This thesis explores the transformative potential of the co-authorship dynamic between game developers and players in The Squared Circle, an abstract video game designed to facilitate personality development. Drawing inspiration from existentialist philosophy, psychotherapy, and game design, the study examines the intricate interplay between gameplay mechanics, narrative depth, and psychological exploration. Employing a research-through-design methodology, the researcher analyzes The Squared Circle’s elements through psychological, philosophical, and ludological literature. The game's initial focus on engaging gameplay mechanics evolved to incorporate textual significance and symbolic play, inspired by Carl Jung's theory of Individuation. Through playtesting, observations, and interviews, the study investigates the psychological and philosophical effects of the game. Players engage in symbolic representation and journaling, delving into their unconscious aspects and exploring personal experiences within the game world. The co-authorship dynamic fosters introspection expands self-understanding, and invites transformative experiences. The findings highlight the significance of journaling and symbolic play as tools for personal growth and self-expression within the game. Players navigate the symbolic landscape, uncover hidden meanings, and co-create their own narrative, leading to increased self-awareness and psychological integration. This research contributes to understanding games as a medium for personal transformation and psychological exploration. The study underscores the importance of co-authorship, journaling, and symbolic representation in designing games that facilitate introspection, meaningful experiences, and the development of the player's personality.

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Métodos de identificação de pessoas sempre foram muito importantes para toda a sociedade. Atualmente, as pesquisas em biometria vêm sendo amplamente incentivadas por diversos setores da indústria mundial com o objetivo de melhorar ou substituir os atuais sistemas de segurança e de identificação de pessoas. O campo da biometria abarca uma grande variedade de tecnologias usadas para identificar e verificar a identidade de uma pessoa por meio da mensuração e análise de diversas características físicas e/ou comportamentais do ser humano. Diversas modalidades biométricas têm sido propostas para reconhecimento de pessoas, como impressão digital, íris, face e fala. Estas modalidades biométricas possuem características distintas em termos de desempenho, mensurabilidade e aceitabilidade. Uma questão a ser considerada com a aplicação biométrica é sua robustez a ataques por circunvenção, repetição e ofuscação. Esses ataques estão se tornando cada vez mais frequentes e questionamentos estão sendo levantados a respeito dos níveis de segurança das formas de reconhecimento. Sinais biomédicos como eletrocardiograma (ECG), eletroencefalograma (EEG) e eletromiograma (EMG) têm sido cada vez mais estudados e aplicados ao reconhecimento biométrico. Em específico, os sinais de ECG têm sido largamente adotados para o reconhecimento biométrico em diversos trabalhos. Por outro lado, análise de séries temporais tem sido usada com sucesso em muitas diferentes aplicações para identificar padrões temporais nos dados. Embora dinâmica simples possa ser observada com ferramentas analíticas tradicionais tais como transformada de fourier, transformada wavelet, a representação simbólica pode melhorar a análise de processos que são complexos e possivelmente caótico. Além disso, representação simbólica pode também reduzir a sensibilidade a ruído e melhorar bastante a eficiência computacional. No entanto, existem aspectos estruturais e paramétricos de projeto que podem conduzir a uma degradação de desempenho. Na ausência de uma metodologia sistemática e de baixo custo para a proposição de técnicas de representação simbólicas otimamente especificadas, os comitês de máquinas, mais especificamente ensemble, se apresentam como alternativas promissoras. Neste estudo, os componentes do ensemble, que correspondem as técnicas de representação simbólicas, e seus respectivos parâmetros foram selecionados via algoritmos evolutivos. O objetivo é explorar conjuntamente potencialidades advindas das técnicas de representação simbólicas e comitê de máquinas para reconhecimento biométrico baseado em sinais de ECG. Resultados experimentais conduzidos sobre dois conjuntos de dados disponíveis publicamente indicam que a abordagem proposta pode melhorar o desempenho do reconhecimento quando comparada com as técnicas tradicionais / Identification people methods have been very important for the whole society. Currently, research on biometrics have been widely encouraged by various sectors of the industry worldwide in order to improve or replace existing security systems and people identification. The field of biometrics includes a variety of technologies used to identify or verify the identity of a person by measuring and analyzing various physical and/or behavioral aspects of the human being. Several biometric methods have been proposed for recognition of people, such as fingerprint, iris, face and speech. These biometric modalities have different characteristics in terms of performance, measurability and acceptability. One issue to be considered with the biometric application in the real world is its robustness to attacks by circumvention, repetition and obfuscation. These attacks are becoming more frequent and more questions are being raised about the levels of security that this technology can offer. Biomedical signals such as electrocardiogram (ECG), electroencephalogram (EEG) and electromyogram (EMG) have been increasingly studied and applied to biometric recognition. Specifically, ECG signals have been widely adopted for biometric recognition in various works. On the other hand, time series analysis has been used successfully in many different applications to identify temporal patterns in the data. Although simple dynamics can be observed with traditional analytical tools such as fourier transform, wavelet transform, the symbolic representation can improve the analysis of processes that are complex and possibly chaotic. In addition, symbolic representation can also reduce noise sensitivity and greatly improve computational efficiency. However, there are structural and parametric design aspects that can lead to performance degradation. In the absence of a systematic and inexpensive methodology for proposing optimally specified symbolic representation techniques, machine committees, more specifically ensemble, present themselves as promising alternatives. In this study, the components of the committee, which correspond to techniques of symbolic representation, and their respective parameters were selected via evolutionary algorithms. The objective is to jointly explore the potentialities of both symbolic representation techniques and machine committee for biometric recognition based on ECG signals. Experimental results conducted on two publicly available datasets indicate that the proposed approach may improve recognition performance when compared to traditional techniques

Métodos de identificação de pessoas sempre foram muito importantes para toda a sociedade. Atualmente, as pesquisas em biometria vêm sendo amplamente incentivadas por diversos setores da indústria mundial com o objetivo de melhorar ou substituir os atuais sistemas de segurança e de identificação de pessoas. O campo da biometria abarca uma grande variedade de tecnologias usadas para identificar e verificar a identidade de uma pessoa por meio da mensuração e análise de diversas características físicas e/ou comportamentais do ser humano. Diversas modalidades biométricas têm sido propostas para reconhecimento de pessoas, como impressão digital, íris, face e fala. Estas modalidades biométricas possuem características distintas em termos de desempenho, mensurabilidade e aceitabilidade. Uma questão a ser considerada com a aplicação biométrica é sua robustez a ataques por circunvenção, repetição e ofuscação. Esses ataques estão se tornando cada vez mais frequentes e questionamentos estão sendo levantados a respeito dos níveis de segurança das formas de reconhecimento. Sinais biomédicos como eletrocardiograma (ECG), eletroencefalograma (EEG) e eletromiograma (EMG) têm sido cada vez mais estudados e aplicados ao reconhecimento biométrico. Em específico, os sinais de ECG têm sido largamente adotados para o reconhecimento biométrico em diversos trabalhos. Por outro lado, análise de séries temporais tem sido usada com sucesso em muitas diferentes aplicações para identificar padrões temporais nos dados. Embora dinâmica simples possa ser observada com ferramentas analíticas tradicionais tais como transformada de fourier, transformada wavelet, a representação simbólica pode melhorar a análise de processos que são complexos e possivelmente caótico. Além disso, representação simbólica pode também reduzir a sensibilidade a ruído e melhorar bastante a eficiência computacional. No entanto, existem aspectos estruturais e paramétricos de projeto que podem conduzir a uma degradação de desempenho. Na ausência de uma metodologia sistemática e de baixo custo para a proposição de técnicas de representação simbólicas otimamente especificadas, os comitês de máquinas, mais especificamente ensemble, se apresentam como alternativas promissoras. Neste estudo, os componentes do ensemble, que correspondem as técnicas de representação simbólicas, e seus respectivos parâmetros foram selecionados via algoritmos evolutivos. O objetivo é explorar conjuntamente potencialidades advindas das técnicas de representação simbólicas e comitê de máquinas para reconhecimento biométrico baseado em sinais de ECG. Resultados experimentais conduzidos sobre dois conjuntos de dados disponíveis publicamente indicam que a abordagem proposta pode melhorar o desempenho do reconhecimento quando comparada com as técnicas tradicionais / Identification people methods have been very important for the whole society. Currently, research on biometrics have been widely encouraged by various sectors of the industry worldwide in order to improve or replace existing security systems and people identification. The field of biometrics includes a variety of technologies used to identify or verify the identity of a person by measuring and analyzing various physical and/or behavioral aspects of the human being. Several biometric methods have been proposed for recognition of people, such as fingerprint, iris, face and speech. These biometric modalities have different characteristics in terms of performance, measurability and acceptability. One issue to be considered with the biometric application in the real world is its robustness to attacks by circumvention, repetition and obfuscation. These attacks are becoming more frequent and more questions are being raised about the levels of security that this technology can offer. Biomedical signals such as electrocardiogram (ECG), electroencephalogram (EEG) and electromyogram (EMG) have been increasingly studied and applied to biometric recognition. Specifically, ECG signals have been widely adopted for biometric recognition in various works. On the other hand, time series analysis has been used successfully in many different applications to identify temporal patterns in the data. Although simple dynamics can be observed with traditional analytical tools such as fourier transform, wavelet transform, the symbolic representation can improve the analysis of processes that are complex and possibly chaotic. In addition, symbolic representation can also reduce noise sensitivity and greatly improve computational efficiency. However, there are structural and parametric design aspects that can lead to performance degradation. In the absence of a systematic and inexpensive methodology for proposing optimally specified symbolic representation techniques, machine committees, more specifically ensemble, present themselves as promising alternatives. In this study, the components of the committee, which correspond to techniques of symbolic representation, and their respective parameters were selected via evolutionary algorithms. The objective is to jointly explore the potentialities of both symbolic representation techniques and machine committee for biometric recognition based on ECG signals. Experimental results conducted on two publicly available datasets indicate that the proposed approach may improve recognition performance when compared to traditional techniques

[pt] O campo joalheiro do Rio de Janeiro vivencia uma realidade impulsionada pela profissionalização de vários setores envolvidos principalmente com as etapas de criação, produção, comercialização e divulgação de novos produtos no mercado. Este cenário vem se configurando desde os anos 1990, quando o design do produto joia passa a ser trabalhado com a intenção de proporcionar novas experiências de consumo, reafirmando sobre seus usuários um encantamento pelo objeto que pode ir além do valor financeiro de sua matéria-prima, tão estimado pelas tradicionais gerações de joalheiros, e que ainda é tida como o argumento número 1 na criação de uma joia. Os cursos superiores, tecnólogos e de aprimoramento no setor, em conjunto com as novas tecnologias fabris, também trouxeram oportunidades para o campo e hoje dividem espaço com as técnicas artesanais de produção de joias. Estas, ainda muito utilizadas, resgatam as origens históricas desse objeto, que é trabalhado pelos designers sob uma nova leitura. Esta pesquisa apresenta uma breve reflexão sobre a importância da prática do design e sua atual contribuição para o campo presente no estado do Rio de Janeiro. / [en] The jewelry field in Rio de Janeiro has showed a reality driven by the professionalization of several sectors, committed mainly with the steps of creation, production, commercialization and marketing of new products. This scenery has been outlined since the 1990 s, when the design of the product jewelry started to be worked out with the intention of offer new consumer experiences, confirming on its wearers an enchantment by the object beyond the financial value of its raw material, so appreciated by the traditional generations of jewelers, and which still is considered the argument number one for the creation of jewelry. Undergraduate courses offered by universities, technical courses and any other formation to improve professionals of this sector, together with new technologies for the textile industry, have also brought opportunities for the field, and today they share this space with the artisanal techniques for the production of jewelry. Still quite used, they bring back the historical origins of this object, which has been revisited by the designers. This research presents a brief reflection about the importance of the design and its current contribution to the field in the Rio de Janeiro state.

Through an exploration of both sculptural and thought processes undertaken in making my Masters exhibition, ‘Hippocampus’, I unpack some possibilities, instabilities, and limitations inherent in representation and visual perception. This thesis explores the Hippocampus as image (seahorse) and concept (brain-structure involved in cognitive mapping of space). Looking at Gilles Deleuze’s writings on representation, I will expand on the notion of the map as being that which does not define and fix a structure or meaning, but rather is open, extendable and experimental. I explore the becoming, rather than the being, of image and concept. The emphasis here is on process, non-representation, and fluidity of meaning. This is supportive of my personal affirmation of the practice and process of art-making as research. I will refer to the graphic prints of Maurits Cornelis Escher as a means to elucidate a visual contextualization of my practical work, particularly with regard to the play with two- and three-dimensional space perception. Through precisely calculated ‘experiments’ that show up the partiality of our visual perception of space, Escher alludes to things that either cannot actually exist as spatial objects or do exist, but resist representation. Similarly I will explore how my own sculptures, although existing in space resist a fixed representation and suggest ideas of other spaces, non-spaces; an in-between space that does not pin itself down and become fixed to any particular image, idea, objector representation.

Distribution grids play an important role in delivering electricityto end users. Electricity customers would like to have a continuouselectricity supply without any disturbance. For customerssuch as airports and hospitals electricity interruption may havedevastating consequences. Therefore, many electricity distributioncompanies are looking for ways to prevent power outages.Sometimes the power outages are caused from the grid sidesuch as failure in transformers or a break down in power cablesbecause of wind. And sometimes the outages are caused bythe customers such as overload. In fact, a very high peak inelectricity consumption and irregular load profile may causethese kinds of failures.In this thesis, we used an approach consisting of two mainsteps for detecting customers with irregular load profile. In thefirst step, we create a dictionary based on all common load profileshapes using daily electricity consumption for one-monthperiod. In the second step, the load profile shapes of customersfor a specific week are compared with the load patterns in thedictionary. If the electricity consumption for any customer duringthat week is not similar to any of the load patterns in thedictionary, it will be grouped as an anomaly. In this case, loadprofile data are transformed to symbols using Symbolic AggregateapproXimation (SAX) and then clustered using hierarchicalclustering.The approach is used to detect anomaly in weekly load profileof a data set provided by HEM Nät, a power distributioncompany located in the south of Sweden.

Cette thèse porte sur la classification audio sous contrainte de faible latence. La classification audio est un sujet qui a beaucoup mobilisé les chercheurs depuis plusieurs années. Cependant, on remarque qu’une grande majorité des systèmes de classification ne font pas état de contraintes temporelles : le signal peut être parcouru librement afin de rassembler les informations nécessaires pour la prise de décision (on parle alors d’une classification hors ligne). Or, on se place ici dans un contexte de classification audio pour des applications liées au domaine des télécommunications. Les conditions d’utilisation sont alors plus sévères : les algorithmes fonctionnent en temps réel et l’analyse du signal et le traitement associé se font à la volée, au fur et à mesure que le signal audio est transmis. De fait, l’étape de classification audio doit également répondre aux contraintes du temps réel, ce qui affecte son fonctionnement de plusieurs manières : l’horizon d’observation du signal se voit nécessairement réduit aux instants présents et à quelques éléments passés, et malgré cela, le système doit être fiable et réactif. Dès lors, la première question qui survient est : quelle stratégie de classification peut-on adopter afin de faire face aux exigences du temps réel ? On retrouve dans littérature deux grandes approches permettant de répondre à des contraintes temporelles plus ou moins fortes : la classification à la trame et la classification sur segment. Dans le cadre d’une classification à la trame, la décision est prise en se basant uniquement sur des informations issues de la trame audio courante. La classification sur segment, elle, exploite une information court-terme en utilisant les informations issues de la trame courante et de quelques trames précédentes. La fusion des données se fait via un processus d’intégration temporelle qui consiste à extraire une information pertinente basée sur l’évolution temporelle des descripteurs audio. À partir de là, on peut s’interroger pour savoir quelles sont les limites de ces stratégies de classification ? Une classification à la trame et une classification sur segment peuvent-elles être utilisées quel que soit le contexte ? Est-il possible d’obtenir des performances convenables avec ces deux approches ? Quelle mode de classification permet de produire le meilleur rapport entre performance de classification et réactivité ? Aussi, pour une classification sur segment, le processus d’intégration temporelle repose principalement sur des modélisation statistiques mais serait-il possible de proposer d’autres approches ? L’exploration de ce sujet se fera à travers plusieurs cas d’étude concrets. Tout d’abord, dans le cadre des projets de recherche à Orange Labs, nous avons pu contribuer au développement d’un nouvel algorithme de protection acoustique, visant à supprimer très rapidement des signaux potentiellement dangereux pour l’auditeur. La méthode mise au point, reposant sur la proposition de trois descripteurs audio, montre un taux de détection élevé tout en conservant un taux de fausse alarme très bas, et ce, quelles que soient les conditions d’utilisation. Par la suite, nous nous sommes intéressés plus en détail à l’utilisation de l’intégration temporelle des descripteurs dans un cadre de classification audio faible latence. Pour cela, nous avons proposé et évalué plusieurs méthodologies d’utilisation de l’intégration temporelle permettant d’obtenir le meilleur compromis entre performance globale et réactivité. Enfin, nous proposons une autre manière d’exploiter l’information temporelle des descripteurs. L’approche proposée s’appuie sur l’utilisation des représentations symboliques permettant de capter la structure temporelle des séries de descripteurs. L’idée étant ensuite de rechercher des motifs temporels caractéristiques des différentes classes audio. Les expériences réalisées montrent le potentiel de cette approche. / This thesis focuses on audio classification under low-latency constraints. Audio classification has been widely studied for the past few years, however, a large majority of the existing work presents classification systems that are not subject to temporal constraints : the audio signal can be scanned freely in order to gather the needed information to perform the decision (in that case, we may refer to an offline classification). Here, we consider audio classification in the telecommunication domain. The working conditions are now more severe : algorithms work in real time and the analysis and processing steps are now operated on the fly, as long as the signal is transmitted. Hence, the audio classification step has to meet the real time constraints, which can modify its behaviour in different ways : only the current and the past observations of the signal are available, and, despite this fact the classification system has to remain reliable and reactive. Thus, the first question that occurs is : what strategy for the classification can we adopt in order to tackle the real time constraints ? In the literature, we can find two main approaches : the frame-level classification and the segment-level classification. In the frame-level classification, the decision is performed using only the information extracted from the current audio frame. In the segment-level classification, we exploit a short-term information using data computed from the current and few past frames. The data fusion here is obtained using the process of temporal feature integration which consists of deriving relevant information based on the temporal evolution of the audio features. Based on that, there are several questions that need to be answered. What are the limits of these two classification framework ? Can an frame-level classification and a segment-level be used efficiently for any classification task ? Is it possible to obtain good performance with these approaches ? Which classification framework may lead to the best trade-off between accuracy and reactivity ? Furthermore, for the segment-level classification framework, the temporal feature integration process is mainly based on statistical models, but would it be possible to propose other methods ? Throughout this thesis, we investigate this subject by working on several concrete case studies. First, we contribute to the development of a novel audio algorithm dedicated to audio protection. The purpose of this algorithm is to detect and suppress very quickly potentially dangerous sounds for the listener. Our method, which relies on the proposition of three features, shows high detection rate and low false alarm rate in many use cases. Then, we focus on the temporal feature integration in a low-latency framework. To that end, we propose and evaluate several methodologies for the use temporal integration that lead to a good compromise between performance and reactivity. Finally, we propose a novel approach that exploits the temporal evolution of the features. This approach is based on the use of symbolic representation that can capture the temporal structure of the features. The idea is thus to find temporal patterns that are specific to each audio classes. The experiments performed with this approach show promising results.

No description available.

Thesis (MA(VA))--Stellenbosch University, 2014. / ENGLISH ABSTRACT: This thesis examines the extent to which the cuff and the collar as semiotic entities played a significant role in the symbolic expression of power and oppression in the seventeenth century Cape of Good Hope. These entities were visually naturalised by the Eurocentric imperialist hegemony at the Cape and offered as undisputed ‘truth’. These symbols permeated the collective consciousness of the society at the Cape on both a physical and cognitive level. The white ruff and cuffs, and the shackles of the slaves represented physical restraints, whilst mentally the slaves were confronted with identity construction and deconstruction. ‘The self’ was pitted against ‘the Other’, and these European values and hierarchies were enforced on the society at the Cape by creating dualistic relationships. An identity implies a certain amount of power. For this reason, the Europeans stripped the slaves of their identities in order to gain control over them. This theory, together with the investigation into the hybrid characteristic of culture as a product of colonialism and slavery at the Cape, will be established concurrently with the aim of my practical work — The Ruff/Rough Collection, The Shackle Collection, and The Soft Steel Collection. This body of work aims to deconstruct the boundaries and hierarchies established by the cuff and the collar (as symbols of the power and oppression paradigm) at the Cape. / AFRIKAANSE OPSOMMING: Hierdie tesis ondersoek die mate waarin die mouboordjie (‘cuff’) en die kraag (‘collar’) as semiotiese entiteite ’n beduidende rol gespeel het in die simboliese uitdrukking van mag en onderdrukking aan die Kaap de Goede Hoop in die sewentiende eeu. Hierdie simbole is visueel deur die Eurosentriese imperialistiese leierskap ingevoer en as onbetwisbare waarheid van hul mag en heerskappy voorgehou. Dié simbole het die kollektiewe bewussyn van die samelewing aan die Kaap op ’n fisieke en geestelike vlak geïnfiltreer. Die wit plooikraag (‘ruff’) wat die Europeërs gedra het om hulself as ‘meesters’ te vestig, en die boeie van die slawe het fisieke beperkings verteenwoordig, terwyl die slawe geestelik gekonfronteer is met die opbou en afbreek van hulle identiteit. ‘Die ek’ is teen ‘die Ander’gestel en Europese waardes is op grond van die Eurosentriese ingesteldheid van die ‘meesters’ op die samelewing afgedwing as ‘n dualistiese verhouding. ’n Identiteit impliseer ’n sekere graad van mag. Daarom het die Europeërs die slawe van hulle identiteit gestroop om sodoende mag oor hulle te verkry. Hierdie teorie, asook die ondersoek na die hibridiese eienskap van kultuur as ’n produk van kolonialisme en slawerny aan die Kaap, sal konkurrent met die doel van my praktiese werk — The Ruff/Rough Collection, The Shackle Collection en The Soft Steel Collection — gevestig word. Die doel van hierdie versameling kontemporêre juweliersware is om die grense en hiërargieë te dekonstrueer, wat deur die mouboordjie (‘cuff’) en die kraag (‘collar’) (as simbole van die mag- en onderdrukkingsparadigma) tot stand gebring is aan die Kaap de Goede Hoop.