Search results for "Intelligence"
showing 10 items of 6959 documents
Chebyshev’s Method on Projective Fluids
2020
We demonstrate the acceleration potential of the Chebyshev semi-iterative approach for fluid simulations in Projective Dynamics. The Chebyshev approach has been successfully tested for deformable bodies, where the dynamical system behaves relatively linearly, even though Projective Dynamics, in general, is fundamentally nonlinear. The results for more complex constraints, like fluids, with a particular nonlinear dynamical system, remained unknown so far. We follow a method describing particle-based fluids in Projective Dynamics while replacing the Conjugate Gradient solver with Chebyshev’s method. Our results show that Chebyshev’s method can be successfully applied to fluids and potentially…
A PARALLEL ALGORITHM FOR ANALYZING CONNECTED COMPONENTS IN BINARY IMAGES
1992
In this paper, a parallel algorithm for analyzing connected components in binary images is described. It is based on the extension of the Cylindrical Algebraic Decomposition (CAD) to a two-dimensional (2D) discrete space. This extension allows us to find the number of connected components, to determine their connectivity degree, and to solve the visibility problem. The parallel implementation of the algorithm is outlined and its time/space complexity is given.
Extracting modular-based backbones in weighted networks
2021
Abstract Networks are an adequate representation for modeling and analyzing a great variety of complex systems. However, understanding networks with millions of nodes and billions of connections can be pretty challenging due to memory and time constraints. Therefore, selecting the relevant nodes and edges of these large-scale networks while preserving their core information is a major issue. In most cases, the so-called backbone extraction methods are based either on coarse-graining or filtering approaches. Coarse-graining techniques reduce the network size by gathering similar nodes into super-nodes, while filter-based methods eliminate nodes or edges according to a statistical property.In…
Detection and classification of microcalcifications clusters in digitized mammograms
2005
In the present paper we discuss a new approach for the detection of microcalcification clusters, based on neural networks and developed as part of the MAGIC-5 project, an INFN-funded program which aims at the development and implementation of CAD algorithms in a GRID-based distributed environment. The proposed approach has as its roots the desire to maximize the rejection of background during the analytical pre-processing stage, in order to train and test the neural network with as clean as possible a sample and therefore maximize its performance. The algorithm is composed of three modules: the image pre-processing, the feature extraction component and the Backpropagation Neural Network mod…
On fuzzification of topological categories
2014
This paper shows that (L,M)-fuzzy topology of U. Hohle, T. Kubiak and A. Sostak is an instance of a general fuzzification procedure for topological categories, which amounts to the construction of a new topological category from a given one. This fuzzification procedure motivates a partial dualization of the machinery of tower extension of topological constructs of D. Zhang, thereby providing the procedure of tower extension of topological categories. With the help of this dualization, we arrive at the meta-mathematical result that the concept of (L,M)-fuzzy topology and the notion of approach space of R. Lowen are ''dual'' to each other.
A system based on neural architectures for the reconstruction of 3-D shapes from images
1991
The connectionist approach to the recovery of 3-D shape information from 2-D images developed by the authors, is based on a system made up by two cascaded neural networks. The first network is an implementation of the BCS, an architecture which derives from a biological model of the low level visual processes developed by Grossberg and Mingolla: this architecture extracts a sort of brightness gradient map from the image. The second network is a backpropagation architecture that supplies an estimate of the geometric parameters of the objects in the scene under consideration, starting from the outputs of the BCS. A detailed description of the system and the experimental results obtained by si…
Action and Deontology
2015
This chapter is concerned with the deontology of actions. According to the presented approach, actions and not propositions are deontologically loaded. Norms direct actions and define the circumstances in which actions are permitted, prohibited, or mandated. Norms are therefore viewed as deontological rules of conduct. The definitions of permission, prohibition, and obligatoriness of an action are formulated in terms of the relation of transition of an action system. A typology of atomic norms is presented. To each atomic norm a proposition is associated and called the normative proposition corresponding to this norm. A logical system, the basic deontic logic, is defined and an adequate sem…
Can CANISO activate CASINO? Transposed-letter similarity effects with nonadjacent letter positions
2004
Nonwords created by transposing two adjacent letters (i.e., transposed-letter (TL) nonwords like jugde) are very effective at activating the lexical representation of their base words. This fact poses problems for most computational models of word recognition (e.g., the interactive-activation model and its extensions), which assume that exact letter positions are rapidly coded during the word recognition process. To examine the scope of TL similarity effects further, we asked whether TL similarity effects occur for nonwords created by exchanging two nonadjacent letters (e.g., canisoCASINO) in three masked form priming experiments using the lexical decision task. The two nonadjacent transpos…
Argumentation graphs with constraint-based reasoning for collaborative expertise
2018
International audience; Collaborative processes are very important in telemedicine domain since they allow for making right decisions in complex situations with multidisciplinary staff. When modelling these collaborative processes, some inconsistencies can appear. In semantic modelling (conceptual graphs), these inconsistencies are verified using constraints. In this work, collaborative processes are represented using an argumentation system modelled in a conceptual graph formalism where inconsistencies could be particular bad attack relation between arguments. To overcome these inconsistencies, two solutions are proposed. The first one is to weight the arguments evolving in the argumentati…
Towards human cell simulation
2019
The faithful reproduction and accurate prediction of the phe-notypes and emergent behaviors of complex cellular systems are among the most challenging goals in Systems Biology. Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because of a variety of reasons. For instance, many quantitative data (e.g., kinetic rates) are usually not available, a problem that hinders the execution of simulation algorithms as long as some parameter estimation methods are used. Though, even with a candidate parameterization, the simulation of mechanistic models could be challenging due to the extr…