The pavement system is subjected to complex stress states under vehicular loading. A combination of axial and shear stress has been identified as a potential cause of top down cracking (or more precisely near surface cracking) in asphalt surface. Therefore, in terms of modeling the material response a pertinent question is whether the typical one-dimensional viscoelastic properties of the material are affected by a multi-axial stress state. Such changes are referred to as interaction non-linearity. The objective of this study was to evaluate whether or not asphalt composites are susceptible to such interaction effects. The study was conducted using fine aggregate matrix (FAM), which comprises graded sand and asphalt binder. To provide multi-modal loading, the rectangular prismatic FAM specimens were used with the Arcan apparatus. This apparatus ensures low bending stress and offers adjustments in the setup to provide different proportions of axial and shear stress. Finite element modeling was done to evaluate the stress state for different orientations of the sample in the Arcan apparatus. For measurement of strain, the study used digital image correlation (DIC), which is an optical, non-contact measurement technology. The strain thus measured was used to compute shear compliance. Fitting parameters of the shear compliances were estimated for power-law and Prony series for different loading orientations. When compared, the measured shear compliances do not show perceivable variation with respect to different proportion of axial stress applied in conjunction. However, further testing with different temperatures and other magnitudes of shear stress is necessary. This study is the first step to allow modeling of stress and crack propagation behavior near the pavement surface where complex stress state is present. / text

In contemporary consumer culture, branding is the term given to the creation of an image or text (visual, aural, textural or multi-sensory) intended to represent a commodity or product sold by a producer or service provider. This product’s commercial viability depends largely on the way it is presented (via branding) to its target market. The aim of this research report is to show that music used consciously as a branding medium, with special reference to film music (in its commodified form), has become a brand in itself, as opposed to merely a component of a multi-modal commercial product. Through analyses of a central film music theme from Star Wars: Episode IV, composed by John Williams, I aim to identify what I will term `audio-branding techniques’ within the music, thereby showing how music has come to be regarded as a brand. The audio branding techniques will relate directly to the four levels of analysis that I propose to conduct. The nature of branding implies the presence of three entities in the cultural and commercial `transaction’ that takes place: namely, the service provider (creator), the product (commodity) and the target market (consumer). I intend to argue that, as a result of powerful creative collaborations between John Williams and his various directors (not to mention his own unique talent), this composer’s film music has increasingly become an audio brand which is almost commensurate with the brand status of the film itself. Williams’s ability to create a symbiotic relationship between a music brand and that of a film has set him apart from most other contemporary art and commercial composers. As a result, it is not simply the actors, directors and producers associated with a movie that induce one to buy tickets to see it, but Williams’s independent audio branding style as well. I thus aim to prove that his film music is an audio brand independent of, and yet also allied with, other brands.

M. Mus. (Composition) by Coursework and Research, Faculty of Humanities, University of the Witwatersrand, 2011 / The aim of this Research Report is to highlight the overt and more subtle roles that contemporary film music plays in the final presentation of a film. An analysis of selected examples by the renowned film music composer, Hans Zimmer, illustrates the techniques and musical tools that he uses to achieve certain effects which influence the way different scenes are perceived by the viewer/listener. Much of the debate revolves around the degree to which the music plays either an obvious or less obvious role in the multi-media modality of film and the techniques that the composer applies to achieve his/her desired dramatic result. I have drawn on the writings of current film music theorists in order to interrogate the interaction between music and some of the other art-forms that coalesce in the creation of the final film product.

Syftet med studien är att undersöka fiollärares syn på och användning av stråkteknik i sin undervisning. Detta görs med följande forskningsfrågor: Hur representerar fiollärare sin syn på stråkteknik? och Hur designar fiollärare sin undervisning i stråkteknik? Studien är kvalitativ och data har samlats in genom semistrukturerade intervjuer med fyra olika fiollärare på musik- och kulturskolor. Studiens teoretiska utgångspunkt utgörs av socialsemiotiskt perspektiv. Intervjuerna ljudinspelades och även videodokumenterades för att sedan transkriberas och analyseras med hjälp av analysverktyg från det valda teoretiska ramverket. I studiens resultat beskrivs fiollärarnas syn på stråkteknik samt hur de designar sin undervisning i stråkteknik. De teman som presenteras är stråkteknik som tonbildning, stråkteknik som hållning, stråkteknik som instrumentteknik, materiella resurser i undervisningen samtkroppsliga och klingande resurser i undervisningen.I resultatet framkommer många skillnader men även likheter i de intervjuade fiollärarnas utsagor, men alla belyser stråkteknikens betydelse i undervisningen och dess funktion. I studiens avslutande kapitel diskuteras resultatet i förhållande till tidigare litteratur och forskning samt till studiens socialsemiotiska perspektiv. De teman som presenteras är undervisning ur ett socialsemiotiskt perspektiv samt stråkteknik kopplat till stråkhållning och tonbildning. Det tas även upp om metoddiskussion, arbetets betydelse samt fortsatt forskning. / The purpose of the study is to investigate violin teachers’ view of and use of bowing technique in their teaching. The study´s research questions concern how do violin teachers represent their view of bow technique? And how do violin teachers design their teaching in bow technique? The study is qualitative, and data has been collected through semi structured interviews with four different violin teachers at music and cultural schools. The theoretical starting point of the study is social semiotic perspective. The interviews were recorded by audio and video and were then transcribe and analyzed. The analysis was conducted with tools from the chosen theoretical framework. In the study's results, the violin teachers' view of bow technique is described and how they design their teaching in bow technique. The themes presented are string techniques such as tone formation, bow technique such as posture, bow technique such as instrument technology, material resources in teachingandbodily and sounding resources in teaching. The result shows many differences but also similarities in the interviewed violin teachers' statements, but all highlight the significance of the bow technique in teaching and its function. In the final chapter of the study, the result is discussed in relation to previous literature and research, and to the social semiotic perspective of the study. The themes presented are teaching from a social semiotic perspectiveand bow technique linked to posture and tone formation. The method discussion, the importance of work and continued research is also mentioned.

<div>With robots expanding their applications in more and more scenarios, practical problems from different scenarios are challenging current 3D measurement techniques. For instance, infrastructure inspection robots need large-scale and high-spatial-resolution 3D data for crack and defect detection, medical robots need 3D data well registered with temperature information, and warehouse robots need multi-resolution 3D shape measurement to adapt to different tasks. In the past decades, a lot of progress has been made in improving the performance of 3D shape measurement methods. Yet, measurement scale and speed and the fusion of multiple modalities of 3D shape measurement techniques remain vital aspects to be improved for robots to have a more complete perception of the real scene. In this dissertation, we will focus on the digital fringe projection technique, which usually can achieve high-accuracy 3D data, and expand the capability of that technique to complicated robot applications by 1) extending the measurement scale, 2) registering with multi-modal information, and 3) improving the measurement speed of the digital fringe projection technique.</div><div><br></div><div>The measurement scale of the digital fringe projection technique mainly focused on a small scale, from several centimeters to tens of centimeters, due to the lack of a flexible and convenient calibration method for a large-scale digital fringe projection system. In this study, we first developed a flexible and convenient large-scale calibration method and then extended the measurement scale of the digital fringe projection technique to several meters. The meter scale is needed in many large-scale robot applications, including large infrastructure inspection. Our proposed method includes two steps: 1) accurately calibrate intrinsics (i.e., focal lengths and principal points) with a small calibration board at close range where both the camera and projector are out of focus, and 2) calibrate the extrinsic parameters (translation and rotation) from camera to projector with the assistance of a low-accuracy large-scale 3D sensor (e.g., Microsoft Kinect). The two-step strategy avoids fabricating a large and accurate calibration target, which is usually expensive and inconvenient for doing pose adjustments. With a small calibration board and a low-cost 3D sensor, we calibrated a large-scale 3D shape measurement system with a FOV of (1120 x 1900 x 1000) mm^3 and verified the correctness of our method.</div><div><br></div><div> Multi-modal information is required in applications such as medical robots, which may need both to capture the 3D geometry of objects and to monitor their temperature. To allow robots to have a more complete perception of the scene, we further developed a hardware system that can achieve real-time 3D geometry and temperature measurement. Specifically, we proposed a holistic approach to calibrate both a structured light system and a thermal camera under exactly the same world coordinate system, even though these two sensors do not share the same wavelength; and a computational framework to determine the sub-pixel corresponding temperature for each 3D point, as well as to discard those occluded points. Since the thermal 2D imaging and 3D visible imaging systems do not share the same spectrum of light, they can perform sensing simultaneously in real time. We developed a hardware system that achieved real-time 3D geometry and temperature measurement at 26Hz with 768 x 960 points per frame.</div><div><br></div><div> In dynamic applications, where the measured object or the 3D sensor could be in motion, the measurement speed will become an important factor to be considered. Previously, people projected additional fringe patterns for absolute phase unwrapping, which slowed down the measurement speed. To achieve higher measurement speed, we developed a method to unwrap a phase pixel by pixel by solely using geometric constraints of the structured light system without requiring additional image acquisition. Specifically, an artificial absolute phase map $\Phi_{min}$, at a given virtual depth plane $z = z_{min}$, is created from geometric constraints of the calibrated structured light system, such that the wrapped phase can be pixel-by-pixel unwrapped by referring to $\Phi_{min}$. Since $\Phi_{min}$ is defined in the projector space, the unwrapped phase obtained from this method is an absolute phase for each pixel. Experimental results demonstrate the success of this proposed novel absolute-phase unwrapping method. However, the geometric constraint-based phase unwrapping method using a virtual plane is constrained in a certain depth range. The depth range limitations cause difficulties in two measurement scenarios: measuring an object with larger depth variation, and measuring a dynamic object that could move beyond the depth range. To address the problem of depth limitation, we further propose to take advantage of an additional 3D scanner and use additional external information to extend the maximum measurement range of the pixel-wise phase unwrapping method. The additional 3D scanner can provide a more detailed reference phase map $\Phi_{ref}$ to assist us to do absolute phase unwrapping without the depth constraint. Experiments demonstrate that our method, assisted by an additional 3D scanner, can work for a large depth range, and the maximum speed of the low-cost 3D scanner is not necessarily an upper bound of the speed of the structured light system. Assisted by Kinect V2, our structured light system achieved 53Hz with a resolution 1600 x 1000 pixels when we measured dynamic objects that were moving in a large depth range.</div><div><br></div><div> In summary, we significantly advanced the 3D shape measurement technology for robots to have a more complete perception of the scene by enhancing the digital fringe projection technique in measurement scale (space domain), speed (time domain), and fusion with other modality information. This research can potentially enable robots to have a better understanding of the scene for more complicated tasks, and broadly impact many other academic studies and industrial practices.</div>

Puisque les traits de biométrie douce peuvent fournir des preuves supplémentaires pour aider à déterminer précisément l’identité de l’homme, il y a eu une attention croissante sur la reconnaissance faciale basée sur les biométrie douce ces dernières années. Parmi tous les biométries douces, le sexe et l’ethnicité sont les deux caractéristiques démographiques importantes pour les êtres humains et ils jouent un rôle très fondamental dans l’analyse de visage automatique. En attendant, la reconnaissance des expressions faciales est un autre challenge dans le domaine de l’analyse de visage en raison de la diversité et de l’hybridité des expressions humaines dans différentes cultures, genres et contextes. Ce thèse est dédié à combiner la texture du visage 2D et la morphologie du visage 3D pour estimer les biométries douces: le sexe, l’ethnicité, etc., et reconnaître les expressions faciales. Pour la reconnaissance du sexe et de l’ethnicité, nous présentons une approche efficace en combinant à la fois des textures locales et des caractéristiques de forme extraites à partir des modèles de visage 3D, contrairement aux méthodes existantes qui ne dépendent que des textures ou des caractéristiques de forme. Afin de souligne exhaustivement la différence entre les groupes sexuels et ethniques, nous proposons un nouveau descripteur, à savoir local circular patterns (LCP). Ce descripteur améliore Les motifs binaires locaux (LBP) et ses variantes en remplaçant la quantification binaire par une quantification basée sur le regroupement, entraînant d’une puissance plus discriminative et une meilleure résistance au bruit. En même temps, l’algorithme Adaboost est engagé à sélectionner les caractéristiques discriminatives fortement liés au sexe et à l’ethnicité. Les résultats expérimentaux obtenus sur les bases de données FRGC v2.0 et BU-3DFE démontrent clairement les avantages de la méthode proposée. Pour la reconnaissance des expressions faciales, nous présentons une méthode automatique basée sur les multi-modalité 2D + 3D et démontrons sa performance sur la base des données BU-3DFE. Notre méthode combine des textures locales et des descripteurs de formes pour atteindre l’efficacité et la robustesse. Tout d’abord, un grand ensemble des points des caractéristiques d’images 2D et de modèles 3D sont localisés à l’aide d’un nouvel algorithme, à savoir la cascade parallèle incrémentielle de régression linéaire (iPar-CLR). Ensuite, on utilise un nouveau descripteur basé sur les histogrammes des gradients d’ordre secondaire (HSOG) en conjonction avec le descripteur SIFT pour décrire la texture locale autour de chaque point de caractéristique 2D. De même, la géométrie locale autour de chaque point de caractéristique 3D est décrite par deux nouveaux descripteurs de forme construits à l’aide des quantités différentielle de géométries de la surface au premier ordre et au second ordre, à savoir meshHOG et meshHOS. Enfin, les résultats de reconnaissance des descripteurs 2D et 3D fournis par le classifier SVM sont fusionnés à la fois au niveau de fonctionnalité et de score pour améliorer la précision. Les expérimentaux résultats démontrent clairement qu’il existe des caractéristiques complémentaires entre les descripteurs 2D et 3D. Notre approche basée sur les multi-modalités surpasse les autres méthodes de l’état de l’art en obtenant une précision de reconnaissance 86,32%. De plus, une bonne capacité de généralisation est aussi présentée sur la base de données Bosphorus. / Since soft biometrics traits can provide sufficient evidence to precisely determine the identity of human, there has been increasing attention for face based soft biometrics identification in recent years. Among those face based soft biometrics, gender and ethnicity are both key demographic attributes of human beings and they play a very fundamental and important role in automatic machine based face analysis. Meanwhile, facial expression recognition is another challenge problem in face analysis because of the diversity and hybridity of human expressions among different subjects in different cultures, genders and contexts. This Ph.D thesis work is dedicated to combine 2D facial Texture and 3D face morphology for estimating people’s soft biometrics: gender, ethnicity, etc., and recognizing facial expression. For the gender and ethnicity recognition, we present an effective and efficient approach on this issue by combining both boosted local texture and shape features extracted from 3D face models, in contrast to the existing ones that only depend on either 2D texture or 3D shape of faces. In order to comprehensively represent the difference between different genders or ethnics groups, we propose a novel local descriptor, namely local circular patterns (LCP). LCP improves the widely utilized local binary patterns (LBP) and its variants by replacing the binary quantization with a clustering based one, resulting in higher discriminative power as well as better robustness to noise. Meanwhile, the following Adaboost based feature selection finds the most discriminative gender- and ethnic-related features and assigns them with different weights to highlight their importance in classification, which not only further raises the performance but reduces the time and memory cost as well. Experimental results achieved on the FRGC v2.0 and BU-3DFE data sets clearly demonstrate the advantages of the proposed method. For facial expression recognition, we present a fully automatic multi-modal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU–3DFE database. Our approach combines multi-order gradientbased local texture and shape descriptors in order to achieve efficiency a nd robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar–CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are employed to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both featurelevel and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU–3DFE benchmark to compare our approach to the state-of-the-art ones. Our multi-modal feature-based approach outperforms the others by achieving an average recognition accuracy of 86,32%. Moreover, a good generalization ability is shown on the Bosphorus database.

Introdução: Quedas representam risco extremamente incidente entre idosos, e sua recuperação produz altos custos. Algumas das causas mais comuns podem ser atenuadas por exercícios, se oferecidos de forma acessível. Objetivos: Comparar os efeitos de um treinamento físico multimodal quando realizado de forma supervisionada e semissupervisionada, sobre variáveis reconhecidamente relacionadas ao risco de quedas em idoso com preservada independência e histórico de quedas. Métodos: Setenta e seis idosos com histórico de quedas, acima de 70 anos, média de 79,06 anos (±4,55), foram avaliados sobre a saúde geral, histórico e risco de quedas, perigos domésticos, e foram submetidos aos seguintes testes: Timed up and Go (TUG), Walk Performance Test (WPT), Berg Balance Scale (BBS), avaliação isocinética do joelho e os seguintes testes em plataforma de equilibrio: Tandem Walk (TW), Sit to Stand (STS), Step up Over (SUO), Limits of Stability (LOS) e Modified Clinical Test of Sensory Integration on Balance (MCTSIB). Foram aleatoriamente alocados em 3 grupos: Supervisionado (S), orientado em todas as sessões, Semissupervisionado (SS), orientado quinzenalmente a executar exercícios em casa, e Controle (C), sem intervenção. O programa de exercícios multimodais foi executado em 3 sessões semanais de 50 minutos, por 4 meses. Participantes registraram quedas em calendário, e avaliações foram repetidas ao final do período. Resultados: Após intervenção o grupo S reduziu tempo do TUG (p<0,001) e no WPT (p<0,001) e aumentou a pontuação do BBS (p= 0,018), a Potência Média (p<0,001), o Pico de Torque/ Peso (p= 0,036) e a Média do Pico de Torque (p= 0,006) na flexão direita. Reduziu Tempo de Transferência no STS (p= 0,039), o Índice de Impacto na descida no SUO (p= 0.047), e a Oscilação no MCTSIB na 1ª (p= 0,037) e na 4ª (p= 0,032) condições avaliadas. No LOS, aumentou Velocidade (p<0,001), a Máxima Excursão (p<0,001) e o Controle de Direção (p= 0,004). O grupo SS reduziu o tempo no TUG (p= 0,001), aumentou o Índice de Fadiga na flexão do joelho direito (p= 0,043), aumentou Velocidade e reduziu Oscilação no TW (p= 0,008 e 0,020 respectivamente). No LOS, aumentou Velocidade (p= 0,023), a Máxima Excursão (p= 0,035) e o Controle de Direção (p= 0,006). O grupo C reduziu Velocidade no TW (p= 0,033) e aumentou o Índice de Fadiga na flexão direita (p= 0,017). O grupo S apresentou magnitude do efeito diferente na Potência Média da Flexão do Joelho direito (p= 0,002 para S versus SS, e p= 0,004 para S versus C). Os grupos S e C apresentaram diferença entre si na variação da Velocidade do LOS (p= 0,003). Os grupos S e SS obtiveram alterações diferentes do grupo C no TUG (p= 0,003 para C vs. S, e p= 0,021 para C vs. SS), e na Velocidade do TW (p= 0,007 para C vs. S, e p= 0,003 para C vs. SS). Conclusões: Numa população de idosos não institucionalizados, com independência preservada, baixa renda, pouca escolaridade, e com histórico de quedas, um treinamento físico multimodal, aplicado tanto de forma semissupervisionada, em casa, quanto de forma supervisionada, no centro de saúde, pode ser efetivo em melhorar variáveis previamente reconhecidas como sendo altamente relacionadas ao risco de quedas. Os resultados equivalentes entre os grupos S e SS impedem-nos de afirmar que a supervisão acrescente expressiva extensão a este benefício / Background: Falls are an extremely incidental healthcare risk among the geriatric populations and lead to high recuperative costs. Muscle weakness and balance impairment are among the most common causes and can be attenuated by exercises, if provided in an accessible way. Objectives: To compare the effects on variables related to falls risk, of a fully supervised center-based and a semi-supervised home-based multi-modal exercise program in elderly with preserved independence, and history of falls. Methods: Seventy six older adults with history of falls, over 70 years old, mean age of 79.06 years (±4.55) were assessed about general health, falls history and risk, home hazard and were submitted to the following tests: Timed up and Go (TUG), Walk Performance Test (WPT), Berg Balance Scale (BBS), Knee Isokinetic dynamometer test, and five tests on balance force plate: Tandem Walk (TW), Sit to Stand (STS), Step up Over (SUO), Limits of Stability (LOS) and modified Clinical Test of Sensory Integration on Balance (MCTSIB). Participants were randomized into three groups: supervised (S) that was instructed in all sessions, semi-supervised (SS) that received orientation every other week and performed the exercises at home, and control (C) that did not receive any exercise intervention. The multi-modal program consisted in three 50-minute sessions per week over four months. Participants recorded falls in a calendar and assessments were repeated at the end of the period Results: After intervention, S groups reduced time in TUG (p<0.001) and WPT (p<0.001), increased the BBS score (p= 0.018), the Average Power (p<0.001), the Peak Torque/Weight (p= 0.036), and the average Peak Torque (p= 0.006) of right knee flexion. It reduced Transfer Time in STS (p= 0.039), o Impact Index on SUO (p= 0.047), and End Sway on MCTSIB on 1st (p= 0.037) and 4th (p= 0.032) conditions assessed. On LOS, increased Movement Velocity (p<0.001), Maximum Excursion (p<0.001), and Directional Control (p= 0.004). The SS group reduced TUG (p= 0.001), increased Fatigue Work on right knee flexion (p= 0.043), increased Speed and reduced End Sway on TW (p= 0.008 e 0.020 respectively). On LOS, increased the velocity (p= 0,023), the Maximum Excursion (p= 0.035) and Directional Control (p= 0.006). The C group reduced TW speed (p= 0.033) and increased Fatigue Work of right knee flexion (p= 0.017). The S group showed different magnitude of effect in Average Power of right knee flexion (p= 0.002 for S vs. SS, and p= 0,004 for S vs. C). Groups S and C were different from each other on LOS Velocity (p= 0.003). Comparing to C, both trained groups, S and SS, had different magnitude of effect on TUG (p= 0.003 for C vs. S, and p= 0.021 for C vs. SS), and TW Speed (p= 0.007 for C vs. S, and p= 0.003 for C vs. SS). Conclusions: In a community-dwelling elderly population with preserved independence, low income and minimal education, with history of falls, a semi-supervised home-based and supervised center-based multi-modal exercise program, may be effective in improving variables previously recognized as highly related to falls risk. The similar results between trained groups prevent us to affirm that supervision adds expressive extent to the benefit

Curtin Universitys Embodied Conversational Agents (ECA) combine an MPEG-4 compliant Facial Animation Engine (FAE), a Text To Emotional Speech Synthesiser (TTES), and a multi-modal Dialogue Manager (DM), that accesses a Knowledge Base (KB) and outputs Virtual Human Markup Language (VHML) text which drives the TTES and FAE. A user enters a question and an animated ECA responds with a believable and affective voice and actions. However, this response to the user is normally marked up in VHML by the KB developer to produce the required facial gestures and emotional display. A real person does not react by fixed rules but on personality, beliefs, previous experiences, and training. This thesis details the design, implementation and pilot study evaluation of an Affective Personality Model for an ECA. The thesis discusses the Email Agent system that informs a user when they have email. The system, built in Curtins ECA environment, has personality traits of Friendliness, Extraversion and Neuroticism. A small group of participants evaluated the Email Agent system to determine the effectiveness of the implemented personality system. An analysis of the qualitative and quantitative results from questionnaires is presented.

Identity verification systems are an important part of our every day life. A typical example is the Automatic Teller Machine (ATM) which employs a simple identity verification scheme: the user is asked to enter their secret password after inserting their ATM card; if the password matches the one prescribed to the card, the user is allowed access to their bank account. This scheme suffers from a major drawback: only the validity of the combination of a certain possession (the ATM card) and certain knowledge (the password) is verified. The ATM card can be lost or stolen, and the password can be compromised. Thus new verification methods have emerged, where the password has either been replaced by, or used in addition to, biometrics such as the person’s speech, face image or fingerprints. Apart from the ATM example described above, biometrics can be applied to other areas, such as telephone & internet based banking, airline reservations & check-in, as well as forensic work and law enforcement applications. Biometric systems based on face images and/or speech signals have been shown to be quite effective. However, their performance easily degrades in the presence of a mismatch between training and testing conditions. For speech based systems this is usually in the form of channel distortion and/or ambient noise; for face based systems it can be in the form of a change in the illumination direction. A system which uses more than one biometric at the same time is known as a multi-modal verification system; it is often comprised of several modality experts and a decision stage. Since a multi-modal system uses complimentary discriminative information, lower error rates can be achieved; moreover, such a system can also be more robust, since the contribution of the modality affected by environmental conditions can be decreased. This thesis makes several contributions aimed at increasing the robustness of single- and multi-modal verification systems. Some of the major contributions are listed below. The robustness of a speech based system to ambient noise is increased by using Maximum Auto-Correlation Value (MACV) features, which utilize information from the source part of the speech signal. A new facial feature extraction technique is proposed (termed DCT-mod2), which utilizes polynomial coefficients derived from 2D Discrete Cosine Transform (DCT) coefficients of spatially neighbouring blocks. The DCT-mod2 features are shown to be robust to an illumination direction change as well as being over 80 times quicker to compute than 2D Gabor wavelet derived features. The fragility of Principal Component Analysis (PCA) derived features to an illumination direction change is solved by introducing a pre-processing step utilizing the DCT-mod2 feature extraction. We show that the enhanced PCA technique retains all the positive aspects of traditional PCA (that is, robustness to compression artefacts and white Gaussian noise) while also being robust to the illumination direction change. Several new methods, for use in fusion of speech and face information under noisy conditions, are proposed; these include a weight adjustment procedure, which explicitly measures the quality of the speech signal, and a decision stage comprised of a structurally noise resistant piece-wise linear classifier, which attempts to minimize the effects of noisy conditions via structural constraints on the decision boundary.

<p>A difficult issue in stress management is to use biomedical sensor signal in the diagnosis and treatment of stress. Clinicians often make their diagnosis and decision based on manual inspection of physiological signals such as, ECG, heart rate, finger temperature etc. However, the complexity associated with manual analysis and interpretation of the signals makes it difficult even for experienced clinicians. Today the diagnosis and decision is largely dependent on how experienced the clinician is interpreting the measurements.  A computer-aided decision support system for diagnosis and treatment of stress would enable a more objective and consistent diagnosis and decisions.</p><p>A challenge in the field of medicine is the accuracy of the system, it is essential that the clinician is able to judge the accuracy of the suggested solutions. Case-based reasoning systems for medical applications are increasingly multi-purpose and multi-modal, using a variety of different methods and techniques to meet the challenges of the medical domain. This research work covers the development of an intelligent clinical decision support system for diagnosis, classification and treatment in stress management. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques have been investigated to enable a more reliable and efficient diagnosis and treatment of stress such as case-based reasoning, textual information retrieval, rule-based reasoning, and fuzzy logic. Functionalities and the performance of the system have been validated by implementing a research prototype based on close collaboration with an expert in stress. The case base of the implemented system has been initiated with 53 reference cases classified by an experienced clinician. A case study also shows that the system provides results close to a human expert. The experimental results suggest that such a system is valuable both for less experienced clinicians and for experts where the system may function as a second option.</p> / IPOS, PROEK