Search results for " algorithms"
showing 10 items of 612 documents
Reinforcement Learning for P2P Searching
2005
For a peer-to-peer (P2P) system holding massive amount of data, an efficient and scalable search for resource sharing is a key determinant to its practical usage. Unstructured P2P networks avoid the limitations of centralized systems and the drawbacks of a highly structured approach, because they impose few constraints on topology and data placement, and they support highly versatile search mechanisms. However their search algorithms are usually based on simple flooding schemes, showing severe inefficiencies. In this paper, to address this major limitation, we propose and evaluate the adoption of a local adaptive routing protocol. The routing algorithm adopts a simple Reinforcement Learning…
Computing Subdivision Surface Intersection
2003
Computer surface intersections is fundamental problem in geometric modeling. Any Boolean operation can be seen as an intersection calculation followed by a selection of parts necessary for building the surface of the resulting object. This paper deals with the computing of intersection curveson subdivision surfaces (surfaces generated by the Loop scheme). We present three variants of our algorithm. The first variant calculates this intersection after classification of the object faces into intersecting and non-intersecting pairs of faces. the second variant is based on 1-neighborhood of the intersecting faces. The third variant uses the concept of bipartite graph.
Computational aspects in checking of coherence and propagation of conditional probability bounds
2000
In this paper we consider the problem of reducing the computational difficulties in g-coherence checking and propagation of imprecise conditional probability assessments. We review some theoretical results related with the linear structure of the random gain in the betting criterion. Then, we propose a modi ed version of two existing algorithms, used for g-coherence checking and propagation, which are based on linear systems with a reduced number of unknowns. The reduction in the number of unknowns is obtained by an iterative algorithm. Finally, to illustrate our procedure we give some applications.
Algorithms for coherence checking and propagation of conditional probability bounds
2001
In this paper, we propose some algorithms for the checking of generalized coherence (g-coherence) and for the extension of imprecise conditional probability assessments. Our concept of g-coherence is a generalization of de Finetti’s coherence principle and is equivalent to the ”avoiding uniform loss” property for lower and upper probabilities (a la Walley). By our algorithms we can check the g-coherence of a given imprecise assessment and we can correct it in order to obtain the associated coherent assessment (in the sense of Walley and Williams). Exploiting some properties of the random gain we show how, in the linear systems involved in our algorithms, we can work with a reduced set of va…
On the use of multi-temporal series of COSMO-SkyMed data for LANDcover classification and surface parameter retrieval over agricultural sites
2011
The objective of this paper is to report on the activities carried out during the first year of the Italian project “Use of COSMO-SkyMed data for LANDcover classification and surface parameters retrieval over agricultural sites” (COSMOLAND), funded by the Italian Space Agency. The project intends to contribute to the COSMO-SkyMed mission objectives in the agriculture and hydrology application domains.
LA SCALA DI MOMO AI MUSEI VATICANI. Curve coniche gobbe e superfici rigate da esse generate.
2014
This study is part of a more vast research that aims to examine in depth the geometrical-spatial origin of skew curves belonging to conical surfaces of revolution: conical spiral and conical helix. The study begins with an investigation concerning the geometrical tracing, and the spatial origin of both the skew curves and the ruled surfaces they generate, carrying out a comparison of the different formal characteristics through a number of algorithms that control the reference properties, written within the renown Rhinoceros plug-in, Grasshopper. Then follows an in-depth analysis of an admirable example of architecture dating back to the first thirty years of the past century and made by th…
Soundscape design through evolutionary engines
2008
Abstract Two implementations of an Evolutionary Sound Synthesis method using the Interaural Time Difference (ITD) and psychoacoustic descriptors are presented here as a way to develop criteria for fitness evaluation. We also explore a relationship between adaptive sound evolution and three soundscape characteristics: keysounds, key-signals and sound-marks. Sonic Localization Field is defined using a sound attenuation factor and ITD azimuth angle, respectively (Ii, Li). These pairs are used to build Spatial Sound Genotypes (SSG) and they are extracted from a waveform population set. An explanation on how our model was initially written in MATLAB is followed by a recent Pure Data (Pd) impleme…
SparseHC: A Memory-efficient Online Hierarchical Clustering Algorithm
2014
Computing a hierarchical clustering of objects from a pairwise distance matrix is an important algorithmic kernel in computational science. Since the storage of this matrix requires quadratic space with respect to the number of objects, the design of memory-efficient approaches is of high importance to this research area. In this paper, we address this problem by presenting a memory-efficient online hierarchical clustering algorithm called SparseHC. SparseHC scans a sorted and possibly sparse distance matrix chunk-by-chunk. Meanwhile, a dendrogram is built by merging cluster pairs as and when the distance between them is determined to be the smallest among all remaining cluster pairs. The k…
Synchronous R-NSGA-II: An Extended Preference-Based Evolutionary Algorithm for Multi-Objective Optimization
2015
Classical evolutionary multi-objective optimization algorithms aim at finding an approx- imation of the entire set of Pareto optimal solutions. By considering the preferences of a decision maker within evolutionary multi-objective optimization algorithms, it is possible to focus the search only on those parts of the Pareto front that satisfy his/her preferences. In this paper, an extended preference-based evolutionary algorithm has been proposed for solving multi-objective optimiza- tion problems. Here, concepts from an interactive synchronous NIMBUS method are borrowed and combined with the R-NSGA-II algorithm. The proposed synchronous R-NSGA-II algorithm uses preference information provid…
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