Em nosso trabalho analisamos os dados provenientes da BM&F Bovespa, a bolsa de valores de São Paulo, no período de janeiro de 2011, referentes aos índices: BOVESPA (IND), o mini índice BOVESPA (WIN) e a taxa de câmbio (DOL). Estes dados são de alta frequência e representam vários aspectos da dinâmica das negociações. No conjunto de valores encontram-se horários e datas dos negócios, preços, volumes oferecidos e outras características da negociação. A primeira etapa da tese foi extrair as informações necessárias para análises a partir de um arquivo em protocolo FIX, foi desenvolvido um programa em R com essa finalidade. Em seguida, estudamos o carácter da dependência temporal nos dados, testando as propriedades de Markov de um comprimento de memória fixa e variável. Os resultados da aplicação mostram uma grande variabilidade no caráter de dependência, o que requer uma análise mais aprofundada. Acreditamos que esse trabalho seja de muita importância em futuros estudos acadêmicos. Em particular, a parte do carácter específico do protocolo FIX utilizado pela Bovespa. Este era um obstáculo em uma série de estudos acadêmicos, o que era, obviamente, indesejável, pois a Bovespa é um dos maiores mercados comerciais do mundo financeiro moderno. / In our work we analyzed data from BM&F Bovespa, the stock exchange in São Paulo. The dataset refers to the month January 2011 and is related to BOVESPA index (IND), mini BOVESPA index (WIN) and the exchange tax (DOL). These, are high frequency data representing various aspects of the dynamic of negotiations. The array of values includes the dates/times of trades, prices, volumes offered for trade and others trades characteristics. The first stage of the thesis was to extract information to the analysis from an archive in FIX protocol, it was developed a program in R with this aim. Afterwards, we studied the character of temporal dependence in the data, testing Markov properties of a fixed and variable memory length. The results of this application show a great variability in the character of dependence, which requires further analysis. We believe that our work is of great importance in future academic studies. In particular, the specific character of the FIX protocol used by Bovespa. This was an obstacle in a number of academic studies, which was, obviously, undesirable since Bovespa is one of the largest trading markets in the modern financial world.

Audiobook reading has traditionally been used for educational purposes but has in recent times grown into a popular alternative to the more traditional means of consuming literature. In order to differentiate themselves from other players in the market, but also provide their users enjoyable literature, several audiobook companies have lately directed their efforts on producing own content. Creating highly rated content is, however, no easy task and one reoccurring challenge is how to make a bestselling story. In an attempt to identify latent features shared by successful audiobooks and evaluate proposed methods for literary quantification, this thesis employs an array of frameworks from the field of Statistics, Machine Learning and Natural Language Processing on data and literature provided by Storytel - Sweden’s largest audiobook company. We analyze and identify important features from a collection of 3077 Swedish books concerning their promotional and literary success. By considering features from the aspects Metadata, Theme, Plot, Style and Readability, we found that popular books are typically published as a book series, cover 1-3 central topics, write about, e.g., daughter-mother relationships and human closeness but that they also hold, on average, a higher proportion of verbs and a lower degree of short words. Despite successfully identifying these, but also other factors, we recognized that none of our models predicted “bestseller” adequately and that future work may desire to study additional factors, employ other models or even use different metrics to define and measure popularity. From our evaluation of the literary quantification methods, namely topic modeling and narrative approximation, we found that these methods are, in general, suitable for Swedish texts but that they require further improvement and experimentation to be successfully deployed for Swedish literature. For topic modeling, we recognized that the sole use of nouns provided more interpretable topics and that the inclusion of character names tended to pollute the topics. We also identified and discussed the possible problem of word inflections when modeling topics for more morphologically complex languages, and that additional preprocessing treatments such as word lemmatization or post-training text normalization may improve the quality and interpretability of topics. For the narrative approximation, we discovered that the method currently suffers from three shortcomings: (1) unreliable sentence segmentation, (2) unsatisfactory dictionary-based sentiment analysis and (3) the possible loss of sentiment information induced by translations. Despite only examining a handful of literary work, we further found that books written initially in Swedish had narratives that were more cross-language consistent compared to books written in English and then translated to Swedish.

A pesquisa está inserida no contexto do Design Computacional, área que explora a computação como uma ferramenta de projeto de arquitetura. Para declarar e desenvolver projetos, é comum a utilização de linguagens de programação visual. No entanto, limitações no uso de linguagens visuais são reconhecidas, como as restrições encontradas na flexibilidade e escalabilidade dos códigos. Para estender o acesso à métodos de resolução de problemas nesses sistemas, usuários frequentemente recorrem ao uso de linguagens de programação textual, que permitem a utilização de mais estruturas de controle. Ainda assim, é comum que arquitetos sejam induzidos a realizar mudanças nos processos para acomodar a falta de controle e resultados inesperados de projeto. Isso acontece em parte pela falta de clareza em como utilizar a programação e todo o potencial dos métodos computacionais. Além disso, há uma falta de evidências empíricas usando projetos reais de arquitetura que apoiem discussões sobre o futuro das ferramentas de programação para arquitetos. Esta pesquisa investiga a comparação entre o uso de linguagens de programação visual e textual e visa sugerir diretrizes para melhorar as interfaces de programação utilizadas atualmente na área. Para isso, realizamos análises baseadas em métricas de avaliação de linguagens de programação e nas Dimensões Cognitivas (GREEN; PETRE, 1996). Adicionalmente, exploramos como estudo de aplicação um Projeto Orientado ao Desempenho, o Vancouver Academic Building do escritório americano Perkins+Will. O escritório implementou inicialmente o projeto usando a linguagem visual Grasshopper, com o objetivo de otimizar o design de uma fachada explorando o equilíbrio entre aspectos de iluminância e eficiência energética. Reimplementamos o estudo de aplicação utilizando uma linguagem textual e o ambiente de programação Rosetta (LOPES; LEITÃO, 2011). À medida que procuramos solucionar a lacuna existente na comparação dos fluxos de trabalho entre linguagens visuais e textuais recorrendo a um projeto real, selecionamos este estudo de aplicação porque ele abrange um processo orientado ao desempenho em vez de um projeto apenas paramétrico. Existem diferenças fundamentais encontradas entre estes dois fluxos de trabalho em relação a estratégias de escalabilidade e fluxo de dados, pois o orientado ao desempenho requer mais estruturas de controle como iteração e recursão. Identificamos diferenças relevantes entre ambas as linguagens e o potencial no uso das textuais no aumento significativo da escalabilidade do código e do modelo; aumento da confiabilidade dos resultados de desempenho do projeto e maior controle e clareza do processo utilizado. Apontamos também para as qualidades de interação e expressividade inerente das linguagens visuais. A partir do cruzamento teórico-prático, indicamos diretrizes que compõem em que medida o uso preferencial de linguagens textuais e linguagens híbridas (que integram ambas) podem melhorar a confiabilidade do Projeto Orientado ao Desempenho, assim como a possibilidade de aplicar métodos mais claros e eficazes no desenvolvimento do Projeto Algorítmico. / This research is contextualized in the Computational Design field, an area that explores computation as an architectural design tool. To declare and develop projects, it is common to use visual programming languages. However, limitations in the use of visual languages are well known, such as the constraints found in the flexibility and scalability of codes. To extend access to problem-solving methods in these systems, users often resort to the use of textual programming languages, which allow the use of more control structures. However, it is common for architects to be induced to make changes to processes to accommodate the lack of control and unexpected design results. This happens partly due to the lack of clarity in how to use programming and the full potential of computational methods. In addition, there is a lack of empirical evidence using real architectural designs that support discussions about the future of programming tools for architects. This research investigates the comparison between the use of visual and textual programming languages and aims to suggest guidelines to improve the programming interfaces currently used in the area. To achieve this, we perform analyzes based on evaluation metrics of programming languages and Cognitive Dimensions (GREEN; PETRE, 1996). In addition, we explored a Performance-driven Architectural Design as a study case, the Vancouver Academic Building, from Perkins+Will. The office initially implemented the design using Grasshopper visual language to optimize the design of a façade by exploring the balance between aspects of illuminance and energy efficiency. We reimplement the case study using a textual language and the Rosetta programming environment (LOPES; LEITÃO, 2011). As we attempt to solve the existing gap in the comparison of workflows between visual and textual languages using a real project, we select this case study because it covers a performance-oriented process rather than a parametric design only. There are fundamental differences found between these two workflows in relation to scalability and data flow strategies since the performance-driven one requires more control structures such as iteration and recursion. We identified relevant differences between both languages and the potential in the use of textual ones in the significant increase of code and model scalability; increased reliability of project performance results and better control and clarity of the process. We also point to the inherent qualities of interaction and expressiveness of visual languages. From the theoretical-practical cross, we indicate the guidelines that make up the extent to which the preferential use of textual languages and hybrid languages (which integrate both) can improve the reliability of the Performance-driven Design, as well as the possibility of applying clearer and more effective methods in the development of the Algorithmic Design.

Analog-to-digital converters (ADCs) are key design blocks in state-of-art image, capacitive, and biomedical sensing applications. In these sensing applications, algorithmic ADCs are the preferred choice due to their high resolution and low area advantages. Algorithmic ADCs are based on the same operating principle as that of pipelined ADCs. Unlike pipelined ADCs where the residue is transferred to the next stage, an N-bit algorithmic ADC utilizes the same hardware N-times for each bit of resolution. Due to the cyclic nature of algorithmic ADCs, many of the low power techniques applicable to pipelined ADCs cannot be directly applied to algorithmic ADCs. Consequently, compared to those of pipelined ADCs, the traditional implementations of algorithmic ADCs are power inefficient. This thesis presents two novel energy efficient techniques for algorithmic ADCs. The first technique modifies the capacitors' arrangement of a conventional flip-around configuration and amplifier sharing technique, resulting in a low power and low area design solution. The other technique is based on the unit multiplying-digital-to-analog-converter approach. The proposed approach exploits the power saving advantages of capacitor-shared technique and capacitor-scaled technique. It is shown that, compared to conventional techniques, the proposed techniques reduce the power consumption of algorithmic ADCs by more than 85\%. To verify the effectiveness of such approaches, two prototype chips, a 10-bit 5 MS/s and a 12-bit 10 MS/s ADCs, are implemented in a 130-nm CMOS process. Detailed design considerations are discussed as well as the simulation and measurement results. According to the simulation results, both designs achieve figures-of-merit of approximately 60 fJ/step, making them some of the most power efficient ADCs to date.

Swarm robotics for music is a relatively new way to explore algorithmic composition as well as new modes of human robot interaction. This work outlines a strategy for making music with a robotic swarm constrained by acoustic sound, rhythmic music using sequencers, motion causing changes in the music, and finally human and swarm interaction. Two novel simulation programs are created in this thesis: the first is a multi-agent simulation designed to explore suitable parameters for motion to music mappings as well as parameters for real time interaction. The second is a boid-based robotic swarm simulation that adheres to the constraints established, using derived parameters from the multi-agent simulation: orientation, number of neighbors, and speed. In addition, five interaction modes are created that vary along an axis of direct and indirect forms of human control over the swarm motion. The mappings and interaction modes of the swarm robot simulation are evaluated in a user study involving music technology students. The purpose of the study is to determine the legibility of the motion to musical mappings and evaluate user preferences for the mappings and modes of interaction in problem solving and in open-ended contexts. The findings suggest that typical users of a swarm robot system do not necessarily prefer more inherently legible mappings in open-ended contexts. Users prefer direct and intermediate modes of interaction in problem solving scenarios, but favor intermediate modes of interaction in open-ended ones. The results from this study will be used in the design and development of a new swarm robotic system for music that can be used in both contexts.

Verschiedene simultan wirkende Signale beeinflussen die Signalverarbeitung und die Genregulation von Säugetieren auf der systemischen Ebene. Die Signale müssen integriert und in ihrem jeweiligen Zusammenhang bewertet werden. Dabei können die Signale auch synergistisch miteinander interagieren, wobei dann einzig durch dieses Zusammenspiel auf genregulatorischer Ebene neue Funktionen induziert werden. Gängige experimentelle Ansätze zur Detektion von synergistischen Interaktionen erkennen zwar die beeinflussten Gene, aber die zugrunde liegenden Mechanismen bleiben unklar. In dieser Arbeit wurde deshalb ein globales systembiologisches Verfahren entwickelt, welches Synergien anhand ihrer generellen topologischen Eigenschaften in einem bipartiten Graphen detektiert. Das für die Analyse notwendige globale bipartite und mechanistische Signaltransduktionsreferenznetzwerk wurde auf der Basis experimentell verifizierter Daten aus verschiedenen Datenbanken sowie aktueller Literatur in dieser Arbeit rekonstruiert. Synergien sind besonders im Immunsystem relevant, wo verschiedene Signale parallel eine Immunreaktion auslösen. Eine adäquate Antwort kann dabei nur durch eine gleichzeitige und präzise regulierte Bewertung der wirkenden Signale ermöglicht werden. Das entwickelte Verfahren wurde auf die, für die Immunantwort essentiellen, Immunsignale Interleukin-3 (IL-3) und humanes Influenza Virus (Flu) in menschlichen plasmacytoiden dendritischen Zellen, einem Immunzelltyp, angewandt. Um synergistische Effekte während der Signalintegration zu untersuchen wurde das Referenznetzwerk auf die säugerspezifischen, in pDC präsenten und durch IL-3 und Flu aktivierten Signalpfade eingeschränkt. Es wurden unter anderem die synergistischen Interaktionspunkte detektiert, ihre regulierten Transkriptionsfaktoren sowie die durch sie regulierten Zielgene. Durch den Vergleich der ausgelösten Funktionen und der jeweils induzierten Signalwege konnte gezeigt werden, dass das entwickelte Verfahren die immunrelevanten synergistisch regulierten Gene besser detektiert als ein vergleichbares experimentelles Verfahren.

Disertacijoje nagrinėjamos taikomųjų uždavinių, kurių duomenys išreikšti reliacinėmis aibėmis, sprendimus realizuojančių priemonių adaptyvumo problemos. Pagrindiniai tyrimo objektai yra adaptyvieji duomenų modeliai: duomenų išrinkimo modelis, duomenų agregavimo modelis ir duomenų apdorojimo projektavimo modelis. Darbo tikslas – sukurti adaptyviąją duomenų apdorojimo projektavimo technologiją, kuri leistų išrinkti, agreguoti ir apdoroti duomenis keičiant tik šią technologiją sudarančių adaptyviųjų duomenų modelių formalių išraiškų parametrus. Naudojant sukurtą technologiją skirtingiems uždaviniams spęsti taikomas vienas ir tas pats duomenų apdorojimo principas. Kitaip tariant, visą algoritmų ir juos realizuojančių programini�� modulių sistemą galime pritaikyti skirtingiems taikomojo pobūdžio uždaviniams spręsti. Tai leidžia sumažinti naujų programinių priemonių kūrimo apimtis ir sąnaudas. / The dissertation deals with the adaptivity difficulties of the solutions implemented to solve applied problems whose data is expressed as relational sets. The main objects of research are adaptive data models: a data selection model, a data aggregation model and a model for designing data processing. The aim of the work is to create an adaptive technology for designing data processing that would enable to perform data selection, aggregation and processing by changing only the parameters of formal expressions for the adaptive data models forming the technology. While using the technology created for solving different problems the same data processing principle is used. In other words, the whole system of algorithms and program modules implementing them can be adjusted for solving different problems of applied nature. This allows to decrease the volume and expenses of creating new software.

In the dissertation the adaptation problem of the software whose instability is caused by the changes in primary data contents and structure as well as the algorithms for applied problems implementing solutions to problems of applied nature is examined. The solution to the problem is based on the methodology of adapting models for the data expressed as relational sets. / Disertacijoje nagrinėjama taikomųjų uždavinių sprendimus realizuojančių programinių priemonių, kurių nepastovumą lemia pirminių duomenų turinio, jų struktūrų ir sprendžiamų taikomojo pobūdžio uždavinių algoritmų pokyčiai, adaptavimo problema.

Analog-to-digital converters (ADCs) are key design blocks in state-of-art image, capacitive, and biomedical sensing applications. In these sensing applications, algorithmic ADCs are the preferred choice due to their high resolution and low area advantages. Algorithmic ADCs are based on the same operating principle as that of pipelined ADCs. Unlike pipelined ADCs where the residue is transferred to the next stage, an N-bit algorithmic ADC utilizes the same hardware N-times for each bit of resolution. Due to the cyclic nature of algorithmic ADCs, many of the low power techniques applicable to pipelined ADCs cannot be directly applied to algorithmic ADCs. Consequently, compared to those of pipelined ADCs, the traditional implementations of algorithmic ADCs are power inefficient. This thesis presents two novel energy efficient techniques for algorithmic ADCs. The first technique modifies the capacitors' arrangement of a conventional flip-around configuration and amplifier sharing technique, resulting in a low power and low area design solution. The other technique is based on the unit multiplying-digital-to-analog-converter approach. The proposed approach exploits the power saving advantages of capacitor-shared technique and capacitor-scaled technique. It is shown that, compared to conventional techniques, the proposed techniques reduce the power consumption of algorithmic ADCs by more than 85\%. To verify the effectiveness of such approaches, two prototype chips, a 10-bit 5 MS/s and a 12-bit 10 MS/s ADCs, are implemented in a 130-nm CMOS process. Detailed design considerations are discussed as well as the simulation and measurement results. According to the simulation results, both designs achieve figures-of-merit of approximately 60 fJ/step, making them some of the most power efficient ADCs to date.

This thesis covers three topics in Market Microstructure. Chapter 1 demonstrates that market access frictions may play a significant role in the competition between trading platforms. Analyzing a recent dataset of the trading activity in French and German stocks, we provide evidence that the incumbent markets dominate because the sole market entrant exposes liquidity providers to an excessive adverse selection risk due to a lack of noise traders. Chapter 2 presents a theoretical model of price formation in a dynamic limit order market with slow human traders and fast algorithmic traders. We show that in most cases, algorithmic trading has a detrimental effect on human traders’ welfare. Finally, Chapter 3 empirically analyzes the role of pre-trade transparency in call auctions. Comparing the trading mechanisms in place on the French and German stock exchanges, we find that transparency is associated with higher trading volume, greater liquidity, and better price discovery. / Esta tesis estudia tres temas diferentes de la microestructura de los mercados financieros. El capítulo 1 demuestra que fricciones en el acceso al mercado pueden desempeñar un papel significativo en la competencia entre plataformas de negociación de activos. El análisis de un conjunto de datos recientes de la actividad en acciones francesas y alemanas demuestra que los mercados primarios dominan debido a que el único mercado satélite expone los proveedores de liquidez a un riesgo excesivo de selección adversa, causado por una falta de noise traders. El capítulo 2 presenta un modelo teórico de formación de precios en un mercado dinámico con limit order book poblado por agentes humanos lentos y agentes algorítmicos rápidos. Se demuestra que, en la mayoría de los casos, la negociación algorítmica tiene un efecto negativo sobre el bienestar de agentes humanos. Por último, el capítulo 3 analiza empíricamente el papel de la transparencia pre-negociación en las subastas de apertura y de cierre. Comparando los mecanismos en las bolsas francesas y alemanas, encontramos que la transparencia está asociada con un volumen mayor, una liquidez mayor y un mejor price discovery.