Search results for "Cure"

showing 10 items of 518 documents

Influence of the Resin Layer Thickness at the Interface of Hybrid Metal-composite Co-cured Joints

2011

As discussed in literature, the accurate analysis of the modern co-cured joints between composite materials or between a metal and a composite material (hybrid joints) is complicated by the influence of the interface resin layer on the interface singular stress field. In such joints, in fact, there is not a proper adhesive layer and the thickness of the resin layer, that plays the role of the adhesive, is not constant due to the presence of the reinforcing fibers in the composite adherent. For this reason several authors assume that a generic co-cured joint can not be studied as a simple bi-material joint, without considering the particular characteristics of the actual resin layer. This pr…

stress intensity factor.Work (thermodynamics)PhotoelasticityphotoelasticityMaterials scienceComposite numberGeneral Medicinestress intensity factorcomposite materialStress fieldSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di Macchineco-cured jointAdhesiveComposite materialJoint (geology)Boundary element methodLayer (electronics)Engineering(all)Procedia Engineering
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Subcontract approval clauses in the anti-corruption framework under Italian public procurement law

2012

subcontract public procurement anti-corruption
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Pratica e criticità delle sopraelevazioni nella costruzione storica palermitana. Practice and deficiencies of additional storeys in the construction …

2017

Per secoli lo sviluppo delle città è avvenuto soprattutto attraverso la trasformazione degli edifici esistenti, in particolare per mezzo di estese sopraele-vazioni. Questa pratica ha portato con sé numerose criticità, connesse alla vulne-rabilità sismica delle strutture e alle condizioni d’igiene e benessere degli ambienti interni e dello spazio urbano circostante. Soprattutto le ultime elevazioni sono esemplari della distanza dalle esigenze di sicurezza strutturale e benessere termico dell’utenza contemporanea, distanza che sempre più spesso si imputa agli edifici storici. In un passato non lontano è stata suggerita anche un’estesa demolizione di tali manufatti, operazione che cercava sost…

superfetazionesalubritàthermic and hygrometric wellnesopraelevazioneSettore ICAR/10 - Architettura Tecnicahealthinestructural safetysicurezza strutturalePalermobenessere termico e igrometrico
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A novel heuristic memetic clustering algorithm

2013

In this paper we introduce a novel clustering algorithm based on the Memetic Algorithm meta-heuristic wherein clusters are iteratively evolved using a novel single operator employing a combination of heuristics. Several heuristics are described and employed for the three types of selections used in the operator. The algorithm was exhaustively tested on three benchmark problems and compared to a classical clustering algorithm (k-Medoids) using the same performance metrics. The results show that our clustering algorithm consistently provides better clustering solutions with less computational effort.

ta113Determining the number of clusters in a data setBiclusteringClustering high-dimensional dataDBSCANComputingMethodologies_PATTERNRECOGNITIONTheoretical computer scienceCURE data clustering algorithmCorrelation clusteringCanopy clustering algorithmCluster analysisAlgorithmMathematics2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
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Twister Tries

2015

Many commonly used data-mining techniques utilized across research fields perform poorly when used for large data sets. Sequential agglomerative hierarchical non-overlapping clustering is one technique for which the algorithms’ scaling properties prohibit clustering of a large amount of items. Besides the unfavorable time complexity of O(n 2 ), these algorithms have a space complexity of O(n 2 ), which can be reduced to O(n) if the time complexity is allowed to rise to O(n 2 log2 n). In this paper, we propose the use of locality-sensitive hashing combined with a novel data structure called twister tries to provide an approximate clustering for average linkage. Our approach requires only lin…

ta113Hierarchical agglomerative clusteringta112Fuzzy clusteringBrown clusteringComputer scienceSingle-linkage clusteringcomputer.software_genreHierarchical clusteringLocality-sensitive hashingData setCURE data clustering algorithmlocality-sensitive hashingaverage linkageData miningHierarchical clustering of networkslinear complexityCluster analysishierarchical clusteringAlgorithmcomputerTime complexityProceedings of the 2015 ACM SIGMOD International Conference on Management of Data
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Scalable Hierarchical Clustering: Twister Tries with a Posteriori Trie Elimination

2015

Exact methods for Agglomerative Hierarchical Clustering (AHC) with average linkage do not scale well when the number of items to be clustered is large. The best known algorithms are characterized by quadratic complexity. This is a generally accepted fact and cannot be improved without using specifics of certain metric spaces. Twister tries is an algorithm that produces a dendrogram (i.e., Outcome of a hierarchical clustering) which resembles the one produced by AHC, while only needing linear space and time. However, twister tries are sensitive to rare, but still possible, hash evaluations. These might have a disastrous effect on the final outcome. We propose the use of a metaheuristic algor…

ta113Theoretical computer scienceBrown clusteringComputer scienceCorrelation clusteringSingle-linkage clusteringHierarchical clusteringCURE data clustering algorithmhierrchial clusteringCanopy clustering algorithmHierarchical clustering of networksCluster analysisclustering2015 IEEE Symposium Series on Computational Intelligence
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Scalable implementation of dependence clustering in Apache Spark

2017

This article proposes a scalable version of the Dependence Clustering algorithm which belongs to the class of spectral clustering methods. The method is implemented in Apache Spark using GraphX API primitives. Moreover, a fast approximate diffusion procedure that enables algorithms of spectral clustering type in Spark environment is introduced. In addition, the proposed algorithm is benchmarked against Spectral clustering. Results of applying the method to real-life data allow concluding that the implementation scales well, yet demonstrating good performance for densely connected graphs. peerReviewed

ta113ta213Apache SparkComputer sciencedatasetsCorrelation clusteringdata miningcomputer.software_genrealgorithmsSpectral clusteringComputational sciencedependence clusteringData stream clusteringCURE data clustering algorithmScalabilitySpark (mathematics)algoritmitCanopy clustering algorithmData miningtiedonlouhintaCluster analysisclustering algorithmscomputerdata processingtietojenkäsittely
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Synchronization of hidden chaotic attractors on the example of radiophysical oscillators

2017

In the present paper we consider the problem of synchronization of hidden and self-excited attractors in the context of application to a system of secure communication. The system of two coupled Chua models was studied. Complete synchronization was observed as for self-excited, as hidden attractors. Beside it for hidden attractors some special type of dynamic was revealed.

ta213oscillatorsbusiness.industryComputer scienceta111elektroniset piiritMathematicsofComputing_NUMERICALANALYSISChaoticContext (language use)dynamical systemsType (model theory)TopologyoskillaattoritNonlinear Sciences::Chaotic DynamicsSecure communicationSynchronization (computer science)Attractorelectronic circuitsdynaamiset systeemitbusinessBifurcation2017 Progress In Electromagnetics Research Symposium - Spring (PIERS)
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aspetti bioetici, deontologici e legali della terapia antalgica

2009

terapia del dolore responsabilità professionale scala di valutazione del dolore. consenso informato cure palliative
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L’ultima parola. Il problema dello stato vegetativo nel dibattito sulle dichiarazioni anticipate di volontà, in M. Gensabella Furnari - A. Ruggeri (a…

2010

testamento biologico cure anticipate diritto all'autodeterminazioneSettore M-FIL/03 - Filosofia Morale
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