Opinion mining and sentiment analysis for Arabic on-line texts: application on the political domain

Since the continuous proliferation of the journalistic content online and the changing political landscape in many Arabic countries, we started our current research in order to implement a media monitoring system about the opinion mining in political field. This system allows political actors, despite of the large volume of online data, to be constantly informed about opinions expressed on the web in order to properly monitor their actual standing, orient their communication strategy and prepare the election campaigns. The developed system is based on a linguistic approach using NooJ’s linguistic engine to formalize the automatic recognition rules and apply them to a dynamic corpus composed of journalistic articles. The first implemented rules allow identifying and annotating the different political entities (political actors and organizations). Then these annotations are used in our system of media monitoring in order to identify the opinions associated with the extracted named entities. The system is mainly based on a set of local grammars developed for the identification of different structures of the political opinion phrases. These grammars are using the entries of the opinion lexicon that contain the different opinion words (verbs, adjectives, nouns) where each entry is associated with the corresponding semantic marker (polarity and intensity). Our developed system is able to identify and properly annotate the opinion holder, the opinion target and the polarity (positive or negative) of the phraseological expression (nominal or verbal) expressing the opinion. Our experiments showed that the adopted method of extraction is consistent with 0.83 F-measure.     

Optoelectrical Behavior of Ferroelectric Lithium Rubidium Sulfate Crystals

Single crystals of lithium rubidium sulfate with good transparency have been grown from aqueous solution by a slow evaporation technique. Single-crystal x-ray diffraction results revealed that, at room temperature, the crystal belongs to the monoclinic system in space group P2₁/n. From the transmittance and reflectance spectra, various optoelectrical constants such as the refractive index, extinction coefficient, optical bandgap for direct transition, optical conductivity, electronic polarizability, high-frequency dielectric constant, and optical electronegativity were calculated for the investigated lithium rubidium sulfate crystal. A correlation between the various optical parameters was also observed. The refractive index was fit to a three-term Cauchy dispersion relationship. The single-oscillator Wemple–DiDomenico model was applied to discuss the dispersion of the refractive index. The optical transmittance study revealed transparency of the crystal in the entire visible region with wide optical bandgap. The electronic polarizability values calculated from the Clausius–Mossotti equation and from bandgap analysis were found to be in good agreement.     

Energy efficient communications over the AWGN relay channel

This paper addresses the energy efficiency analysis of the relay channel under additive white Gaussian noise. We consider the rate bounds given by decode and forward and the cut set bound and assume that resources are optimally allocated to maximize the spectral efficiency according to the channel information and the sum network energy. The low energy analysis tools are used to compute the maximum rate per energy (RPE) and the slope of the spectral efficiency as a function of the energy per bit. Using these metrics, the energy efficiency benefit of several capabilities at terminals is investigated. Specifically, we take into account: i) the phase synchronization between transmitters, ii) the full duplex capability at the relay and iii) the channel access via superposition.     

Effects of oil and natural or synthetic vitamin E on ruminal and milk fatty acid profiles in cows receiving a high-starch diet

Among trans fatty acids, trans-10,cis-12 CLA has negative effects on cow milk fat production and can affect human health. In high-yielding dairy cows, a shift from the trans-11 to the trans-10 pathway of biohydrogenation (BH) can occur in the rumen of cows receiving high-concentrate diets, especially when the diet is supplemented with unsaturated fat sources. In some but not all experiments, vitamin E has been shown to control this shift. To ascertain the effects of vitamin E on this shift of BH pathway, 2 studies were conducted. The first study explored in vitro the effects of addition of natural (RRR-α-tocopherol acetate) and synthetic (dl-α-tocopherol acetate) vitamin E. Compared with control and synthetic vitamin E, the natural form resulted in a greater trans-10/trans-11 ratio; however, the effect was very low, suggesting that vitamin E was neither a limiting factor for rumen BH nor a modulator of the BH pathway. An in vivo study investigated the effect of natural vitamin E (RRR-α-tocopherol) on this shift and subsequent milk fat depression. Six rumen-fistulated lactating Holstein cows were assigned to a 2 × 2 crossover design. Cows received 20-kg DM of a control diet based on corn silage with 22% of wheat, and after 2 wk of adaptation, the diet was supplemented with 600 g of sunflower oil for 2 more weeks. During the last week of this 4-wk experimental period, cows were divided into 2 groups: an unsupplemented control group and a group receiving 11 g of RRR-α-tocopherol acetate per day. A trans-10 shift of ruminal BH associated with milk fat depression due to oil supplementation of a high-wheat diet was observed, but vitamin E supplementation of dairy cows did not result in a reversal toward a trans-11 BH pathway, and did not restore milk fat content.     

Synthesis, characterization, electrical and thermal properties of nanocomposite of polythiophene with nanophotoadduct: a potent composite for electronic use

Materials having high thermal stability and electrical conductivity form potential candidates for electronics. In this study, a thermally stable nanocomposite of nanophotoadduct of pentaamminechlorocobalt(III) chloride with hexamine and polythiophene (PTh) was prepared by oxidative chemical polymerization in the presence of FeCl₃ as oxidant and thiophene monomer. Photoadduct was obtained by photoirradiation followed by substitution with hexamine ligand which was then milled in G5 planetary ball mill to obtain nanophotoadduct which is confirmed by X-ray powder diffraction. The formation of nanophotoadduct and its incorporation in PTh structure was endorsed by fourier transform infrared analysis. Empirical formula of the nanophotoadduct was found to be [Co(NH₃)₂(OH)₃C₆H₁₂N₄]·2H₂O. SEM analysis revealed uniform distribution of nanophotoadduct in PTh matrix. Crystallite size and strain analysis revealed further decrease in size from 34 (nanophotoadduct) to 15 nm (nanocomposite) using different methods of analysis which were well correlated. This size reduction was attributed to the microstrain in the nanocomposite. TG revealed that the nanocomposite and PTh underwent 62 and 80 % weight loss at 1,000 °C respectively which clearly indicated the higher thermal stability of nanocomposite compared to pure PTh. Little change in the glass transition temperatures of PTh (170 °C) and nanocomposite (167 °C) is observed from DSC which indicated smaller plasticizing effect of nanophotoadduct. I–V curves of nanophotoadduct showed its diode like behavior while as nanocomposite depict nearly ohmic behavior. These results illustrate that the nanophotoadduct play two important roles, one that it acts as a Schottky diode material and second that it increases the conductance and thermal stability of PTh. Nanocomposite thus obtained can operate at relatively high temperatures in electrical appliances.     

Learning with intelligent tutors and worked examples: selecting learning activities adaptively leads to better learning outcomes than a fixed curriculum

The main learning activity provided by intelligent tutoring systems is problem solving, although several recent projects investigated the effectiveness of combining problem solving with worked examples. Previous research has shown that learning from examples is an effective learning strategy, especially for novice learners. A worked example provides step-by-step explanations of how a problem is solved. Many studies have compared learning from examples to unsupported problem solving, and suggested presenting worked examples to students in the initial stages of learning, followed by problem solving once students have acquired enough knowledge. This paper presents a study in which we compare a fixed sequence of alternating worked examples and tutored problem solving with a strategy that adapts learning tasks to students’ needs. The adaptive strategy determines the type of the task (a worked example, a faded example or a problem to be solved) based on how much assistance the student received on the previous problem. The results show that students in the adaptive condition learnt significantly more than their peers who were presented with a fixed sequence of worked examples and problem solving. Novices from the adaptive condition learnt faster than novices from the control group, while the advanced students from the adaptive condition learnt more than their peers from the control group.     

Study on thickness loss of cut-pile carpet produced with heat process modified polyester pile yarn. Part II: dynamic loading

Thickness loss (TL) is one of the most important mechanical properties in each carpet. In this research, four types of ATY polyester pile yarns were used to prepare the cut-pile carpet samples. They were normal ATY polyester filament pile yarns and three yarns that modified by heat processes including friezing, heat setting, and twist heat setting. Woven carpet samples are subjected to standard dynamic loading test. Results show that friezing and heat setting processes have no significant effects on carpet dynamic recovery or TL after dynamic loading. Also, decreasing temperature of twist heat setting, the polyester pile yarns could not modify carpet TL after dynamic loading.     

Online short text clustering using infinite extensions of discrete mixture models

Short text clustering is one of the fundamental tasks in natural language processing. Different from traditional documents, short texts are ambiguous and sparse due to their short form and the lack of recurrence in word usage from one text to another, making it very challenging to apply conventional machine learning algorithms directly. In this article, we propose two novel approaches for short texts clustering: collapsed Gibbs sampling infinite generalized Dirichlet multinomial mixture model infinite GSGDMM) and collapsed Gibbs sampling infinite Beta-Liouville multinomial mixture model (infinite GSBLMM). We adopt two flexible and practical priors to the multinomial distribution where in the first one the generalized Dirichlet distribution is integrated, while the second one is based on the Beta-Liouville distribution. We evaluate the proposed approaches on two famous benchmark datasets, namely, Google News and Tweet. The experimental results demonstrate the effectiveness of our models compared to basic approaches that use Dirichlet priors. We further propose to improve the performance of our methods with an online clustering procedure. We also evaluate the performance of our methods for the outlier detection task, in which we achieve accurate results.     

Bounded multivariate generalized Gaussian mixture model using ICA and IVA

Pattern Analysis and Applications - A bounded multivariate generalized Gaussian mixture model with a full covariance matrix is proposed for modeling data in a bounded support region. For model...