Text mining na análise de sentimentos em contextos de big data

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Metaphorisms in programming

This paper introduces the metaphorism pattern of relational specification and addresses how specification following this pattern can be refined into recursive programs. Metaphorisms express input-output relationships which preserve relevant information while at the same time some intended optimization takes place. Text processing, sorting, representation changers, etc., are examples of metaphorisms. The kind of metaphorism refinement proposed in this paper is a strategy known as change of virtual data structure. It gives sufficient conditions for such implementations to be calculated using relation algebra and illustrates the strategy with the derivation of quicksort as example.

Thermal technologies in food processing

[Excerpt] Introduction: Thermal processing is probably the most important process in food industry that has been used since prehistoric times, when it was discovered that heat enhanced the palatability and the life of the heat-treated food. Thermal processing comprehends the heating of foods at a defined temperature for a certain length of time. However, in some foods, the high thermotolerance of certain enzymes and microorganisms, their physical properties (e.g.,highviscosity),ortheircomponents(e.g.,solidfractions) require the application of extreme heat treatments that not only are energy intensive, but also will adversely affect the nutritional and organoleptic properties of the food. Technologies such as ohmic heating, dielectric heating (which includes microwave heating and radiofrequency heating), inductive heating, and infrared heating are available to replace, or complement, the traditional heat-dependent technologies (heating through superheated steam, hot air, hot water, or other hot liquid, being the heating achieved either through direct contact with those agents – mostly superheated steam – or through contact with a hot surface which is in turn heated by such agents). Given that the “traditional” heatdependent technologies are thoroughly described in the literature, this text will be mainly devoted to the so-called “novel” thermal technologies. (...)

In-line rheo-optical characterization during small-scale polymer processing and compounding

As increasingly more sophisticated materials and products are being developed and times-to-market need to be minimized, it is important to make available fast response characterization tools using small amounts of sample, capable of conveying data on the relationships between rheological response, process-induced material structure and product characteristics. For this purpose, a single / twin-screw mini-extrusion system of modular construction, with well-controlled outputs in the range 30-300 g/h, was coupled to a in- house developed rheo-optical slit die able to measure shear viscosity and normal-stress differences, as well as performing rheo-optical experiments, namely small angle light scattering (SALS) and polarized optical microscopy (POM). In addition, the mini-extruder is equipped with ports that allow sample collection, and the extrudate can be further processed into products to be tested later. Here, we present the concept and experimental set-up [1, 2]. As a typical application, we report on the characterization of the processing of a polymer blend and of the properties of extruded sheets. The morphological evolution of a PS/PMMA industrial blend along the extruder, the flow-induced structures developed and the corresponding rheological characteristics are presented, together with the mechanical and structural characteristics of produced sheets. The application of this experimental tool to other material systems will also be discussed.

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

Enzymatic processing of protein-based fibers

Wool and silk are major protein fiber materials used by the textile industry. Fiber protein structure-function relationships are briefly described here, and the major enzymatic processing routes for textiles and other novel applications are deeply reviewed. Fiber biomodification is described here with various classes of enzymes such as protease, transglutaminase, tyrosinase, and laccase. It is expected that the reader will get a perspective on the research done as a basis for new applications in other areas such as cosmetics and pharma.

The role of social cognition and motor imagery in gesture processing: a patients' study

Dissertação de mestrado integrado em Psicologia

The role of deviant-letter position in cognate word processing

Dissertação de mestrado integrado em Psicologia

Reconstructing transcriptional regulatory networks using data integration and text mining

Transcriptional Regulatory Networks (TRNs) are powerful tool for representing several interactions that occur within a cell. Recent studies have provided information to help researchers in the tasks of building and understanding these networks. One of the major sources of information to build TRNs is biomedical literature. However, due to the rapidly increasing number of scientific papers, it is quite difficult to analyse the large amount of papers that have been published about this subject. This fact has heightened the importance of Biomedical Text Mining approaches in this task. Also, owing to the lack of adequate standards, as the number of databases increases, several inconsistencies concerning gene and protein names and identifiers are common. In this work, we developed an integrated approach for the reconstruction of TRNs that retrieve the relevant information from important biological databases and insert it into a unique repository, named KREN. Also, we applied text mining techniques over this integrated repository to build TRNs. However, was necessary to create a dictionary of names and synonyms associated with these entities and also develop an approach that retrieves all the abstracts from the related scientific papers stored on PubMed, in order to create a corpora of data about genes. Furthermore, these tasks were integrated into @Note, a software system that allows to use some methods from the Biomedical Text Mining field, including an algorithms for Named Entity Recognition (NER), extraction of all relevant terms from publication abstracts, extraction relationships between biological entities (genes, proteins and transcription factors). And finally, extended this tool to allow the reconstruction Transcriptional Regulatory Networks through using scientific literature.

On the routines of wild-type silk fibroin processing toward silk-inspired materials: a review

For years, silk fibroin of a domestic silkworm, Bombyx mori, has been recognized as a valuable material and extensively used. In the last decades, new application fields are emerging for this versatile material. Those final, specific applications of silk dictate the way it has been processed in industry and research. This review focuses on the description of various approaches for silk downstream processing in a laboratory scale, that fall within several categories. The detailed description of workflow possibilities from the naturally found material to a finally formulated product is presented. Considerable attention is given to (bio-) chemical approaches of silk fibroin transformation, particularly, to its enzyme-driven modifications. The focus of the current literature survey is exclusively on the methods applied in research and not industry.

Processing and characterization of plates made from granulate of waste electrical cables

This article is intended to evaluate the density and the mechanical, acoustic and thermal properties of compression moulded plates composed of granulate from electrical cables wastes. Those cable wastes are the insulation part from the electric cables, and are composed of PVC, PE, EMP and PEX rubber. After these materiais lose their initial properties and cease to be useful as insulation material, due to safety requirements, it is possible to reuse them into new applications like industrial or playground floorings, as sound insulation material to be applied in walls or floors, or to dampen vibrations from equipments. Recovering electric cable waste has been a major concern to the European Commission due to its leveis of toxicity when incineration and land fill ing is the solution to dispose this material. Such as the European Commission's study for DG Xl[1] suggested that recycling may be the most favourable future waste management option.

Abnormalities in the processing of emotional prosody from single words in schizophrenia

Background: Abnormalities in emotional prosody processing have been consistently reported in schizophrenia and are related to poor social outcomes. However, the role of stimulus complexity in abnormal emotional prosody processing is still unclear. Method: We recorded event-related potentials in 16 patients with chronic schizophrenia and 16 healthy controls to investigate: 1) the temporal course of emotional prosody processing; and 2) the relative contribution of prosodic and semantic cues in emotional prosody processing. Stimuli were prosodic single words presented in two conditions: with intelligible (semantic content condition—SCC) and unintelligible semantic content (pure prosody condition—PPC). Results: Relative to healthy controls, schizophrenia patients showed reduced P50 for happy PPC words, and reduced N100 for both neutral and emotional SCC words and for neutral PPC stimuli. Also, increased P200 was observed in schizophrenia for happy prosody in SCC only. Behavioral results revealed higher error rates in schizophrenia for angry prosody in SCC and for happy prosody in PPC. Conclusions: Together, these data further demonstrate the interactions between abnormal sensory processes and higher-order processes in bringing about emotional prosody processing dysfunction in schizophrenia. They further suggest that impaired emotional prosody processing is dependent on stimulus complexity.

The music of language: an ERP investigation of the effects of musical training on emotional prosody processing

Recent studies have demonstrated the positive effects of musical training on the perception of vocally expressed emotion. This study investigated the effects of musical training on event-related potential (ERP) correlates of emotional prosody processing. Fourteen musicians and fourteen control subjects listened to 228 sentences with neutral semantic content, differing in prosody (one third with neutral, one third with happy and one third with angry intonation), with intelligible semantic content (semantic content condition--SCC) and unintelligible semantic content (pure prosody condition--PPC). Reduced P50 amplitude was found in musicians. A difference between SCC and PPC conditions was found in P50 and N100 amplitude in non-musicians only, and in P200 amplitude in musicians only. Furthermore, musicians were more accurate in recognizing angry prosody in PPC sentences. These findings suggest that auditory expertise characterizing extensive musical training may impact different stages of vocal emotional processing.

Automatic distinction of Fernando Pessoas’ heteronyms

Text Mining has opened a vast array of possibilities concerning automatic information retrieval from large amounts of text documents. A variety of themes and types of documents can be easily analyzed. More complex features such as those used in Forensic Linguistics can gather deeper understanding from the documents, making possible performing di cult tasks such as author identi cation. In this work we explore the capabilities of simpler Text Mining approaches to author identification of unstructured documents, in particular the ability to distinguish poetic works from two of Fernando Pessoas' heteronyms: Alvaro de Campos and Ricardo Reis. Several processing options were tested and accuracies of 97% were reached, which encourage further developments.