a robust and reliable quantitative structure-property relationship (qspr) study was established to forecast the melting points (mps)  of a diverse and long set including 250 drug-like compounds. based on the calculated descriptors by dragon software package, to detect homogeneities and to split the whole dataset into training and test sets, a principal component analysis (pca) approach was used...

bearing capacity prediction of axially loaded piles is one of the most important problems in geotechnical engineering practices, with a wide variety range of methods which have been introduced to forecast it accurately. machine learning methods have been reported by many contemporary researches with some degree of success in modeling geotechnical phenomena. in this study, a fairly new machine l...

In this work some quantitative structure activity relationship models were developed for prediction of three bioenvironmental parameters of 28 volatile organic compounds, which are used in assessing the behavior of pollutants in soil. These parameters are; half-life, non dimensional effective degradation rate constant and effective Péclet number in two type of soil. The most effective descripto...

Background: Diabetes mellitus as a chronic disease is the most common disease caused by metabolic disorders and it is one of the most important health issues all around the world. Nowadays, data mining methods are applied in different fields of sciences due to data mining methods capability. Therefore, in this study, we compared the efficiency of data mining methods in predicting type 2 diabete...

January is is the second progress report for Project /// (Generative Kernels and Score Spaces for Classiication of Speech) within the Global Uncertainties Programme. is project combines the current generative models developed in the speech community with discriminative classiiers. An important aspect of the approach is that the generative models are used to deene a score-space that can be used ...

Audio is one of important information carriers in the multimedia. It contains abundant semantics and enriches information perception and acquisition. At present, it always uses vision information in the multimedia retrieval, but ignores audio information. In this paper, the problem of audio classification is discussed. The combination of Support Vector Machine and Hidden Markov Model is describ...

This paper proposes a simple model for speaker recognition based on i–vector pairs, and analyzes its similarity and differences with respect to the state–of–the–art Probabilistic Linear Discriminant Analysis (PLDA) and Pairwise Support Vector Machine (PSVM) models. Similar to the discriminative PSVM approach, we propose a generative model of i–vector pairs, rather than an usual i–vector based m...

The use of discriminative models is an interesting alternative to generative models for speech recognition. This paper examines one form of these models, structured support vector machines (SVMs), for noise robust speech recognition. One important aspect of structured SVMs is the form of the joint feature space. In this work features based on generative models are used, which allows model-based...