Dissertations / Theses on the topic 'Multimodal analysis and synthesis'
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Prakosa, Adityo. "Analysis and simulation of multimodal cardiac images to study the heart function." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00837857.
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This thesis focuses on the analysis of the cardiac electrical and kinematic function for heart failure patients. An expected outcome is a set of computational tools that may help a clinician in understanding, diagnosing and treating patients suffering from cardiac motion asynchrony, a specific aspect of heart failure. Understanding the inverse electro-kinematic coupling relationship is the main task of this study. With this knowledge, the widely available cardiac image sequences acquired non-invasively at clinics could be used to estimate the cardiac electrophysiology (EP) without having to perform the invasive cardiac EP mapping procedures. To this end, we use real clinical cardiac sequence and a cardiac electromechanical model to create controlled synthetic sequence so as to produce a training set in an attempt to learn the cardiac electro-kinematic relationship. Creating patient-specific database of synthetic sequences allows us to study this relationship using a machine learning approach. A first contribution of this work is a non-linear registration method applied and evaluated on cardiac sequences to estimate the cardiac motion. Second, a new approach in the generation of the synthetic but virtually realistic cardiac sequence which combines a biophysical model and clinical images is developed. Finally, we present the cardiac electrophysiological activation time estimation from medical images using a patient-specific database of synthetic image sequences.
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Baum, Karl G. "Multimodal breast imaging : registration, visualization, and image synthesis /." Online version of thesis, 2008. http://hdl.handle.net/1850/7063.
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Beskow, Jonas. "Talking Heads - Models and Applications for Multimodal Speech Synthesis." Doctoral thesis, KTH, Tal, musik och hörsel, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3561.
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This thesis presents work in the area of computer-animatedtalking heads. A system for multimodal speech synthesis hasbeen developed, capable of generating audiovisual speechanimations from arbitrary text, using parametrically controlled3D models of the face and head. A speech-specific directparameterisation of the movement of the visible articulators(lips, tongue and jaw) is suggested, along with a flexiblescheme for parameterising facial surface deformations based onwell-defined articulatory targets. To improve the realism and validity of facial and intra-oralspeech movements, measurements from real speakers have beenincorporated from several types of static and dynamic datasources. These include ultrasound measurements of tonguesurface shape, dynamic optical motion tracking of face pointsin 3D, as well as electromagnetic articulography (EMA)providing dynamic tongue movement data in 2D. Ultrasound dataare used to estimate target configurations for a complex tonguemodel for a number of sustained articulations. Simultaneousoptical and electromagnetic measurements are performed and thedata are used to resynthesise facial and intra-oralarticulation in the model. A robust resynthesis procedure,capable of animating facial geometries that differ in shapefrom the measured subject, is described. To drive articulation from symbolic (phonetic) input, forexample in the context of a text-to-speech system, bothrule-based and data-driven articulatory control models havebeen developed. The rule-based model effectively handlesforward and backward coarticulation by targetunder-specification, while the data-driven model uses ANNs toestimate articulatory parameter trajectories, trained ontrajectories resynthesised from optical measurements. Thearticulatory control models are evaluated and compared againstother data-driven models trained on the same data. Experimentswith ANNs for driving the articulation of a talking headdirectly from acoustic speech input are also reported. A flexible strategy for generation of non-verbal facialgestures is presented. It is based on a gesture libraryorganised by communicative function, where each function hasmultiple alternative realisations. The gestures can be used tosignal e.g. turn-taking, back-channelling and prominence whenthe talking head is employed as output channel in a spokendialogue system. A device independent XML-based formalism fornon-verbal and verbal output in multimodal dialogue systems isproposed, and it is described how the output specification isinterpreted in the context of a talking head and converted intofacial animation using the gesture library. Through a series of audiovisual perceptual experiments withnoise-degraded audio, it is demonstrated that the animatedtalking head provides significantly increased intelligibilityover the audio-only case, in some cases not significantly belowthat provided by a natural face. Finally, several projects and applications are presented,where the described talking head technology has beensuccessfully employed. Four different multimodal spokendialogue systems are outlined, and the role of the talkingheads in each of the systems is discussed. A telecommunicationapplication where the talking head functions as an aid forhearing-impaired users is also described, as well as a speechtraining application where talking heads and languagetechnology are used with the purpose of improving speechproduction in profoundly deaf children.QC 20100506
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Almayyan, Waheeda. "Performance analysis of multimodal biometric fusion." Thesis, De Montfort University, 2012. http://hdl.handle.net/2086/5998.
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Biometrics is constantly evolving technology which has been widely used in many official and commercial identification applications. In fact in recent years biometric-based authentication techniques received more attention due to increased concerns in security. Most biometric systems that are currently in use typically employ a single biometric trait. Such systems are called unibiometric systems. Despite considerable advances in recent years, there are still challenges in authentication based on a single biometric trait, such as noisy data, restricted degree of freedom, intra-class variability, non-universality, spoof attack and unacceptable error rates. Some of the challenges can be handled by designing a multimodal biometric system. Multimodal biometric systems are those which utilize or are capable of utilizing, more than one physiological or behavioural characteristic for enrolment, verification, or identification. In this thesis, we propose a novel fusion approach at a hybrid level between iris and online signature traits. Online signature and iris authentication techniques have been employed in a range of biometric applications. Besides improving the accuracy, the fusion of both of the biometrics has several advantages such as increasing population coverage, deterring spoofing activities and reducing enrolment failure. In this doctoral dissertation, we make a first attempt to combine online signature and iris biometrics. We principally explore the fusion of iris and online signature biometrics and their potential application as biometric identifiers. To address this issue, investigations is carried out into the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. We compare the results of the multimodal approach with the results of the individual online signature and iris authentication approaches. This dissertation describes research into the feature and decision fusion levels in multimodal biometrics.
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Sun, Felix (Felix W. ). "Speech Representation Models for Speech Synthesis and Multimodal Speech Recognition." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106378.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 59-63).
The field of speech recognition has seen steady advances over the last two decades, leading to the accurate, real-time recognition systems available on mobile phones today. In this thesis, I apply speech modeling techniques developed for recognition to two other speech problems: speech synthesis and multimodal speech recognition with images. In both problems, there is a need to learn a relationship between speech sounds and another source of information. For speech synthesis, I show that using a neural network acoustic model results in a synthesizer that is more tolerant of noisy training data than previous work. For multimodal recognition, I show how information from images can be effectively integrated into the recognition search framework, resulting in improved accuracy when image data is available.
by Felix Sun.
M. Eng.
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Specker, Elizabeth. "L1/L2 Eye Movement Reading of Closed Captioning: A Multimodal Analysis of Multimodal Use." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/194820.
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Learning in a multimodal environment entails the presentation of information in a combination of more than one mode (i.e. written words, illustrations, and sound). Past research regarding the benefits of multimodal presentation of information includes both school age children and adult learners (e.g. Koolstra, van der Voort & d'Ydewalle, 1999; Neumen & Koskinen, 1992), as well as both native and non-native language learners (e.g. d'Ydewalle & Gielen, 1992; Kothari et al, 2002). This dissertation focuses how the combination of various modalities are used by learners of differing proficiencies in English to gain better comprehension (cf. Mayer, 1997, 2005; Graber, 1990; Slykhuis et al, 2005). The addition of the written mode (closed captioning) to the already multimodal environment that exists in film and video presentations is analyzed. A Multimodal Multimedia Communicative Event is used to situate the language learner. Research questions focus on the eye movements of the participants as they read moving text both with and without the audio and video modes of information. Small case studies also give a context to four participants by bringing their individual backgrounds and observations to bear on the use of multimodal texts as language learning tools in a second or foreign language learning environment. It was found that Non Native English Speakers (NNS) (L1 Arabic) show longer eye movement patterns in reading dynamic text (closed captioning), echoing past research with static texts while Native Speakers of English (NS) tend to have quicker eye movements. In a multimodal environment the two groups also differed: NNS looked longer at the closed captioning and NS were able to navigate the text presentation quickly. While associative activation (Paivio, 2007) between the audio and print modalities was not found to alter the eye movement patterns of the NNS, participants did alternate between the modalities in search of supplementary information. Other research using additional closed captioning and subtitling have shown that viewing a video program with written text added turns the activity into a reading activity (Jensema, 2000; d'Ydewalle, 1987). The current study found this to be the case, but the results differed in regard to proficiency and strategy.
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Marcollo, Hayden 1972. "Multimodal vortex-induced vibration." Monash University, Dept. of Mechanical Engineering, 2002. http://arrow.monash.edu.au/hdl/1959.1/7674.
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Zhang, Weiwei. "Multimodal Cardiovascular Image Analysis Using Phase Information." Thesis, University of Oxford, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491680.
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Cardiovascular heart disease (CVD) is one of the world's leading causes of death. Among the existing imaging techniques, cardiovascular magnetic imaging (CMR) and real-time three-dimensional echocardiography (RT3DUS) are receiving a lot of attention at the current time. Due to the 3D nature of the heart and its complex motion in 3D space, the RT3DUS is well-suited for 3D analysis of the cardiac disease. However, RT3DUS has lower specificity and sensitivity than the high spatial resolution CMR, which makes it difficult to interpret. This motivates research on assisting a clinician to automatically fuse the information from multiple imaging modalities for the early diagnosis and therapy of cardiac disease. This thesis establishes a framework for multimodal cardiovascular image analysis. First, we develop a (static) nonrigid registration of a RT3DUS volume slice and a CMR image. The local phase presentation of both images is utilized as an image descriptor of the 'featureness'. The local deformation of ventricles is modeled by a polyaffine transformation. The anchor points (or control points) used in the polyaffine transformation are automatically detected and refined by calculating a local misalignment measure based on phase mutual information. The registration process is built in an adaptive multi-scale framework to maximize the phase-based similarity measure by optimizing the parameters of the polyaffine transformation. Next, we explore a spatia-temporal alignment of RT3DUS and CMR sequences. The deformation field between both sequences is decoupled into spatial and temporal components. Temporal alignment is performed by re-slicing both sequences to contain the same number of frames and to make them correspond to the same temporal position using a differential registration. Spatial alignment is then carried out by extending the static nonrigid registration in a frame-by-frame manner. Landmarkbased validation shows that this new registration algorithm gives an accurate result. Finally, we proposed a registration-guided segmentation of the left ventricle in RT3DUS datasets. The image phase gradient is used as the edged indicator function. Incorporating local phase into the variational level set method without re-initialization enables a flexible initialization. This allows the co-registration of multimodal cardiovascular sequences to provide a strong prior knowledge about the shape of the left ventricle. We develop a registration-guided segmentation algorithm that efficiently converges to the object boundary of interest.
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Svitlichna. "ANALYSIS OF MULTIMODAL SERVICE MARKET IN UKRAINE." Thesis, Київ 2018, 2018. http://er.nau.edu.ua/handle/NAU/33914.
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Jancsary, Dennis, Markus Höllerer, and Renate Meyer. "Critical analysis of visual and multimodal texts." SAGE, 2016. http://epub.wu.ac.at/6126/1/Dennis_etal_2016_SAGE%2Dcritical%2Danalysis.pdf.
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Chen, Xun. "Multimodal biomedical signal processing for corticomuscular coupling analysis." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/45811.
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Corticomuscular coupling analysis using multiple data sets such as electroencepha-logram (EEG) and electromyogram (EMG) signals provides a useful tool for understanding human motor control systems. A popular conventional method to assess corticomuscular coupling is the pair-wise magnitude-squared coherence (MSC). However, there are certain limitations associated with MSC, including the difficulty in robustly assessing group inference, only dealing with two types of data sets simultaneously and the biologically implausible assumption of pair-wise interactions.
In this thesis, we propose several novel signal processing techniques to overcome the disadvantages of current coupling analysis methods. We propose combining partial least squares (PLS) and canonical correlation analysis (CCA) to take advantage of both techniques to ensure that the extracted components are maximally correlated across two data sets and meanwhile can well explain the information within each data set. Furthermore, we propose jointly incorporating response-relevance and statistical independence into a multi-objective optimization function, meaningfully combining the goals of independent component analysis (ICA) and PLS under the same mathematical umbrella.
In addition, we extend the coupling analysis to multiple data sets by proposing a joint multimodal group analysis framework. Finally, to acquire independent components but not just uncorrelated ones, we improve the multimodal framework by exploiting the complementary property of multiset canonical correlation analysis (M-CCA) and joint ICA. Simulations show that our proposed methods can achieve superior performances than conventional approaches. We also apply the proposed methods to concurrent EEG, EMG and behavior data collected in a Parkinson's disease (PD) study. The results reveal highly correlated temporal patterns among the multimodal signals and corresponding spatial activation patterns. In addition to the expected motor areas, the corresponding spatial activation patterns demonstrate enhanced occipital connectivity in PD subjects, consistent with previous medical findings.
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Doleman, Brett. "A meta-analysis of gabapentin and multimodal analgesics." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/43385/.
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Multimodal analgesia has been proposed as a useful strategy to reduce postoperative pain while decreasing opioid consumption and thus opioid adverse events. Gabapentin is one such agent although previous results have been heterogeneous. This thesis aimed to review randomised controlled trials of gabapentin for reducing pain, opioid adverse effects and the haemodynamic response to intubation while attempted to predict clinical effectiveness from these trials using meta-regression. Extending this principle, we evaluated other multimodal analgesic agents to identify whether heterogeneity could be explained by various clinical and methodological covariates. Our gabapentin review included 133 randomised controlled trials and demonstrated its efficacy in reducing pain scores, opioid consumption and opioid adverse events such as nausea, vomiting and pruritus. However, gabapentin increased the risk of sedation. Gabapentin was effective at reducing the haemodynamic response to intubation in 29 randomised controlled trials although trials failed to report on clinically relevant outcomes. Gabapentin exhibited no pre-emptive analgesic effect in 4 randomised controlled trials. There was evidence of considerable statistical heterogeneity on meta-analysis of gabapentin for pain scores and 24-hour morphine consumption. Meta-regression analysis showed however that baseline risk predicted the majority of the heterogeneity between studies. Extending this approach to other multimodal analgesics from 344 randomised controlled trials; we demonstrated this was true for analgesic agents in general. In addition to baseline risk, methodological limitations, especially inadequate allocation concealment, explained some of the residual heterogeneity. There was evidence of funnel plot asymmetry for most analgesic agents, suggesting publication bias. However, this may be a product of trials with higher baseline risk having larger standard errors, rather than true publication bias. Indeed, when we simulated meta-analyses with no publication bias, with both effect size and standard deviations dependent on baseline risk, funnel plot asymmetry was still evident (p < 0.001). Therefore, conventional funnel plots may be an unsuitable method of detecting publication bias where baseline risk predicts between-study heterogeneity. We present an alternative method using meta-regression residuals that corrects funnel plot asymmetry in the presence of no publication bias. Finally, due to concerns that methodological limitations exaggerated effect estimates, we used trial sequential analysis to determine whether sufficient low risk of bias evidence exists to reject type I and type II errors in the analyses of analgesic adjuncts. We demonstrated there is currently insufficient evidence from low risk of bias trials to be confident of the efficacy of the majority of analgesic adjuncts.
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Soltaninejad, Mohammadreza. "Supervised learning-based multimodal MRI brain image analysis." Thesis, University of Lincoln, 2017. http://eprints.lincoln.ac.uk/30883/.
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Medical imaging plays an important role in clinical procedures related to cancer, such as diagnosis, treatment selection, and therapy response evaluation. Magnetic resonance imaging (MRI) is one of the most popular acquisition modalities which is widely used in brain tumour analysis and can be acquired with different acquisition protocols, e.g. conventional and advanced. Automated segmentation of brain tumours in MR images is a difficult task due to their high variation in size, shape and appearance. Although many studies have been conducted, it still remains a challenging task and improving accuracy of tumour segmentation is an ongoing field. The aim of this thesis is to develop a fully automated method for detection and segmentation of the abnormal tissue associated with brain tumour (tumour core and oedema) from multimodal MRI images. In this thesis, firstly, the whole brain tumour is segmented from fluid attenuated inversion recovery (FLAIR) MRI, which is commonly acquired in clinics. The segmentation is achieved using region-wise classification, in which regions are derived from superpixels. Several image features including intensity-based, Gabor textons, fractal analysis and curvatures are calculated from each superpixel within the entire brain area in FLAIR MRI to ensure a robust classification. Extremely randomised trees (ERT) classifies each superpixel into tumour and non-tumour. Secondly, the method is extended to 3D supervoxel based learning for segmentation and classification of tumour tissue subtypes in multimodal MRI brain images. Supervoxels are generated using the information across the multimodal MRI data set. This is then followed by a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. The information from the advanced protocols of diffusion tensor imaging (DTI), i.e. isotropic (p) and anisotropic (q) components is also incorporated to the conventional MRI to improve segmentation accuracy. Thirdly, to further improve the segmentation of tumour tissue subtypes, the machine-learned features from fully convolutional neural network (FCN) are investigated and combined with hand-designed texton features to encode global information and local dependencies into feature representation. The score map with pixel-wise predictions is used as a feature map which is learned from multimodal MRI training dataset using the FCN. The machine-learned features, along with hand-designed texton features are then applied to random forests to classify each MRI image voxel into normal brain tissues and different parts of tumour. The methods are evaluated on two datasets: 1) clinical dataset, and 2) publicly available Multimodal Brain Tumour Image Segmentation Benchmark (BRATS) 2013 and 2017 dataset. The experimental results demonstrate the high detection and segmentation performance of the III single modal (FLAIR) method. The average detection sensitivity, balanced error rate (BER) and the Dice overlap measure for the segmented tumour against the ground truth for the clinical data are 89.48%, 6% and 0.91, respectively; whilst, for the BRATS dataset, the corresponding evaluation results are 88.09%, 6% and 0.88, respectively. The corresponding results for the tumour (including tumour core and oedema) in the case of multimodal MRI method are 86%, 7%, 0.84, for the clinical dataset and 96%, 2% and 0.89 for the BRATS 2013 dataset. The results of the FCN based method show that the application of the RF classifier to multimodal MRI images using machine-learned features based on FCN and hand-designed features based on textons provides promising segmentations. The Dice overlap measure for automatic brain tumor segmentation against ground truth for the BRATS 2013 dataset is 0.88, 0.80 and 0.73 for complete tumor, core and enhancing tumor, respectively, which is competitive to the state-of-the-art methods. The corresponding results for BRATS 2017 dataset are 0.86, 0.78 and 0.66 respectively. The methods demonstrate promising results in the segmentation of brain tumours. This provides a close match to expert delineation across all grades of glioma, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management. In the experiments, texton has demonstrated its advantages of providing significant information to distinguish various patterns in both 2D and 3D spaces. The segmentation accuracy has also been largely increased by fusing information from multimodal MRI images. Moreover, a unified framework is present which complementarily integrates hand-designed features with machine-learned features to produce more accurate segmentation. The hand-designed features from shallow network (with designable filters) encode the prior-knowledge and context while the machine-learned features from a deep network (with trainable filters) learn the intrinsic features. Both global and local information are combined using these two types of networks that improve the segmentation accuracy.
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Kassel, Jan-Frederik [Verfasser]. "On intelligible multimodal visual analysis / Jan-Frederik Kassel." Hannover : Gottfried Wilhelm Leibniz Universität Hannover, 2020. http://d-nb.info/1220422258/34.
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García, Marcos Eloy. "Glandular tissue pattern analysis through multimodal MRI-mammography registration." Doctoral thesis, Universitat de Girona, 2018. http://hdl.handle.net/10803/585969.
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Breast cancer is the most common cancer among women worldwide. Several studies have shown that the combination of the different medical image modalities, such as the x-ray mammography and the magnetic resonance imaging (MRI), leads to a more accurate diagnosis. The aim of this thesis is double, on the one hand, to evaluate the similarity between the information obtained from x-ray mammography and from MRI images and, on the other hand, to propose new registration algorithms to perform the correlation between the two image modalities. The problem includes from the biomechanical model construction, obtained from the MRI volume, the mechanical deformation, which is performed during the mammographic acquisition, the x-ray beam simulation traversing the breast in order to obtain the image (pseudo-mammogram) and the registration process to improve the similarity between the real and the synthetic imagesEl càncer de mama és el tipus de càncer més comú entre les dones de tot el món. Diversos estudis han demostrat que la combinació de diferents modalitats d'imatge mèdica, com ara la mamografia i la ressonància magnètica (MRI), comporta un diagnòstic més precís. L'objectiu d'aquesta tesi és doble, per una banda avaluar la similitud de la informació entre la mamografia de raigs X i la MRI i, d’altra banda, proposar nous algoritmes de registre que serveixin per a correlacionar la posició espacial en les dues modalitats d'imatge. El problema abarca la construcció del model biomecànic de la mama a partir de la ressonància magnètica, la simulació de la deformació que pateix la mama durant l’adquisició mamogràfica, la simulació dels rajos X atravessant la mama fins a obtenir la imatge (pseudo-mamografia) i els mètodes de registre posteriors per tal de millorar la similitud entre la imatge real i la simulada
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Bolaños, Solà Marc. "Deep Multimodal Learning for Egocentric Storytelling and Food Analysis." Doctoral thesis, Universitat de Barcelona, 2021. http://hdl.handle.net/10803/671672.
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The world of Machine Learning and Computer Vision has experienced a revolution since the last years. The appearance of Deep Learning algorithms and Convolutional Neural Networks, altogether with the increased processing capabilities provided by modern GPUs and the enormous amounts of annotated data publicly available, have allowed a boost in the field as never seen before.
These notable improvements achieved in the Machine Learning world have led to the appearance of new fields like the Multimodal Learning, which encompasses and learns from many subfields. Additionally, new applications have taken profit of these advancements in order to reach high levels of performance. The huge results improvement of the currently available algorithms have allowed not only revolutionizing the academic world, but also bringing AI-based solutions to the market that looked like science fiction barely 10 years ago.
This thesis, which is written as a papers compendium, focuses on delving deeper into the novel topic of Deep Multimodal Learning by proposing new algorithms and solutions for both already existing and newly defined problems. From the applications perspective, most of the papers presented can be divided in two areas of applicability. From the one hand, Egocentric Vision and Storytelling, which consists in acquiring images from the daily life of a person in order to analyse its behaviour patterns like social interactions, activities and events, interactions with objects, etc.
And on the other hand, Food Recognition and Analysis, which consists in visually analysing and recognizing the food appearing on images in multiple contexts and with different levels of complexity, from food groups recognition to nutritional analysis. In both applications, the final purpose of the proposed papers is building tools that provide information that could lead to a better quality of life of the users.El mundo del Machine Learning y la Visión por Computador ha experimentado una revolución los últimos años. La aparición de algoritmos de Deep Learning y Convolutional Neural Networks, junto con las mayores capacidades de procesamiento proporcionadas por GPU modernas y las enormes cantidades de datos anotados disponibles públicamente, han permitió un impulso en el campo como nunca antes se había visto.Estas notables mejoras logradas en el mundo del Machine Learning han llevado a la aparición de nuevos campos como el Aprendizaje Multimodal, que engloba y aprende de muchos subcampos. Además, nuevas aplicaciones han aprovechado estos avances para alcanzar altos niveles de rendimiento. La enorme mejora en los resultados de los algoritmos disponibles actualmente ha permitido no solo revolucionar el mundo académico, sino también llevar al mercado soluciones basadas en IA que parecían ciencia ficción hace apenas 10 años.Esta tesis, que está escrita como un compendio de artículos, se enfoca en profundizar en el novedoso tema del Aprendizaje Multimodal Profundo al proponer nuevos algoritmos y soluciones para problemas ya existentes y recientemente definidos. Desde la perspectiva de las aplicaciones, la mayoría de los trabajos presentados se pueden dividir en dos áreas de aplicabilidad. Por un lado, la Visión Egocéntrica y el Storytelling, que consiste en la adquisición de imágenes de la vida diaria de una persona para analizar su comportamiento y extraer patrones asociadas a estos como por ejemplo interacciones sociales, actividades y eventos, interacciones con objetos, etc. Y por otro lado, el Reconocimiento y Análisis de Alimentos, que consiste en visualmente analizar y reconocer la comida que aparece en imágenes en múltiples contextos y con diferentes niveles de complejidad, desde el reconocimiento de grupos de alimentos hasta el análisis nutricional.En ambas aplicaciones, el propósito final de los artículos propuestos es construir herramientas que brinden información que pueda conducir a una mejor calidad de vida de los usuarios.
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Yu, C. (Changrong). "Emotional display in argument, storytelling and teasing:a multimodal analysis." Doctoral thesis, Oulun yliopisto, 2012. http://urn.fi/urn:isbn:9789514298516.
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Abstract This dissertation studies emotional displays in talk-in-interaction, especially focusing on conversational argument, storytelling and teasing. The aim is to understand how verbal expressions, prosodic cues, and embodied actions interact with each other in emotional expression. The main analytic approach and methodology is conversation analysis and multimodal interaction analysis, applied to interactional sequences from everyday conversations. The research data comes from three different video recordings and their transcripts. First, the dissertation reveals two broad types of frustration in conversational argument. The findings suggest that combined verbal and nonverbal expression of frustration involves a complex interplay of prosodic cues and embodied actions. Nonverbal expression of frustration is displayed by embodied actions alone. Second, the dissertation shows how shared joy is conveyed between storytellers and recipients in storytelling. They can achieve shared joy because the recipients express willing participation and active recipiency in two main ways: they display verbal appreciation of the story, or they join in the storytelling through laughter, smiles, head nods, and gaze exchanges. The recipients may also offer summaries or interpretations of events in the story by comparing their own experiences to events in the story. Third, the dissertation analyzes playful teasing activity, showing how teasing activity can bring about a shared experience of amusement for both teasers and their “targets.” The study argues that recipients of teasing are active contributors in the social interaction. The transient embarrassment felt by the teased participants does not prevent the exchange from reaching a shared experience of amusementTiivistelmä Väitöskirja tutkii tunteiden osoittamista arkisissa keskustelutilanteissa ja erityisesti väittelyn, tarinankerronnan ja kiusoittelun kuluessa. Tutkimusmetodi on pääasiassa keskustelunanalyysi, jonka avulla tutkitaan, miten kielelliset ilmaukset, prosodiset vihjeet sekä keholliset toiminnot yhdessä tuottavat tunneilmauksia. Tutkimusaineiston muodostaa kolme videoitua keskustelua ja niiden litteraatiot. Tutkimus osoittaa arkikeskusteluissa esiintyvissä väittelyissä ilmenevän kahtalaista turhautumisen tyyppiä. Ensimmäisessä puhujat tuottavat rinnan kielellisiä ja ei-kielellisiä turhautumisen ilmauksia, toisessa turhautumista osoitetaan vain ei-kielellisin keinoin. Tuloksien mukaan edellisessä tyypissä prosodia ja keholliset toiminnot ovat monimutkaisessa vuorovaikutuksessa keskenään. Jälkimmäisessä tyypissä turhautumista ilmaistaan pelkästään keholla. Toiseksi väitöskirja osoittaa, miten jaettu ilon tunne syntyy puhujien ja vastaanottajien välisenä toimintana. Tarinankerronnassa saavutetaan ilon hetkiä, koska vastaanottajat ovat halukkaasti mukana kerronnassa ja osoittavat aktiivista vastaanottoa kahdella tavalla: he osoittavat arvostusta kertomusta kohtaan verbaalisin keinoin, tai he liittyvät kerrontaan mukaan nauramalla, hymyilemällä, nyökkäilemällä, vaihtamalla katseita keskenään, referoimalla ja tulkitsemalla kertojan aiempaa puhetta formulaatioillaan ja vertailemalla omia kokemuksiaan tarinan tilanteeseen. Kolmanneksi tutkimus analysoi leikkisää kiusoittelua, joka saadaan aikaan liioittelevilla kielellisillä ilmauksilla sekä liioittelevilla prosodisilla vihjeillä ja eleillä. Tutkimus näyttää, että kiusoittelun kohteet aktiivisesti myötävaikuttavat kiusoittelutoimintaan. He voivat olla siinä mukana liioittelevilla vastausvuoroilla, nauramalla tai toimimalla mukana pelkästään eleiden avulla. Empiirinen analyysi näyttää, että kiusoittelutoiminta tuottaa yhteisen huvittuneisuuden kokemuksen keskustelun kuluessa. Kiusoittelijan ja kiusoittelun kohteen kokema ohimenevä nolous tai kiusaantuneisuus ei estä tämän yhteisen huvittuneisuuden kokemuksen saavuttamista
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Nordensvärd, Eje. "Multimodality : An EFL textbook comparison using multimodal discourse analysis." Thesis, Södertörns högskola, Lärarutbildningen, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-6007.
Full textAbstract:
This essay aims to compare two EFL (English as a Foreign Language) textbooks by using a multimodal discourse analysis in order to find out how EFL textbooks have changed in design and visually. In this essay the textual content is treated as one of several pillars making up design, this essay is interested in the visual changes. This analysis is done using two EFL textbooks with twenty years in between them, both are used in the same school by different teachers. A study like this is going to be published later this year but that study includes three subjects (English being one of them) and starts with textbooks from the 1930s up until now. In this essay, two chapters of each textbook will be looked at in a closer analysis to represent each textbook; every page is analyzed without first reading the text. The conclusion of this essay is that the written communication still seem to be the most credible of the different communicative methods of making meaning, however, it is no longer the only credible way of making meaning.
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Hennessey, James W. "Assistive visual content creation tools via multimodal correlation analysis." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10046053/.
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Visual imagery is ubiquitous in society and can take various formats: from 2D sketches and photographs to photorealistic 3D renderings and animations. The creation processes for each of these mediums have their own unique challenges and methodologies that artists need to overcome and master. For example, for an artist to depict a 3D scene in a 2D drawing they need to understand foreshortening effects to position and scale objects accurately on the page; or, when modeling 3D scenes, artists need to understand how light interacts with objects and materials, to achieve a desired appearance. Many of these tasks can be complex, time-consuming, and repetitive for content creators. The goal of this thesis is to develop tools to alleviate artists from some of these issues and to assist them in the creation process. The key hypothesis is that understanding the relationships between multiple signals present in the scene being created enables such assistive tools. This thesis proposes three assistive tools. First, we present an image degradation model for depth-augmented image editing to help evaluate the quality of the image manipulation. Second, we address the problem of teaching novices to draw objects accurately by automatically generating easy-to-follow sketching tutorials for arbitrary 3D objects. Finally, we propose a method to automatically transfer 2D parametric user edits made to rendered 3D scenes to global variations of the original scene.
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Raschke, Felix. "Tissue type analysis of brain tumours using multimodal MRI." Thesis, St George's, University of London, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.617006.
Full textAbstract:
The aim of this thesis is to investigate the spatial extent of brain tumours by developing new methods combining the metabolic information provided by low resolution 1 H magnetic resonance spectroscopic imaging (MRSI) data with high resolution structural information from diffusion tensor imaging (DTI). In chapter 3 and chapter 4, the spectral analysis tool LCModel is used to decompose single voxel (SV) MRS data of common adult and childhood brain tumours into the most likely tissue class respectively. Classification according to the highest estim,ated tissue proportion suggested comparable performance to published specialised pattern recognition methods and emphasises the flexibility of the method. In chapter 5, the LCModel tissue type analysis is refined and extended to decompose short echo MRSI data of glioma patients into normal and abnormal tissue proportions. Spatial assessment revealed metabolic low grade characteristics around most grade IV glioblastomas as potential tumour infiltration. Several visualisation techniques explored reveal heterogeneous infiltration patterns varying across patients. In chapter 6 a radial choline-to-N-acetyl-aspartate index (rCNI) is presented as an alternative method for the delineation of brain tumour MRSI exams using the choline to NAA ratio. Both simulations and analysis of real 1.5T and 3T glioma data suggest a higher specificity at similar sensitivity for rCNI over the previously published CN!. The final chapter 7 presents a novel method for the combination of the LCModel tissue type information from chapter 5 with DTI and conventional MRI data. The tissue type information is used to sample high confidence regions of tumour and normal brain and extract the underlying DTI and MRI information and create tissue specific probability density distributions. Additional distributions from areas of tumour infiltration and vasogenic oedema were sampled from glioma and metastasis data respectively. Bayes' theorem was then used to calculate probability maps of the different tissue types which show promise for tumour grading and the differentiation of vasogenic oedema and tumour infiltration.
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Balakrishnan, Arjun. "Integrity Analysis of Data Sources in Multimodal Localization System." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASG060.
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Les véhicules intelligents sont un élément clé pour des systèmes de transport plus sûrs, efficaces et accessibles à travers le monde. En raison de la multitude de sources de données et de processus associés aux véhicules intelligents, la fiabilité de l'ensemble du système dépend fortement de la possibilité d'erreurs ou de mauvaises performances observées dans ses composants. Dans notre travail, nous nous intéressons à la tâche critique de localisation des véhicules intelligents et relevons les défis de la surveillance de l'intégrité des sources de données utilisées dans la localisation. La contribution clé de notre recherche est la proposition d'un nouveau protocole d'intégrité en combinant les concepts d'intégrité des systèmes d'information et les concepts d'intégrité existants dans les Systèmes de Transport Intelligents (STI). Un cadre de surveillance de l'intégrité basé sur le protocole d'intégrité proposé qui peut gérer les problèmes de localisation multimodale est développé. Dans la première étape, une preuve de concept pour ce cadre est développée sur la base d'une estimation de cohérence croisée des sources de données à l'aide de modèles polynomiaux. Sur la base des observations de la première étape, une représentation des données «Feature Grid» est proposée dans la deuxième étape et un prototype généralisé pour le cadre est mis en œuvre. Le cadre est testé sur les autoroutes ainsi que dans des scénarios urbains complexes pour démontrer que le cadre proposé est capable de fournir des estimations d'intégrité continue des sources de données multimodales utilisées dans la localisation intelligente des véhiculesIntelligent vehicles are a key component in humanity’s vision for safer, efficient, and accessible transportation systems across the world. Due to the multitude of data sources and processes associated with Intelligent vehicles, the reliability of the total system is greatly dependent on the possibility of errors or poor performances observed in its components. In our work, we focus on the critical task of localization of intelligent vehicles and address the challenges in monitoring the integrity of data sources used in localization. The primary contribution of our research is the proposition of a novel protocol for integrity by combining integrity concepts from information systems with the existing integrity concepts in the field of Intelligent Transport Systems (ITS). An integrity monitoring framework based on the theorized integrity protocol that can handle multimodal localization problems is formalized. As the first step, a proof of concept for this framework is developed based on cross-consistency estimation of data sources using polynomial models. Based on the observations from the first step, a 'Feature Grid' data representation is proposed in the second step and a generalized prototype for the framework is implemented. The framework is tested in highways as well as complex urban scenarios to demonstrate that the proposed framework is capable of providing continuous integrity estimates of multimodal data sources used in intelligent vehicle localization
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Tobón, Gómez Catalina. "Three-dimensional statistical shape models for multimodal cardiac image analysis." Doctoral thesis, Universitat Pompeu Fabra, 2011. http://hdl.handle.net/10803/37473.
Full textAbstract:
Las enfermedades cardiovasculares (ECVs) son la principal causa de mortalidad en el mundo
Occidental. El interés de prevenir y tratar las ECVs ha desencadenado un rápido desarrollo de los
sistemas de adquisición de imágenes médicas. Por este motivo, la cantidad de datos de imagen
recolectados en las instituciones de salud se ha incrementado considerablemente. Este hecho ha
aumentado la necesidad de herramientas automatizadas para dar soporte al diagnóstico, mediante
una interpretación de imagen confiable y reproducible. La tarea de interpretación requiere traducir
los datos crudos de imagen en parámetros cuantitativos, los cuales son considerados relevantes
para clasificar la condición cardiaca de un paciente. Para realizar tal tarea, los métodos basados en
modelos estadísticos de forma han recibido favoritismo dada la naturaleza tridimensional (o 3D+t)
de las imágenes cardiovasculares. Deformando el modelo estadístico de forma a la imagen de un
paciente, el corazón puede analizarse de manera integral.
Actualmente, el campo de las imágenes cardiovasculares esta constituido por diferentes modalidades.
Cada modalidad explota diferentes fenómenos físicos, lo cual nos permite observar el
órgano cardiaco desde diferentes ángulos. El personal clínico recopila todas estas piezas de información
y las ensambla mentalmente en un modelo integral. Este modelo integral incluye información
anatómica y funcional que muestra un cuadro completo del corazón del paciente. Es
de alto interés transformar este modelo mental en un modelo computacional capaz de integrar la
información de manera global. La generación de un modelo como tal no es simplemente un reto de
visualización. Requiere una metodología capaz de extraer los parámetros cuantitativos relevantes
basados en los mismos principios técnicos. Esto nos asegura que las mediciones se pueden comparar
directamente. Tal metodología debe ser capaz de: 1) segmentar con precisión las cavidades
cardiacas a partir de datos multimodales, 2) proporcionar un marco de referencia único para integrar
múltiples fuentes de información, y 3) asistir la clasificación de la condición cardiaca del
paciente.
Esta tesis se basa en que los modelos estadísticos de forma, y en particular los Modelos Activos
de Forma, son un método robusto y preciso con el potencial de incluir todos estos requerimientos.
Para procesar múltiples modalidades de imagen, separamos la información estadística de forma
de la información de apariencia. Obtenemos la información estadística de forma a partir de una
modalidad de alta resolución y aprendemos la apariencia simulando la física de adquisición de
otras modalidades.
Las contribuciones de esta tesis pueden ser resumidas así: 1) un método genérico para construir
automáticamente modelos de intensidad para los Modelos Activos de Forma simulando la
física de adquisición de la modalidad en cuestión, 2) la primera extensión de un simulador de Resonancia
Magnética Nuclear diseñado para producir estudios cardiacos realistas, y 3) un método
novedoso para el entrenamiento automático de modelos de intensidad y de fiabilidad aplicado a
estudios cardiacos de Resonancia Magnética Nuclear. Cada una de estas contribuciones representa
un artículo publicado o enviado a una revista técnica internacional.Cardiovascular diseases (CVDs) are the major cause of death in the Western world. The desire to prevent and treat CVDs has triggered a rapid development of medical imaging systems. As a consequence, the amount of imaging data collected in health care institutions has increased considerably. This fact has raised the need for automated analysis tools to support diagnosis with reliable and reproducible image interpretation. The interpretation task requires to translate raw imaging data into quantitative parameters, which are considered relevant to classify the patient’s cardiac condition. To achieve this task, statistical shape model approaches have found favoritism given the 3D (or 3D+t) nature of cardiovascular imaging datasets. By deforming the statistical shape model to image data from a patient, the heart can be analyzed in a more holistic way. Currently, the field of cardiovascular imaging is constituted by different modalities. Each modality exploits distinct physical phenomena, which allows us to observe the cardiac organ from different angles. Clinicians collect all these pieces of information to form an integrated mental model. The mental model includes anatomical and functional information to display a full picture of the patient’s heart. It is highly desirable to transform this mental model into a computational model able to integrate the information in a comprehensive manner. Generating such a model is not simply a visualization challenge. It requires having a methodology able to extract relevant quantitative parameters by applying the same principle. This assures that the measurements are directly comparable. Such a methodology should be able to: 1) accurately segment the cardiac cavities from multimodal datasets, 2) provide a unified frame of reference to integrate multiple information sources, and 3) aid the classification of a patient’s cardiac condition. This thesis builds upon the idea that statistical shape models, in particular Active Shape Models, are a robust and accurate approach with the potential to incorporate all these requirements. In order to handle multiple image modalities, we separate the statistical shape information from the appearance information. We obtain the statistical shape information from a high resolution modality and include the appearance information by simulating the physics of acquisition of other modalities. The contributions of this thesis can be summarized as: 1) a generic method to automatically construct intensity models for Active Shape Models based on simulating the physics of acquisition of the given imaging modality, 2) the first extension of a Magnetic Resonance Imaging (MRI) simulator tailored to produce realistic cardiac images, and 3) a novel automatic intensity model and reliability training strategy applied to cardiac MRI studies. Each of these contributions represents an article published or submitted to a peer-review archival journal.
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Ma, Mei-lin Linda. "Multimodal discourse analysis of advertisements of Hong Kong charity organizations." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B31789729.
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Reimer, Mark. "Multimodal transportation systems analysis to characterize petroleum-related freight flows." Transportation Research Board of the National Academies, 2014. http://hdl.handle.net/1993/30288.
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The purpose of this research is to inform planning, engineering, and management decisions concerning transportation systems that serve the petroleum exploration and production industry in North America. The research applies the transportation systems analysis approach to characterize the petroleum activity system and transportation system in southwest Manitoba and to develop freight flows. The research develops a framework to estimate and assign petroleum-related truck traffic to the regional highway network taking into account the variability of the industry. This is done by integrating components of freight demand modeling and truck traffic monitoring processes to improve understanding of truck traffic flow characteristics related to the industry. The results of the research are presented in an interactive mapping data dissemination tool. The approach and methodologies of this research are transferable to other jurisdictions and can be used to address the needs of other industry-specific developments.
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Ma, Mei-lin Linda, and 馬美蓮. "Multimodal discourse analysis of advertisements of Hong Kong charity organizations." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B31789729.
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Li, Yanan, and 李亚男. "Multimodal analysis of academic posters by student writers across disciplines." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/207138.
Full textAbstract:
This dissertation examines the multimodal discourse of academic posters from three disciplines, namely, Chemistry, Speech & Hearing Sciences and Linguistics, in an attempt to unravel how writers from different disciplinary communities build their communicative purposes into the verbal and visual modes in their posters. The analytical framework adopted for this study builds upon the one proposed by D’Angelo(2010), which incorporates Hyland’s metadiscourse model (2005) and Kress and van Leeuwen’s visual grammar paradigm (2006) for the verbal and visual analyses respectively, and supplements it with multimodal content analysis adapted from Jones’s (2007) model. Follow-up interviews with members of the discourse communities were also conducted to enhance the validity of the results. The findings reveal that there exist a wide range of differences in the use of metadiscourse markers (e.g. hedges, boosters, evidentials, code glosses) across the three group texts pertaining to disciplinary influences. There is also evidence that academics in different subjects value some of the same qualities in the texts necessitated either by the peculiar context of poster presentations (e.g. frame markers, engagement markers) or a need to maintain scientific formality (e.g. self-mentions). Visually, the concern for the context and ‘scientificness’ continue to exert great influences, rendering a myriad of visual manifestations (e.g. framing, modality) that are commonly shared across the data, whereas the cross-discipline discrepancy mainly narrows down to the image usage(functions and types).published_or_final_version
Applied English Studies
Master
Master of Arts in Applied Linguistics
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Gonzalez, Temer Veronica. "A multimodal analysis of assessment sequences in Chilean Spanish interaction." Thesis, University of York, 2017. http://etheses.whiterose.ac.uk/20579/.
Full textAbstract:
This thesis presents a study of food assessments in Chilean Spanish interaction. The data consists of video recordings of six pairs of Chilean participants sampling British foods unknown to them. They tried each food at the same time and discussed their opinions. They were asked to do a joint ranking of these products to elicit sequences of agreement and disagreement. The data is analysed combining the methods of conversation analysis with those of interactional linguistics and the study of embodied interaction. There are three analytic chapters. The first one explores what constitutes a canonical assessment, i.e. aspects of the turn design of assessments in the particular context of the data and how they compare to the literature in English. The second analytic chapter is about the lead-up to an assessment. I explore how speakers initiate assessments (with particular attention to the role of eye gaze). The third analytic chapter deals with how non-lexical (and other) tokens and the co-occurring embodied aspects of their production (prosodic features, gestures, etc.) are designed and understood as projecting a stance towards the food. All things considered, this thesis contributes to filling a knowledge gap in relation to the study of assessments in the Spanish language. It also contributes the novelty of studying food assessments among non-experts. Finally, this thesis sheds light on how assessments arise in interaction and about the emergence of linguistic organisation through other non-verbal activities.
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Alduhaim, Asmaa. "Multimodal translation analysis : Arab Spring speeches in Arabic and English." Thesis, University of Birmingham, 2018. http://etheses.bham.ac.uk//id/eprint/8561/.
Full textAbstract:
In the contemporary globalized world, translation plays a key role in sharing news across the globe, in particular in the age of multimedia, where meaning is transferred through various modes and genres. This study focuses on two Arab Spring speeches of Mummar Algaddafi’s and Hosni Mubarak’s and their translations in different media. The thesis initially conducts a comparative study of the source texts (STs), including a textual/contextual analysis drawing on Norman Fairclough’s Critical Discourse Analysis, and on Gunther Kress’ multimodal analysis. This is followed by examining the target texts (TTs) to investigate the inventible changes that occur during the translation process, particularly if the translation involves not only a transfer of meaning from Arabic to English but also from mode to mode (such as, speaking to writing) and genre to genre (a political speech to a newspaper article). The thesis introduces the Multimodal Translation Analysis model to investigate the following aspects of the TTs: linguistic aspects of the TTs, the TT’s multimodal qualities, and, drawing on Mona Baker’s narrative theory, the role of dominant narratives in the shaping of the TT.
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Gupta, Rakesh 1968. "Prototyping and design for assembly analysis using multimodal virtual environments." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11103.
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Song, Yale. "Structured video content analysis : learning spatio-temporal and multimodal structures." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90003.
Full textAbstract:
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 141-154).
Video data exhibits a variety of structures: pixels exhibit spatial structure, e.g., the same class of objects share certain shapes and/or colors in image; sequences of frames exhibit temporal structure, e.g., dynamic events such as jumping and running have a certain chronological order of frame occurrence; and when combined with audio and text, there is multimodal structure, e.g., human behavioral data shows correlation between audio (speech) and visual information (gesture). Identifying, formulating, and learning these structured patterns is a fundamental task in video content analysis. This thesis tackles two challenging problems in video content analysis - human action recognition and behavior understanding - and presents novel algorithms to solve each: one algorithm performs sequence classification by learning spatio-temporal structure of human action; another performs data fusion by learning multimodal structure of human behavior. The first algorithm, hierarchical sequence summarization, is a probabilistic graphical model that learns spatio-temporal structure of human action in a fine-to-coarse manner. It constructs a hierarchical representation of video by iteratively summarizing the video sequence, and uses the representation to learn spatio-temporal structure of human action, classifying sequences into action categories. We developed an efficient learning method to train our model, and show that its complexity grows only sublinearly with the depth of the hierarchy. The second algorithm focuses on data fusion - the task of combining information from multiple modalities in an effective way. Our approach is motivated by the observation that human behavioral data is modality-wise sparse, i.e., information from just a few modalities contain most information needed at any given time. We perform data fusion using structured sparsity, representing a multimodal signal as a sparse combination of multimodal basis vectors embedded in a hierarchical tree structure, learned directly from the data. The key novelty is in a mixed-norm formulation of regularized matrix factorization via structured sparsity. We show the effectiveness of our algorithms on two real-world application scenarios: recognizing aircraft handling signals used by the US Navy, and predicting people's impression about the personality of public figures from their multimodal behavior. We describe the whole procedure of the recognition pipeline, from the signal acquisition to processing, to the interpretation of the processed signals using our algorithms. Experimental results show that our algorithms outperform state-of-the-art methods on human action recognition and behavior understanding.
by Yale Song.
Ph. D.
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Bao-Rozee, Jie. "Using multimodal analysis to investigate the role of the interpreter." Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/24665.
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Recent research in Interpreting Studies has favoured the argument that, in practice, the interpreter plays an active role, rather than the prescribed role stipulated in professional codes of conduct. Cutting-edge studies utilising multimodal research methods have taken a more comprehensive approach to investigating this argument, searching for evidence of the interpreter’s active involvement not only through textual analysis, but also by examining a range of non-verbal communicative means. Studies using multimodal analysis, such as those by Pasquandrea (2011) and Davitti (2012), have succeeded in offering new insights into the interpreter’s role in interaction. This research presents further investigation into the interpreter’s role through multimodal analysis by focusing on the use of gesture movements, gaze and body orientation in interpreter-mediated communication; it also looks at the impact of the state of knowledge asymmetry on the interpreter’s role. This thesis presents findings from six simulated face-to-face dialogue interpreting cases featuring three different groups of participants and interpreters representing different interpreting settings (e.g. parent-teacher meeting, business meeting, doctor-patient meeting, etc.). By adapting a multimodal approach, findings of this study (a) contribute to our understanding of the active role of the interpreter in Interpreting Studies by exploring new insights from a multimodal approach, and (b) offer new empirical findings from interpreter-mediated interactions to the technical analysis of multimodal communication.
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Diehn, Sabrina Maria. "Analysis of data from multimodal chemical characterizations of plant tissues." Doctoral thesis, Humboldt-Universität zu Berlin, 2021. http://dx.doi.org/10.18452/23065.
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Die Vorverarbeitung und Analyse von spektrometrischen und spektroskopischen Daten von Pflanzengewebe sind in den unterschiedlichsten Forschungsbereichen wie der Pflanzenbiologie, Agrarwissenschaften und Klimaforschung von großer Bedeutung. Der Schwerpunkt dieser Arbeit liegt auf der optimierten Nutzung von Daten von Pflanzengeweben, insbesondere der Daten gewonnen durch Matrix–Assistierte Laser–Desorption–Ionisierung Massenspektrometrie, Raman-Spektroskopie und Fourier-Transform-Infrarotspektroskopie. Die Klassifizierungsfähigkeit mit diesen Methoden wird insbesondere nach Kombination der Daten untereinander und mit zusätzlichen chemischen und biologischen Informationen verglichen. Die diskutierten Beispiele befassen sich mit der Untersuchung und Einordnung innerhalb einer bestimmten Pflanzenart, beispielsweise der Unterscheidung von Proben aus unterschiedlichen Populationen, Wachstumsbedingungen oder Gewebeunterstrukturen. Die Daten wurden mit sowohl mit explorativen Werkzeugen wie der Hauptkomponentenanalyse und der hierarchischen Clusteranalyse, als auch mit Methoden des maschinellen Lernens wie die Diskriminanzanalyse oder künstliche neuronale Netzwerke umfassten. Konkret zeigen die Ergebnisse, dass die Kombination der Methoden mit zusätzlichen pflanzenbezogenen Informationen in einer Konsensus-Hauptkomponentenanalyse zu einer umfassenden Charakterisierung der Proben führt. Es werden verschiedene Strategien zur Datenvorbehandlung diskutiert, um nicht relevante spektrale Information zu reduzieren, z.B. aus Karten von Pflanzengeweben oder eingebetteten Pollenkörnern. Die Ergebnisse dieser Arbeit weisen auf die Relevanz der gezielten Nutzung spektrometrischer und spektroskopischer Daten hin und lassen sich nicht nur auf pflanzenbezogene Themen, sondern auch auf andere analytische Klassifizierungsprobleme übertragen.The pre-processing and analysis of spectrometric and spectroscopic data of plant tissue are important in a wide variety of research areas, such as plant biology, agricultural science, and climate research. The focus of the thesis is the optimized utilization of data from plant tissues, which includes data from Matrix-Assisted-Laser Desorption/Ionization time of flight mass spectrometry, Raman spectroscopy, and Fourier transform infrared spectroscopy. The ability to attain a classification using these methods is compared, in particular after combination of the data with each other and with additional chemical and biological information. The discussed examples are concerned with the investigation and classification within a particular plant species, such as the distinction of samples from different populations, growth conditions, or tissue substructures. The data were analyzed by exploratory tools such as principal component analysis and hierarchical cluster analysis, as well as by predictive tools that included partial least square-discriminant analysis and machine learning approaches. Specifically, the results show that combination of the methods with additional plant-related information in a consensus principal component analysis leads to a comprehensive characterization of the samples. Different data pre-treatment strategies are discussed to reduce non-relevant spectral information, e.g., from maps of plant tissues or embedded pollen grains. The results in this work indicate the relevance of the targeted utilization of spectrometric and spectroscopic data and could be applied not only to plant-related topics but also to other analytical classification problems.
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Dicerto, Sara. "Multimodal pragmatics : building a new model for source text analysis." Thesis, University of Surrey, 2015. http://epubs.surrey.ac.uk/808325/.
Full textAbstract:
In an age where technological advancements are providing people with new forms of communication, or increasing the communicative potential of forms previously available, translation is an activity which is growing more and more complex and cannot be accounted for in linguistic terms only. Translation Studies has traditionally dealt with meaning as a linguistic product; however, source texts nowadays very often include resources like images and/or sounds, which interact with the linguistically communicated message, considerably affecting meaning. More accurately, it can be said that linguistic, visual and aural meaning influence each other and create a multimodal message whose interpretation requires different types of literacy and the ability to combine them. Appropriate models analysing multimodal texts, however, are still missing. Furthermore, as no area of translation has been left untouched by the multimodal phenomenon, future translators need to be competent ‘readers’ of multimodal texts. However, the theoretical resources available to train translators are mostly concerned with texts in which the message is communicated verbally; this creates a gap between translation theory and practice as well as a gap between the training translators receive and the reality of the translation industry they need to face, in which translators find themselves working on texts where the message is communicated by more than ‘just’ words. Addressing these gaps, the main aim of this work is to develop a new model for source text analysis for translation purposes. The model brings together aspects of meaning production as it is viewed in Pragmatics, Multimodality, Translation and Semiotics and merges them in a single theoretical framework that can be applied to the analysis of any multimodal source text in order to gain a better understanding of how it conveys meaning. The model aims to contribute to a better general understanding of meaning not just as a linguistic, but as a multimodal product and it is also proposed as a theoretical resource for trainee translators.
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Kamaly, Nazila. "Design, synthesis and evaluation of multimodal paramagnetic lipids for liposomal fluorescence and magnetic resonance imaging." Thesis, Imperial College London, 2007. http://hdl.handle.net/10044/1/1242.
Full textAbstract:
Molecular imaging is a large field encompassing a range of techniques which allow for visualisation of disease processes at the molecular and cellular level. These techniques range from radionuclide, fluorescence and bioluminescence based to magnetic resonance based. Magnetic resonance imaging (MRI) is a clinical imaging technique that benefits from a high degree of spatial resolution and is capable of producing opaque 3D images of tissues within the millimetre range consistently and in a short period of time. The project described is based on the development of contrast agents which are capable of further enhancing images obtained with MRI. The synthesised agents are lipidic based and can therefore be used to formulate liposomes, which are then subsequently used to label cells for cd tracking studies, or used to image tumours in vivo. A further potential of these paramagnetic liposomes is their ability to deliver therapeutic agents such as drugs or nucleic acids into cells and as such their in vitro transfection efficiency was also assessed. Bimodal and trimodal liposomal components were also synthesised and developed to allow for a multimodal imaging platform whereby liposomal particles can be tracked by fluorescel1ce, 1H and 19 F magnetic resonance imaging. Using a combination of solution and solid phase chemistry, paramagnetic and fluorescent lipids were synthesised and characterised. The optimal liposome formulation for in vitro cell labelling was determined along with cytotoxicity studies. MR images of labelled cells were obtained and liposomal uptake into cells determined and validated with fluorescence microscopy. Paramagnetic liposomes were injected into tumour bearing mice and a substantial increase in tumour signal post injection was observed. The paramagnetic liposomes were further functionalised by incorporating a targeting moiety selective for human ovarian cancer cells. A drastic improvement in signal enhancement ability was observed by MRI for targeted liposomes compared to non-targeted liposomes.
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Boase, Nathan R. B. "Hyperbranched polymers for in vivo multimodal molecular imaging." Thesis, University of Queensland, 2015. https://eprints.qut.edu.au/96267/1/96267.pdf.
Full textAbstract:
For the development of the next generation of polymeric nanomedicines, it is crucial to gain a fundamental understanding of their behaviour and interactions with and within biological systems. Moving beyond in vitro models, into in vivo models, earlier in the development process will greatly aid in the advancement of the next generation of nanomedicines. By moving to whole animal models, our understanding of these systems progresses beyond cell targeting and uptake, to developing mechanisms for how these materials will distribute through tissues and their pharmacokinetic profile. This information is important for truly assessing the performance of a nanomedicine. One possible set of tools for obtaining this information is molecular imaging.
Molecular imaging is a field of research dedicated to the real time monitoring of biological processes in vivo, without the use of invasive techniques such as biopsies and dissections. Molecular imaging has been used extensively to follow the in vivo behaviour of a labelled material. This is advantageous because the performance of a single material in one subject can be monitored and mapped against the progression of disease. It can help to provide the pharmacokinetic information necessary for preclinical development of nanomedicines. Nanomedicines can be designed to combine molecular imaging with targeting molecules and therapeutic agents to create a theranostic, which can be used for simultaneous imaging and treatment of disease.
This thesis aims to synthesise novel multimodal molecular imaging agents based on a hyperbranched polymer architecture, and to gain a deeper understanding of how these materials behave in vivo. To achieve this, biocompatible hyperbranched polymers with defined architectures were synthesised using RAFT polymerisation techniques. These materials were extensively characterised using a wide range of spectroscopic techniques to thoroughly understand their physical and chemical properties. A variety of synthetic strategies were investigated for functionalising both the α- and ω-chain ends of these polymers with multiple imaging ligands to form multimodal imaging agents. Far-red and near-infrared fluorophores provided for fluorescence imaging and radiometal chelators allowed for positron emission tomography (PET) imaging.
These hyperbranched polymer systems were first evaluated as molecular imaging agents in C57 BL/6J mice using whole animal fluorescence and PET-CT imaging. It was shown that the rate of excretion was dependent on the size and level of branching of the hyperbranched polymer cores. The larger more highly branched material showed extended circulation times, making it suitable for use as a passive targeting agent for cancer. It was demonstrated in a murine model for melanoma, that the material showed significant uptake within the tumour after 24 hours and that the material was not cleared from the tissue within 72 hours.
To gain a deeper understanding of the behaviour of these materials in vivo, PET imaging was combined with gadolinium contrast enhanced MRI, in order to gain both molecular and physiological information. Using this technique, we were able to show that while a folic acid targeted hyperbranched polymer did accumulate in the tumour tissue, its distribution was concentrated in highly vascularised areas of the tumour. This is the first time that this phenomenon has been demonstrated at a macroscopic level, in a living animal. This has important implications for using these materials as theranostics, because heterogeneous distribution of the nanomaterial, and therefore delivery of a therapeutic, can lead to ineffective treatment of the cancer and thus lead to tumour recurrence.
In further development of these imaging agents into theranostics, targeting of the hyperbranched polymers by conjugating single chain fragment antibodies (scFv) was explored. Two potential routes to improve efficiency of conjugation were investigated. Both approaches used novel bifunctional oligoethylene glycol (OEG) linkers to introduce the required chemical functionality to either the hyperbranched polymer or scFv. The first approach utilised a heterobifunctional OEG which was synthesised with a pentafluorophenol ester at one end for coupling with amines and an ω-azide group at the other end to allow for the copper catalysed Huigsen 1,3-dipolar cycloaddition reactions. This linker was first attached to the scFv via activated ester chemistry, to provide the necessary azide functionality for coupling of the scFv to the alkyne end groups of the hyperbranched polymer. The second route used an enzymatic cross coupling approach using the sortase enzyme. In order to achieve this, a triglycine functionalised OEG ligand was synthesised and attached to the hyperbranched polymer. The triglycine could then be used as a substrate for enzymatic cross coupling to scFv bioengineered to possess the required recognition sequence (LPETG). Despite both OEG linkers being demonstrated to be able to undergo conjugation to both the hyperbranched polymers and scFv independently, further optimisation is required to achieve conjugation of the two macromolecules.
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CASTELLANOS, REYNEL MARTÍNEZ. "CHARACTERIZATION OF IRON ORE PELLETS BY MULTIMODAL MICROSCOPY AND IMAGE ANALYSIS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2016. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=27187@1.
Full textAbstract:
PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIROCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO
Pelotas de minério de ferro são formadas a partir da aglomeração de finos de minério e constituem o principal insumo para o processo de redução na indústria siderúrgica. As frações de fases sólidas e de poros afetam propriedades tais como resistência à compressão, permeabilidade a gases durante o processo de redução, e redutibilidade. No presente trabalho desenvolveu-se um método automático para a identificação e a quantificação automáticas das fases sólidas e poros presentes em pelotas de minério de ferro, mediante a correlação de imagens obtidas por duas técnicas diferentes – microscopia ótica (MO) e eletrônica de varredura (MEV). Imagens em mosaico cobrindo completamente uma seção transversal equatorial da pelota foram capturadas em MO e MEV. Utilizando técnicas de processamento de imagens, as fases e os poros foram identificados e quantificados em cada tipo de imagem. No entanto, cada técnica apresenta limitações na discriminação de certas fases, impedindo uma quantificação completa. Por outro lado, a combinação de imagens dos dois tipos permite discriminar todas as fases. Para isso as imagens de MO e MEV foram automaticamente registradas utilizando pontos de referência homólogos obtidos pela técnica SIFT – Scale Invariant Feature Transform. Após o registro, fases e poros foram individualmente identificadas e quantificadas, levando a resultados muito mais precisos do que os obtidos separadamente. Comparou-se também o resultado de porosidade com o obtido por microtomografia de raios-x (MicroCT). Para isso, um procedimento de correlação identificou a camada de uma tomografia 3D mais similar às imagens de MO ou MEV, foi realizado o registro e mediu-se a fração de área de poros. O valor encontrado foi muito menor na imagem de MicroCT, fato atribuído à pior resolução espacial desta técnica.
Iron ore pellets are formed by an agglomeration process and currently constitute the main source for the reduction process in steel making. The fractions of solid phases and pores directly affect pellets´ properties such as compression resistance, gas permeability during the reduction process, and reducibility. In this work a method for the automatic identification and quantification of phases and pores in iron ore pellets was developed, based on the correlation between images obtained with two different techniques – optical microscopy (OM) and scanning electron microscopy (SEM). Mosaic images covering the full equatorial cross section of a pellet were acquired with OM and SEM. Employing digital image processing techniques the phases and pores were identified and quantified in each type of image. However, each imaging technique has limitations in the discrimination of certain phases, preventing a full quantification. On the other hand, the combination of the two types of images allows discriminating all phases. For that, OM and SEM images were automatically registered using homologous reference points obtained with the SIFT – Scale Invariant Feature Transform technique. After registration, phases and pores were individually identified and quantified, leading to much more accurate results than those provided separately by OM or SEM. The porosity was also compared with that provided by x-ray MicroCT. For that, a correlation procedure identified the closest matching MicroCT layer to the OM or SEM images, the image was registered and the pore fraction was measured. The obtained value is much lower for the MicroCT image, what was attributed to the worse spatial resolution of the technique.
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Varga, Kate, and Ronja Cato. "A multimodal critical discourse analysis of Swedish teaching materials for English." Thesis, Malmö universitet, Malmö högskola, Institutionen för kultur, språk och medier (KSM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-41075.
Full textAbstract:
Education in the Swedish school system should aim to assist pupils in the development of fundamental values. This study investigates to what extent different groups of people are represented within two textbooks for English language teaching (ELT), produced in Sweden and commonly used in Swedish schools and how these representations correlate with the values indicated in the curriculum. Additionally, this study explores if textbooks designed for ELT can be adapted and used as a resource in the Arts classroom for multimodal representation analysis. The study used a multimodal critical discourse analysis with a social semiotic approach to address these questions, looking at the textbooks' textual and visual elements. The result is addressed both quantitatively and qualitatively and showed that, while women were shown in active roles, white men were overrepresented in both the visual and textual representations and people of colour of both genders were underrepresented. The results imply that ELT textbooks have some ways to go in order to meet the representation demands that the curriculum sets and that more research needs to address how to more accurately and frequently represent different groups of people within ELT teaching materials.
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Rose, Richard Travis. "MacVisSTA: A System for Multimodal Analysis of Human Communication and Interaction." Thesis, Virginia Tech, 2007. http://hdl.handle.net/10919/34281.
Full textAbstract:
The study of embodied communication requires access to multiple data sources such as multistream video and audio, various derived and meta-data such as gesture, head, posture, facial expression and gaze information. This thesis presents the data collection, annotation, and analysis for multiple participants engaged in planning meetings. In support of the analysis tasks, this thesis presents the multimedia Visualization for Situated Temporal Analysis for Macintosh (MacVisSTA) system. It supports the analysis of multimodal human communication through the use of video, audio, speech transcriptions, and gesture and head orientation data. The system uses a multiple linked representation strategy in which different representations are linked by the current time focus. MacVisSTA supports analysis of the synchronized data at varying timescales for coarse-to-fine observational studies. The hybrid architecture may be extended through plugins. Finally, this effort has resulted in encoding of behavioral and language data, enabling collaborative research and embodying it with the aid of, and interface to, a database management system.Master of Science
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Taleb, Catherine. "Parkinson's desease detection by multimodal analysis combining handwriting and speech signals." Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT039.
Full textAbstract:
La maladie de Parkinson (MP) est un trouble neurologique causé par une diminution du niveau de dopamine dans le cerveau. Cette maladie est caractérisée par des symptômes moteurs et non moteurs qui s'aggravent avec le temps. Aux stades avancés de la maladie de Parkinson, le diagnostic clinique est clair. Cependant, dans les premiers stades, lorsque les symptômes sont souvent incomplets ou subtils, le diagnostic devient difficile et, parfois, le sujet peut rester non diagnostiqué. En outre, il n'existe pas de méthodes efficaces et fiables permettant d'établir avec certitude un diagnostic précoce du MP. La difficulté de la détection précoce est une forte motivation pour les outils d'évaluation informatisés/outils d'aide à la décision/instruments de test qui peuvent aider au diagnostic précoce et à la prédiction de la progression de la maladie de Parkinson. La détérioration de l'écriture et la déficience vocale peuvent être l'un des premiers indicateurs de l'apparition de la maladie. Selon la documentation examinée, un modèle indépendant du langage pour détecter la maladie de Parkinson à l'aide de signaux multimodaux n'a pas été suffisamment étudié. L'objectif principal de cette thèse est de construire un système multimodal indépendant du langage pour évaluer les troubles moteurs chez les patients atteints de la maladie de Parkinson à un stade précoce, basé sur des signaux combinés d'écriture et de parole, en utilisant des techniques d'apprentissage automatique. Dans ce but et en raison de l'absence d'un ensemble de données multimodales et multilingues, une telle base de données, également répartie entre les témoins et les patients atteints de la maladie de Parkinson, a d'abord été construite. La base de données comprend des enregistrements de l'écriture, de la parole et des mouvements oculaires recueillis auprès de patients témoins et de patients atteints de la maladie de Parkinson en deux phases (avec médication et sans médication). Dans cette thèse, nous nous sommes concentrés sur l'analyse de l'écriture et de la parole, où les patients atteints de la maladie de Parkinson ont été étudiés avec médication.Des modèles indépendants du langage pour la détection de la maladie de Parkinson basés sur les caractéristiques de l'écriture ont été construits ; deux approches ont été envisagées, étudiées et comparées : une approche classique d'extraction et de classification des caractéristiques et une approche d'apprentissage approfondi. Les deux approches ont permis d'atteindre une précision de classification d'environ 97 %. Un classificateur SVM multi-classes pour la détection des étapes basées sur les caractéristiques de l'écriture a été construit. Les performances obtenues n'étaient pas satisfaisantes par rapport aux résultats obtenus pour la détection de MD en raison des nombreux obstacles rencontrés.Un autre ensemble de caractéristiques acoustiques indépendantes de la langue et de la tâche a été construit pour évaluer les troubles moteurs chez les patients atteints de la maladie de Parkinson. Nous avons réussi à construire un modèle SVM indépendant du langage pour le diagnostic de la MP par analyse vocale avec une précision de 97,62%. Enfin, un système multimodal indépendant du langage pour la détection de la maladie de Parkinson en combinant l'écriture et les signaux vocaux a été mis au point, où le modèle SVM classique et les modèles d'apprentissage profond ont tous deux été analysés. Une précision de classification de 100 % est obtenue lorsque des caractéristiques artisanales des deux modalités sont combinées et appliquées au SVM. Malgré les résultats encourageants obtenus, il reste encore du travail à faire avant de mettre notre modèle multimodal de détection de la MP en usage clinique en raison de certaines limitations inhérentes à cette thèseParkinson’s disease (PD) is a neurological disorder caused by a decreased dopamine level on the brain. This disease is characterized by motor and non-motor symptoms that worsen over time. In advanced stages of PD, clinical diagnosis is clear-cut. However, in the early stages, when the symptoms are often incomplete or subtle, the diagnosis becomes difficult and at times, the subject may remain undiagnosed. Furthermore, there are no efficient and reliable methods capable of achieving PD early diagnosis with certainty. The difficulty in early detection is a strong motivation for computer-based assessment tools/decision support tools/test instruments that can aid in the early diagnosing and predicting the progression of PD.Handwriting’s deterioration and vocal impairment may be ones of the earliest indicators for the onset of the illness. According to the reviewed literature, a language independent model to detect PD using multimodal signals has not been enough addressed. The main goal of this thesis is to build a language independent multimodal system for assessment the motor disorders in PD patients at an early stage based on combined handwriting and speech signals, using machine learning techniques. For this purpose and due to the lack of a multimodal and multilingual dataset, such database that is equally distributed between controls and PD patients was first built. The database includes handwriting, speech, and eye movements’ recordings collected from control and PD patients in two phases (“on-state” and “off-state”). In this thesis we focused on handwriting and speech analysis, where PD patients were studied in their “on-state”.Language-independent models for PD detection based on handwriting features were built; where two approaches were considered, studied and compared: a classical feature extraction and classifier approach and a deep learning approach. Approximately 97% classification accuracy was reached with both approaches. A multi-class SVM classifier for stage detection based on handwriting features was built. The achieved performance was non-satisfactory compared to the results obtained for PD detection due to many obstacles faced.Another language and task-independent acoustic feature set for assessing the motor disorders in PD patients was built. We have succeeded to build a language independent SVM model for PD diagnosis through voice analysis with 97.62% accuracy. Finally, a language independent multimodal system for PD detection by combining handwriting and voice signals was built, where both classical SVM model and deep learning models were both analyzed. A classification accuracy of 100% is obtained when handcrafted features from both modalities are combined and applied to the SVM. Despite the encouraging results obtained, there is still some works to do before putting our PD detection multimodal model into clinical use due to some limitations inherent to this thesis
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Villanueva-Jordán, Iván. "Translation and Telefiction: Multimodal Analysis of Paratextual Pieces for HBO’s Looking." Universitat Jaume I, 2021. http://hdl.handle.net/10757/656886.
Full textAbstract:
This paper presents an analysis of the trailers for a telefiction series originally produced in
English and simultaneously distributed in Spanish in Latin America. Looking (aired between
2014 and 2016 by HBO) was a contemporary dramedy series, a hybrid genre typical of the
quality TV promoted by HBO, that told the story of three gay friends living in San Francisco.
The aesthetics of the series reveals the auteur cinematic work of Andrew Haigh, a film
director who applied his visual narrative repertoire to Looking. Using the multimodal
analysis model proposed by Kaindl (2020) and the structure of communicative modes
proposed by Chaume (2004) and Stöckl (2004), this paper analyzes the translation and Latin
American adaptation of two trailers of the series to understand whether the semiotic
integration of the paratexts represents or intensifies the narrative aspects of the hybrid
genre series.
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Lesprier, Jérémy. "Synthèse et validation de lois de commande de vol robustes en présence d’incertitudes paramétriques et de non-linéarités." Thesis, Toulouse, ISAE, 2015. http://www.theses.fr/2015ESAE0031/document.
Full textAbstract:
Les méthodes de synthèse et de validation de lois de pilotage utiliséesdans le milieu industriel aéronautique sont bien souvent longues et coûteuses àmettre en œuvre. Pourtant, des alternatives pour traiter les larges domaine d’évolutionexistent, comme l’inversion dynamique robuste. Ce travail de thèse chercheà en corriger les défauts, notamment grâce à une meilleure prise en compte desincertitudes du système et à une réjection des non-linéarités non compensées. Ceciest rendu possible grâce aux techniques de synthèse H¥ structurée multi-modèles,qui peuvent considérer plusieurs configurations pire-cas déterminées par des outilsd’analyse de robustesse. Une autre contribution est d’ailleurs l’amélioration destechniques permettant d’évaluer la marge de robustesse d’un système LTI, souventtrop conservatives ou nécessitant un temps de calcul prohibitif. Les méthodes proposéessont appliquées au pilotage automatique d’un avion civil et d’un drone àvoilure fixe, dont la modélisation est également traitée avec précisionControl laws design and validation methods used in the aeronautical industryare generally time-consuming and costly to set up. However, alternativesexist to cope with large operating domains, such as robust dynamic inversion.This thesis work aims at fixing its drawbacks by better considering the systemuncertainties, and by rejecting the uncompensated nonlinearities. Thanks to recentadvances in structured multimodel H¥ design techniques, it is now possible toconsider multiple worst-case configurations, determined using robustness analysistools. Besides, another part of this work is devoted to the improvement of existingtechniques to evaluate the robustness margin of an LTI system, which are oftentoo conservative or computationally costly. All these contributions are applied tothe control of a civil aircraft and a small fixed-wing UAV, whose modeling is alsothoroughly described
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Marunowski, Kenneth Ray. "The Euro: A Multimodal Study in Presence." [Kent, Ohio] : Kent State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=kent1155924832.
Full textAbstract:
Thesis (Ph.D.)--Kent State University, 2006.Title from PDF t.p. (viewed Oct. 16, 2006). Advisor: Christina Haas. Keywords: visual rhetoric; European integration; euro; multimodal discourse; presence. Includes bibliographical references (p. 179-185).
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Damaskinidis, George. "Image analysis for translating English multimodal texts into Greek : a multimodal semiotics approach to translation training in a Greek higher education context." Thesis, Open University, 2012. http://oro.open.ac.uk/49080/.
Full textAbstract:
This study explores the image analysis practices of undergraduate translation trainees in a Greek. university. The key research questions focused on the trainees' perception of the role of visual literacy in translation, the nature of their verbal and visual associations and activities effective for developing this role. Visual literacy, semiotics, and translation theories provided the conceptual framework for this multimodal semiotics approach to translation training, which guided my examination of the way the trainees described semiotic resources, how they used verbal and visual elements of Cl. translation task, and the extent to which they focused on the visual. Expanding on the concept of mediation, I developed a 'verbo-visual' mediation model that included visual semiotic elements to provide a detailed description of the ways in which the trainees intervened in the translation process. Through an action research study I gauged the extent to which the trainees had developed visual literacy skills. I planned a series of tasks centred on the translation of a multimodal text from English into Greek. I used direct and video observation of the students as they performed the tasks and afterwards evaluated their translations. The main findings of my research reveal that the trainees found it difficult initially to consider all the semiotic elements of the data-text whilst simultru1eously translating its verbal elements. However. by providing examples of potential verbal-visual interactions and reflecting on and modifying the tasks, I found that the trainees began to appreciate non-verbal elements as potential translational factors. I was thus able to demonstrate a raised level of awareness of the visual elements of multimodal texts to some extent for all trainees in this study. The research suggests that customized image analysis, photo-elicitation and visualization techniques may play a part in the improvement of translation training in a multimodal semiotics translation environment.
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Fyrner, Timmy. "Synthesis of Orthogonally Functionalized Oligosaccharides for Self-assembled Monolayers and as Multimodal Tools in Chemical Biology." Doctoral thesis, Linköpings universitet, Institutionen för fysik, kemi och biologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-76733.
Full textAbstract:
This thesis covers different topics in the field of synthetic organic chemistry combined with the field of surface science and glycobiology. First, the text presents a series of orthogonally protected oligosaccharides (tri-, penta-, and heptasaccharides) of varying length and structures, which are synthesized with the aim of developing novel heterobifunctional biocompatible cross-linkers. Successful conjugation with different chemical handles is also described and used to illustrate the potential implementation of defined carbohydrate based compounds have potential use in biosensing applications. The results of incubation experiments using living cells indicate that the linker is incorporated into cell surfaces and enriched in microdomains. Second, synthesis of various saccharide-terminated alkane thiols immobilized on gold surfaces is reported. The protein adsorption and antifouling characteristics of these surfaces were investigated using model proteins and the common fouling organisms, Ulva linza and Balanus amphitrite. Further, oligo(lactose)-based thiols (di-, tetra-, and hexasaccharides) were synthesized and immobilized on gold nanoparticles to investigate how well these rigid, rod-like oligosaccharides can stabilize such nanoparticles for future use in constructing hybrid nanoparticles. Finally, the thesis describes synthesis of a systematic series of oligo(ethylene) glycols possessing either hydrogen- or methyl-terminated groups. Investigation of the fundamental characteristics of self-assembled monolayers, will give important insights into the design of protein repellant surfaces.
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Bok, Sarah H. "A multimodal analysis of selected National Lovelife HIV/AIDS prevention campaign texts." Thesis, University of the Western Cape, 2008. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_4155_1259739735.
Full textAbstract:
"
This study investigates the ever-changing trends in visual texts and images used during HIV-prevention campaigns in South Africa. The aim is to evaluate and analyse the effect of multimodal texts used in HIV/AIDS campaigns on the understanding and interpretation by the target group, and thus gauge their effectiveness. Using a text-based multimodal approach (Kress and van Leeuwen, 1996/2006
Martin and Rose, 2004), the study takes into account variables such as socio-economic status, literacy levels, language and cultural differences of readers to evaluate the efficacy of loveLife campaigns to disseminate the HIV/AIDS prevention message. This study focuses on the choice of images and words, and whether they cohere to make a meaningful message. The study analyses how the design features, including images, colour and words, impact on the interpretation of the message and also how the design acts as an aid or barrier to the process of decoding the message. The choice of a two-pronged approach combining multimodality and a text-based (discourse) analyses often favoured by those working in systemic functional linguistics is that it enables the researcher to account for social context, economic, linguistic, cultural and behavioural factors that play a role during the decoding phase..."
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Thomas, Martin. "Localizing pack messages : A framework for corpus-based cross-cultural multimodal analysis." Thesis, University of Leeds, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.507881.
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Bießmann, Felix Verfasser], and Klaus-Robert [Akademischer Betreuer] [Müller. "Data-driven analysis for multimodal neuroimaging / Felix Bießmann. Betreuer: Klaus-Robert Müller." Berlin : Universitätsbibliothek der Technischen Universität Berlin, 2012. http://d-nb.info/1018985220/34.
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Gimenes, Gabriel Perri. "Advanced techniques for graph analysis: a multimodal approach over planetary-scale data." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-26062015-105026/.
Full textAbstract:
Applications such as electronic commerce, computer networks, social networks, and biology (protein interaction), to name a few, have led to the production of graph-like data in planetary scale { possibly with millions of nodes and billions of edges. These applications pose challenging problems when the task is to use their data to support decision making processes by means of non-obvious and potentially useful patterns. In order to process such data for pattern discover, researchers and practitioners have used distributed processing resources organized in computational clusters. However, building and managing such clusters can be complex, bringing technical and financial issues that can be prohibitive in a variety of scenarios. Alternatively, it is desirable to process large scale graphs using only one computational node. To do so, we developed processes and algorithms according to three different approaches, building up towards an analytical set capable of revealing patterns, comprehension, and to help with the decision making process over planetary-scale graphs.Aplicações como comércio eletrônico, redes de computadores, redes sociais e biologia (interação proteica), entre outras, levaram a produção de dados que podem ser representados como grafos à escala planetária { podendo possuir milhões de nós e bilhões de arestas. Tais aplicações apresentam problemas desafiadores quando a tarefa consiste em usar as informações contidas nos grafos para auxiliar processos de tomada de decisão através da descoberta de padrões não triviais e potencialmente utéis. Para processar esses grafos em busca de padrões, tanto pesquisadores como a indústria tem usado recursos de processamento distribuído organizado em clusters computacionais. Entretanto, a construção e manutenção desses clusters pode ser complexa, trazendo tanto problemas técnicos como financeiros que podem ser proibitivos em diversos casos. Por isso, torna-se desejável a capacidade de se processar grafos em larga escala usando somente um nó computacional. Para isso, foram desenvolvidos processos e algoritmos seguindo três abordagens diferentes, visando a definição de um arcabouço de análise capaz de revelar padrões, compreensão e auxiliar na tomada de decisão sobre grafos em escala planetária.
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Rukšytė, Eligija. "Communicating corporate image: A Multimodal Critical Discourse Analysis on LinkedIn Job Advertisements." Thesis, Malmö universitet, Institutionen för konst, kultur och kommunikation (K3), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-45971.
Full textAbstract:
Corporate image reflects on how a company is perceived to the public outside of the organisation. It is based on the reputation the company already has and constantly creates. Today numerous people use and rely on social media networks which encourage companies to try to reach their audiences and shape company image by the usage of different digital networks. One of the platforms where companies can represent their business is LinkedIn, as it is designed specifically for organizations and individuals to develop a professional image. One of the platform’s most popular feature is the possibility to post job advertisings that are seen in several platform areas. These job offers serve as a recruitment tool but also simultaneously shape the image of a company. Therefore, it is interesting to explore how job posts of a company manage to stay informative, focused on the targeted audience and, at the same time, shape corporate image. Thesis project, “Communicating corporate image: A Multimodal Critical Discourse Analysis on LinkedIn Job Advertisements”, aims to examine how world leading Swedish companies create their corporate image through job advertisements posted on the social media platform LinkedIn and what that image is. The study draws on media logic theory together with the concept of discourse and tries to reach the project’s aim by applying multimodal critical discourse analysis. By this model, job advertisements of 3 companies based in Sweden were analysed. Results show that corporate image through job advertisements is created equally by the company and the platform LinkedIn. Companies in job advertisements use semi-formal language, creative elements, address accomplishments, values and goals to attract the reader. While LinkedIn places main company information that can influence job advertisement readers to obtain a primary opinion about the enterprise.
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Gonzalez, Johansen Karin. "Weight bias amongst health professionals on Instagram : A critical multimodal discourse analysis." Thesis, Högskolan i Halmstad, Akademin för hälsa och välfärd, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-43512.
Full textAbstract:
Weight bias and weight stigmatization are independent risk factors for poor health, and are brought up within health promotion, as focus areas when it comes to interventions targeting body weight (WHO, 2017; Pearl, 2018). Discourses within the society, can either reinforce weight bias and weight stigmatization towards people in larger bodies, or disrupt them. A gap in the literature exists, when it comes to health professionals and their means of communicating health on social media platforms, such as Instagram. This gap was the inspiration for the present study. The study sought to critically examine the discourses communicated by doctors and registered dietitians on the social media platform Instagram. With the specific focus of examining their presentation of body weight and health, the manifestations of roles and the discourses presented. The study was based on the theory of social semiotics, using critical multimodal discourse analysis, that include elements from the critical discourse analysis framework, by Fairclough (2010) (Machin & Mayr, 2012). The study found that the chosen health professionals generally presented weight bias and presented body weight as a sum of individual choices, as well as body weight as a personal responsibility. The health professionals used both visual and verbal techniques, to establish authority and power, and were generally promoting health as a commodity, as well as using their own body to promote the thin ideal. The strongest discourses present were those of healthism, paternalism and aesthetics defining health, findings that are supported within the literature, when looking at other health promoting entities, such as personal trainers. The study brought forth important implications within health communication on social media platforms, thus that healthism is an area that is important to educate health professionals within, as well as there being basis to further investigate this notion. The study also brought forth important considerations for ethics and validity within this type of research.