Search results for "Tributi"

Smart city dvelopment with digital twin technology

2020

Growing urban areas are major consumers of natural resources, energy and raw materials. Understanding cities´ urban metabolism is salient when developing sustainable and resilient cities. This paper addresses concepts of smart city and digital twin technology as means to foster more sustainable urban development. Smart city has globally been well adopted concept in urban development. With smart city development cities aim to optimize overall performance of the city, its infrastructures, processes and services, but also to improve socio-economic wellbeing. Dynamic digital twins are constituted to form real-time connectivity between virtual and physical objects. Digital twin combines virtual …

Chlorinated Ethanes: Sources, Distribution, Environmental Impact, and Health Effects

1984

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.

Predictive and Contextual Feature Separation for Bayesian Metanetworks

2007

Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, depending on a context, many attributes of the model might not be relevant. If a Bayesian Network has been learned across multiple contexts then all uncovered conditional dependencies are averaged over all contexts and cannot guarantee high predictive accuracy when applied to a concrete case. We are considering a context as a set of contextual attributes, which are not directly effect probability distribution of the target attributes, but they effect on "relevance" of the predictive attributes towards target attribut…

Prediction of Disease–lncRNA Associations via Machine Learning and Big Data Approaches

2021

This chapter introduces long non-coding RNAs and their role in the occurrence and progress of diseases. The discovery of novel lncRNA-disease associations may provide valuable input to the understanding of disease mechanisms at the lncRNA level, as well as to the detection of biomarkers for disease diagnosis, treatment, prognosis, and prevention. Unfortunately, due to costs and time complexity, the number of possible disease-related lncRNAs verified by traditional biological experiments is very limited. Computational approaches for the prediction of potential disease-lncRNA associations can effectively decrease the time and cost of biological experiments. We first review the main computatio…

Assessment of qualitative judgements for conditional events in expert systems

1991

Capacity studies of spatially correlated MIMO Rice channels

2010

In this paper, we have studied the statistical properties of the capacity of spatially correlated multiple-input multiple-output (MIMO) Rice channels. We have derived an exact closed-form expression for the probability density function (PDF) and an exact expression for the cumulative distribution function (CDF) of the channel capacity for single-input multiple-output (SIMO) and multiple-input single-output (MISO) systems. Furthermore, an accurate closed-form expression has been derived for the level-crossing rate (LCR) and an accurate expression has been obtained for the average duration of fades (ADF) of the SIMO and MISO channel capacities. For the MIMO case, we have investigated the PDF,…