Search results for "Abstract data type"
showing 10 items of 1140 documents
Car style-holon recognition in computer-aided design
2019
Abstract Multi-scale design can presumably stimulate greater intelligence in computer-aided design (CAD). Using the style-holon concept, this paper proposes a computational approach to address multi-scale style recognition for automobiles. A style-holon is both a whole—it contains sub-styles of which it is composed—as well as a part of a broader style. In this paper, we first apply a variable precision rough set-based approach to car evaluation and ranking. Secondly, we extracted and subsequently computed the each car's characteristic lines from the CAD models. Finally, we identified style-holons using the property of a double-headed style-holon. A style-holon is necessarily included in a t…
A naive relevance feedback model for content-based image retrieval using multiple similarity measures
2010
This paper presents a novel probabilistic framework to process multiple sample queries in content based image retrieval (CBIR). This framework is independent from the underlying distance or (dis)similarity measures which support the retrieval system, and only assumes mutual independence among their outcomes. The proposed framework gives rise to a relevance feedback mechanism in which positive and negative data are combined in order to optimally retrieve images according to the available information. A particular setting in which users interactively supply feedback and iteratively retrieve images is set both to model the system and to perform some objective performance measures. Several repo…
Multimode entanglement in reconfigurable graph states using optical frequency combs
2017
Multimode entanglement is an essential resource for quantum information processing and quantum metrology. However, multimode entangled states are generally constructed by targeting a specific graph configuration. This yields to a fixed experimental setup that therefore exhibits reduced versatility and scalability. Here we demonstrate an optical on-demand, reconfigurable multimode entangled state, using an intrinsically multimode quantum resource and a homodyne detection apparatus. Without altering either the initial squeezing source or experimental architecture, we realize the construction of thirteen cluster states of various sizes and connectivities as well as the implementation of a secr…
Co-citation Percentile Rank and JYUcite : a new network-standardized output-level citation influence metric and its implementation using Dimensions A…
2022
AbstractJudging value of scholarly outputs quantitatively remains a difficult but unavoidable challenge. Most of the proposed solutions suffer from three fundamental shortcomings: they involve (i) the concept of journal, in one way or another, (ii) calculating arithmetic averages from extremely skewed distributions, and (iii) binning data by calendar year. Here, we introduce a new metric Co-citation Percentile Rank (CPR), that relates the current citation rate of the target output taken at resolution of days since first citable, to the distribution of current citation rates of outputs in its co-citation set, as its percentile rank in that set. We explore some of its properties with an examp…
Mean sets for building 3D probabilistic liver atlas from perfusion MR images
2012
This paper is concerned with liver atlas construction. One of the most important issues in the framework of computational abdominal anatomy is to define an atlas that provides a priori information for common medical task such as registration and segmentation. Unlike other approaches already proposed so far (to our knowledge), in this paper we propose to use the concept of random compact mean set to build probabilistic liver atlases. To accomplish this task a two-tier process was carried out. First a set of 3D images was manually segmented by a physician. We see the different 3D segmented shapes as a realization of a random compact set. Secondly, elements of two known definitions of mean set…
A convolutional neural network framework for blind mesh visual quality assessment
2017
In this paper, we propose a new method for blind mesh visual quality assessment using a deep learning approach. To do this, we first extract visual representative features by computing locally curvature and dihedral angles from each distorted mesh. Then, we determine from these features a set of 2D patches which are learned to a convolutional neural network (CNN). The network consists of two convolutional layers with two max-pooling layers. Then, a multilayer perceptron (MLP) with two fully connected layers is integrated to summarize the learned representation into an output node. With this network structure, feature learning and regression are used to predict the quality score of a given d…
Energy market segmentation for distributed energy resources implementation purposes
2007
The new power market scene has made its actors aware of the importance of offering customers a set of products according to their specific needs. At the same time, a desirable massive deployment of distributed energy resources would require that the products be designed for specific purposes for each type of customer. For these reasons, it is essential to identify the energy behaviour of different customer segments existing in the electricity market. This paper presents a segmentation methodology that allows the identification of different types of customers in accordance with their energy use. This segmentation is conceptually different from the one that is currently performed by the utili…
An Alternative to Medial Axis for the 3D Reconstruction of Unorganized Set of Points Using Implicit Surfaces
2006
Rebuilding three-dimensional objects represented by a set of points is a classical problem in computer graphics. Multiple applications like medical imaging or industrial techniques require finding shape from scattered data. Therefore, the reconstruction of a set of points that represents a shape has been widely studied, depending on data source and reconstruction's objectives. This purpose of this paper is to provide an automatic reconstruction from an unorganized cloud describing an unknown shape in order to provide a solution that will allow to compute the object's volume and to deform it with constant volume. The main idea in this paper consists in filling the object's interior with an e…
Analysis and Validation of Learning Technology Models, Standards and Specifications
2010
The paper presents a model for the analysis, comparison and validation of standards, specifications and in particular reference models in the field of Technology Enhanced Learning (TEL). The Reference Model Analysis Grid (RMAG) establishes categories of reference models and standards. Based on those categories, a set of criteria for the analysis and validation of standards was elaborated as a part of the ICOPER project that aims at interoperable open content for competency-based TEL. The analysis of standards in this context is targeted at developing a set of validated approaches that lead to a new reference model. Four standards were investigated, taking into account a broad range of aspec…
Acoustic Detection of Moving Vehicles
2018
This chapter outlines a robust algorithm to detect the arrival of a vehicle of arbitrary type when other noises are present. It is done via analysis of its acoustic signature against an existing database of recorded and processed acoustic signals. To achieve it with minimum number of false alarms, a construction of a training database of acoustic signatures of signals emitted by vehicles using the distribution of the energies among blocks of wavelet packet coefficients (waveband spectra, see Sect. 4.6) is combined with a procedure of random search for a near-optimal footprint (RSNOFP). The number of false alarms in the detection is minimized even under severe conditions such as: signals emi…