This thesis studies the applicability of two cardiac traits, the electrocardiogram (ECG) and the phonocardiogram (PCG), as biometrics. There is strong evidence that cardiac electrical activity (ECG) embeds highly distinctive characteristics, suitable for applications such as the recognition of human subjects. On the other hand, having the same origin with the ECG signal, it is believed that the PCG signal conveys distinctive information of an individual which can be deployed in biometric applications. Such recognition systems traditionally provide two modes of functionality, identification and authentication; frameworks for subject recognition are herein proposed and analyzed in both scenarios. Moreover, the expression of the cardiac signals is subject to alternation with heart rate and noise components. Thus, the central consideration of this thesis is the design and evaluation of robust recognition approaches that can compensate for these effects. A recognition system based on each, the ECG and the PCG, is developed and evaluated. Furthermore, a fusion of the two signals in a multimodal biometric system is investigated.

This thesis studies the applicability of two cardiac traits, the electrocardiogram (ECG) and the phonocardiogram (PCG), as biometrics. There is strong evidence that cardiac electrical activity (ECG) embeds highly distinctive characteristics, suitable for applications such as the recognition of human subjects. On the other hand, having the same origin with the ECG signal, it is believed that the PCG signal conveys distinctive information of an individual which can be deployed in biometric applications. Such recognition systems traditionally provide two modes of functionality, identification and authentication; frameworks for subject recognition are herein proposed and analyzed in both scenarios. Moreover, the expression of the cardiac signals is subject to alternation with heart rate and noise components. Thus, the central consideration of this thesis is the design and evaluation of robust recognition approaches that can compensate for these effects. A recognition system based on each, the ECG and the PCG, is developed and evaluated. Furthermore, a fusion of the two signals in a multimodal biometric system is investigated.

La surveillance de la santé foetale permet aux cliniciens d’évaluer le bien-être du foetus,de faire une détection précoce des anomalies cardiaques foetales et de fournir les traitementsappropriés. Les développements technologies actuels visent à permettre la mesurede l’électrocardiogramme (ECG) foetal de façon non-invasive afin d’extraire non seulementle rythme cardiaque mais également la forme d’onde du signal. Cet objectif est rendudifficile par le faible rapport signal sur bruit des signaux mesurés sur l’abdomen maternel.Cette mesure est donc toujours un challenge auquel se confrontent beaucoup d’études quiproposent des solutions de traitement de signal basées sur la seule modalité ECG.Le but de cette thèse est d’utiliser la modélisation des processus Gaussiens pour améliorerl’extraction des signaux cardiaques foetaux, dans une base multi-modale. L’ECG est utiliséconjointement avec le signal Phonocardiogramme (PCG) qui peut apporter une informationcomplémentaire à l’ECG. Une méthode générale pour la modélisation des signauxquasi-périodiques est présentée avec l’application au débruitage de l’ECG et à l’extractionde l’ECG du foetus. Différents aspects de la multi-modalité (synchronisation, · · · ) proposéesont étudiées afin de détecter avec plus de robustesse les battements cardiaques foetaux.La méthode considère l’application sur les signaux ECG et PCG à travers deux aspects:l’aspect du traitement du signal et l’expérimental. La modélisation des processus Gaussien,avec le signal PCG pris comme la référence, est utilisée pour extraire des modèles flexibleset des estimations non linéaires de l’information. La méthode cherche également à faciliterla mise en oeuvre pratique en utilisant un codage 1-bit des signaux de référence.Le modèle proposé est validé sur des signaux synthétiques et également sur des donnéespréliminaires réelles qui ont été enregistrées afin d’amorcer la constitution d’une base dedonnées multi-modale synchronisée. Les premiers résultats montrent que la méthode permettraà terme aux cliniciens d’étudier les battements cardiaques ainsi que la morphologiede l’ECG. Ce dernier aspect était jusqu’à présent limité à l’analyse d’enregistrements ECGinvasifs prélevés pendant l’accouchement par le biais d’électrodes posées sur le scalp dufoetus. / Fetal health must be carefully monitored during pregnancy to detect early fetal cardiac diseases, and provide appropriate treatment. Technological development allows a monitoring during pregnancy using the non-invasive fetal electrocardiogram (ECG). Noninvasive fetal ECG is a method not only to detect fetal heart rate, but also to analyze the morphology of fetal ECG, which is now limited to analysis of the invasive ECG during delivery. However, the noninvasive fetal ECG recorded from the mother's abdomen is contaminated with several noise sources among which the maternal ECG is the most prominent.In the present study, the problem of noninvasive fetal ECG extraction is tackled using multi-modality. Beside ECG signal, this approach benefits from the Phonocardiogram (PCG) signal as another signal modality, which can provide complementary information about the fetal ECG.A general method for quasi-periodic signal analysis and modeling is first described and its application to ECG denoising and fetal ECG extraction is explained. Considering the difficulties caused by the synchronization of the two modalities, the event detection in the quasi-periodic signals is also studied which can be specified to the detection of the R-peaks in the ECG signal.The method considers both clinical and signal processing aspects of the application on ECG and PCG signals. These signals are introduced and their characteristics are explained. Then, using PCG signal as the reference, the Gaussian process modeling is employed to provide the possibility of flexible models as nonlinear estimations. The method also tries to facilitate the practical implementation of the device by using the less possible number of channels and also by using only 1-bit reference signal.The method is tested on synthetic data and also on real data that is recorded to provide a synchronous multi-modal data set.Since a standard agreement for the acquisition of these modalities is not yet taken into much consideration, the factors which influence the signals in recording procedure are introduced and their difficulties and effects are investigated.The results show that the multi-modal approach is efficient in the detection of R-peaks and so in the extraction of fetal heart rate, and it also provides the results about the morphology of fetal ECG.

Le coeur est un muscle. Son fonctionnement mécanique est celui d'une pompe chargée de distribuer et de récupérer le sang dans les poumons et dans le système cardiovasculaire. Son fonctionnement électrique est régulé par le son noeud sinusal, un stimulateur ou régulateur électrique chargé de déclencher les battements naturels du coeur qui rythment le fonctionnement du corps. Les médecins surveillent ce fonctionnement électromécanique du coeur en enregistrant un signal électrique appelé électrocardiogramme (ECG) ou un signal sonore : le phono-cardiogramme (PCG). L'analyse et le traitement de ces deux signaux sont fondamentaux pour établir un diagnostic et aider à déceler des anomalies et des pathologies cardiaques. L’objectif de cette thèse est de développer des techniques de traitement des signaux ECG et notamment PCG afin d’aider le médecin dans son analyse de ces signaux. L’idée de fond est de mettre en point des algorithmes relativement simples et peu coûteux en temps de calcul. Le premier intérêt serait de garantir leur implantation aisée dans un système mobile de surveillance cardiaque à l’usage du médecin, voire du patient. Le deuxième intérêt réside dans la possibilité d’une analyse automatique en temps réel des signaux avec le dispositif mobile, autorisant le choix de la transmission de ces signaux pour une levée de doute. De nombreux travaux ont mené à des avancées significatives dans l’analyse des signaux ECG et la reconnaissance automatiques des pathologies cardiaques. Des bases de données de signaux réels ou synthétiques annotées permettent également d’évaluer les performances de toute nouvelle méthode. Quant aux signaux PCG, ils sont nettement moins étudiés, difficiles à analyser et à interpréter. Même si les grandes familles de méthodes (Fourier, Wigner Ville et ondelettes) ont été testées, elles n’autorisent pas une reconnaissance automatique des signatures, d’en avoir une analyse et une compréhension assez fines.La Transformée en Ondelettes (TO) sur les signaux cardiaques a montré son efficacité pour filtrer et localiser les informations utiles mais elle fait intervenir une fonction externe de traitement (ondelette mère) dont le choix dépend de la connaissance au préalable du signal à traiter. Ce n'est pas toujours adapté aux signaux cardiaques. De plus, la Transformée en ondelettes induit généralement une imprécision dans la localisation due à la fonction externe et éventuellement au sous-échantillonnage des signatures. La nature non stationnaire de l'ECG et du PCG et leur sensibilité aux bruits rendent difficile la séparation d’une transition informative d'une transition due aux bruits de mesure. Le choix de l'outil de traitement doit permettre un débruitage et une analyse de ces signaux sans délocalisation des singularités ni altération de leurs caractéristiques. En réponse à nos objectifs et considérant ces différents problèmes, nous proposons de nous appuyer principalement sur la décomposition modale empirique (EMD) ou transformée de Hilbert Huang (THH) pour développer des solutions. L’EMD est une approche non linéaire capable de décomposer le signal étudié en fonctions modales intrinsèques (IMF), oscillations du type FM-AM, donnant ainsi une représentation temps/échelle du signal. Associée à la transformée de Hilbert (TH), la THH permet de déterminer les amplitudes instantanées (AI) et les fréquences instantanées (FI) de chaque mode, menant ainsi à une représentation temps/fréquence des signaux.Sans faire intervenir une fonction externe, on peut ainsi restaurer (réduction de bruit), analyser et reconstruire le signal sans délocalisation de ses singularités. Cette approche permet de localiser les pics R de l'ECG, déterminer le rythme cardiaque et étudier la variabilité fréquentielle cardiaque (VFC), localiser et analyser les composantes des bruits B1 et B2 du PCG. / The heart is a muscle. Its mechanical operation is like a pump charged for distributing and retrieving the blood in the lungs and cardiovascular system. Its electrical operation is regulated by the sinus node, a pacemaker or electric regulator responsible for triggering the natural heart beats that punctuate the functioning of the body.Doctors monitor the electromechanical functioning of the heart by recording an electrical signal called an electrocardiogram (ECG) or an audible signal : the phonocardiogram (PCG). The analysis and processing of these two signals are essential for diagnosis, to help detect anomalies and cardiac pathologies.The objective of this thesis is to develop signal processing tools on ECG and PCG to assist cardiologist in his analysis of these signals. The basic idea is to develop algorithms of low complexity and having inexpensive computing time. The primary interest is to ensure their easy implementation in a mobile heart monitoring system for use by the doctor or the patient. The second advantage lies in the possibility of automatic real-time analysis of signals with the mobile device, allowing control of the transmission of these signals to a removal of doubt.Numerous studies have led to significant advances in the analysis of ECG signals and the automatic recognition of cardiac conditions. Databases of real or synthetic signals annotated also assess the performance of new methods. PCG signals are much less studied, difficult to analyze and to interpret. The main methods (Fourier, wavelet and Wigner Ville) were tested : they do not allow automatic recognition of signatures, and an accurate understanding of their contents.Wavelet Transform (WT) on cardiac signals showed its effectiveness to filter and locate useful information, but it involves an external processing function (mother wavelet) whose the choice depends on the prior knowledge on the signal to be processed. This is not always suitable for cardiac signals. Moreover, the wavelet transform generally induces inaccuracies in the location due to the external function and optionally due to the sub- sampling of the signatures.The non-stationary nature of the ECG and PCG and their sensitivity to noise makes it difficult to separate an informative transition of a transition due to measurement noise. The choice of treatment tool should allow denoising and analysis of these signals without alteration or the processing tool delocalization of the singularities.In response to our objectives and considering these problems, we propose to rely primarily on empirical mode decomposition (EMD) and Hilbert Huang Transform (HHT) to develop solutions. The EMD is a non linear approach decomposing the signal in intrinsic signal (IMF), oscillations of the type FM-AM, giving a time/scale signal representation. Associated with the Hilbert transform (TH), the THH determines the instantaneous amplitude (IA) and instantaneous frequency (IF) of each mode, leading to a time/frequency representation of the ECG and PCG.Without involving an external function, EMD approach can restore (noise reduction), analyze and reconstruct the signal without relocation of its singularities. This approach allows to locate R peaks of the ECG, heart rate and study the cardiac frequency variability (CFV), locate and analyze the sound components B1 and B2 of the PCG.Among the trials and developments that we made, we present in particular a new method (EDA : empirical denoising approach) inspired by the EMD approach for denoising cardiac signals. We also set out the implementation of two approaches for locating ECG signature (QRS complex, T and P waves). The first is based on the detection of local maxima : in using Modulus Maxima and Lipschitz exponent followed by a classifier. The second uses NFLS, wich an nonlinear approach for the detection and location of unique transitions in the discrete domain.

Procedural Content Generation (PCG) has become more common in usage in game development nowadays, with the motivation of finding new ways to make games replayable, new ways for games to be played or for generating content during development. This paper explores the question how often Procedural Generation is used in practice and furthermore how often it is used by different game genres and how they use PCG in their particular games. This paper will try to answer these questions through both an industry review, discovering which games have used Procedural Generation and also through a literature study to find out what kind of research has been done within the area ofPCG and how Game Developers could utilize that in the future. The findings were that even if the usage of PCG differentiated between genres, certain areas like Level Generationand entity instancating were more commonly using Procedural Generation compared with others such as Puzzle generation, Plot generation and Dynamic Systems. The literature study gave a perspective that there are plenty of research done within PCG on how to create new, different and unique ways to generate content, but it is usually in forms of prototypes and not ready to be used in games yet.This gives the conclusion that game genres use Procedural Generation to maximize the user experience with what the game wants out from that genre or use it to make game development more efficient. However, certain genres such as Adventure-games and Role-playing-games could benefit from having PCG for parts of the games where it is not used today which means there is still room for potentially using Procedural Generation. But with that also comes a discussion about what areas of PCG can be improved to meet the needs of the developers and make them more willing to use PCG on areas where it is not currently used.

Procedural Content Generation (PCG) and Dynamic Difficulty Adjustment (DDA) have been used separately in games to improve player experience. We explore using PCG and DDA together in a feedback loop to keep a player in the "flow zone." The central tenet of this work is a conjecture about how the shape of the performance versus difficulty curve changes at the boundaries of the flow zone. Based on this conjecture, we have developed an algorithm that detects when the player has left the flow zone and appropriately adjusts the difficulty to bring the gameplay back into flow, even as the skill of the player is changing. We developed a game-independent algorithm, implemented our algorithm for the open-source Infinite Mario Bros (IMB) game and conducted a user study that supports the hypothesis that players will enjoy the game more with DDA - PCG algorithm.

Although all cells in a multicellular organism contain the same set of genes, the spatiotemporal expression of these genes needs to be dynamically regulated for morphogenesis and life cycle transitions to take place. Polycomb-group (PcG) proteins are evolutionarily-conserved epigenetic regulators that function – via epigenetic marks such as H3K27me3 and modifications to chromatin structure – to maintain the repression of developmentally-important genes so that these genes are only expressed in the appropriate cells at the appropriate times. This repressive activity of the PcG is antagonised by the trithorax-group (trxG) of proteins. Although they maintain specific patterns of gene repression, PcG proteins are ubiquitously expressed. How their activity is regulated is largely unknown. To identify such regulatory pathways, a genetic screen for modifiers of PcG activity in Arabidopsis was carried out previously using the PcG mutant curly leaf (clf), which has moderately-severe developmental defects due to the ectopic or untimely expression of developmental regulators such as floral homeotic genes and the important flowering time regulator FLOWERING LOCUS T (FT). I characterised three novel potential regulators identified in this genetic screen: the chromatin-associated protein AT-HOOK MOTIF NUCLEAR LOCALISED PROTEIN 22 (AHL22), the 26S proteasome and the novel trithorax-group members ANTAGONIST OF LHP1 1 and 2 (ALP1 and ALP2). I found that the dominant sop-11D mutation is caused by over expression of AHL22 which suppresses the phenotype of clf by reducing FT expression. However, genetic analysis suggests that AHL22 may act in a parallel pathway to the PcG. I showed that mutations affecting diverse subunits of the 26S proteasome reduce the mis-expression of CLF targets and suppress the phenotypes of clf although they do not restore H3K27me3 levels at these targets. Pharmacological inhibition of the proteasome also alleviated the mis-expression of target genes found in clf mutants. Analysis of PcG protein levels following proteasome inhibition suggests that the 26S proteasome antagonises the PcG by degrading the key PcG member EMBRYONIC FLOWER 1 (EMF1), which is likely to be important for implementing target gene repression. Surprisingly, my proteomic analysis showed that the novel trxG members ALP1 and ALP2 are accessory components of a core PcG complex – the Polycomb Repressive Complex 2 (PRC2) – in vivo, suggesting that that ALP1 and ALP2 may antagonise PcG repression by preventing the association of core PRC2 components with accessory components EMF1, LIKE HETEROCHROMATIN PROTEIN 1 and the PHD finger proteins VERNALISATION5 and VIN3-LIKE 1. My results reveal a previously unknown role for 26S proteasomal degradation in the regulation of PcG activity during vegetative development and identify novel in vivo associators of the core PRC2 and point to their role in modulating PcG activity. These results thereby increase our understanding of how the PcG is regulated and serve as a starting point to discover how specificity is given to the PcG mediated repression, either by targeted degradation of EMF1 by various E3 ligases or by different combinations of PRC2 associators.

This thesis explores the uses of a multi-agent system(MAS) for procedural content generation(PCG) in the Generative Design in Minecraft (GDMC) competition. The generatorconstructed is capable of surveying the terrain and determining where to start building a roadnetwork. Extendor and connector agents build the road network used for the settlement. Aplotting agent surveys the area around the created roads for plots appropriate for buildinghouses. A house building agent then generates basic buildings on these plots. Finally afurniture agent places furniture in these buildings. The result of the thesis shows that thegenerator is capable of generating an interesting road network that is appropriate to its terrain.The buildings have potential but are lacking in form of adaptability to the current biome andbuildings are overall too similar to be interesting, causing it to get low scores in the userstudy and competition. The generator was entered to the GDMC-competition in 2021 where itplaced 17th of 20th place.

Ända sedan 1960-talet har idén om ett symbiotiskt partnerskap mellan dator och människa presenterats och att detta partnerskap kan ge lösningar bättre än människan ensam kan. Detta symbiotiska partnerskap har spridit sig till processuell generering (PCG) genom angripningssättet “blandade initiativ”, där människa och dator turas om bidra med lösningar. Inom spelutveckling kan viss innehåll skapas bättre av en generator och en annan del av en människa. Denna forskning fokuserar på att tillämpa den “blandade initiativ” metoden för att skapa uppdrag i “dungeon” spel, genom den utvecklade artefakten kan användaren skapa uppdrag i “Evolutionary dungeon designer” (EDD) för att designa nivåer av spelgenren “dungeons”. Artefakten använder en generator för att ge användaren automatisk genererade förslag. Generatorn har utvärderats genom ett “expressive range”-experiment som utvärderade dominansen av de aktioner som fungerar som byggstenar för uppdragen. Utöver experimentet genomfördes en användarstudie för att utvärdera artefaktens användbarhet. Mottagandet av artefakten i användarstudien var positivt. En majoritet av deltagarna upplevde en ökad kreativitet och beskrev artefakten som ett resurseffektivt verktyg för spelutvecklare, som bidrar med snabba lösningar och hjälper till att motverka inspirationsblockeringar. / Ever since the 1960s the idea of a symbiotic partnership between computer and man has been laid out, suggesting a partnership can provide solutions better than man alone can. This symbiotic relationship has been branched out to procedural content generation (PCG), through it’s “mixed initiative” approach, taking turns to provide suggestions. Within game development, some content is better created by a generator, and some by a human. This research focuses on applying the mixed initiative approach in quest creation in dungeon games, through an artefact that lets the user create quests in “Evolutionary dungeon designer” (EDD) to design dungeons in dungeon games. The artefact developed uses a generator to provide the user with automatic generated suggestions. The generator has been evaluated through an expressive range experiment to investigate the dominance of the actions which acts like building blocks for the quests. In addition to the experiment a user study was conducted. The result of the user study was that the experiences relating to the artefact were positive. A majority of the participants experienced increased creativity and described the artefact as a resource efficient tool for game developers, providing fast solutions and helping reduce inspirational blockages.

Abstract - Through our work we validated the symmetry and leniency heuristics used to evaluate content which has been procedurally generated in a mixed-initiative tool called the Evolutionary Dungeon Designer (EDD). This was done by analyzing and comparing how said heuristics differs from what a human player perceives the metrics to be. A user study was performed for which we developed a game for human testers to try and experience different dungeons, in order to collect the data needed for making the necessary comparisons. We propose potential improvements to the metrics that are intended to represent difficulty and aesthetics used in EDD so that they could better match their intended goals. In general, the testers found the maps to be close to the expected difficulty but there was a big discrepancy in the symmetry metric and how aesthetic they found the maps. We further discuss how the research performed by us could be expanded upon for the purpose of making further improvements to automatic evaluation heuristics, by either making similar research on games of different genres or on games with different game mechanics.