4 resultados para Embedded memories

em QSpace: Queen's University - Canada


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Commemorations are a critical window for exploring the social, political, and cultural trends of a specific time period. Over the past two centuries, the commemorative landscape of Ontario reaffirmed the inclusion/exclusion of particular racial groups. Intended as static markers to the past, monuments in particular visually demonstrated the boundaries of a community and acted as ongoing memorials to existing social structures. Using a specific type of iconography and visual language, the creators of monuments imbued the physical markers of stone and bronze with racialized meanings. As builders were connected with their own time periods and social contexts, the ideas behind these commemorations shifted. Nonetheless, creators were intent on producing a memorial that educated present and future generations on the boundaries of their “imagined communities.” This dissertation considers the carefully chosen iconographies of Ontario’s monuments and how visual symbolism was attached to historical memory. Through the examination of five case studies, this dissertation examines the shifting commemorative landscape of Ontario and how memorials were used to mark the boundaries of communities. By integrating the visual analysis of monuments and related images, it bridges a methodological and theoretical gap between history and art history. This dissertation opens an important dialogue between these fields of study and demonstrates how monuments themselves are critical “documents” of the past.

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Two novel studies examining the capacity and characteristics of working memory for object weights, experienced through lifting, were completed. Both studies employed visually identical objects of varying weight and focused on memories linking object locations and weights. Whereas numerous studies have examined the capacity of visual working memory, the capacity of sensorimotor memory involved in motor control and object manipulation has not yet been explored. In addition to assessing working memory for object weights using an explicit perceptual test, we also assessed memory for weight using an implicit measure based on motor performance. The vertical lifting or LF and the horizontal GF applied during lifts, measured from force sensors embedded in the object handles, were used to assess participants’ ability to predict object weights. In Experiment 1, participants were presented with sets of 3, 4, 5, 7 or 9 objects. They lifted each object in the set and then repeated this procedure 10 times with the objects lifted either in a fixed or random order. Sensorimotor memory was examined by assessing, as a function of object set size, how lifting forces changed across successive lifts of a given object. The results indicated that force scaling for weight improved across the repetitions of lifts, and was better for smaller set sizes when compared to the larger set sizes, with the latter effect being clearest when objects were lifting in a random order. However, in general the observed force scaling was poorly scaled. In Experiment 2, working memory was examined in two ways: by determining participants’ ability to detect a change in the weight of one of 3 to 6 objects lifted twice, and by simultaneously measuring the fingertip forces applied when lifting the objects. The results showed that, even when presented with 6 objects, participants were extremely accurate in explicitly detecting which object changed weight. In addition, force scaling for object weight, which was generally quite weak, was similar across set sizes. Thus, a capacity limit less than 6 was not found for either the explicit or implicit measures collected.

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This paper presents a vision that allows the combined use of model-driven engineering, run-time monitoring, and animation for the development and analysis of components in real-time embedded systems. Key building block in the tool environment supporting this vision is a highly-customizable code generation process. Customization is performed via a configuration specification which describes the ways in which input is provided to the component, the ways in which run-time execution information can be observed, and how these observations drive animation tools. The environment is envisioned to be suitable for different activities ranging from quality assurance to supporting certification, teaching, and outreach and will be built exclusively with open source tools to increase impact. A preliminary prototype implementation is described.

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The work presented in this thesis examines the properties of BPEs of various configurations and under different operating conditions in a large planar LEC system. Detailed analysis of time-lapsed fluorescence images allows us to calculate the doping propagation speed from the BPEs. By introducing a linear array of BPEs or dispersed ITO particles, multiple light-emitting junctions or a bulk homojunction have been demonstrated. In conclusion, it has been observed that both applied bias voltages and sizes of BPEs affected the electrochemical doping from the BPE. If the applied bias voltage was initially not sufficiently high enough, a delay in appearance of doping from the BPE would take place. Experiments of parallel BPEs with different sizes (large, medium, small) demonstrate that the potential difference across the BPEs has played a vital role in doping initiation. Also, the p-doping propagation distance from medium-sized BPE has displayed an exponential growth over the time-span of 70 seconds. Experiments with a linear array of BPEs with the same size demonstrate that the doping propagation speed of each floating BPE was the same regardless of its position between the driving electrodes. Probing experiments under high driving voltages further demonstrated the potential of having a much more efficient light emission from an LEC with multiple BPEs.