Search results for " ANN"
showing 10 items of 1343 documents
Forecasting : theory and practice
2022
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a varie…
A Two-Stage Reconstruction of Microstructures with Arbitrarily Shaped Inclusions
2020
The main goal of our research is to develop an effective method with a wide range of applications for the statistical reconstruction of heterogeneous microstructures with compact inclusions of any shape, such as highly irregular grains. The devised approach uses multi-scale extended entropic descriptors (ED) that quantify the degree of spatial non-uniformity of configurations of finite-sized objects. This technique is an innovative development of previously elaborated entropy methods for statistical reconstruction. Here, we discuss the two-dimensional case, but this method can be generalized into three dimensions. At the first stage, the developed procedure creates a set of black synthetic …
Classical and Quantum Annealing in the Median of Three Satisfiability
2011
We determine the classical and quantum complexities of a specific ensemble of three-satisfiability problems with a unique satisfying assignment for up to N = 100 and 80 variables, respectively. In the classical limit, we employ generalized ensemble techniques and measure the time that a Markovian Monte Carlo process spends in searching classical ground states. In the quantum limit, we determine the maximum finite correlation length along a quantum adiabatic trajectory determined by the linear sweep of the adiabatic control parameter in the Hamiltonian composed of the problem Hamiltonian and the constant transverse field Hamiltonian. In the median of our ensemble, both complexities diverge e…
Automatic Generation of Subject-Based Image Transitions
2011
This paper presents a novel approach for the automatic generation of image slideshows. Counter to standard cross-fading, the idea is to operate the image transitions keeping the subject focused in the intermediate frames by automatically identifying him/her and preserving face and facial features alignment. This is done by using a novel Active Shape Model and time-series Image Registration. The final result is an aesthetically appealing slideshow which emphasizes the subject. The results have been evaluated with a users’ response survey. The outcomes show that the proposed slideshow concept is widely preferred by final users w.r.t. standard image transitions.
Il soggetto dell'annuncio
2015
The pictorial topic of “Annunciation” gives the possibility of an understanding of Heidegger’s masterful reading of announcement as Erscheinung in its distinction from Phänomen as self-manifestation. In particular, three paintings – L’annunciazione di Recanati by Lorenzo Lotto, Ecce Ancilla Domini by Dante Gabriel Rossetti, The Annunciation by John William Waterhouse – allow in the analysis of announcement a reference to subjectivity as receiver which is grasped in its primordial passivity, but also in its capacity of answering and self-positioning in front of announcement.
Ex Iani Gruteri in L. Senecam animadversionibus excerpta quaedam notatu digniora et ab aliis nondum explicata / inservimus una nonnullas Fr. Iureti n…
1501
Caplletres ornades
Hybrid Genetic Algorithms in Data Mining Applications
2009
Genetic algorithms (GAs) are a class of problem solving techniques which have been successfully applied to a wide variety of hard problems (Goldberg, 1989). In spite of conventional GAs are interesting approaches to several problems, in which they are able to obtain very good solutions, there exist cases in which the application of a conventional GA has shown poor results. Poor performance of GAs completely depends on the problem. In general, problems severely constrained or problems with difficult objective functions are hard to be optimized using GAs. Regarding the difficulty of a problem for a GA there is a well established theory. Traditionally, this has been studied for binary encoded …
Predicting Heuristic Search Performance with PageRank Centrality in Local Optima Networks
2015
Previous studies have used statistical analysis of fitness landscapes such as ruggedness and deceptiveness in order to predict the expected quality of heuristic search methods. Novel approaches for predicting the performance of heuristic search are based on the analysis of local optima networks (LONs). A LON is a compressed stochastic model of a fitness landscape's basin transitions. Recent literature has suggested using various LON network measurements as predictors for local search performance.In this study, we suggest PageRank centrality as a new measure for predicting the performance of heuristic search methods using local search. PageRank centrality is a variant of Eigenvector centrali…
Contribution to the knowledge of the therophytic flora of Sardinia
2003
The abundance of therophytes, largely contributes to the naturalistic value of Sardinia. Moreover, most of the annual species belonging to the Sardinian flora have an historical and cultural value, as they followed the men in his migrations and still reflect the different ways of traditional land exploitation characterising the island. As a matter of fact, the development of human technology increased number and frequency of the annual plants of Sardinia. Nowadays, annuals occur in several habitats of the island, where they play a primary ecological role, both as biomass producers and protecting the soil from rill erosion during the rainy season, at least where the environmental factors do …
AnABlast: Re-searching for Protein-Coding Sequences in Genomic Regions
2019
AnABlast is a computational tool that highlights protein-coding regions within intergenic and intronic DNA sequences which escape detection by standard gene prediction algorithms. DNA sequences with small protein-coding genes or exons, complex intron-containing genes, or degenerated DNA fragments are efficiently targeted by AnABlast. Furthermore, this algorithm is particularly useful in detecting protein-coding sequences with nonsignificant homologs to sequences in databases. AnABlast can be executed online at http://www.bioinfocabd.upo.es/anablast/ .