PROBABILITY DISTRIBUTION OVER THE SET OF CLASSES IN ARABIC DIALECT CLASSIFICATION TASK

Subject of Research.We propose an approach for solving machine learning classification problem that uses the information about the probability distribution on the training data class label set. The algorithm is illustrated on a complex natural language processing task - classification of Arabic dialects. Method. Each object in the training set is associated with a probability distribution over the class label set instead of a particular class label. The proposed approach solves the classification problem taking into account the probability distribution over the class label set to improve the quality of the built classifier. Main Results. The suggested approach is illustrated on the automatic Arabic dialects classification example. Mined from the Twitter social network, the analyzed data contain word-marks and belong to the following six Arabic dialects: Saudi, Levantine, Algerian, Egyptian, Iraq, Jordan, and to the modern standard Arabic (MSA). The paper results demonstrate an increase of the quality of the built classifier achieved by taking into account probability distributions over the set of classes. Experiments carried out show that even relatively naive accounting of the probability distributions improves the precision of the classifier from 44% to 67%. Practical Relevance. Our approach and corresponding algorithm could be effectively used in situations when a manual annotation process performed by experts is connected with significant financial and time resources, but it is possible to create a system of heuristic rules. The implementation of the proposed algorithm enables to decrease significantly the data preparation expenses without substantial losses in the precision of the classification

Nuclei transformations in electric discharge conditions

The products obtained through a low-energy electric discharge between carbon electrodes in glycerin's water solution are investigated by means of Mass Spectrometry, Raster Electronic Microscopy, and X-ray Fluorescence Analysis. The residue formed during experiment is found to possess chemical composition differing from the initial components by its chemistry and macrostructure. The mechanism and the catalyst of a lowenergy nuclear transformation course are discussed

Magnetic phase composition of strontium titanate implanted with iron ions

Thin magnetic films were synthesized by means of implantation of iron ions into single-crystalline (1 0 0) substrates of strontium titanate. Depth-selective conversion electron Mössbauer spectroscopy (DCEMS) indicates that origin of the samples magnetism is α-Fe nanoparticles. Iron-substituted strontium titanate was also identified but with paramagnetic behaviour at room temperature. Surface magneto-optical Kerr effect (SMOKE) confirms that the films reveal superparamagnetism (the low-fluence sample) or ferromagnetism (the high-fluence sample), and demonstrate absence of magnetic in-plane anisotropy. These findings highlight iron implanted strontium titanate as a promising candidate for composite multiferroic material and also for gas sensing applications. © 2011 Elsevier Ltd. All rights reserved

A study of active power losses in the asynchronous motor in function of the supply voltage

Проведені дослідження втрат активної потужності в електродвигуні у функції коефіцієнта завантаження та рівня живлячої напруг

Nuclei transformations in electric discharge conditions

The products obtained through a low-energy electric discharge between carbon electrodes in glycerin's water solution are investigated by means of Mass Spectrometry, Raster Electronic Microscopy, and X-ray Fluorescence Analysis. The residue formed during experiment is found to possess chemical composition differing from the initial components by its chemistry and macrostructure. The mechanism and the catalyst of a lowenergy nuclear transformation course are discussed

Nuclei transformations in electric discharge conditions

The products obtained through a low-energy electric discharge between carbon electrodes in glycerin's water solution are investigated by means of Mass Spectrometry, Raster Electronic Microscopy, and X-ray Fluorescence Analysis. The residue formed during experiment is found to possess chemical composition differing from the initial components by its chemistry and macrostructure. The mechanism and the catalyst of a lowenergy nuclear transformation course are discussed

Nuclei transformations in electric discharge conditions

The products obtained through a low-energy electric discharge between carbon electrodes in glycerin's water solution are investigated by means of Mass Spectrometry, Raster Electronic Microscopy, and X-ray Fluorescence Analysis. The residue formed during experiment is found to possess chemical composition differing from the initial components by its chemistry and macrostructure. The mechanism and the catalyst of a lowenergy nuclear transformation course are discussed

Magnetic phase composition of strontium titanate implanted with iron ions

Thin magnetic films were synthesized by means of implantation of iron ions into single-crystalline (1 0 0) substrates of strontium titanate. Depth-selective conversion electron Mössbauer spectroscopy (DCEMS) indicates that origin of the samples magnetism is α-Fe nanoparticles. Iron-substituted strontium titanate was also identified but with paramagnetic behaviour at room temperature. Surface magneto-optical Kerr effect (SMOKE) confirms that the films reveal superparamagnetism (the low-fluence sample) or ferromagnetism (the high-fluence sample), and demonstrate absence of magnetic in-plane anisotropy. These findings highlight iron implanted strontium titanate as a promising candidate for composite multiferroic material and also for gas sensing applications. © 2011 Elsevier Ltd. All rights reserved

Magnetic phase composition of strontium titanate implanted with iron ions

Thin magnetic films were synthesized by means of implantation of iron ions into single-crystalline (1 0 0) substrates of strontium titanate. Depth-selective conversion electron Mössbauer spectroscopy (DCEMS) indicates that origin of the samples magnetism is α-Fe nanoparticles. Iron-substituted strontium titanate was also identified but with paramagnetic behaviour at room temperature. Surface magneto-optical Kerr effect (SMOKE) confirms that the films reveal superparamagnetism (the low-fluence sample) or ferromagnetism (the high-fluence sample), and demonstrate absence of magnetic in-plane anisotropy. These findings highlight iron implanted strontium titanate as a promising candidate for composite multiferroic material and also for gas sensing applications. © 2011 Elsevier Ltd. All rights reserved