most invariant schemes, our method eliminates explicit re-synchronization. The method resists geometric distortions at both global and local scales. It is also robust against JPEG compression and common image processing. In addition, it exploits perceptual masking property of the DT-CWT subbands, and its watermark detection step does not require the cover image. Experiment on a large set of natural images shows the robustness of the new scheme
Principal type inference for GHC-style multi-parameter type classes

We observe that the combination of multi-parameter type classes with existential types and type annotations leads to a loss of principal types and undecidability of type inference. This may be a surprising fact for users of these popular features. We conduct a concise investigation of the problem and are able to give a type inference procedure which, if successful, computes principal types under the conditions imposed by the Glasgow Haskell Compiler (GHC). Our results provide new insights on how to perform type inference for advanced type extensions.status: publishe
Speeding up target-language driven part-of-speech tagger training for machine translation

When training hidden-Markov-model-based part-of-speech (PoS) taggers involved in machine translation systems in an unsupervised manner the use of target-language information has proven to give better results than the standard Baum-Welch algorithm. The target-language-driven training algorithm proceeds by translating every possible PoS tag sequence resulting from the disambiguation of the words in each source-language text segment into the target language, and using a target-language model to estimate the likelihood of the translation of each possible disambiguation. The main disadvantage of this method is that the number of translations to perform grows exponentially with segment length, translation being the most time-consuming task. In this paper, we present a method that uses a priori knowledge obtained in an unsupervised manner to prune unlikely disambiguations in each text segment, so that the number of translations to be performed during training is reduced. The experimental results show that this new pruning method drastically reduces the amount of translations done during training (and, consequently, the time complexity of the algorithm) without degrading the tagging accuracy achieved.Work funded by the Spanish Ministry of Science and Technology through project TIC2003-08681-C02-01, and by the Spanish Ministry of Education and Science and the European Social Found through research grant BES-2004-4711
Spanish all-words semantic class disambiguation using Cast3LB corpus

In this paper, an approach to semantic disambiguation based on machine learning and semantic classes for Spanish is presented. A critical issue in a corpus-based approach for Word Sense Disambiguation (WSD) is the lack of wide-coverage resources to automatically learn the linguistic information. In particular, all-words sense annotated corpora such as SemCor do not have enough examples for many senses when used in a machine learning method. Using semantic classes instead of senses allows to collect a larger number of examples for each class while polysemy is reduced, improving the accuracy of semantic disambiguation. Cast3LB, a SemCor-like corpus, manually annotated with Spanish WordNet 1.5 senses, has been used in this paper to perform semantic disambiguation based on several sets of classes: lexicographer files of WordNet, WordNet Domains, and SUMO ontology.This paper has been supported by the Spanish Government under projects CESS-ECE (HUM2004-21127-E) and R2D2 (TIC2003-07158-C04-01)
Provenance explorer: Customized provenance views using semantic inferencing

This paper presents Provenance Explorer, a secure provenance visualization tool, designed to dynamically generate customized views of scientific data provenance that depend on the viewer\u27s requirements and/or access privileges. Using RDF and graph visualizations, it enables scientists to view the data, states and events associated with a scientific workflow in order to understand the scientific methodology and validate the results. Initially the Provenance Explorer presents a simple, coarse-grained view of the scientific process or experiment. However the GUI allows permitted users to expand links between nodes (input states, events and output states) to reveal more fine-grained information about particular sub-events and their inputs and outputs. Access control is implemented using Shibboleth to identify and authenticate users and XACML to define access control policies. The system also provides a platform for publishing scientific results. It enables users to select particular nodes within the visualized workflow and drag-and-drop them into an RDF package for publication or e-learning. The direct relationships between the individual components selected for such packages are inferred by the rule-inference engine
Extending Greenstone for Institutional Repositories

We examine the problem of designing a generalized system for building institutional repositories. Widely used schemes such as DSpace are tailored to a particular set of requirements: fixed metadata set; standard view when searching and browsing; pre-determined sequence for depositing items; built-in workflow for vetting new items. In contrast, Fedora builds in flexibility: institutional repositories are just one possible instantiation—however generality incurs a high overhead and uptake has been sluggish. This paper shows how existing components of the Greenstone software can be repurposed to provide a generalized institutional repository that falls between these extremes
Use and Linkage of Source and Output Repositories and the Expectations of the Chemistry Research Community About Their Use

This paper presents findings from a questionnaire survey that aimed to identify the issues around the use and linkage of source and output repositories and the expectations of the chemistry research community about their use. In the context of the StORe project (http://jiscstore.jot.com/WikiHome), which sought to develop new ways of linking academic publications with repositories of research data, thirty eight (38) members of academic and research staff from institutions across the UK provided valuable feedback regarding the nature of the research that they conduct, the type of data that they produce, the sharing and availability of research data and the use and expectations of source and output repositories
Resources Required for Preparing Graph States

International audienceGraph states have become a key class of states within quantum computation. They form a basis for universal quantum computation, capture key properties of entanglement, are related to quantum error correction , establish links to graph theory, violate Bell inequalities, and have elegant and short graph-theoretical descriptions. We give here a rigorous analysis of the resources required for producing graphs states. Using a novel graph-contraction procedure, we show that any graph state can be prepared by a linear-size constant-depth quantum circuits, and we establish trade-offs between depth and width. We show that any minimal-width quantum circuit requires gates that acts on several qubits, regardless of the depth. We relate the complexity of preparing graph states to a new graph-theoretical concept, the local minimum degree, and show that it captures basic properties of graph states
On the importance of public-key validation in the MQV and HMQV key agreement protocols

7th International Conference on Cryptology in India, Calcutta, INDIAHMQV is a hashed variant of the MQV key agreement protocol proposed by Krawczyk at CRYPTO 2005. In this paper, we present some attacks on HMQV and MQV that are successful if public keys are not properly validated. In particular, we present an attack on the two-pass HMQV protocol that does not require knowledge of the victim's ephemeral private keys. The attacks illustrate the importance of performing some form of public-key validation in Diffie-Hellman key agreement protocols, and furthermore highlight the dangers of relying on security proofs for discrete-logarithm protocols where a concrete representation for the underlying group is not specified
Membership Functions for Spatial Proximity

Formalising nearness has been the subject of extensive work, resulting in many membership functions based on absolute distance metrics, relative distance metrics, and combinations of those. The possible strengths and weaknesses of these functions have been discussed and argued at length, but strangely enough, no experiment seems to have been conducted to assess the merits and shortcomings of competing approaches. Conducting such experiments can be expected not only to provide an objective evaluation of the various measures that have been proposed, but also to suggest new measures that outperform all those being analysed. This paper fulfills these expectations, and gives further evidence that fuzzy logic provides fruitful and powerful methods to formalise qualitative reasoning and capture fundamental qualitative notions. The proposed fuzzy membership functions can be directly used in qualitative reasoning about spatial proximity in Geographic Information Systems, which are becoming more and more important in software development for diverse purposes such as Tourist Information Systems or property development
Abnormal behavior detection for early warning of terrorist attack

Many terrorist attacks are accomplished by bringing explosive devices hidden in ordinary-looking objects to public places. In such case, it is almost impossible to distinguish a terrorist from ordinary people just from the isolated appearance. However, valuable clues might be discovered through analyzing a series of actions of the same person. Abnormal behaviors of object fetching, deposit, or exchange in public places might indicate potential attacks. Based on the widely equipped CCTV surveillance systems at the entrance of many public places, this paper proposes an algorithm to detect such abnormal behaviors for early warning of terrorist attack.<br /
A Move Generating Algorithm for Hex Solvers

Generating good move orderings when searching for solutions to games can greatly increase the efficiency of game solving searches. This paper proposes a move generating algorithm for the board game called Hex, which in contrast to many other approaches, determines\ud
move orderings from knowledge gained during the search. This move generator has been used in Hex searches solving the 6x6 Hex board with comparative results indicating a signifcant improvement in performance. One anticipates this move generator will be advantageous in searches for complete solutions of Hex boards, equal to, and larger than, the 7x7 Hex board
A secure architecture for mobile ad hoc networks

International audienceIn this paper, we propose a new architecture based on an efficient trust model and clustering algorithm in order to distribute a certification authority (CA) for ensuring the distribution of certificates in each cluster. We use the combination of fully self-organized security for trust model like PGP adapted to ad-hoc technology and the clustering algorithm which is based on the use of trust and mobility metric, in order to select the clusterhead and to establish PKI in each cluster for authentication and exchange of data. Furthermore, we present new approach Dynamic Demilitarized Zone (DDMZ) to protect CA in each cluster. The principle idea of DDMZ consists to select the dispensable nodes, also called registration authorities; these nodes must be confident and located at one-hope from the CA. Their roles are to receive, filter and treat the requests from any unknown node to CA. With this approach, we can avoid the single point of failure in each cluster. This architecture can be easily extended to other hierarchical routing protocols. Simulation results confirm that our architecture is scalable and secure
Designing a knowledge management approach for the CAMRA Community of Science

Practical Aspects of Knowledge Management, pp. 315-325.CAMRA (Center for Advancing Microbial Risk Assessment) gathers a
community of scientists that investigate several stages in the life cycle of biological
agents of concern. This paper describes the knowledge management (KM) approach
adopted for CAMRA’s community of scientists. The approach includes knowledge
facilitators, a web- and repository-based KM system, and use-centered design. The
approach relies on a KM methodology that addresses the most common causes of
failures in KM approaches that was complemented with a use-centered design
methodology. The resulting combined methodology represents a unique way of
implementing KM to promote knowledge sharing and collaboration. We describe the
principles in our design and the initial steps undertaken to implement it for CAMRA.
We conclude by laying out our future steps
A distributed backbone formation algorithm for mobile ad hoc networks

4th International Symposium on Parallel and Distributed Processing and Applications, ISPA 2006; Sorrento; Italy; 4 December 2006 through 6 December 2006Construction of a backbone architecture is an important issue in mobile ad hoc networks(MANET)s to ease routing and resource management. We propose a new fully distributed algorithm for backbone formation in MANETs that constructs a directed ring architecture. We show the operation of the algorithm, analyze its message complexity and provide results in the simulation environment of ns2. Our results conform that the algorithm is scalable in terms of its running time and roundtrip delay against mobility, surface area, number of nodes and number of clusterheads
A replication-based fault tolerance protocol using group communication for the grid

4th International Symposium on Parallel and Distributed Processing and Applications, ISPA 2006; Sorrento; Italy; 4 December 2006 through 6 December 2006We describe a replication-based protocol that uses group communication for fault tolerance in the Computational Grid. The Grid is partitioned into a number of clusters and each cluster has a designated coordinator that manages the states of the replicas within its cluster. The coordinators belong to a process group and the proposed protocol ensures the correct sequence of message deliveries to the replicas by the coordinators. Any failing node of the Grid is replaced by an active replica to provide correct continuation of the operation of the application. We show the theoretical framework along with illustrations of the replication protocol and its implementation results and analyze its performance and scalability
HLA and HIV Infection Progression: Application of the Minimum
  Description Length Principle to Statistical Genetics

The minimum description length (MDL) principle states that the best model to
account for some data minimizes the sum of the lengths, in bits, of the
descriptions of the model and the residual error. The description length is
thus a criterion for model selection. Description-length analysis of HLA
alleles from the Chicago MACS cohort enables classification of alleles
associated with plasma HIV RNA, an indicator of infection progression.
Progression variation is most strongly associated with HLA-B. Individuals
without B58s supertype alleles average viral RNA levels 3.6-fold greater than
individuals with them.Comment: 17 pages, 1 figur
What is the average human face?

This paper examines the generation of a generic face model from a moderate sized database.  Generic models of a human face have been used in a number of computer vision fields, including reconstruction, active appearance model fitting and face recognition.  The model that is constructed in this paper is based upon the mean of the squared errors that are generated by comparing average faces that are calculated from two independent and random samplings of a database of 3D range images.  This information is used to determine the average amount of error that is present at given height locations along the generic face based on the number of samples that are considered.  These results are then used to sub-region the generic face into areas where the greatest variations occur in the generic face models
An improved 'gas of circles' higher-order active contour model and its application to tree crown extraction.

A central task in image processing is to find the region in the image\ud
corresponding to an entity. In a number of problems, the region takes the form of\ud
a collection of circles, e.g. tree crowns in remote sensing imagery; cells in biological\ud
and medical imagery. In [1], a model of such regions, the ‘gas of circles’\ud
model, was developed based on higher-order active contours, a recently developed\ud
framework for the inclusion of prior knowledge in active contour energies.\ud
However, the model suffers from a defect. In [1], the model parameters were adjusted\ud
so that the circles were local energy minima. Gradient descent can become\ud
stuck in these minima, producing phantom circles even with no supporting data.\ud
We solve this problem by calculating, via a Taylor expansion of the energy, parameter\ud
values that make circles into energy inflection points rather than minima.\ud
As a bonus, the constraint halves the number of model parameters, and severely\ud
constrains one of the two that remain, a major advantage for an energy-based\ud
model. We use the model for tree crown extraction from aerial images. Experiments\ud
show that despite the lack of parametric freedom, the new model performs\ud
better than the old, and much better than a classical active contour
Simultaneous object recognition and segmentation by image exploration

Ferrari V., Tuytelaars T., Van Gool L., ''Simultaneous object recognition and segmentation by image exploration'', Lecture notes in computer science : toward category-level object recognition, vol. 4170, pp. 145-169, 2006.Methods based on local, viewpoint invariant features have
proven capable of recognizing objects in spite of viewpoint changes, occlusion and clutter. However, these approaches fail when these factors are too strong, due to the limited repeatability and discriminative power of the features. As additional shortcomings, the objects need to be rigid and
only their approximate location is found. We present an object recognition approach which overcomes these limitations. An initial set of feature correspondences is first generated. The method anchors on it and then gradually explores the surrounding area, trying to construct more and more matching features, increasingly farther from the initial ones. The resulting process covers the object with matches, and simultaneously separates the correct matches from the wrong ones. Hence, recognition and
segmentation are achieved at the same time. Only very few correct initial matches suffice for reliable recognition. Experimental results on still images and television news broadcasts demonstrate the stronger power of the presented method in dealing with extensive clutter, dominant occlu-
sion, large scale and viewpoint changes. Moreover non-rigid deformations are explicitly taken into account, and the approximative contours of the object are produced. The approach can extend any viewpoint invariant feature extractor.status: publishe
Intelligent Decision Support for Medication Review

This paper examines an implementation of a Multiple Classification Ripple Down Rules system which can be used to provide quality Decision Support Services to pharmacists practicing medication reviews (MRs), particularly for high risk patients. The system was trained on 84 genuine cases by an expert in the field; over the course of 15 hours the system had learned 197 rules and was considered to encompass around 60% of the domain. Furthermore, the system was found able to improve the quality and consistency of the medication review reports produced, as it was shown that there was a high incidence of missed classifications under normal conditions, which were repaired by the system automatically
A new model for classifying DNA code inspired\ud
by neural networks and FSA

This paper introduces a new model of classifiers CL(V,E,l,r)\ud
designed for classifying DNA sequences and combining the flexibility of\ud
neural networks and the generality of finite state automata. Our careful\ud
and thorough verification demonstrates that the classifiers CL(V,E,l,r)\ud
are general enough and will be capable of solving all classification tasks\ud
for any given DNA dataset. We develop a minimisation algorithm for\ud
these classifiers and include several open questions which could benefit\ud
from contributions of various researchers throughout the world
A Fibred Tableau Calculus for Modal Logics of Agents

In previous works we showed how to combine propositional multimodal logics using Gabbay\u27s \emph{fibring} methodology. In this paper we extend the above mentioned works by providing a tableau-based proof technique for the combined/fibred logics. To achieve this end we first make a comparison between two types of tableau proof systems, (\emph{graph} $\&$ \emph{path}), with the help of a scenario (The Friend\u27s Puzzle). Having done that we show how to uniformly construct a tableau calculus for the combined logic using Governatori\u27s labelled tableau system \KEM. We conclude with a discussion on \KEM\u27s features