pinecone/core-2020-05-10-deduplication huggingface dataset:
A Mesh-Based Model for Prediction of Initial Tooth Movement

Orthodontics is making an evolution from a highly experience based treatment towards a computer assisted patient specific therapy. The development of models that can predict tooth movement therefore is a critical research topic. Many existing models, FEM as well as analytical, simplify the calculations by assuming that the tooth root can be approximated by a paraboloïd or an elliptical paraboloïd. Other studies state that these approximations are only allowed within a certain range for tipping movements. But when it comes to bodily movement the real root and the approximation can give very different FEM results. This paper presents a model that is based on an analytical approach using paraboloïds. The analytical approach is chosen to avoid FEM analysis and to limit calculation time. The developed model expands the applicability so that it can do the calculations for a mesh representation of the root. As a validation a set of elliptical paraboloïds is constructed and the results for the analytic and the mesh-based procedure are compared. This is done by comparing the forces necessary to cause a certain displacement or rotation of the root. Both methods produced the same results except for small deviations that can be assigned to the mesh accuracy and the accuracy of the
numerical integration that is used within the analytical
approach. This makes the presented model an interesting tool
for the evaluation of the correctness of an approximating
paraboloïd. It is also suitable for the calculation of initial tooth movement as part of a model for the simulation of orthodontic tooth movement.status: publishe
Diagnosis of ischemic heart disease with cardiogoniometry – Linear discriminant analysis versus support vector machines

The Ischemic Heart Disease (IHD) is characterized by an insufficient supply with blood of the myocardium usually caused by an artherosclerotic disease of the coronary arteries (coronary artery disease CAD). The IHD and its consequences have become a leading problem in the industrialized nations. The aim of this study was to evaluate a new diagnosing method, the cardiogoniometry, using two different classifying techniques: the method of linear discriminant function analysis (LDA) and the method of Support Vector Machines (SVM). Data of a group of 109 female subjects (62 healthy, 47 with IHD) were analyzed on the basis of extracted parameters from the three-dimensional vector loops of the heart. The LDA achieved an accuracy of 83,5% (Sensitivity 78,7%, Specificity 87,1%), whereas the SVM achieved an accuracy of 86% (Sensitivity 80,5%, Specificity 89,8%). It could be shown that cardiogoniometry, an electrophysiological diagnostic method performed at rest, detects variables that are helpful in identifying ischemic heart disease. As it is easy to apply, non-invasive, and provides an automated interpretation it may become an inexpensive addition to the cardiologic diagnostic armamentarium, possibly useful for early diagnosis of IHD or CAD, as well as in patients who do not tolerate exercise testing. It was also proven that by applying Support Vector Machines an increased diagnostic precision in comparison to the conventional discriminant function analysis can be achieved.Peer ReviewedPostprint (published version
Deceptive behavior in plants: I. Pollination by sexual deception in Orchids: a host-parasite perspective

Sexually deceptive orchids attract male insects as pollinators by mimicking the reproductive signals emitted by the targeted females. Since this mimicry system involves the imitation of female mating signals of certain insects, and since mating signals, especially sex pheromones, generally act on a species-specific basis, theory holds that each sexually deceptive orchid is usually pollinated by only one or a few male insect species. While these orchids rely exclusively on their specialized pollinators for their own reproduction, the male insects derive no benefit from this interaction. In this chapter, I will argue that incorporating questions relevant to the field of animal-centered host–parasite interactions into investigations on the evolutionary ecology of orchid pollination by deception will provide important insights at both the proximate (or mechanistic) and at the ultimate (or evolutionary) levels
TAPAs: A Tool for the Analysis of Process Algebras

Process algebras are formalisms for modelling concurrent systems that permit mathematical reasoning with respect to a set of desired properties. TAPAs is a tool that can be used to support the use of process algebras to specify and analyze concurrent systems. It does not aim at guaranteeing high performances, but has been developed as a support to teaching. Systems are described as process algebras terms that are then mapped to labelled transition systems (LTSs). Properties are verified either by checking equivalence of concrete and abstract systems descriptions, or by model checking temporal formulae over the obtained LTS. A key feature of TAPAs, that makes it particularly suitable for teaching, is that it maintains a consistent double representation of each system both as a term and as a graph. Another useful didactical feature is the exhibition of counterexamples in case equivalences are not verified or the proposed formulae are not satisfied
Self-stabilizing Numerical Iterative Computation

Many challenging tasks in sensor networks, including sensor calibration,
ranking of nodes, monitoring, event region detection, collaborative filtering,
collaborative signal processing, {\em etc.}, can be formulated as a problem of
solving a linear system of equations. Several recent works propose different
distributed algorithms for solving these problems, usually by using linear
iterative numerical methods.
  In this work, we extend the settings of the above approaches, by adding
another dimension to the problem. Specifically, we are interested in {\em
self-stabilizing} algorithms, that continuously run and converge to a solution
from any initial state. This aspect of the problem is highly important due to
the dynamic nature of the network and the frequent changes in the measured
environment.
  In this paper, we link together algorithms from two different domains. On the
one hand, we use the rich linear algebra literature of linear iterative methods
for solving systems of linear equations, which are naturally distributed with
rapid convergence properties. On the other hand, we are interested in
self-stabilizing algorithms, where the input to the computation is constantly
changing, and we would like the algorithms to converge from any initial state.
We propose a simple novel method called \syncAlg as a self-stabilizing variant
of the linear iterative methods. We prove that under mild conditions the
self-stabilizing algorithm converges to a desired result. We further extend
these results to handle the asynchronous case.
  As a case study, we discuss the sensor calibration problem and provide
simulation results to support the applicability of our approach
L-diversity based dynamic update for large time-evolving microdata

Data anonymization techniques based on enhanced privacy principles have been the focus of intense research in the last few years. All existing methods achieving privacy principles assume implicitly that the data objects to be anonymized are given once and fixed, which makes it unsuitable for time evolving data. However, in many applications, the real world data sources are dynamic. In such dynamic environments, the current techniques may suffer from poor data quality and/or vulnerability to inference. In this paper, we investigate the problem of updating large time-evolving microdata based on the sophisticated l-diversity model, in which it requires that every group of indistinguishable records contains at least l distinct sensitive attribute values; thereby the risk of attribute disclosure is kept under 1/l. We analyze how to maintain the l-diversity against time evolving updating. The experimental results show that the updating technique is very efficient in terms of effectiveness and data quality.\ud
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A Hybrid Nonlinear-Discriminant Analysis Feature Projection Technique

Feature set dimensionality reduction via Discriminant Analysis (DA) is one of the most sought after approaches in many applications. In this paper, a novel nonlinear DA technique is presented based on a hybrid of Artificial Neural Networks (ANN) and the Uncorrelated Linear Discriminant Analysis (ULDA). Although dimensionality reduction via ULDA can present a set of statistically uncorrelated features, but similar to the existing DAs it assumes that the original data set is linearly separable, which is not the case with most real world problems. In order to overcome this problem, a one layer feed-forward ANN trained with a Differential Evolution (DE) optimization technique is combined with ULDA to implement a nonlinear feature projection technique. This combination acts as nonlinear discriminant analysis. The proposed approach is validated on a Brain Computer Interface (BCI) problem and compared with other techniques
Character Recognition using Hierarchical Vector Quantization and Temporal Pooling

In recent years, there has been a cross-fertilization of ideas between computational neuroscience models of the operation of the neo-cortex and artificial intelligence models of machine learning. Much of this work has focussed on the mammalian visual cortex, treating it as a hierarchically-structured pattern recognition machine that exploits statistical regularities in retinal input. It has further been proposed that the neocortex represents sensory information probabilistically, using some form of Bayesian inference to disambiguate noisy data. In the current paper, we focus on a particular model of the neocortex developed by Hawkins, known as hierarchical temporal memory (HTM). Our aim is to evaluate an important and recently implemented aspect of this model, namely its ability to represent temporal sequences of input within a hierarchically structured vector quantization algorithm. We test this temporal pooling feature of HTM on a benchmark of cursive hand-writing recognition problems and compare it to a current state-of-the-art support vector machine implementation. We also examine whether two pre-processing techniques can enhance the temporal pooling algorithm's performance. Our results show that a relatively simple temporal pooling approach can produce recognition rates that approach the current state-of-the-art without the need for extensive tuning of parameters. We also show that temporal pooling performance is surprisingly unaffected by the use of preprocessing techniques.Griffith Sciences, School of Information and Communication TechnologyFull Tex
An Ontology Formalization of Relation Type Hierarchy in Conceptual Structure Theory

This paper presents an enhancement to ontology formalization, combining previous work in Conceptual Structure Theory and Order-Sorted Logic. In particular, the relation type hierarchy of the former theory is a subset of the predicate hierarchy of the latter. Most existing ontology formalisms place greater importance on concept types, but this paper focuses more on relation types, which are in essence predicates on concept types. New notions are introduced and new properties identified with the aim of completing missing arguments in relation types. The end result is a new ontology, that we call the closure of the original ontology, on which automated inference could be more easily produced (e.g., a query-answering system for legal knowledge)
Revisiting character-based affective storytelling under a narrative BDI framework

Belief-Desire-Intention (BDI) is a well-known cognitive theory, especially in the field of Software Agents. Modelling characters using software agents has been proven to be a suitable approach for obtaining emergent and autonomous behaviours in Interactive Storytelling. In this paper it is claimed that an effective extension of previous models to the BDI framework is useful for designing intelligent characters. An example shows how internal thoughts and motivations of Madame Bovary's main characters can be more naturally formalised as a cognitive side of the story. A narrative reformulation of BDI theory is needed to avoid the implicit complexity of other proposals
The IRIS network of excellence: Integrating research in interactive storytelling

Interactive Storytelling is a major endeavour to develop new media which could offer a radically new user experience, with a potential to revolutionise digital entertainment. European research in Interactive Storytelling has played a leading role in the development of the field, and this creates a unique opportunity to strengthen its position even further by structuring collaboration between some of its main actors. IRIS (Integrating Research in Interactive Storytelling) aims at creating a virtual centre of excellence that will be able to progress the understanding of fundamental aspects of Interactive Storytelling and the development of corresponding technologies
Digital simulation of dominant eddies of a co-flowing jet

This paper described a method for virtual construction of turbulent jet flow field from a limited set of experimental data. The objective is for jet visualization enhancement in near-field plume models. The method is based on the proper orthogonal decomposition (POD), which is an efficient tool to capture the turbulent field based on principal components. A set of experimental flow images at a number of cross-sections of a coflowing jet is obtained in the laboratory. Four hundred instantaneous flow images are taken at each jet section and are subjected to POD analysis. The first 60 principal modes are used in the reconstruction of jet turbulence via a low dimensional generation of jet images. The inclusion of additional modes is shown to produce little improvement on the visual appearance of the reconstructed jet images. Linear interpolation is attempted to generate jet images at an intermediate jet section between two experimental stations. Jet flow field on a central longitudinal section of the jet are assembled from the reconstructed flow images at all jet sections. The resulting development of concentration jet width is shown to agree well with the analytical solution.postprintThe 16th IAHR-APD 2008 Congress and 3rd Symposium of IAHR-ISHS, Nanjing, China, 20-23 October 2008. In Advances in Water Resources & Hydraulic Engineering, 2009, v. 2, p. 618-62
Design and evaluation of a multi-class based multicast routing protocol

Serie : Lecture notes in computer science, ISSN 0302-9743 ; vol. 5200Most of current multicast QoS routing proposals are based on the principle that QoS routes must be computed for each request, where requests explicitly express their resource requirements. As a result, within this environment, the goal of QoS routing is to satisfy individual request requirements, resorting to resource reservation to maintain those requirements after a feasible path has been found. This type of strategy is suited within the IntServ model but does not seem adequate in presence of DiffServ networks. According to DiffServ model, traffic flows are aggregated into specific classes-of-service and each flow receives a specific treatment accordingly to its class-of-service. There are no per flow guarantees, only per class differentiation. In this environment instead of per flow path computation, per class path calculation should be made, and so, within multicast scenarios, multiple multicast trees must be computed in order to satisfy different QoS requirements of different traffic classes. 
This paper presents a new multicast routing protocol enabling per class multicast tree computation. The proposed heuristics enable directed trees establishment, instead of reverse path ones, due to the importance of link asymmetry within an environment which is, essentially, unidirectional. The proposed protocol is implemented and simulated using Network Simulator. A set of simulation results are presented, analyzed and compared against PIM-SM, a widely deployed multicast routing protocol
On the early release of burst-control packets in Optical Burst-Switched networks

Revised Selected Papers of International Conference, ICOIN 2007, Estoril, Portugal, January 23-25, 2007.The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-89524-4_4In Optical Burst-Switched networks, the so-called Burst-Control Packet is sent a given offset-time ahead of the optical data burst to advertise the imminent burst arrival, and reserve a time-slot at each intermediate node to allocate it. This work proposes a methodology to estimate the number of packets to arrive in a given amount of time, in order to make it possible to send the BCP packet straightafter the first packet arrival and reduce the latency experienced during the burst-assembly process.
The following studies the impact of a wrong guess in terms of over-reservation of resources and waiting-time at the assembler, providing a detailed characterisation of their probability density functions. Additionally, a case example in a scenario with non-homogeneous Poisson arrivals is analysed and it is shown how to choose the appropriate burst-assembly algorithm values to never exceed a given over-reservation amount.This work was funded by the European Union e-Photon/ONe+ project and by the
Spanish Ministry of Science and Education under the DIOR projec
LORE: A Compound Object Authoring and Publishing Tool for the Australian Literature Studies Community

This paper presents LORE (Literature Object Re-use and Exchange), a light-weight tool which is designed to allow scholars and teachers of Australi-an literature to author, edit and publish compound information objects encapsulating related digital resources and bibliographic records. LORE enables users to easily create OAI-ORE-compliant compound objects, which build on the IFLA FRBR model, and also enables them to describe and publish them to an RDF repository as Named Graphs. Using the tool, literary scholars can create typed relationships between individual atomic objects using terms from a bibli-ographic ontology and can attach metadata to the compound object. This paper describes the implementation and user interface of the LORE tool, as developed within the context of an ongoing case study being conducted in collaboration with AustLit: The Australian Literature Resource, which focuses on compound objects for teaching and research within the Australian literature studies community
Adenosine receptors and reperfusion injury of the heart

Adenosine, a catabolite of ATP, exerts numerous effects in the heart, including modulation of the cardiac response to stress, such as occurs during myocardial ischemia and reperfusion.  Over the past 20 years substantial evidence has accumulated that adenosine, administered either prior to ischemia or during reperfusion, reduces both reversible and irreversible myocardial injury.  The latter effect results in reduction of both necrosis or myocardial infarction (MI) and apoptosis.  These effects appear to be mediated via the activation of one or more G-protein coupled receptors (GPCRs), referred to as A1, A2A, A2B and A3 adenosine receptor (AR) subtypes.  Experimental studies in different species and models suggest that activation of the A1 or A3ARs prior to ischemia is cardioprotective.  Further experimental studies reveal that the administration of A2AAR agonists during reperfusion can also reduce MI, and recent reports suggest that A2BARs may also play an important role in modulating myocardial reperfusion injury.  Despite convincing experimental evidence for AR-mediated cardioprotection, there have been only a limited number of clinical trials examining the beneficial effects of adenosine or adenosine-based therapeutics in humans, and the results of these studies have been equivocal.  This review summarizes our current knowledge of AR-mediated cardioprotection, and the roles of the four known ARs in experimental models of ischemia-reperfusion.  The chapter concludes with an examination of the clinical trials to date assessing the safety and efficacy of adenosine as a cardioprotective agent during coronary thrombolysis in humans.Griffith Health, School of Medical ScienceFull Tex
Comparison of Discrete Curvature Estimators and Application to Corner Detection

International audienceSeveral curvature estimators along digital contours were pro- posed in recent works [1-3]. These estimators are adapted to non perfect digitization process and can process noisy contours. In this paper, we compare and analyse the performances of these estimators on several types of contours and we measure execution time on both perfect and noisy shapes. In a second part, we evaluate these estimators in the con- text of corner detection. Finally to evaluate the performance of a non curvature based approach, we compare the results with a morphological corner detector [4]
Discrete Contour Extraction from Reference Curvature Function

International audienceA robust discrete curvature estimator was recently proposed by Kerautret et al. [1]. In this paper, we exploit the precision and sta- bility of this estimator in order to deﬁne a contour extraction method for analysing geometric features. We propose to use a reference curva- ture function for extracting the frontier of a shape in a gray level image. The frontier extraction is done by using both geometric information rep- resented by the reference curvature and gradient information contained in the source image. The application of this work is done in a medical application
Knowledge Assessment: A Modal Logic Approach

The possible worlds semantics is a fruitful approach used in Artificial Intelligence (AI) for both modelling as well as reasoning about knowledge in agent systems via modal logics. In this work our main idea is not to model/reason about knowledge but to provide a theoretical framework for knowledge assessment (KA) with the help of Monatague-Scott (MS) semantics of modal logic. In KA questions asked and answers collected are the central elements and knowledge notions will be defined from these (i.e., possible states of knowledge of subjects in a population with respect to a field of information)
Settling on the group\u27s goals: An n-person argumentation game approach

Argumentation games have been proved to be a robust and flexible tool to resolve conflicts among agents. An agent can propose its explanation and its goal known as a claim, which can be refuted by other agents. The situation is more complicated when there are more than two agents playing the game. We propose a weighting mechanism for competing premises to tackle with conflicts from multiple agents in an n-person game. An agent can defend its proposal by giving a counter-argument to change the ``opinion\u27\u27 of the majority of opposing agents. During the game, an agent can exploit the knowledge that other agents expose in order to promote and defend its main claim