Professional writing students must analyze communications in multiple modalities, on page or screen. This project argues that student analysts benefit from using articulated heuristics, summaries of articles, books, or theories in chart form that remain in the visual field with the communication to be analyzed. Keeping the heuristic in view reduces students' cognitive load by narrowing the search for solution to the categories in the heuristic. These heuristics, often one page or one screen, contain key words, phrases, or questions that allow students to approach analysis from experts' points of view at more than one level of complexity. Students locate instantiations of the categories in the communication analyzed, incorporating the category/instantiation pairs into personal schemas for analysis. As students classify communications, relate parts together and to other communications, and perform operations on the content, they see how communication achieves its meaning and formulate appropriate responses. Rather than rely on one all-purpose heuristic, this dissertation presents a range of heuristics reflecting rhetorical, discourse, linguistic, usability, and visual strategies that enable students to critique both form and function in communication. The heuristics reflect a systematically ordered workplace context, articulate an appropriate and specific theory for the situation, interface with other heuristic systems for depth and efficacy, and instantiate the categories at some helpful secondary level of complexity. To theorize the visual nature of the heuristic chart displays, I employ the semiotic of Charles Sanders Peirce, working through the implications of chart construction as I diagram Peirce's theory of diagrammatic iconicity.

Decisions regarding the mapping of system-on-chip (SoC) components onto a NoC become more difficult with increasing complexity of system design. These complex systems capable of providing multiple functionalities tend to operate in multiple modes of operation. Modeling the system communication in these multimodes aids in efficient system design. This research provides a heuristic that gives a flexible mapping solution of the multimode system communications onto the NoC topology of choice. The solution specifies the immediate neighbors of the SoC components and the routes taken by all communications in the system. We validate the mapping results with a network-on-chip simulator (NoCSim). This thesis also investigates the cost associated with the interfacing of the components to the NoC. With the goal of reducing communication latency, we examine the packetization strategies in the NoC communication. Three schemes of implementations were analyzed, and the costs in terms of latency, and area were projected through actual synthesis.

The number of Institutional Repositories (IRs), such as DalSpace, has been growing in the past few years. However, most IRs are not widely used by the intended end users. Evaluating the user interfaces is an essential part of any process to increase users' acceptance of IRs. There are two foci of this thesis: to evaluate the usability of DalSpace's interface using Nielsen's heuristics to uncover usability problems for development purposes and to examine the differences between user-interface experts and non-experts in uncovering problems with the interface. To apply the heuristics to the interface, I formed user profiles (also known as personas) to represent potential end-users groups. These profiles helped to communicate users' needs, abilities, tasks, and problems. To produce a reliable list of usability problems by applying the heuristic evaluation approach, I examined the impact of expertise on the quality of the results. From the individual heuristic analyses (by both experts and novices), I distilled 66 usability problems classified by severity. Also, the frequency of each violated heuristic was used to assign priority to the uncovered usability problems as well as the severity level. The results of applying the heuristic evaluation show that both experts and non-experts can uncover usability problems. In fact, the ability to find difficult and easy problems was recorded for both types of evaluators. However, experts tend to reveal more serious problems, while novices uncover less severe problems. Interestingly, the best evaluator (who found 21% of the total number of problems) was a novice. Our results indicate that we cannot rely on one evaluator even if the evaluator is an expert. The administrative interface is out of the scope of the thesis; however, the usability of the interface should be examined for improvement purposes. More user profiles should be formed to represent additional user groups for more interfaces including the end user and staff's interfaces. Both results from the user profiles and the list of usability problems will be given as tools to the development team for improvement.

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Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

This study is undertaken to improve the performance of a Chemotherapy Treatment Unit by increasing the throughput of the clinic and reducing the average patients’ waiting time. In order to achieve this objective, a simulation model of this system is built and several scenarios that target matching the arrival pattern of the patients and resources availability are designed and evaluated. After performing detailed analysis, one scenario proves to provide the best system’s performance. The best scenario determines a rational arrival pattern of the patient matching with the nurses’ availability and can serve 22.5% more patients daily. Although the simulation study shows the way to serve more patients daily, it does not explain how to sequence them properly to minimize the average patients’ waiting time. Therefore, an efficient scheduling algorithm was developed to build a scheduling template that minimizes the total flow time of the system.

Political scientists have largely overlooked the issue of effort. It is a seemingly simple concept with great implications for the study of political behavior. With intuition alone we can often classify behaviors as more or less effortful. And many of the behaviors that interest political scientists concern this fundamental concept, but, somehow, we have failed to formally incorporate effort into our theories. Indeed, normatively speaking, citizens will engage the democratic process effortfully, not effortlessly. But what makes a behavior more or less effortful? How does the amount of effort expended in pursuit of a behavior affect the likelihood of actualizing that behavior? To answer these questions I have developed a resource model of political cognition which posits that effortful behaviors are essentially fueled by a limited, but renewable, supply of cognitive resources. In this dissertation I report the results of a series of experiments in which I apply the resource model to collective action behaviors as well as information processing. The results suggest that these behaviors, and mostly likely others as well, are, to a significant degree, dependent upon the sufficient availability of cognitive resources.

This study is undertaken to improve the performance of a Chemotherapy Treatment Unit by increasing the throughput of the clinic and reducing the average patients’ waiting time. In order to achieve this objective, a simulation model of this system is built and several scenarios that target matching the arrival pattern of the patients and resources availability are designed and evaluated. After performing detailed analysis, one scenario proves to provide the best system’s performance. The best scenario determines a rational arrival pattern of the patient matching with the nurses’ availability and can serve 22.5% more patients daily. Although the simulation study shows the way to serve more patients daily, it does not explain how to sequence them properly to minimize the average patients’ waiting time. Therefore, an efficient scheduling algorithm was developed to build a scheduling template that minimizes the total flow time of the system.

Software needs to be adequately tested in order to increase the confidence that the system being developed is reliable. However, testing is a complicated and expensive process. Formal specification based models such as finite state machines have been widely used in system modelling and testing. In this PhD thesis, we primarily investigate fault detection and identification when testing from finite state machines. The research in this thesis is mainly comprised of three topics - construction of multiple Unique Input/Output (UIO) sequences using Metaheuristic Optimisation Techniques (MOTs), the improved fault coverage by using robust Unique Input/Output Circuit (UIOC) sequences, and fault diagnosis when testing from finite state machines. In the studies of the construction of UIOs, a model is proposed where a fitness function is defined to guide the search for input sequences that are potentially UIOs. In the studies of the improved fault coverage, a new type of UIOCs is defined. Based upon the Rural Chinese Postman Algorithm (RCPA), a new approach is proposed for the construction of more robust test sequences. In the studies of fault diagnosis, heuristics are defined that attempt to lead to failures being observed in some shorter test sequences, which helps to reduce the cost of fault isolation and identification. The proposed approaches and techniques were evaluated with regard to a set of case studies, which provides experimental evidence for their efficacy.