O presente estudo tem por objetivo analisar Colocações Lexicais Especializadas (CLEs) da Hemodinâmica que apresentam bases nominais, por meio da Teoria Sentido-Texto. CLEs são colocações (agrupamentos lexicais) típicas de linguagem especializada que contém em sua constituição uma unidade terminológica, que pode ou não ser a base, além de elementos chamados de colocados, que são especificadores ou caracterizadores da base. Colocados são sempre selecionados em função da base. Além disso, outra forte característica das CLEs é o seu caráter semicomposicional ou fortemente composicional. Assim, para realizar tal objetivo, metodologicamente, escolhemos selecionar 37 CLEs a partir de termos típicos do Vocabulário Panlatino de Hemodinâmica da Realiter. A fim de constatar que os termos escolhidos participavam de colocações ativas na área, recorremos a artigos científicos (pesquisados na plataforma SciELO). Os artigos serviram de fonte para extrairmos as provas textuais das CLEs analisadas e para a formulação das definições dessas CLEs A análise dos dados permitiu que identificássemos as seguintes características das CLEs da Hemodinâmica: (i) quanto à extensão dos elementos (CLEs têm de 2 a 5 elementos); (ii) sobre a característica dos termos que exerciam papel de base nas CLEs examinadas (constituíram núcleos cem por cento nominais); (iii) sobre as características do complemento da base (complementos adjetivais, a maioria, e preposicionais); (iv) quanto aos tipos de Funções Lexicais (FLs) (adjetivais aplicadas a bases com complemento adjetival, preposicionais aplicadas a bases com complemento preposicional); (v) quanto à complexidade da FL (uso apenas de FL simples); e, por fim, (vi) sobre a necessidade de acréscimo de informação à FLs standards (em todos os casos houve acréscimo de informações para completar o sentido da definição, isto é, lançamos mão de FLs não-standards). / This study aims to analyze Specialized Lexical Combinations (SLCs) of Hemodynamic, with nominal base, through Meaning-Text Theory. SLCs are typical collocations (lexical groups) of specialized language that contain in their constitution a terminological unit, which may or may not be a base, in addition to elements called collocatives which are specifiers or characterizers of the base. Collocatives are always selected as a function of the base. In addition, another strong feature of SLCs is your semicomposicional or strongly compositional character. Thus, to achieve this goal, methodologically, we selected the 37 SLCs from typical terms present in the ‘Vocabulário Planlatino de Hemodinâmica’ of Realiter. In order to verify that the chosen terms participate in active placements in the area, we resorted to scientific articles from SciELO platform. The articles served as a source for extracting textual evidence for SLCs and formulating the definitions of SLCs. The analysis of the admissible data identifies the following characteristics of Hemodynamic SLCs: (i) the extension of the elements; (ii) the feature of terms that play the hole of base in the SLCs examined; (iii) the characteristics of the base complement; (iv) the types of Lexical Functions applied in the SLCs; (v) the complexity of LFs applied; and finally (vi) the necessity to increase information in the LFs standard (in all cases, there was added information to complete the meaning of the definition, we applied non-standard LFs).

The popularity of digital image and video is increasing rapidly. To help users navigate libraries of image and video, Content Based Information Retrieval (CBIR) system that can automatically index image and video documents are needed. However, due to the semantic gap between low-level machine descriptors and high-level semantic descriptors, the existing CBIR systems are still far from perfect. Text embedded in multi-media data, as a well-defined model of concepts for humans' communication, contains much semantic information related to the content. This text information can provide a much truer form of content-based access to the image and video documents if it can be extracted and harnessed efficiently. This dissertation solves the problem involved in detecting text object in image and video and tracking text event in video. For text detection problem, we propose a new unsupervised text detection algorithm. A new text model is constructed to describe text object using pictorial structure. Each character is a part in the model and every two neighboring characters are connected by a spring-like link. Two characters and the link connecting them are defined as a text unit. We localize candidate parts by extracting closed boundaries and initialize the links by connecting two neighboring candidate parts based on the spatial relationship of characters. For every candidate part, we compute character energy using three new character features, averaged angle difference of corresponding pairs, fraction of non-noise pairs, and vector of stroke width. They are extracted based on our observation that the edge of a character can be divided into two sets with high similarities in length, curvature, and orientation. For every candidate link, we compute link energy based on our observation that the characters of a text typically align along certain direction with similar color, size, and stroke width. For every candidate text unit, we combine character and link energies to compute text unit energy which indicates the probability that the candidate text model is a real text object. The final text detection results are generated using a text unit energy based thresholding. For text tracking problem, we construct a text event model by using pictorial structure as well. In this model, the detected text object in each video frame is a part and two neighboring text objects of a text event are connected by a spring-like link. Inter-frame link energy is computed for each link based on the character energy, similarity of neighboring text objects, and motion information. After refining the model using inter-frame link energy, the remaining text event models are marked as text events. At character level, because the proposed method is based on the assumption that the strokes of a character have uniform thickness, it can detect and localize characters from different languages in different styles, such as typewritten text or handwriting text, if the characters have approximately uniform stroke thickness. At text level, however, because the spatial relationship between two neighboring characters is used to localize text objects, the proposed method may fail to detect and localize the characters with multiple separate strokes or connected characters. For example, some East Asian language characters, such as Chinese, Japanese, and Korean, have many strokes of a single character. We need to group the strokes first to form single characters and then group characters to form text objects. While, the characters of some languages, such Arabic and Hindi, are connected together, we cannot extract spatial information between neighboring characters since they are detected as a single character. Therefore, in current stage the proposed method can detect and localize the text objects that are composed of separate characters with connected strokes with approximately uniform thickness. We evaluated our method comprehensively using three English language-based image and video datasets: ICDAR 2003/2005 text locating dataset (258 training images and 251 test images), Microsoft Street View text detection dataset (307 street view images), and VACE video dataset (50 broadcast news videos from CNN and ABC). The experimental results demonstrate that the proposed text detection method can capture the inherent properties of text and discriminate text from other objects efficiently.

O presente estudo tem por objetivo analisar Colocações Lexicais Especializadas (CLEs) da Hemodinâmica que apresentam bases nominais, por meio da Teoria Sentido-Texto. CLEs são colocações (agrupamentos lexicais) típicas de linguagem especializada que contém em sua constituição uma unidade terminológica, que pode ou não ser a base, além de elementos chamados de colocados, que são especificadores ou caracterizadores da base. Colocados são sempre selecionados em função da base. Além disso, outra forte característica das CLEs é o seu caráter semicomposicional ou fortemente composicional. Assim, para realizar tal objetivo, metodologicamente, escolhemos selecionar 37 CLEs a partir de termos típicos do Vocabulário Panlatino de Hemodinâmica da Realiter. A fim de constatar que os termos escolhidos participavam de colocações ativas na área, recorremos a artigos científicos (pesquisados na plataforma SciELO). Os artigos serviram de fonte para extrairmos as provas textuais das CLEs analisadas e para a formulação das definições dessas CLEs A análise dos dados permitiu que identificássemos as seguintes características das CLEs da Hemodinâmica: (i) quanto à extensão dos elementos (CLEs têm de 2 a 5 elementos); (ii) sobre a característica dos termos que exerciam papel de base nas CLEs examinadas (constituíram núcleos cem por cento nominais); (iii) sobre as características do complemento da base (complementos adjetivais, a maioria, e preposicionais); (iv) quanto aos tipos de Funções Lexicais (FLs) (adjetivais aplicadas a bases com complemento adjetival, preposicionais aplicadas a bases com complemento preposicional); (v) quanto à complexidade da FL (uso apenas de FL simples); e, por fim, (vi) sobre a necessidade de acréscimo de informação à FLs standards (em todos os casos houve acréscimo de informações para completar o sentido da definição, isto é, lançamos mão de FLs não-standards). / This study aims to analyze Specialized Lexical Combinations (SLCs) of Hemodynamic, with nominal base, through Meaning-Text Theory. SLCs are typical collocations (lexical groups) of specialized language that contain in their constitution a terminological unit, which may or may not be a base, in addition to elements called collocatives which are specifiers or characterizers of the base. Collocatives are always selected as a function of the base. In addition, another strong feature of SLCs is your semicomposicional or strongly compositional character. Thus, to achieve this goal, methodologically, we selected the 37 SLCs from typical terms present in the ‘Vocabulário Planlatino de Hemodinâmica’ of Realiter. In order to verify that the chosen terms participate in active placements in the area, we resorted to scientific articles from SciELO platform. The articles served as a source for extracting textual evidence for SLCs and formulating the definitions of SLCs. The analysis of the admissible data identifies the following characteristics of Hemodynamic SLCs: (i) the extension of the elements; (ii) the feature of terms that play the hole of base in the SLCs examined; (iii) the characteristics of the base complement; (iv) the types of Lexical Functions applied in the SLCs; (v) the complexity of LFs applied; and finally (vi) the necessity to increase information in the LFs standard (in all cases, there was added information to complete the meaning of the definition, we applied non-standard LFs).

O presente estudo tem por objetivo analisar Colocações Lexicais Especializadas (CLEs) da Hemodinâmica que apresentam bases nominais, por meio da Teoria Sentido-Texto. CLEs são colocações (agrupamentos lexicais) típicas de linguagem especializada que contém em sua constituição uma unidade terminológica, que pode ou não ser a base, além de elementos chamados de colocados, que são especificadores ou caracterizadores da base. Colocados são sempre selecionados em função da base. Além disso, outra forte característica das CLEs é o seu caráter semicomposicional ou fortemente composicional. Assim, para realizar tal objetivo, metodologicamente, escolhemos selecionar 37 CLEs a partir de termos típicos do Vocabulário Panlatino de Hemodinâmica da Realiter. A fim de constatar que os termos escolhidos participavam de colocações ativas na área, recorremos a artigos científicos (pesquisados na plataforma SciELO). Os artigos serviram de fonte para extrairmos as provas textuais das CLEs analisadas e para a formulação das definições dessas CLEs A análise dos dados permitiu que identificássemos as seguintes características das CLEs da Hemodinâmica: (i) quanto à extensão dos elementos (CLEs têm de 2 a 5 elementos); (ii) sobre a característica dos termos que exerciam papel de base nas CLEs examinadas (constituíram núcleos cem por cento nominais); (iii) sobre as características do complemento da base (complementos adjetivais, a maioria, e preposicionais); (iv) quanto aos tipos de Funções Lexicais (FLs) (adjetivais aplicadas a bases com complemento adjetival, preposicionais aplicadas a bases com complemento preposicional); (v) quanto à complexidade da FL (uso apenas de FL simples); e, por fim, (vi) sobre a necessidade de acréscimo de informação à FLs standards (em todos os casos houve acréscimo de informações para completar o sentido da definição, isto é, lançamos mão de FLs não-standards). / This study aims to analyze Specialized Lexical Combinations (SLCs) of Hemodynamic, with nominal base, through Meaning-Text Theory. SLCs are typical collocations (lexical groups) of specialized language that contain in their constitution a terminological unit, which may or may not be a base, in addition to elements called collocatives which are specifiers or characterizers of the base. Collocatives are always selected as a function of the base. In addition, another strong feature of SLCs is your semicomposicional or strongly compositional character. Thus, to achieve this goal, methodologically, we selected the 37 SLCs from typical terms present in the ‘Vocabulário Planlatino de Hemodinâmica’ of Realiter. In order to verify that the chosen terms participate in active placements in the area, we resorted to scientific articles from SciELO platform. The articles served as a source for extracting textual evidence for SLCs and formulating the definitions of SLCs. The analysis of the admissible data identifies the following characteristics of Hemodynamic SLCs: (i) the extension of the elements; (ii) the feature of terms that play the hole of base in the SLCs examined; (iii) the characteristics of the base complement; (iv) the types of Lexical Functions applied in the SLCs; (v) the complexity of LFs applied; and finally (vi) the necessity to increase information in the LFs standard (in all cases, there was added information to complete the meaning of the definition, we applied non-standard LFs).