The residential sector is recognized as a major energy consumer and thus a significant contributor to climate change. Rather than focus only on current energy consumption and the associated emissions, there is a need to broaden sustainability research to include full life cycle contributions and impacts. This thesis looks at houses from the perspective of the Ecological Footprint (EF), a well-known sustainability indicator. The research objective is to integrate EF and Life Cycle Analysis (LCA) measures to provide an enhanced tool to measure the sustainability implications of residential energy retrofit decisions. Exemplifying single-detached houses of the early 20th century, the century-old REEP House (downtown Kitchener, Canada), together with its high performance energy retrofits, is examined in detail. This research combines material, energy and carbon emission studies. Its scope covers the life cycle of the house, including the direct and indirect consumption of material and energy, and concomitant carbon emissions during its stages of material extraction, transportation, construction, operation, and demolition. The results show that the REEP House had a significant embodied impact on the environment when it was built and high operating energy and EF requirements because of the low levels of insulation. Even though the renovations to improve energy efficiency by 80% introduce additional embodied environmental impacts, they are environmentally sound activities because the environmental payback period is less than two years.

Theories of writing are one of the fundamental ways by which Indigenous peoples have been labeled as "uncivilized." In these discussions, writing becomes synonymous with history, literacy, and often times Truth. As such, scholars studying Nahua codices and Andean khipu sometimes juxtapose the two because together they present a break in an evolutionary theory of writing systems that links alphabetic script with the construction of "complex civilizations." Contemporary scholars tend to offer an "inclusive" approach to the study of Latin American histories through challenging exclusive definitions of writing. These definitions are always informed and limited by language-the extent to which these "writing" systems represent language. However, recentering discussions of writing and language on what Gregory Cajete has called Native Science shifts the discussion to matters of ecology in a way that intersects with current scholarship in bicocultural diversity studies regarding the link between language, culture, and biodiversity. Because of the ways in which language configures rhetoric and writing studies, a shift in understanding how language emerges bears great impact on how we understand not only the histories tied to codices and khipu but also how they function as epistemologies. In my dissertation, I build a model of relationality using Indigenous and decolonial methodologies alongside the Nahua concept of in ixtli in yollotl (a wise face/a wise heart) and embodied rhetorics. The model I construct here offers a path for understanding "traditional" knowledges as fluid and mobile. I specifically look at the relationship between land, bodies, language, and Native Science functions on the reciprocal relationship between those three components in making meaning. I then extend this argument to show how the complex web of relations that we might call biocultural diversity produces and is produced by "things" like images from codices and khipu that in turn help to (re)produce biocultural diversity. Thing theory, in emerging material culture studies, argues for the agency of cultural artifacts in the making of various realities. These "things" always-already bear a relationship to bodies and "nature." Thing theory, then, can challenge us to see artifacts like khipu and Nahua images as language artifacts and help us connect Nahua images and khipu to language outside of a text-based model. Ultimately, I argue that Native Science asks us to see language as a practice connected to biocultural diversity.

"This work explores how current embodied theories of cognition can account for the comprehension of narrative texts. Theoretically, this thesis develops a framework for the study of narrative text comprehension by linking current advances in embodied theories of cognition, discourse processing, and neurosciences. Experimentally, two experiments are reported in which participants were required to read passages of text implying emotional states. The coherence of critical sentences in relation to the preceding text was manipulated in terms of both the emotional adjectives used and the sensory-motor component. In the first experiment, three tasks were used to index the effect of the manipulations on the critical sentences. The first was an on-line naming task in which response times to name emotional labels which matched the implied emotional state of the texts were recorded. [...] The second experiment used backward masking in the naming task with the aim of providing a more sensitive index of the effect of the text manipulations on on-line processing." / Master of Applied Science by research

"This work explores how current embodied theories of cognition can account for the comprehension of narrative texts. Theoretically, this thesis develops a framework for the study of narrative text comprehension by linking current advances in embodied theories of cognition, discourse processing, and neurosciences. Experimentally, two experiments are reported in which participants were required to read passages of text implying emotional states. The coherence of critical sentences in relation to the preceding text was manipulated in terms of both the emotional adjectives used and the sensory-motor component. In the first experiment, three tasks were used to index the effect of the manipulations on the critical sentences. The first was an on-line naming task in which response times to name emotional labels which matched the implied emotional state of the texts were recorded. [...] The second experiment used backward masking in the naming task with the aim of providing a more sensitive index of the effect of the text manipulations on on-line processing." / Master of Applied Science by research

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A tatuagem é uma antiga forma de inscrição corporal que apesar de sua idade não sofreu alterações em termos de materiais e técnicas. O desenvolvimento de tecnologias para a concepção de novas modalidades de intervenção orgânica terá ramificações em diversas áreas, permitindo o uso de novas interfaces epiteliais interativas (tatuagens dinâmicas responsivas), e criando novas vias de interação e comunicação incorporada. Em contraste à prática tradicional de imagens estáticas, as tatuagens dinâmicas (TDs) permitem a geração de imagens dinâmicas e interativas na pele. Nosso objetivo aqui é apresentar este novo campo de pesquisa e refletir sobre o papel do designer no projeto de tatuagens dinâmicas e as implicações destas tatuagens que transformam a pele em uma nova fonte de inscrições interativas e reversíveis. / Tattoo art is a very old form of bodily inscription. In spite of its long history, tattoo art has not changed very significantly in terms of applying new materials and techniques. The impact of developing technologies for the conception of new modalities of organic interventions will have ramifications in unprecedented areas, allowing the use of new interactive epithelial interfaces (responsive dynamic tattoos), and creating new ways of interaction and embodied communication. In contrast to traditional tattoo art of static images, new tattoo art (NT) allows the generation of dynamic interactive images on the skin. Our purpose here is to present this new field of research and speculate on the role of the designer in the design of dynamic tattoo images, and the implications of these tattoos which transform the skin into a new source of interactive and reversible inscription.

abstract: Intuitive decision making refers to decision making based on situational pattern recognition, which happens without deliberation. It is a fast and effortless process that occurs without complete awareness. Moreover, it is believed that implicit learning is one means by which a foundation for intuitive decision making is developed. Accordingly, the present study investigated several factors that affect implicit learning and the development of intuitive decision making in a simulated real-world environment: (1) simple versus complex situational patterns; (2) the diversity of the patterns to which an individual is exposed; (3) the underlying mechanisms. The results showed that simple patterns led to higher levels of implicit learning and intuitive decision-making accuracy than complex patterns; increased diversity enhanced implicit learning and intuitive decision-making accuracy; and an embodied mechanism, labeling, contributes to the development of intuitive decision making in a simulated real-world environment. The results suggest that simulated real-world environments can provide the basis for training intuitive decision making, that diversity is influential in the process of training intuitive decision making, and that labeling contributes to the development of intuitive decision making. These results are interpreted in the context of applied situations such as military applications involving remotely piloted aircraft. / Dissertation/Thesis / Ph.D. Psychology 2011

abstract: Due to the push down of academics, today's elementary students are being asked to learn more concepts and sit for longer periods of time. Sitting slows thinking, whereas movement wakes up the brain. Using movement to learn is embodied cognition, or learning through both the body and the brain. Movement should be part of instruction for young students; however teachers are often not sure how to incorporate movement in their lesson plans. The Japanese practice of lesson study may help because it embeds teachers' new learning in their classrooms while intimately connecting it to the learning of their students, and it links with the cyclical, constructed theory of learning provided by Vygotsky Space. If teachers incorporate movement in their lessons, children have the potential to become more engaged and learn. This action research study was designed to understand if two first grade, two second grade, and one third grade teacher at a Title One elementary school in the Southwestern United States could learn how to use movement more during instruction through lesson study. This innovation took place for 14-weeks during which 12 lessons using movement were developed and taught. Data were collected prior to the study and during each portion of the cyclical process including, while teachers learned, during lessons using movement, and when lessons were discussed and changed. The data sources were pre and post teacher surveys, student surveys, observation protocols, lesson plans, transcripts of lesson study meetings, and researcher notes. To reduce bias a triangulated mixed methods design was used. Results indicate that through lesson study teachers were able to learn about movement, try it, observe the results, and adjust it to fit their teaching style and their students' needs. Data showed increased student engagement in lessons that incorporated movement as evidenced in the students' words, bodies, and learning. After participating in the study, the teachers realized they personally use movement to learn, and teachers' efficacy regarding their ability to plan movement in their lessons increased. Additionally, they started purposefully planning movement across their curriculum. Based on the results, further cycles / Dissertation/Thesis / Ed.D. Leadership and Innovation 2012

In this thesis I report the development of FARSA (Framework for Autonomous Robotics Simulation and Analysis), a simulation tool for the study of the interaction between language and action in cognitive robots and more in general for experiments in embodied cognitive science. Before presenting the tools, I will describe a series of experiments that involve simulated humanoid robots that acquire their behavioural and language skills autonomously through a trial-and-error adaptive process in which random variations of the free parameters of the robots’ controller are retained or discarded on the basis of their effect on the overall behaviour exhibited by the robot in interaction with the environment. More specifically the first series of experiments shows how the availability of linguistic stimuli provided by a caretaker, that indicate the elementary actions that need to be carried out in order to accomplish a certain complex action, facilitates the acquisition of the required behavioural capacity. The second series of experiments shows how a robot trained to comprehend a set of command phrases by executing the corresponding appropriate behaviour can generalize its knowledge by comprehending new, never experienced sentences, and by producing new appropriate actions. Together with their scientific relevance, these experiments provide a series of requirements that have been taken into account during the development of FARSA. The objective of this project is that to reduce the complexity barrier that currently discourages part of the researchers interested in the study of behaviour and cognition from initiating experimental activity in this area. FARSA is the only available tools that provide an integrated framework for carrying on experiments of this type, i.e. it is the only tool that provides ready to use integrated components that enable to define the characteristics of the robots and of the environment, the characteristics of the robots’ controller, and the characteristics of the adaptive process. Overall this enables users to quickly setup experiments, including complex experiments, and to quickly start collecting results.

Embodied Conversational Agents (ECAs) are intelligent software entities with an embodiment used to communicate with users, using natural language. Their purpose is to exhibit the same properties as humans in face-to-face conversation, including the ability to produce and respond to verbal and nonverbal communication. Researchers in the field of ECAs try to create agents that can be more natural, believable and easy to use. Designing an ECA requires understanding that manner, personality, emotion, and appearance are very important issues to be considered. In this thesis, we are interested in increasing believability of ECAs by placing personality at the heart of the human-agent verbal interaction. We propose a model relating personality facets and hidden communication goals that can influence ECA behaviors. Moreover, we apply our model in agents that interact in a puzzle game application. We develop five distinct personality oriented agents using an expressive communication language and a plan-based BDI approach for modeling and managing dialogue according to our proposed model. In summary, we present and test an innovative approach to model mental aspects of ECAs trying to increase their believability and to enhance human-agent affective communication. With this research, we hope to improve the understanding on how ECAs with expressive and affective characteristics can establish and maintain long-term human-agent relationships.

O presente trabalho propõe um novo modelo de rede neural artificial voltado a aplicações robóticas, em especial a tarefas de natureza espaço-temporal e de horizonte infinito. Este modelo apresenta três características que o tornam único e que foram tomadas como guia para a sua concepção: auto-organização, representação temporal e aprendizado construtivo. O algoritmo de aprendizagem auto-organizada incorpora todos os mecanismos que são básicos para a auto-organização: competição global, cooperação local e auto-amplificação seletiva. A rede neural é suprida com propriedades dinâmicas através de uma memória de curto prazo. A memória de curto prazo é inserida na estrutura da rede por meio de integradores e diferenciadores, os quais são implementados na camada de entrada da rede. Nesta abordagem existe uma evidente separação de papéis: a rede é responsável pela não-linearidade e a memória é responsável pelo tempo. A construção automática da arquitetura da rede neural é realizada de acordo com uma unidade de habituação. A unidade de habituação regula o crescimento e a poda de neurônios. O procedimento de inclusão, adaptação e remoção de conexões sinápticas é realizado conforme o método de aprendizado hebbiano competitivo. Em muitos problemas práticos, como os existentes na área da robótica, a auto-organização, a representação temporal e o aprendizado construtivo são fatores imprescindíveis para o sucesso da tarefa. A grande dificuldade e, ao mesmo tempo, a principal contribuição deste trabalho consiste em integrar tais tecnologias em uma arquitetura de rede neural artificial de maneira eficiente. Estudos de caso foram elaborados para validar e, principalmente, determinar as potencialidades e as limitações do modelo neural proposto. Os cenários abrangeram tarefas simples de classificação de padrões e segmentação temporal. Os resultados preliminares obtidos demonstraram a eficiência do modelo neural proposto frente às arquiteturas conexionistas existentes e foram considerados bastante satisfatórios com relação aos parâmetros avaliados. No texto são apresentados, também, alguns aspectos teóricos das ciências cognitivas, os fundamentos de redes neurais artificiais, o detalhamento de uma ferramenta de simulação robótica, conclusões, limitações e possíveis trabalhos futuros. / The present work proposes a new artificial neural network model suitable for robotic applications, in special to spatiotemporal tasks and infinite horizon tasks. This model has three characteristics which make it unique and are taken as means to guide its conception: self-organization, temporal representation and constructive learning. The algorithm of self-organizing learning incorporates all the mechanisms that are basic to the self-organization: global competition, local cooperation and selective self-amplification. The neural network is supplied with dynamic properties through a short-term memory. The short-term memory is added in the network structure by means of integrators and differentiators, which are implemented in the input layer of the network. In this approach exists an evident separation of roles: the network is responsible for the non-linearity and the memory is responsible for the time. The automatic construction of the neural network architecture is carried out taking into account habituation units. The habituation unit regulates the growing and the pruning of neurons. The procedure of inclusion, adaptation and removal of synaptic connections is carried out in accordance with competitive hebbian learning technique. In many practical problems, as the ones in the robotic area, self-organization, temporal representation and constructive learning are essential factors to the success of the task. The great difficulty and, at the same time, the main contribution of this work consists in the integration of these technologies in a neural network architecture in an efficient way. Some case studies have been elaborated to validate and, mainly, to determine the potentialities and the limitations of the proposed neural model. The experiments comprised simple tasks of pattern classification and temporal segmentation. Preliminary results have shown the good efficiency of the neural model compared to existing connectionist architectures and they have been considered sufficiently satisfactory with regard to the evaluated parameters. This text also presents some theoretical aspects of the cognitive science area, the fundamentals of artificial neural networks, the details of a robotic simulation tool, the conclusions, limitations and possible future works.