Search results for "algorithm"
showing 10 items of 4887 documents
Schema-Backed Visual Queries over Europeana and Other Linked Data Resources
2021
We describe and demonstrate the process of extracting a data-driven schema of the Europeana cultural heritage Linked data resource (with actual data classes, properties and their connections, and cardinalities) and application of the extracted schema to create a visual query environment over Europeana. The extracted schema information allows generating SHACL data shapes describing the actual data endpoint structure. The schema extraction process can be applied also to other data endpoints with a moderate data schema size and a potentially large data triple count, as e.g., British National Bibliography Linked data resource.
A Dynamic Attribute-Based Authentication Scheme
2015
Attribute-based authentication (ABA) is an approach to authenticate users by their attributes, so that users can get authenticated anonymously and their privacy can be protected. In ABA schemes, required attributes are represented by attribute trees, which can be combined with signature schemes to construct ABA schemes. Most attribute trees are built from top to down and can not change with attribute requirement changes. In this paper, we propose an ABA scheme based on down-to-top built attribute trees or dynamic attribute trees, which can change when attribute requirements change. Therefore, the proposed dynamic ABA scheme is more efficient in a dynamic environment by avoiding regenerating…
Motion Cueing Algorithms: A Review
2017
Robotic motion platforms are commonly used in motion-based vehicle simulation. However, the reproduction of realistic accelerations within a reduced workspace is a major challenge. Thus, high-level control strategies commonly referred to as motion cueing algorithms (MCA) are required to convert the simulated vehicle physical state into actual motion for the motion platform. This paper reviews the most important strategies for the generation of motion cues in simulators, listing the advantages and drawbacks of the different solutions. The motion cueing problem, a general scheme and the four most common approaches – classical washout, adaptive washout, optimal control and model predictive con…
Combining hashing and enciphering algorithms for epidemiological analysis of gathered data.
2008
Summary Objectives: Compiling individual records coming from different sources is necessary for multi-center studies. Legal aspects can be satisfied by implementing anonymization procedures. When using these procedures with a different key for each study it becomes almost impossible to link records from separate data collections. Methods: The originality of the method relies on the way the combination of hashing and enciphering techniques is performed: like in asymmetric encryption, two keys are used but the private key depends on the patient’s identity. Results: The combination of hashing and enciphering techniques provides a great improvement in the overall security of the proposed scheme…
The PCHIP subdivision scheme
2016
In this paper we propose and analyze a nonlinear subdivision scheme based on the monotononicity-preserving third order Hermite-type interpolatory technique implemented in the PCHIP package in Matlab. We prove the convergence and the stability of the PCHIP nonlinear subdivision process by employing a novel technique based on the study of the generalized Jacobian of the first difference scheme. MTM2011-22741
On Using “Stochastic Learning on the Line” to Design Novel Distance Estimation Methods for Three-Dimensional Environments
2019
We consider the unsolved problem of Distance Estimation (DE) when the inputs are the x and y coordinates (i.e., the latitudinal and longitudinal positions) of the points under consideration, and the elevation/altitudes of the points specified, for example, in terms of their z coordinates (3DDE). The aim of the problem is to yield an accurate value for the real (road) distance between the points specified by all the three coordinates of the cities in question (This is a typical problem encountered in a GISs and GPSs.). In our setting, the distance between any pair of cities is assumed to be computed by merely having access to the coordinates and known inter-city distances of a small subset o…
Discretized Bayesian Pursuit – A New Scheme for Reinforcement Learning
2012
Published version of a chapter in the book: Advanced Research in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31087-4_79 The success of Learning Automata (LA)-based estimator algorithms over the classical, Linear Reward-Inaction ( L RI )-like schemes, can be explained by their ability to pursue the actions with the highest reward probability estimates. Without access to reward probability estimates, it makes sense for schemes like the L RI to first make large exploring steps, and then to gradually turn exploration into exploitation by making progressively smaller learning steps. However, this behavior becomes counter-intuitive wh…
A General Frame for Building Optimal Multiple SVM Kernels
2012
The aim of this paper is to define a general frame for building optimal multiple SVM kernels. Our scheme follows 5 steps: formal representation of the multiple kernels, structural representation, choice of genetic algorithm, SVM algorithm, and model evaluation. The computation of the optimal parameter values of SVM kernels is performed using an evolutionary method based on the SVM algorithm for evaluation of the quality of chromosomes. After the multiple kernel is found by the genetic algorithm we apply cross validation method for estimating the performance of our predictive model. We implemented and compared many hybrid methods derived from this scheme. Improved co-mutation operators are u…
Application of Adaptive Hypergraph Model to Impulsive Noise Detection
2001
In this paper, using hypergraph theory, we introduce an image model called Adaptive Image Neighborhood Hypergraph (AINH). From this model we propose a combinatorial definition of noisy data. A detection procedure is used to classify the hyperedges either as noisy or clean data. Similar to other techniques, the proposed algorithm uses an estimation procedure to remove the effects of the noise. Extensive simulations show that the proposed scheme consistently works well in suppressing of impulsive noise.
Generalized wavelets design using Kernel methods. Application to signal processing
2013
Abstract Multiresolution representations of data are powerful tools in signal processing. In Harten’s framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called the prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact values and the predicted values. In this paper we present a multiresolution scheme using local polynomial regression theory in order to design a more accurate prediction operator. The stability of the scheme is proved and the order of the method is calculated. Finally, some results are presented comparing our method with the classical…