Search results for "Artificial"
showing 10 items of 7394 documents
Classification of stilbenoid compounds by entropy of artificial intelligence
2013
A set of 66 stilbenoid compounds is classified into a system of periodic properties by using a procedure based on artificial intelligence, information entropy theory. Eight characteristics in hierarchical order are used to classify structurally the stilbenoids. The former five features mark the group or column while the latter three are used to indicate the row or period in the table of periodic classification. Those stilbenoids in the same group are suggested to present similar properties. Furthermore, compounds also in the same period will show maximum resemblance. In this report, the stilbenoids in the table are related to experimental data of bioactivity and antioxidant properties avail…
Nonlinear data description with Principal Polynomial Analysis
2012
Principal Component Analysis (PCA) has been widely used for manifold description and dimensionality reduction. Performance of PCA is however hampered when data exhibits nonlinear feature relations. In this work, we propose a new framework for manifold learning based on the use of a sequence of Principal Polynomials that capture the eventually nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) is shown to generalize PCA. Unlike recently proposed nonlinear methods (e.g. spectral/kernel methods and projection pursuit techniques, neural networks), PPA features are easily interpretable and the method leads to a fully invertible transform, which is a desirable property…
Modeling user preferences in content-based image retrieval: A novel attempt to bridge the semantic gap
2015
This paper is concerned with content-based image retrieval from a stochastic point of view. The semantic gap problem is addressed in two ways. First, a dimensional reduction is applied using the (pre-calculated) distances among images. The dimension of the reduced vector is the number of preferences that we allow the user to choose from, in this case, three levels. Second, the conditional probability distribution of the random user preference, given this reduced feature vector, is modeled using a proportional odds model. A new model is fitted at each iteration. The score used to rank the image database is based on the estimated probability function of the random preference. Additionally, so…
A principled approach to network-based classification and data representation
2013
Measures of similarity are fundamental in pattern recognition and data mining. Typically the Euclidean metric is used in this context, weighting all variables equally and therefore assuming equal relevance, which is very rare in real applications. In contrast, given an estimate of a conditional density function, the Fisher information calculated in primary data space implicitly measures the relevance of variables in a principled way by reference to auxiliary data such as class labels. This paper proposes a framework that uses a distance metric based on Fisher information to construct similarity networks that achieve a more informative and principled representation of data. The framework ena…
Spectral clustering with the probabilistic cluster kernel
2015
Abstract This letter introduces a probabilistic cluster kernel for data clustering. The proposed kernel is computed with the composition of dot products between the posterior probabilities obtained via GMM clustering. The kernel is directly learned from the data, is parameter-free, and captures the data manifold structure at different scales. The projections in the kernel space induced by this kernel are useful for general feature extraction purposes and are here exploited in spectral clustering with the canonical k-means. The kernel structure, informative content and optimality are studied. Analysis and performance are illustrated in several real datasets.
Fuzzy sigmoid kernel for support vector classifiers
2004
This Letter proposes the use of the fuzzy sigmoid function presented in (IEEE Trans. Neural Networks 14(6) (2003) 1576) as non-positive semi-definite kernel in the support vector machines framework. The fuzzy sigmoid kernel allows lower computational cost, and higher rate of positive eigenvalues of the kernel matrix, which alleviates current limitations of the sigmoid kernel.
Use of hierarchical Bayesian framework in MTS studies to model different causes and novel possible forms of acquired MTS
2015
Abstract: An integrative account of MTS could be cast in terms of hierarchical Bayesian inference. It may help to highlight a central role of sensory (tactile) precision could play in MTS. We suggest that anosognosic patients, with anesthetic hemisoma, can also be interpreted as a form of acquired MTS, providing additional data for the model.
Colour assessment of milk and milk products using computer vision system and colorimeter
2021
Abstract A computer vision system (CVS) and a colorimeter were compared for their abilities to measure the colour of twenty-seven different milks and milk products. The frequency of similarity test showed that CVS-generated colour chips were similar to the actual sample colour in all trials (100%). The CVS-obtained colours were found to be more similar to the colour of sample visualised on the monitor, compared with colorimeter-generated colour chips, with values of 83.3–100.0% depending on the milk product. The third test showed that there was difference between colour measured by CVS and the colorimeter; colorimeter readings resulted in a darker and yellower colour based on average L∗a∗b∗…
Normalization 2.0: A longitudinal analysis of German online campaigns in the national elections 2002–9
2011
This article examines the functional, relational and discursive dimensions of the normalization thesis in one study, for both Web 1.0 and Web 2.0 features, in a longitudinal design. It is based on a quantitative content and structural analysis of German party websites in the national elections between 2002 and 2009. The results show that the normalization thesis holds true in all its dimensions over time and in the Web 2.0 era: parties still focus on the top-down elements of information provision and delivery while interactive options are scarce. The digital divide between parliamentary and non-parliamentary parties has narrowed over time, but remains visible for all online functions in 200…