Distinctive Features of Mobile Messages Processing

World���s mobile market pushes past 2 billion lines in 2005. Success in these competitive markets requires operational excellence with product and service innovation to improve the mobile performance. Mobile users very often prefer to send a mobile instant message or text messages rather than talking on a mobile. Well developed ���written speech analysis��� does not work not only with ���verbal speech��� but also with ���mobile text messages���. The main purpose of our paper is, firstly, to highlight the problems of mobile text messages processing and, secondly, to show the possible ways of solving these problems.

Responsive fixture design using dynamic product inspection and monitoring technologies for the precision machining of large-scale aerospace parts

When machining a large-scale aerospace part, the part is normally located and clamped firmly until a set of features are machined. When the part is released, its size and shape may deform beyond the tolerance limits due to stress release. This paper presents the design of a new fixing method and flexible fixtures that would automatically respond to workpiece deformation during machining. Deformation is inspected and monitored on-line, and part location and orientation can be adjusted timely to ensure follow-up operations are carried out under low stress and with respect to the related datum defined in the design models.

Exploring demographic information in social media for product recommendation

In many e-commerce Web sites, product recommendation is essential to improve user experience and boost sales. Most existing product recommender systems rely on historical transaction records or Web-site-browsing history of consumers in order to accurately predict online users��� preferences for product recommendation. As such, they are constrained by limited information available on specific e-commerce Web sites. With the prolific use of social media platforms, it now becomes possible to extract product demographics from online product reviews and social networks built from microblogs. Moreover, users��� public profiles available on social media often reveal their demographic attributes such as age, gender, and education. In this paper, we propose to leverage the demographic information of both products and users extracted from social media for product recommendation. In specific, we frame recommendation as a learning to rank problem which takes as input the features derived from both product and user demographics. An ensemble method based on the gradient-boosting regression trees is extended to make it suitable for our recommendation task. We have conducted extensive experiments to obtain both quantitative and qualitative evaluation results. Moreover, we have also conducted a user study to gauge the performance of our proposed recommender system in a real-world deployment. All the results show that our system is more effective in generating recommendation results better matching users��� preferences than the competitive baselines.

Connecting social media to e-commerce:cold-start product recommendation using microblogging information

In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.

Mining product adopter information from online reviews for improving product recommendation

We present in this article an automated framework that extracts product adopter information from online reviews and incorporates the extracted information into feature-based matrix factorization formore effective product recommendation. In specific, we propose a bootstrapping approach for the extraction of product adopters from review text and categorize them into a number of different demographic categories. The aggregated demographic information of many product adopters can be used to characterize both products and users in the form of distributions over different demographic categories. We further propose a graphbased method to iteratively update user- and product-related distributions more reliably in a heterogeneous user-product graph and incorporate them as features into the matrix factorization approach for product recommendation. Our experimental results on a large dataset crawled from JINGDONG, the largest B2C e-commerce website in China, show that our proposed framework outperforms a number of competitive baselines for product recommendation.

Radiological characterization of clay mixed red mud in particular as regards its leaching features

<p>The reuse of industrial by-products such as red mud is of great importance. In the case of the building material industry the reuse of red mud requires a cautious attitude, since the enhanced radionuclide content of red mud can have an effect on human health. The natural radionuclide content of red mud from the Ajka red mud reservoir and the clay sample from a Hungarian brick factory were determined by gamma spectrometry. It was found that maximum 27.8% red mud content can be added to fulfil the conditions of the EU-BSS. The effect of heat treatment was investigated on a red mud-clay mixture and it was found that in the case of radon and thoron exhalation the applied heat reduced remarkably the exhalation capacities. The leaching features of red mud and different mixtures were studied according to the MSZ-21470-50 Hungarian standard, the British CEN/TS 14429 standard and the Tessier sequential extraction method. The Tessier method and the MSZ-21470-50 standard are suitable for the characterization of materials; however, they do not provide enough information for waste deposition purposes. To this end, we propose using the CEN/TS 14429 method, because it is easy to use, and gives detailed information about the material's behaviour under different pH conditions, however, further measurements are necessary.</p>

FEATURES OF THE BRAZILIAN PEOPLE IN GOTA D�����GUA

This paper aims to analyze elements of the play Gota d&rsquo;&aacute;gua, written by Chico Buarque and Paulo Pontes from televised script by Oduvaldo Vianna Filho, based on the tragedy Euripides&rsquo; Medea. The work preserves the central plot of the Greek text, but presents aspects of Brazilian reality and strong social content, dealing with themes that remain fairly current, such as right to housing, the situation of dependence of the poor class, the search for survival and maintenance power of action and decision in the hands of those who hold the capital. In the plot, recreated in suburban Rio, the representation of poor Brazilian workers emerges, with poverty being approached from a different profile than that spread by recent works of national literature, in which another facet of the lower social classes is highlighted, linking them to crime and violence, as well as the representation even more common, with an emphasis on black or northeastern origin. To this analysis we have purposed our considerations are guided primarily by studies of Antonio Candido (1970, 1989 and 2006) and Roberto Schwarz (1982 and 2000), joining artistic text and social series via character category, with characterization, a priori, through labor relations. Our approach lays not on Joana, representing Medea, the protagonist of that Greek tragedy, but especially from Egeu, minor character in the Euripides&rsquo; play, who, however, plays an important role in that modern version, being imperative in the wake of reflections of Brazilian society. On the other hand, we have observed that the entrepreneur Creonte Vasconcelos, who represents the power of capital, and Jas&atilde;o de Oliveira, a dubious character, who suffers more transformations during the plot, hesitating between the miserable universe of his origin and the economic power, rising socially, becoming a product of the cultural industry and leading us to think about the use of the most capable people by the capitalist system.

The Behavior of Hydroxyl Units of Synthetic Goethite and its Dehydroxylated Product Hematite

The behavior of the hydroxyl units of synthetic goethite and its dehydroxylated product hematite was characterized using a combination of Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) during the thermal transformation over a temperature range of 180-270 degrees C. Hematite was detected at temperatures above 200 degrees C by XRD while goethite was not observed above 230 degrees C. Five intense OH vibrations at 3212-3194, 1687-1674, 1643-1640, 888-884 and 800-798 cm(-1), and a H2O vibration at 3450-3445 cm(-1) were observed for goethite. The intensity of hydroxyl stretching and bending vibrations decreased with the extent of dehydroxylation of goethite. Infrared absorption bands clearly show the phase transformation between goethite and hematite: in particular. the migration of excess hydroxyl units from goethite to hematite. Two bands at 536-533 and 454-452 cm(-1) are the low wavenumber vibrations of Fe-O in the hematite structure. Band component analysis data of FTIR spectra support the fact that the hydroxyl units mainly affect the a plane in goethite and the equivalent c plane in hematite.

Study on microwave dielectric properties of epoxy resin mixtures used for rapid product development

This paper presents a preliminary study on the dielectric properties and curing of three different types of epoxy resins mixed at various stichiometric mixture of hardener, flydust and aluminium powder under microwave energy. In this work, the curing process of thin layers of epoxy resins using microwave radiation was investigated as an alternative technique that can be implemented to develop a new rapid product development technique. In this study it was observed that the curing time and temperature were a function of the percentage of hardener and fillers presence in the epoxy resins. Initially dielectric properties of epoxy resins with hardener were measured which was directly correlated to the curing process in order to understand the properties of cured specimen. Tensile tests were conducted on the three different types of epoxy resins with hardener and fillers. Modifying dielectric properties of the mixtures a significant decrease in curing time was observed. In order to study the microstructural changes of cured specimen the morphology of the fracture surface was carried out by using scanning electron microscopy.

Exploring the effectiveness of virtual product placement on recall and recognition of new brands

This paper investigates the effectiveness of virtual product placement as a marketing tool by examining the relationship between brand recall and recognition and virtual product placement. It also aims to address a gap in the existing academic literature by focusing on the impact of product placement on recall and recognition of new brands. The growing importance of product placement is discussed and a review of previous research on product placement and virtual product placement is provided. The research methodology used to study the recall and recognition effects of virtual product placement are described and key findings presented. Finally, implications are discussed and recommendations for future research provided.