Dissertations / Theses on the topic 'Structured World Model'

Diese Dissertation besteht aus drei Aufsätzen, in denen verschiedene Aspekte von zweiseitigen Märkten untersucht werden. Dabei handelt es sich um Märkte mit zwei verschiedenen Nutzergruppen, von denen jede Netzwerkeffekte auf die jeweils andere Seite ausübt. Im ersten Aufsatz werden die Wechselwirkungen zwischen den traditionellen (offline) Nachfragekanälen und den neuen (online) Nachfragekanälen in der deutschen Zeitschriftenindustrie analysiert. Dabei liegt der Fokus insbesondere auf den Effekten zwischen Offlinewerbung und Onlinewerbung. Das Ergebnis der Schätzung eines dafür entwickelten ökonomischen Modells ist, dass Offline- und Onlinewerbung moderate Substitute füreinander sind. Dies erklärt die Verlagerung von Offline- zu Onlinewerbung, die man in den vergangen Jahren beobachten konnte. Im zweiten Aufsatz wird ein semistruktureller Ansatz zur Messung von Netzwerk-Effekten auf potentiell zweiseitigen Monopol-Plattformen entwickelt. Der Test ist hinreichend, wenn lediglich Daten zum Gesamtumsatz der Plattform zur Verfügung stehen. Sind getrennte Umsatzdaten für die beiden Seiten verfügbar, dann ist der Test sowohl notwendig als auch hinreichend. Der dritte Aufsatz untersucht Mechanismen und Anreize, die die Koordination von Angebot und Nachfrage auf Kreditmärkten ermöglichen, in denen es keine Finanzintermediäre mit eigener finanzieller Beteiligung an den vergebenen Darlehen gibt. Dazu wird der Online-Direktkreditmarkt analysiert, in welchem an die Stelle von klassischen Finanzintermediären ein System von Gruppen tritt. Anhand eines Differenz-in-Differenzen-Ansatzes wird gezeigt, dass Entgelte für die Leiter dieser Gruppen zu adversen Anreizen führen können. Nach Abschaffung der Entgelte differenzieren die Leiter der Gruppen deutlich stärker bei der Auswahl derjenigen Kreditgesuche, die sie als investitionswürdig empfehlen. Gleiches ist zu beobachten, wenn die Leiter der Gruppen selbst zu einem großen Teil an den entsprechenden Darlehen beteiligt sind.
This dissertation investigates various aspects of two-sided markets - markets with at least two distinct user groups each of which exerts inter-group network effects on the other side - in the online world. In the first paper, I examine the interactions between the traditional (offline) demand channels and the new (online) demand channels in the German magazines industry, focusing in particular on the link between offline and online advertising. I find that offline and online advertising are substitutes although not perfect ones. This explains the shift from offline to online advertising observed in recent years. In the second paper, I develop a semi-structural approach to identify network effects on two-sided monopoly platforms without data on prices and quantities. A sufficient test for the existence of network effects is derived when only data on total revenue is available. If separate revenue data is available on the two sides, then the test is both necessary and sufficient. The third paper investigates the certification mechanisms and incentives that enable lending markets to match demand and supply despite the absence of financial intermediaries with skin in the game. The institutional setting for this analysis is the online social lending market, in which potential lenders and borrowers interact directly without a financial intermediary but can create self-organized groups instead. A difference-in-difference approach is used to examine how the same groups behave before and after the exogenously imposed elimination of rewards for the leaders of these groups. Allowing group leader rewards is found to be detrimental for the market outcome. Group leaders become more careful in screening after the elimination of these rewards, and if their loan participation is high, i.e. when they have skin in the game and are thus severely hurt by a borrower default.

This thesis presents several novel methods to address some of the real world data modelling issues through the use of local and individualised modelling approaches. A set of real world data modelling issues such as modelling evolving processes, defining unique problem subspaces, identifying and dealing with noise, outliers, missing values, imbalanced data and irrelevant features, are reviewed and their impact on the models are analysed. The thesis has made nine major contributions to information science, includes four generic modelling methods, three real world application systems that apply these methods, a comprehensive review of the real world data modelling problems and a data analysis and modelling software. Four novel methods have been developed and published in the course of this study. They are: (1) DyNFIS – Dynamic Neuro-Fuzzy Inference System, (2) MUFIS – A Fuzzy Inference System That Uses Multiple Types of Fuzzy Rules, (3) Integrated Temporal and Spatial Multi-Model System, (4) Personalised Regression Model. DyNFIS addresses the issue of unique problem subspaces by identifying them through a clustering process, creating a fuzzy inference system based on the clusters and applies supervised learning to update the fuzzy rules, both antecedent and consequent part. This puts strong emphasis on the unique problem subspaces and allows easy to understand rules to be extracted from the model, which adds knowledge to the problem. MUFIS takes DyNFIS a step further by integrating a mixture of different types of fuzzy rules together in a single fuzzy inference system. In many real world problems, some problem subspaces were found to be more suitable for one type of fuzzy rule than others and, therefore, by integrating multiple types of fuzzy rules together, a better prediction can be made. The type of fuzzy rule assigned to each unique problem subspace also provides additional understanding of its characteristics. The Integrated Temporal and Spatial Multi-Model System is a different approach to integrating two contrasting views of the problem for better results. The temporal model uses recent data and the spatial model uses historical data to make the prediction. By combining the two through a dynamic contribution adjustment function, the system is able to provide stable yet accurate prediction on real world data modelling problems that have intermittently changing patterns. The personalised regression model is designed for classification problems. With the understanding that real world data modelling problems often involve noisy or irrelevant variables and the number of input vectors in each class may be highly imbalanced, these issues make the definition of unique problem subspaces less accurate. The proposed method uses a model selection system based on an incremental feature selection method to select the best set of features. A global model is then created based on this set of features and then optimised using training input vectors in the test input vector’s vicinity. This approach focus on the definition of the problem space and put emphasis the test input vector’s residing problem subspace. The novel generic prediction methods listed above have been applied to the following three real world data modelling problems: 1. Renal function evaluation which achieved higher accuracy than all other existing methods while allowing easy to understand rules to be extracted from the model for future studies. 2. Milk volume prediction system for Fonterra achieved a 20% improvement over the method currently used by Fonterra. 3. Prognoses system for pregnancy outcome prediction (SCOPE), achieved a more stable and slightly better accuracy than traditional statistical methods. These solutions constitute a contribution to the area of applied information science. In addition to the above contributions, a data analysis software package, NeuCom, was primarily developed by the author prior and during the PhD study to facilitate some of the standard experiments and analysis on various case studies. This is a full featured data analysis and modelling software that is freely available for non-commercial purposes (see Appendix A for more details). In summary, many real world problems consist of many smaller problems. It was found beneficial to acknowledge the existence of these sub-problems and address them through the use of local or personalised models. The rules extracted from the local models also brought about the availability of new knowledge for the researchers and allowed more in-depth study of the sub-problems to be carried out in future research.

The landscape of world migration involves multiple interacting movements of people at various geographic scales, posing significant challenges to the dyadic-independence assumption underlying standard migration models. To account for emerging patterns of multilateral migration relationships, we represent world migration as a time-evolving, spatial network. The nodes in the World Migration Network (WMN) are countries located in geographic space, and the edges represent migratory movements for each decade from 1960-2000. In the first part of the thesis, we characterise the spatial network structure of the WMN, with a particular focus on detecting and mapping mesoscopic structures called 'communities' (i.e., sets of countries with denser migration connections internally than to the rest of the WMN). We employ a method for community detection that simultaneously accounts for multilateral migration, spatial constraints, time-dependence, and directionality in the WMN. We then introduce an approach for characterising local (intracommunity) and global (intercommunity) connectivity in the WMN. On this basis, we define a threefold typology that distinguishes 'cave', 'bi-regional', and 'bridging' communities. These are characterised with distinct migration patterns, spatial network structures, and temporal dynamics: cave communities are tightly-knit enduring structures that channel local migration between contiguous countries; bi-regional communities merge migration between two distinct geographic regions; bridging communities have hub-and-spoke dynamic structures that emerge from globe-spanning movements. Our results suggest that the WMN is neither a globally interconnected network nor reproducing geographic boundaries but involves heterogeneous patterns of global and local ('glocal') migration connectivity. We examine a set of relational, homophily, and spatial mechanisms that could have possibly generated the 'glocal' structure we observe. We found that communities of different types arise from significantly different mechanisms. Our results suggest that migration communities can have important implications for world migration, as different types of community structure provide distinct opportunities and constraints, thereby distinctively shaping future migration patterns.

The objective of this study is to evaluate the changes in import and export demand in China and India on the United States and global agriculture in 2018. A spatial equilibrium model is developed to optimize production and trade in China, India, and other major importing and exporting regions in the world. This research focuses on four primary crops: wheat, com, rice and soybeans. In the model China and India are divided into 31 and 14 producing and consuming regions, respectively. The model also includes five exporting countries and ten importing countries/regions. The results indicate that India will be able to stay largely self-sufficient in 2018 and China will increase its soybean and com imports to meet rising domestic demand. The research also gives perspectives on production and trade in the United States and other major exporting and importing countries.

2015-05-27に本文を差替
Kyoto University (京都大学)
0048
新制・課程博士
博士(情報学)
甲第18481号
情博第532号
新制||情||94(附属図書館)
31359
京都大学大学院情報学研究科知能情報学専攻
(主査)教授 黒橋 禎夫, 教授 田中 克己, 教授 河原 達也
学位規則第4条第1項該当

The last two decades have seen new insights, data and analytical methods to establish the behaviour of structures in fire. These methods have slowly migrated into practice and now form the basis for modern quantitative structural fire engineering. This study presents a novel methodology for determining the imposed heat fluxes on structural members. To properly characterise the temperature rise of the structural elements, a post-processing model for computational fluid dynamics tools was developed to establish the heat fluxes imposed on all surfaces by a fire. This model acts as a tool for any computational fluid dynamics model and works on the basis of well resolved local gas conditions. Analysis of the smoke layer and products of combustion allow for heat fluxes to be defined based on smoke absorption coefficients and temperatures. These heat fluxes are defined at all points on the structure by considering full spatial and temporal distributions. Furthermore, heat fluxes are defined by considering directionality and both characteristic length and time scales in fires. Length scales are evaluated for different structural member geometries, while time scales are evaluated for different structural materials including applied fire protection. It is the output given by this model that provides the input for the thermal analysis of the structural members that is a necessary step prior to the structural analysis to be undertaken. The model is validated against the experimental results of the previously mentioned large scale fire tests, showing good agreement. In addition, comparisons are made to current methods to highlight their potential inadequacies.

Includes bibliographical references. Addresses the question of what an economic model of the world wine market suggests will happen to wine production, consumption, trade and prices in various regions in the early 21st century. A subsidiary issue is what difference would global or European regional wine liberalisation make to that outlook, according to such a model. Accompanying CD-ROM comprises spreadsheet written by Nick Berger, November 2000, for the Windows and Office97 versions of Excel; a seven region world wine model (WWM7) - base version projecting the world wine market 1996-2005 as a non-linear Armington model. System requirements for accompanying CD-ROM: IBM compatible computer ; Microsoft Excel 97 or later.

Thesis (M.S.)--School of Electrical and Computer Engineering, Georgia Institute of Technology, 2005. Directed by Jain Ramesh.
Ramesh Jain, Committee Chair ; Linda Wills, Committee Member ; Jim McClellan@ece.gatech.edu, Committee Member. Vita. Includes bibliographical references.

The influence of electronic word of mouth (eWOM) on consumers’ purchase intentions has long been known. However, the emergence of social media has brought a new perspective to eWOM through enabling users to communicate with their existing networks on the Internet. On social media, conversely to the other online platforms, users are able to exchange their opinions and experiences about products or services with familiar people, which refers to people who they already know such as friends and acquaintances. This new way of eWOM has the potential for greater impact on consumers. Therefore, the aim of this research is to examine the influence of eWOM in social media on consumers’ purchase intentions. To do so, the research in this thesis involved two major phases. In the first phase, in order to explore the determinants of eWOM information on social media which influences consumers’ purchase intentions, a theoretical model was developed based on the integration of Information Adoption Model (IAM) and related components of Theory of Reasoned Action (TRA). The new model, which is named as Information Acceptance Model (IACM), was validated through structural equation modelling (SEM) based on surveys of 384 social media users in the UK. The results have highlighted that quality, credibility, usefulness and adoption of information, needs of information and attitude towards information are the key factors for eWOM in social media which influence consumers’ purchase intentions. Furthermore, to provide better understanding of the influence of eWOM on social media, the second phase of this research was designed as a comparative study. To explore whether the eWOM between familiar people on social media or the eWOM between anonymous people on other online platforms was more influential on consumers’ purchase intentions, the data collected through survey was reanalysed with a different perspective; and a comparison was conducted based on multiple regression analysis. The results have revealed significant differences and found anonymous reviews to be more influential on consumers’ purchase intentions than friends’ recommendations on social media. However, since these results were contrary to expectations, 10 in-depth interviews were also administered to enlighten the insightful results found through the survey. The interview findings uncovered the survey results. Information quantity, information readiness, detailed information, and dedicated information were discovered as the factors which make online reviews superior than friends’ recommendations in terms of the influence of eWOM. This research contributes to theoretical implications through its validated model and found key dimensions. The research model, IACM, brings a new approach to information adoption by extending IAM and provides new insights to researchers who study Information Systems (IS). In addition, the model highlights the information adoption process as an antecedent of behavioural intention, which is a very important finding for the related literature. Future studies can build new models through considering this relationship between information adoption process and behavioural intention. Moreover, the second phase of this research provides new constructs for future studies through its qualitative findings. The findings reached through in-depth interviews, which explain why consumers prefer anonymous online reviews, can either be tested as components of new theories and models or they can be tested as inclusion of existing theories and models. Both types have potential to provide valuable results for the literature. On the other hand, in terms of practicality, this research provides marketers with a frame of reference to understand the influence of eWOM in social media on consumers’ purchase intentions. Both the contextual and the comparative studies in this research offer valuable insights for marketers; marketers thus can develop better strategies for marketing on social media.

Anthropogenic climate change is predicted to be a major cause of extinctions. Therefore, a major aim of climate change ecology is to understand how species are being impacted and identify which species are most at risk. However, the ability to make these broad generalisations requires large-scale comparative analyses based on appropriate assumptions. This thesis investigates how European birds respond to changes in climate, the validity of several common assumptions, and identifies which species or populations are most at risk based on multiple long-term datasets. Our understanding of how different responses relate and how they affect population persistence is lacking. A conceptual hierarchical framework is introduced in chapter one to better understand and predict when climate-induced trait changes (phenology or physiology) impact demographic rates (survival or reproduction), and subsequently population dynamics. I synthesise the literature to find hypotheses about life-history and ecological characteristics that could predict when population dynamics will likely be affected. An example shows that, although earlier laying with warmer temperatures was associated with improved reproduction, this had no apparent effect on population trends in 35 British birds. Number of broods partly explains which species are most at risk of temperature-induced population declines. It is often assumed that populations within species respond similarly to climate change, and therefore a single value will reflect species-specific responses. Chapter two explores inter- and intra-specific variation in body condition responses to six climatic variables in 46 species over 21 years and 80 sites. Body condition is sensitive to all six variables (primarily in a non-linear way), and declines with warmer temperatures. I find that species signals might not exist as populations of the same species are no more alike than populations of different species. Decreased body condition is typically assumed to have detrimental consequences on species’ vital rates and population dynamics, but this assumption has rarely been tested. Expanding on chapter two, chapter three shows that temperature-induced declines in body condition have no apparent consequences on demography and population dynamics. Instead, temperature has strong effects on reproductive success and population growth rates via unknown traits and demographic rates. Much of the literature investigating climatic impacts assumes that temporal trends accurately reflect responses to climate change, and therefore investigate trait changes over time. In chapter four, I use two long-term datasets to demonstrate that, for four different types of trait responses, trait variation through time cannot be assumed to be due to warming. Non-temperature causal agents are important in explaining temporal trends, often resulting in reinforced effects. Consequently, the roles of climatic and non-climatic effects need to be understood to better predict those species most at risk. This thesis lays the foundations for more holistic climate change research that encompasses relationships among multiple response types, species and populations. Such knowledge will be vital for future conservation efforts.

The need for online banking technology in the banking industry is important to allow financial institutions to serve their customers worldwide, without having the need to be present in person or face-to-face to benefit from the service. Despite the investment in informational technology and information system infrastructure by Saudi Arabian financial institutions, the Saudi banks have lagged their Western counterparts when it comes to provision of online banking services. Given a relatively recent adoption of online banking in Saudi Arabia, consumer trust in online banking is a critical challenge facing bank managers, warranting further research. The aim of this research is to develop a framework to improve consumer trust toward online banking services and its affect consumer intentions to use the online banking service and e-WOM. The literature included the assessment of relevant theories including social cognitive theory, technology acceptance model and commitment trust theory. These theories formed the basis of formulation of research framework, including development of 12 research hypotheses. Perceived usefulness, perceived ease of use, relationship termination cost, shared value, communication, privacy and demographic factors all have an important role in influencing the extent of trust and the subsequent intention of customers to engage in and use online banking services provided by the financial institutions. When it comes to the literature gap, there remains a relative lack of existence of research on the subject of consumer trust in online banking within Saudi Arabia (Zhou, 2012; Alanezi and Brooks, 2014; AL-Malkawi et al., 2016), which presents a gap in the literature warranting further research. Moreover, most of the prior research on the subject of consumer trust in online banking has concentrated on the information cues such as reputation and information quality (Montazemi and Qahri-Saremi, 2015). This is alongside relatively little attention given to other factors such as perceived usefulness, ease of use, shared value, and privacy/security, which are crucial factors in online banking services (Fatima, 2011; Aloul., 2012; Montazemi and Qahri-Saremi, 2015). Regarding methodology, the positivist research philosophy, deductive approach, survey questionnaire and quantitative data collection and analysis techniques were undertaken. A key rationale for selection of such a methodology is the review of relevant literature, which led to development of research hypotheses that are tested through the survey technique, which is consistent with positivist and deductive research approach. The survey questionnaire request was sent online to 800 research participants (users of online services in Saudi Arabia). Out of these 800, 585 responded (indicating a response rate of an impressive 73%). The response rate was improved through giving regular reminders to the research participants who had not responded to the survey earlier. The findings of this research support the argument that trust in e-bank website play an important role in maintaining long term relationship with customers. Therefore, online banks who deal with their customers in a confidential, transparent and honest manner and ultimately protect the consumers' interests are likely to contribute to greater adoption of online banking by customers in Saudi Arabia. Furthermore, it is also concluded that perceived ease of use, trust in online banking website, trust in technology, relationship termination cost, privacy/security, shared value, and communication have positive and significant effect on customer trust in e-bank website, intention to use online banking, and e-WOM.

This thesis contributes to the modeling, understanding and efficient communication in dynamic networks populating the periphery of the Internet. By dynamic networks, we refer to networks that can be modeled by dynamic graphs in which nodes and links change temporally. In the first part of the thesis, we propose a new mobility model - STEPS - which captures a wide spectrum of human mobility behavior. STEPS implements two fundamental principles of human mobility: preferential attachment and attractor. We show that this simple parametric model is able to capture the salient statistical properties of human mobility such as the distribution of inter-contact/contact time. In the second part, using STEPS, we analyze the fundamental behavioral and structural properties of opportunistic networks. We redefine in the context of dynamic networks the concept of small world structure and show how such a structure can emerge. In particular, we show that highly dynamic nodes can play the role of bridges between disconnected components, helping to significantly reduce the length of network path and contribute to the emergence of small-world phenomenon in dynamic networks. We propose a way to model this phenomenon in STEPS. From a regular dynamic network in which nodes limit their mobility to their respective preferential areas. We rewire this network by gradually injecting highly nomadic nodes moving between different areas. We show that when the ratio of such nomadic nodes is around 10%, the network has small world structure with a high degree of clustering and a low characteristic path length. The third contribution of this thesis is the study of the impact of disorder and contact irregularity on the communication capacity of a dynamic network. We analyze the degree of disorder of real opportunistic networks and show that if used correctly, it can significantly improve routing performances. We then introduce a model to capture the degree of disorder in a dynamic network. We propose two simple and efficient algorithms that exploit the temporal structure of a dynamic network to deliver messages with a good tradeoff between resource usage and performance. The simulation and analytical results show that this type of algorithm is more efficient than conventional approaches. We also highlight also the network structure for which this type of algorithm achieves its optimum performance. Based on this theoretical result, we propose a new efficient routing protocol for content centric opportunistic networks. In this protocol, nodes maintain, through their opportunistic contacts, an utility function that summarizes their spatio-temporal proximity to other nodes. As a result, routing in this context consists in following the steepest slopes of the gradient field leading to the destination node. This property leads to a simple and effective algorithm routing that can be used both in the context of IP networks and content centric networks. The simulation results show that this protocol outperforms traditional routing protocols already defined for opportunistic networks. The last contribution of this thesis is to highlight the potential application of dynamic networks in the context of "mobile cloud computing." Using the particle optimization techniques, we show that mobility can significantly increase the processing capacity of dynamic networks. In addition, we show that the dynamic structure of the network has a strong impact on its processing capacity.

Cette thèse apporte des contributions à la modélisation, compréhension ainsi qu'à la communication efficace d'information dans les réseaux dynamiques peuplant la périphérie de l'Internet. Par réseaux dynamiques, nous signifions les réseaux pouvant être modélisés par des graphes dynamiques dans lesquels noeuds et liens évoluent temporellement. Dans la première partie de la thèse, nous proposons un nouveau modèle de mobilité - STEPS - qui permet de capturer un large spectre de comportement de mobilité humains. STEPS mets en oeuvre deux principes fondamentaux de la mobilité humaine : l'attachement préférentiel à une zone de prédilection et l'attraction vers une zone de prédilection. Nous proposons une modélisation markovienne de ce modèle de mobilité. Nous montrons que ce simple modèle paramétrique est capable de capturer les caractéristiques statistiques saillantes de la mobilité humaine comme la distribution des temps d'inter-contacts et de contacts. Dans la deuxième partie, en utilisant STEPS, nous analysons les propriétés comportementales et structurelles fondamentales des réseaux opportunistes. Nous redéfinissons dans le contexte des réseaux dynamiques la notion de structure petit monde et montrons comment une telle structure peut émerger. En particulier, nous montrons que les noeuds fortement dynamiques peuvent jouer le rôle de ponts entre les composants déconnectés, aident à réduire significativement la longueur du chemin caractéristique du réseau et contribuent à l'émergence du phénomène petit-monde dans les réseaux dynamiques. Nous proposons une façon de modéliser ce phénomène sous STEPS. À partir d'un réseau dynamique régulier dans lequel les noeuds limitent leur mobilité à leurs zones préférentielles respectives. Nous recablons ce réseau en injectant progressivement des noeuds nomades se déplaçant entre plusieurs zones. Nous montrons que le pourcentage de tels nœuds nomades est de 10%, le réseau possède une structure petit monde avec un fort taux de clusterisation et un faible longueur du chemin caractéristique. La troisième contribution de cette thèse porte sur l'étude de l'impact du désordre et de l'irrégularité des contacts sur la capacité de communication d'un réseau dynamique. Nous analysons le degré de désordre de réseaux opportunistes réels et montrons que si exploité correctement, celui-ci peut améliorer significativement les performances du routage. Nous introduisons ensuite un modèle permettant de capturer le niveau de désordre d'un réseau dynamique. Nous proposons deux algorithmes simples et efficaces qui exploitent la structure temporelle d'un réseau dynamique pour délivrer les messages avec un bon compromis entre l'usage des ressources et les performances. Les résultats de simulations et analytiques montrent que ce type d'algorithme est plus performant que les approches classiques. Nous mettons également en évidence aussi la structure de réseau pour laquelle ce type d'algorithme atteint ses performances optimum. Basé sur ce résultat théorique nous proposons un nouveau protocole de routage efficace pour les réseaux opportunistes centré sur le contenu. Dans ce protocole, les noeuds maintiennent, via leurs contacts opportunistes, une fonction d'utilité qui résume leur proximité spatio-temporelle par rapport aux autres noeuds. En conséquence, router dans un tel contexte se résume à suivre le gradient de plus grande pente conduisant vers le noeud destination. Cette propriété induit un algorithme de routage simple et efficace qui peut être utilisé aussi bien dans un contexte d'adressage IP que de réseau centré sur les contenus. Les résultats de simulation montrent que ce protocole superforme les protocoles de routage classiques déjà définis pour les réseaux opportunistes. La dernière contribution de cette thèse consiste à mettre en évidence une application potentielle des réseaux dynamiques dans le contexte du " mobile cloud computing ". En utilisant les techniques d'optimisation particulaires, nous montrons que la mobilité peut augmenter considérablement la capacité de calcul des réseaux dynamiques. De plus, nous montrons que la structure dynamique du réseau a un fort impact sur sa capacité de calcul.

The music of Béla Bartók is defined in part by its unique blend of rhythmic vitality and inventiveness, and his string quartets offer a glimpse into a consistency of technique evident throughout his compositional career. Bartók's rhythmic environments are primarily metrical, but many of his rhythmic configurations are placed in such a way as to potentially override established meter. It is necessary, therefore, to institute an analytical means by which the delineation and comparison of rhythmic structures both within and without the metrical context may be accomplished. An analytical method using Timepoint Accent Structures (TAS) allows for the comparison of rhythms resulting from patterns of accent produced by pitch onset, dynamic stress, articulation or any other accentual factors. Timepoint Grouping Structures (TGS) delineate the number of timepoints present in alternating groups/blocks in a texture, thereby allowing for the recognition of patterning created by these larger groups. By applying TAS and TGS analysis, relationships of rhythmic equivalency, rotation, retrograde, complementation, augmentation, diminution, subset, superset, exchange, compression and expansion are clearly confirmed in the string quartets. In addition, symmetrical structures and arithmetic progressions are discovered. In many ways, Bartók's rhythmic organization mimics his procedures of pitch structuring.

The rapid growth of the World Wide Web in the last decade makes it the largest publicly accessible data source in the world, which has become one of the most significant and influential information revolution of modern times. The influence of the Web has impacted almost every aspect of humans' life, activities and fields, causing paradigm shifts and transformational changes in business, governance, and education. Moreover, the rapid evolution of Web 2.0 and the Social Web in the past few years, such as social blogs and friendship networking sites, has dramatically transformed the Web from a raw environment for information consumption to a dynamic and rich platform for information production and sharing worldwide. However, this growth and transformation of the Web has resulted in an uncontrollable explosion and abundance of the textual contents, creating a serious challenge for any user to find and retrieve the relevant information that he truly seeks to find on the Web. The process of finding a relevant Web page in a website easily and efficiently has become very difficult to achieve. This has created many challenges for researchers to develop new mining techniques in order to improve the user experience on the Web, as well as for organizations to understand the true informational interests and needs of their customers in order to improve their targeted services accordingly by providing the products, services and information that truly match the requirements of every online customer. With these challenges in mind, Web mining aims to extract hidden patterns and discover useful knowledge from Web page contents, Web hyperlinks, and Web usage logs. Based on the primary kinds of Web data used in the mining process, Web mining tasks can be categorized into three main types: Web content mining, which extracts knowledge from Web page contents using text mining techniques, Web structure mining, which extracts patterns from the hyperlinks that represent the structure of the website, and Web usage mining, which mines user's Web navigational patterns from Web server logs that record the Web page access made by every user, representing the interactional activities between the users and the Web pages in a website. The main goal of this thesis is to contribute toward addressing the challenges that have been resulted from the information explosion and overload on the Web, by proposing and developing novel Web mining-based approaches. Toward achieving this goal, the thesis presents, analyzes, and evaluates three major contributions. First, the development of an integrated Web structure and usage mining approach that recommends a collection of hyperlinks for the surfers of a website to be placed at the homepage of that website. Second, the development of an integrated Web content and usage mining approach to improve the understanding of the user's Web behavior and discover the user group interests in a website. Third, the development of a supervised classification model based on recent Social Web concepts, such as Tag Clouds, in order to improve the retrieval of relevant articles and posts from Web social blogs.

The rapid growth of the World Wide Web in the last decade makes it the largest publicly accessible data source in the world, which has become one of the most significant and influential information revolution of modern times. The influence of the Web has impacted almost every aspect of humans' life, activities and fields, causing paradigm shifts and transformational changes in business, governance, and education. Moreover, the rapid evolution of Web 2.0 and the Social Web in the past few years, such as social blogs and friendship networking sites, has dramatically transformed the Web from a raw environment for information consumption to a dynamic and rich platform for information production and sharing worldwide. However, this growth and transformation of the Web has resulted in an uncontrollable explosion and abundance of the textual contents, creating a serious challenge for any user to find and retrieve the relevant information that he truly seeks to find on the Web. The process of finding a relevant Web page in a website easily and efficiently has become very difficult to achieve. This has created many challenges for researchers to develop new mining techniques in order to improve the user experience on the Web, as well as for organizations to understand the true informational interests and needs of their customers in order to improve their targeted services accordingly by providing the products, services and information that truly match the requirements of every online customer. With these challenges in mind, Web mining aims to extract hidden patterns and discover useful knowledge from Web page contents, Web hyperlinks, and Web usage logs. Based on the primary kinds of Web data used in the mining process, Web mining tasks can be categorized into three main types: Web content mining, which extracts knowledge from Web page contents using text mining techniques, Web structure mining, which extracts patterns from the hyperlinks that represent the structure of the website, and Web usage mining, which mines user's Web navigational patterns from Web server logs that record the Web page access made by every user, representing the interactional activities between the users and the Web pages in a website. The main goal of this thesis is to contribute toward addressing the challenges that have been resulted from the information explosion and overload on the Web, by proposing and developing novel Web mining-based approaches. Toward achieving this goal, the thesis presents, analyzes, and evaluates three major contributions. First, the development of an integrated Web structure and usage mining approach that recommends a collection of hyperlinks for the surfers of a website to be placed at the homepage of that website. Second, the development of an integrated Web content and usage mining approach to improve the understanding of the user's Web behavior and discover the user group interests in a website. Third, the development of a supervised classification model based on recent Social Web concepts, such as Tag Clouds, in order to improve the retrieval of relevant articles and posts from Web social blogs.

In Swedish dialects we find the terms ris,skäver and skärva referring to illnesses in children. The words are also parts of various compounds which refer to variants of the illnesses. The terms are linguistic expressions denoting two folk categories of illnesses, RIS and SKÄVER/SKÄRVA. These categories are investigated from a cognitive semantic perspective. The cognitive perspective argues that we organize our understanding of reality by using Idealized Cognitive Models (ICM) based on our physical, mental and emotional experiences of the world. The aim is twofold: to demonstrate the bases on which an experienced illness is placed in a certain category, and to show how a folk conception of illness is reflected in the word formation strategies. The word formation strategies emanate from notions of characteristic symptoms, and from notions of causes of illnesses. Both categories, RIS and SKÄVER/SKÄRVA, are based on a number of ICM's. The category RIS is a radial structure, which means that the category is held together although its members have no structural criteria in common. The category SKÄVER/SKÄRVA is a concentrating structure, meaning that all members share all structural criteria. There is a strong connection between word formation strategies and the structures of the categories. Terms related to symptoms refer to members of a category which are part of a radial structure, while terms related to causes refer to members of a category which are part of a concentrating structure. This can be explained by two of the basic assumptions of cognitive semantics: semantic content is structred and symbolized overtly on the surface form of a language and categories are conventional, based on cultural assumptions about the world.
digitalisering@umu

La información de clase semántica de los nombres es fundamental para una amplia variedad de tareas del procesamiento del lenguaje natural (PLN), como la traducción automática, la discriminación de referentes en tareas como la detección y el seguimiento de eventos, la búsqueda de respuestas, el reconocimiento y la clasificación de nombres de entidades, la construcción y ampliación automática de ontologías, la inferencia textual, etc. Una aproximación para resolver la construcción y el mantenimiento de los léxicos de gran cobertura que alimentan los sistemas de PNL, una tarea muy costosa y lenta, es la adquisición automática de información léxica, que consiste en la inducción de una clase semántica relacionada con una palabra en concreto a partir de datos de su distribución obtenidos de un corpus. Precisamente, por esta razón, se espera que la investigación actual sobre los métodos para la producción automática de léxicos de alta calidad, con gran cantidad de información y con anotación de clase como el trabajo que aquí presentamos, tenga un gran impacto en el rendimiento de la mayoría de las aplicaciones de PNL. En esta tesis, tratamos la adquisición automática de información léxica como un problema de clasificación. Con este propósito, adoptamos métodos de aprendizaje automático para generar un modelo que represente los datos de distribución vectorial que, basados en ejemplos conocidos, permitan hacer predicciones de otras palabras desconocidas. Las principales preguntas de investigación que planteamos en esta tesis son: (i) si los datos de corpus proporcionan suficiente información para construir representaciones de palabras de forma eficiente y que resulten en decisiones de clasificación precisas y sólidas, y (ii) si la adquisición automática puede gestionar, también, los nombres polisémicos. Para hacer frente a estos problemas, realizamos una serie de validaciones empíricas sobre nombres en inglés. Nuestros resultados confirman que la información obtenida a partir de la distribución de los datos de corpus es suficiente para adquirir automáticamente clases semánticas, como lo demuestra un valor-F global promedio de 0,80 aproximadamente utilizando varios modelos de recuento de contextos y en datos de corpus de distintos tamaños. No obstante, tanto el estado de la cuestión como los experimentos que realizamos destacaron una serie de retos para este tipo de modelos, que son reducir la escasez de datos del vector y dar cuenta de la polisemia nominal en las representaciones distribucionales de las palabras. En este contexto, los modelos de word embedding (WE) mantienen la “semántica” subyacente en las ocurrencias de un nombre en los datos de corpus asignándole un vector. Con esta elección, hemos sido capaces de superar el problema de la escasez de datos, como lo demuestra un valor-F general promedio de 0,91 para las clases semánticas de nombres de sentido único, a través de una combinación de la reducción de la dimensionalidad y de números reales. Además, las representaciones de WE obtuvieron un rendimiento superior en la gestión de las ocurrencias asimétricas de cada sentido de los nombres de tipo complejo polisémicos regulares en datos de corpus. Como resultado, hemos podido clasificar directamente esos nombres en su propia clase semántica con un valor-F global promedio de 0,85. La principal aportación de esta tesis consiste en una validación empírica de diferentes representaciones de distribución utilizadas para la clasificación semántica de nombres junto con una posterior expansión del trabajo anterior, lo que se traduce en recursos léxicos y conjuntos de datos innovadores que están disponibles de forma gratuita para su descarga y uso.
La información de clase semántica de los nombres es fundamental para una amplia variedad de tareas del procesamiento del lenguaje natural (PLN), como la traducción automática, la discriminación de referentes en tareas como la detección y el seguimiento de eventos, la búsqueda de respuestas, el reconocimiento y la clasificación de nombres de entidades, la construcción y ampliación automática de ontologías, la inferencia textual, etc. Una aproximación para resolver la construcción y el mantenimiento de los léxicos de gran cobertura que alimentan los sistemas de PNL, una tarea muy costosa y lenta, es la adquisición automática de información léxica, que consiste en la inducción de una clase semántica relacionada con una palabra en concreto a partir de datos de su distribución obtenidos de un corpus. Precisamente, por esta razón, se espera que la investigación actual sobre los métodos para la producción automática de léxicos de alta calidad, con gran cantidad de información y con anotación de clase como el trabajo que aquí presentamos, tenga un gran impacto en el rendimiento de la mayoría de las aplicaciones de PNL. En esta tesis, tratamos la adquisición automática de información léxica como un problema de clasificación. Con este propósito, adoptamos métodos de aprendizaje automático para generar un modelo que represente los datos de distribución vectorial que, basados en ejemplos conocidos, permitan hacer predicciones de otras palabras desconocidas. Las principales preguntas de investigación que planteamos en esta tesis son: (i) si los datos de corpus proporcionan suficiente información para construir representaciones de palabras de forma eficiente y que resulten en decisiones de clasificación precisas y sólidas, y (ii) si la adquisición automática puede gestionar, también, los nombres polisémicos. Para hacer frente a estos problemas, realizamos una serie de validaciones empíricas sobre nombres en inglés. Nuestros resultados confirman que la información obtenida a partir de la distribución de los datos de corpus es suficiente para adquirir automáticamente clases semánticas, como lo demuestra un valor-F global promedio de 0,80 aproximadamente utilizando varios modelos de recuento de contextos y en datos de corpus de distintos tamaños. No obstante, tanto el estado de la cuestión como los experimentos que realizamos destacaron una serie de retos para este tipo de modelos, que son reducir la escasez de datos del vector y dar cuenta de la polisemia nominal en las representaciones distribucionales de las palabras. En este contexto, los modelos de word embedding (WE) mantienen la “semántica” subyacente en las ocurrencias de un nombre en los datos de corpus asignándole un vector. Con esta elección, hemos sido capaces de superar el problema de la escasez de datos, como lo demuestra un valor-F general promedio de 0,91 para las clases semánticas de nombres de sentido único, a través de una combinación de la reducción de la dimensionalidad y de números reales. Además, las representaciones de WE obtuvieron un rendimiento superior en la gestión de las ocurrencias asimétricas de cada sentido de los nombres de tipo complejo polisémicos regulares en datos de corpus. Como resultado, hemos podido clasificar directamente esos nombres en su propia clase semántica con un valor-F global promedio de 0,85. La principal aportación de esta tesis consiste en una validación empírica de diferentes representaciones de distribución utilizadas para la clasificación semántica de nombres junto con una posterior expansión del trabajo anterior, lo que se traduce en recursos léxicos y conjuntos de datos innovadores que están disponibles de forma gratuita para su descarga y uso.
Lexical semantic class information for nouns is critical for a broad variety of Natural Language Processing (NLP) tasks including, but not limited to, machine translation, discrimination of referents in tasks such as event detection and tracking, question answering, named entity recognition and classification, automatic construction and extension of ontologies, textual inference, etc. One approach to solve the costly and time-consuming manual construction and maintenance of large-coverage lexica to feed NLP systems is the Automatic Acquisition of Lexical Information, which involves the induction of a semantic class related to a particular word from distributional data gathered within a corpus. This is precisely why current research on methods for the automatic production of high- quality information-rich class-annotated lexica, such as the work presented here, is expected to have a high impact on the performance of most NLP applications. In this thesis, we address the automatic acquisition of lexical information as a classification problem. For this reason, we adopt machine learning methods to generate a model representing vectorial distributional data which, grounded on known examples, allows for the predictions of other unknown words. The main research questions we investigate in this thesis are: (i) whether corpus data provides sufficient distributional information to build efficient word representations that result in accurate and robust classification decisions and (ii) whether automatic acquisition can handle also polysemous nouns. To tackle these problems, we conducted a number of empirical validations on English nouns. Our results confirmed that the distributional information obtained from corpus data is indeed sufficient to automatically acquire lexical semantic classes, demonstrated by an average overall F1-Score of almost 0.80 using diverse count-context models and on different sized corpus data. Nonetheless, both the State of the Art and the experiments we conducted highlighted a number of challenges of this type of model such as reducing vector sparsity and accounting for nominal polysemy in distributional word representations. In this context, Word Embeddings (WE) models maintain the “semantics” underlying the occurrences of a noun in corpus data by mapping it to a feature vector. With this choice, we were able to overcome the sparse data problem, demonstrated by an average overall F1-Score of 0.91 for single-sense lexical semantic noun classes, through a combination of reduced dimensionality and “real” numbers. In addition, the WE representations obtained a higher performance in handling the asymmetrical occurrences of each sense of regular polysemous complex-type nouns in corpus data. As a result, we were able to directly classify such nouns into their own lexical-semantic class with an average overall F1-Score of 0.85. The main contribution of this dissertation consists of an empirical validation of different distributional representations used for nominal lexical semantic classification along with a subsequent expansion of previous work, which results in novel lexical resources and data sets that have been made freely available for download and use.

This thesis examines the problem of an autonomous agent learning a causal world model of its environment. Previous approaches to learning causal world models have concentrated on environments that are too "easy" (deterministic finite state machines) or too "hard" (containing much hidden state). We describe a new domain --- environments with manifest causal structure --- for learning. In such environments the agent has an abundance of perceptions of its environment. Specifically, it perceives almost all the relevant information it needs to understand the environment. Many environments of interest have manifest causal structure and we show that an agent can learn the manifest aspects of these environments quickly using straightforward learning techniques. We present a new algorithm to learn a rule-based causal world model from observations in the environment. The learning algorithm includes (1) a low level rule-learning algorithm that converges on a good set of specific rules, (2) a concept learning algorithm that learns concepts by finding completely correlated perceptions, and (3) an algorithm that learns general rules. In addition this thesis examines the problem of finding a good expert from a sequence of experts. Each expert has an "error rate"; we wish to find an expert with a low error rate. However, each expert's error rate and the distribution of error rates are unknown. A new expert-finding algorithm is presented and an upper bound on the expected error rate of the expert is derived.

This thesis studies data structures in the word-RAM and bitprobe models, with an emphasis on space efficiency. In the word-RAM model of computation the space cost of a data structure is measured in terms of the number of w-bit words stored in memory, and the cost of answering a query is measured in terms of the number of read, write, and arithmetic operations that must be performed. In the bitprobe model, like the word-RAM model, the space cost is measured in terms of the number of bits stored in memory, but the query cost is measured solely in terms of the number of bit accesses, or probes, that are performed. First, we examine the problem of succinctly representing a partially ordered set, or poset, in the word-RAM model with word size Theta(lg n) bits. A succinct representation of a combinatorial object is one that occupies space matching the information theoretic lower bound to within lower order terms. We show how to represent a poset on n vertices using a data structure that occupies n^2/4 + o(n^2) bits, and can answer precedence (i.e., less-than) queries in constant time. Since the transitive closure of a directed acyclic graph is a poset, this implies that we can support reachability queries on an arbitrary directed graph in the same space bound. As far as we are aware, this is the first representation of an arbitrary directed graph that supports reachability queries in constant time, and stores less than n choose 2 bits. We also consider several additional query operations. Second, we examine the problem of supporting range queries on strings of n characters (or, equivalently, arrays of n elements) in the word-RAM model with word size Theta(lg n) bits. We focus on the specific problem of answering range majority queries: i.e., given a range, report the character that is the majority among those in the range, if one exists. We show that these queries can be supported in constant time using a linear space (in words) data structure. We generalize this result in several directions, considering various frequency thresholds, geometric variants of the problem, and dynamism. These results are in stark contrast to recent work on the similar range mode problem, in which the query operation asks for the mode (i.e., most frequent) character in a given range. The current best data structures for the range mode problem take soft-Oh(n^(1/2)) time per query for linear space data structures. Third, we examine the deterministic membership (or dictionary) problem in the bitprobe model. This problem asks us to store a set of n elements drawn from a universe [1,u] such that membership queries can be always answered in t bit probes. We present several new fully explicit results for this problem, in particular for the case when n = 2, answering an open problem posed by Radhakrishnan, Shah, and Shannigrahi [ESA 2010]. We also present a general strategy for the membership problem that can be used to solve many related fundamental problems, such as rank, counting, and emptiness queries. Finally, we conclude with a list of open problems and avenues for future work.

Dissertation presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Marketing Research and CRM
Marketing and business strategy have been globally target of several transformations and improvements during the last century, from a business perspective product-centric, where the demand was bigger than the offer, to a customer-centric perspective, where offer is bigger than the demand. The client is now the focus of the company, the element generating revenues and spreading the word or repurchasing when satisfied, consequently enhancing companies business sustainability and growth. This research intends to contribute to understand the relation between several customer metrics and net promoter score in the insurance sector in Portugal. To achieve this objective, it will estimated a Structural Equation Model using a data set with information collected by Nova Information Management School in scope of the project ECSI covering the latent variables (1) Image (2) Expectations (3) Perceived Quality (4) Perceived Value (5) Trust (6) Satisfaction (7) Loyalty and as target latent variable Net Promoter Score based on the willingness to recommend the organization. It is expected to find results suggesting a positive association between the customer metrics and NPS and therefore by the end of the study we hope to be able to contribute for a growth on customer satisfaction model’s evaluation as well as for implementing policies or strategies to increase the insurance sector overall performance.

Summaries in English and Afrikaans
Daar is gepoog om 'n omvattende, algemeen geldige maatstaf te vind waarmee enige opvoeding vir outentisiteit geevalueer kan word. Die moontlikheid dat die "essensiestruktuur van behoorlike volwassenewees en van opvoedingsdoel" (ES) hieraan voldoen, is ondersoek. Die genoemde essensiestruktuur (ES) is in 'n modeldiagram CESM) saamgevat. Dit bevat die volgende essensies: 'religiositeit', die 'etiese', 'affektiwiteit', 'liggaamlikheid'. 'nasionaliteit' (insluitende 'kulturaliteit'. 'historisiteit' en die 'politiese'), die 'estetiese'. 'individualiteit'. 'sosialiteit'. die 'ekonomiese'. 'vryheid'. 'gesag'. 'taal' en 'redelikheid'. asook die sewe normbeelde wat 'n substruktuur van die 'etiese' is. 'Religiositeit' is hierargies die mees belangrikste essensie. gevolg deur die 'etiese'. Aldie ander essensies verkeer op 'n derde niveau van belangrikheid. Om outentiek te wees behoort 'n opvoedingseksemplaar aan boge noemde hierargie te voldoen. Elk van die genoemde essensies is verduidelik, asook hulle samehangende verbandhoudendheid binne die ESM. Die harmonie binne hierdie gestruktureerdheid is van deurslaggewende belang vir die begryping van outentisiteit by opvoeding. 'n Evalueringsmetode. bekend as ''essensiestruktuur-analise" (ES-analise). is uit bogenoemde deur die navorser ontwikkel. 'n Uiteensetting van mikro-. meso- en makro ES-analise is oak verstrek. Beskrywings van eksemplare van opvoeding en van aanverwante opvoedingsaangeleenthede word in die lig van die ESM geanaliseer. Hoe meer 'n opvoedingseksemplaar ooreenstem met die ESM hoe nader beweeg dit aan outentisiteit. en omgekeerd. Ter illustrasie van die toepassingsmoontlikhede van ES-analise is die mensbeskouing van C.K. Oberholzer. die kindbeskouing van J.C. Coetzee. die Christelike lewensopvatting, die wereldbeskouing van Albert Schweitzer en die opvoedingsleer van die Klassisisme aan ES-analises onderwerp. Die Christelike lewensopvatting kon as outentiek geevalueer word, terwyl die mensbeskouing van Oberholzer. die kindbeskouing van Coetzee en die wereld beskouing van Schweitzer naby aan outentisiteit beweeg. Die opvoedingsleer van die Klassisisme vertoon heelparty essensie-diskrepansies. Die hipotese, dat ES-analise 'n betroubare evalueringsmaatstaf vir outentieke opvoeding kan wees, is bevestig. Derhalwe kon die aanwending vanESanalise oar 'n wye spektrum aanbeveel word. byvoorbeeld by histories opvoedkundige eksemplare, godsdienslere. skoolstelsels en meegaande kurrikula en by die ontwikkeling van opvoedingsprogramme. Die huidige opvoeding en kon temporere leefwyse kan in die toekoms verbeter word indien ES-analise daadwerklik toegepas sou word.
An effort was made to find a universally valid criterion to evaluate any education for authenticity. The "essence-structure of proper adulthood and of education-aim" (ES) was investigated in this regard. This essence-structure (ES) was condensed in a model diagram (ESM). It includes the fo 11 owing essences: · re 1 i gi ousness · , the · ethi ca 1 ' , · affec tiveness'. 'bodiliness'. 'nationality' ('culturality'. 'historicity' and the 'political'), the 'aesthetical'. 'individuality', 'sociality·. the 'economical'. 'freedom·. 'authority'. 'language' and 'rationality'. as well as the seven norm images - a substructure of the 'ethical'. Hierarchically 'religiousness· is the most important essence. followed by the 'ethical·. All other essences exist on a third 1 eve 1 of importance. To qualify as authentic an exemplar of education ought to comply with the above-mentioned hierarchy. Each of the essences and their interrelatedness within the ESM were discussed. The harmonious co-existence within this structuredness is of paramount importance in understanding educational authenticity. Emanating from the above-mentioned an evaluation method. known as "essence structure-analysis" (ES analysis). was developed. Micro. meso and macro-ESanalysis were also explained. Descriptions of exemplars of education and of educationally related matters are analysed using the ESM as the criterion. The more an exemplar corresponds with the ESM. the more it re sembles authenticity, and vice versa. To demonstrate the application potential of ES analysis C.K. Oberholzer's view of man. J.C. Coetzee's view on childhood. the Christian life-view. Albert Schweitzer's world-view and the educational doctrine of the Classicism were subjected toES analyses. The Christian life-view could be evaluated as authentic. while Oberholzer's view of man. Coetzee's view on childhood and Schweitzer's world-view are resembling authenticity closely. The educational doctrine of the Classicism revealed several essence discre pancies. (viii) The hypothesis. that ES analysis can be a reliable evaluation criterion for authentic education. was confirmed. It could thus be recommended that ESanalysis be implemented over a broad spectrum. for example when studying historico-educational exemplars. doctrines of religion. school systems and curricula and assisting in developing educational programs. The contemporary education and way of life can be ameliorated in the future if ES analysis is applied actively.
Educational Studies
D.Ed. (Philosophy of Education)

This study focuses on Bruegel's parodic legacy in the picaresque tradition. It is based, on the one hand, on visual rhetoric, visual parody, and the poetics of epideictic rhetoric; and, on the other, on the interaction between epideictic rhetoric's salient features and the Bruegelian themes of camivalisation, the satirising of human folly, and the ontic order of the World Upside Down topos as organising principles. The relationships between the above themes are chronologically traced in various disguises in pictures by representative picaresque artists from the sixteenth to the twentieth centuries: i.e., in Bruegel, Steen, Hogarth, Daumier, and Grosz. Each of these picaresque artists battled with their own times, parodying the paradigmatic targets of the high mode, in both social and genre hierarchy, and in doing so revealed the complexities of the above themes at work within an ever changing context-bound rhetoricity.
Art History, Visual Arts & Musicology
Thesis (D.Litt. et Phil.)