Objective: The increased survival rate amongst female breast cancer survivors creates a need for an understanding of chronic disability after surgery. The objective of this study is to explore the association between impairments (e.g., pain, mobility, strength) and the personality trait, fear of physical activity, and chronic daily activity limitations for women who had their surgery at least six months prior to the study. Hypothesis: The study hypothesis is that women with high levels of physical impairments and the personality trait of fear of physical activity will also have higher levels of daily activity limitations six months or more after their breast cancer surgery. Design: A cross-sectional design. Outcome Measures: Disabilities of Shoulder, Arm, and Hand (DASH), Visual Analog Scale for Pain (VAS-Pain), Fear Avoidance Belief Questionnaire – Physical Activity (FABQ-PA), and objective measures of shoulder mobility and strength. Participants: Women who had been diagnosed and undergone surgery for breast cancer, stage 1-3. They must have had their surgery at least six months previously and have completed chemotherapy or radiation therapy. Both English- and French-speaking women from the Ottawa-Gatineau region were eligible. Results: Data from twelve women were analysed with a mean age of 58.0±8.9 years and post-operative time of 4.0± 2.8 years. DASH scores mean was 12.2 ± 11.38. VAS-Pain (rs=0.819; p<.001), FABQ-Physical Activity (rs=0.746; p<.005) were significantly associated with DASH score, whereas non-significant associations were found with supraspinatus strength (rs = 0.182; p < .572) or infraspinatus strength (rs=0.553; p<.062) using the Spearman Rho test. Also, no significant relationships were observed between range of motion (hand-behind-back; p =.366; hand-behind-head; p=.390) and DASH scores using a Kruskal-Wallis test. Conclusion: The results of this exploratory study suggest that the reported daily activity limitations of women who have had breast cancer surgery may be related to the participant pain perception and/or fear of physical activity.

Secure wireless communications among sensor nodes is critical to the deployment of wireless sensor networks. However, resource limited sensor nodes cannot afford complex cryptographic algorithms. In this thesis, we propose a low complexity and energy efficient reconfigurable feedback shift register (RFSR) stream cipher, link layer encryption framework RSec and authentication protocol RAuth. RFSR adds one new dimension, reconfigurable cipher structure, to the existing stream ciphers. The proposed RFSR is implemented on a field programmable gate array platform. Simulation results show that much lower power consumption, delay and transmission overhead are achieved compared to the existing microprocessor based cipher implementations. The RSec framework utilizes RFSR ciphers to guarantee message confidentiality. By comparing with other encryption frameworks in terms of energy efficiency, RSec achieves the best benchmark. The RAuth protocol is designed on top of RFSR and RSec. It provides excellent authentication speed and security level by comparing with other authentication protocols. / Graduate / 0544 / 0984 / zggyzz@gmail.com

Young children with Autism Spectrum Disorder (ASD) experience significant delays in their fundamental motor skills (FMS) yet, FMS are virtually ignored in the intervention literature as traditional therapies focus on the core challenges in the social, communicative, and behavioural domains. This study sought to examine the effectiveness of a FMS intervention at improving the motor skills, adaptive behaviour, and social skills of 4 year old children with ASD. Motor Outcomes (Manuscript 1): Results demonstrated significant improvements in motor skills following the intervention; these improvements were retained at the 6-week follow-up. Adaptive Behaviour and Social Skill Outcomes (Manuscript 2): Results demonstrated individual gains in adaptive behaviour and social skills; although no significant group improvements were found. Conclusion: The results of this study suggest that a FMS intervention can be effective at improving motor skills, and may result in individual behavioural improvements. These findings warrant further research with a larger sample.

Parallel robotic manipulators are a specific type of robot that has multiple limbs which are ultimately connected to a moving body. Within this regime, there are several sub-classes of robots characterized by certain inherent traits. Common to all sub-classes is the ability to articulate the moving platform by actuating each of the limbs. In general, it has been shown that these types of robotic manipulators possess several types of advantageous properties. Some of these properties are: good dynamic character, high stiffness, high precision, large payload to weight ratio, and high speed. Flexible and reconfigurable manufacturing regimes are new manufacturing system paradigms that aim at achieving cost-effective and rapid system changes. Essentially, a system classified as flexible or reconfigurable would be one that is adaptive to change in the market without the need to re-design or re-develop its components. The advantage of such a system is in theory very large. To date, there has been some enhancements made in the area, however there are still many open aims and possible improvements to be investigated. Much of which aims at furthering the concepts from theory to practical applications. The main objective of this dissertation is to enhance the knowledge base in flexible and reconfigurable systems through parallel robotics. Specifically, by utilizing new ideas in parallel robotics tailored to these manufacturing regimes, significant improvements in the knowledge base are attained. These can be classified under one specific regime of parallel robotics and further categorized as passive, semi-active, and active (adaptive). This thesis first focuses on a new design methodology related to flexible and reconfigurable manufacturing. Essentially, the method proposes a systematic approach to recon figure the dynamic properties of robotic devices for various functional requirements that would be part of a flexible manufacturing situation. The method is tested on an example structure and results indicate that the proposed reconfiguration method outperforms existing devices. Next, this dissertation focuses on the design of new robotic architectures that are more adaptive. Specifically, the goal is to achieve structures that can be adaptive in real-time. Existing structures are only reconfigurable passively and need to stop operation in order to reconfigure manually. To this end, a hybrid structure that is semi-active reconfigurable is first investigated. It is dubbed the ReSl-Bot. A complete engineering analysis and design is conducted illustrating its properties. To take this one step further, a novel class of hybrid adaptive parallel robots is then proposed. A 6-DOF robot belonging to this class called the HAPM mk.1 is studied in detail. It is effectively shown that this novel design has the ability to adapt properties actively. This type of adaption could be used for the performance enhancement in many applications, particularly for flexible manufacturing. Properties such as DOF, stiffness, dexterity, precision, kinetics, energy consumption, backlash, etc. could potentially be altered for varying applications and requirements. Notably, a complete theoretical analysis is conducted, ending with analytical dynamics and control.

The developing discipline of Food Crime requires the analysis of food safety responsibility from a critical structural perspective. Analyzing the Canadian dairy industry, this project seeks to answer how the legal definition of food safety impacts the production practices of farmers, and where farmers place the burden of food safety responsibility, while partially testing institutional anomie theory. A legal discourse analysis of food safety law in Canada is performed to contextualize individual interviews with six active family-farmers in rural southern Ontario in order to determine how dairy farmers experience food safety legislation. As hypothesized, farmers experience food safety law through forms of disempowerment and alienation involving dairy production products, leading to a partial displacement of responsibility for safe food. The ideas of institutional anomie theory were insignificant or inconclusive for these case studies. More research is required to determine potential policy implications concerning the safety of Canadian food.

Wireless Sensor Network routing protocols rely on the estimation of the quality of the links between nodes to determine a suitable path from the data source nodes to a data-collecting node. Several link estimators have been proposed, but most of these use only one link property. Fuzzy logic based link quality estimators have been recently proposed which consider a number of link quality metrics. The fuzzification of crisp values to fuzzy values is done through membership functions. The shape of the fuzzy link quality estimator membership functions is primarily performed leveraging qualitative knowledge and an improper assignment of fuzzy membership functions can lead to poor route selection and hence to unacceptable packet losses. This thesis evaluated the Channel Quality membership function of, an existing fuzzy link quality estimator and it was seen that this membership function didn???t perform as well as expected. This thesis presents an experimental approach to determine a suitable Channel Quality fuzzy membership function based on varying the shape of the fuzzy set for a multipath wireless sensor network scenario and choosing an optimum shape that maximizes the Packet Delivery Ratio of the network. The computed fuzzy set membership functions were evaluated against an existing fuzzy link quality estimator under more complex scenarios and it is shown the performance of the experimental refined membership function was better in terms of packet reception ratio and end to end delay.The fuzzy link quality estimator was applied in WiseRoute (a simple converge cast based routing protocol) and shown that this SNR based fuzzy link estimator performed better than the original implemented RSSI based link quality used in WiseRoute.

Imaging and image processing have been used in variety of applications, such as medical, astronomy, forensic, and industry. Numerous techniques have been proposed to solve speci c problems faced in particular applications which are comprised of a series of processes such as, image enhancement, ltering, segmentation, representation, and recognition. However, there is no a universal algorithm which can be applied to variant image modalities with corresponding applications. With the aim of learning image processing tasks, as supervised learning techniques, we can develop e ective algorithms which are image and task oriented. Learning image processing comprises two main phases, namely: training and testing phases. During training phase, the algorithm has the capability of discovering and adjusting an optimum transformation function or optimal mathematical morphology chain by utilizing a user-prepared ground-truth (gold) sample. Later on, in testing phase, the obtained transform function of morphological chain is applied to untrained test images. The current thesis has three main parts as follows. In the rst part, genetic programming (GP) is employed to obtain an optimum transformation function. The GP utilizes one user-prepared gold sample to learn from. The magni cent feature of this method is that it does not require a prior knowledge or large training set to learn from. The performance of the proposed approach has been examined on 147 X-ray lung images. The results for image thresholding (i.e., Otsu's method) after applying optimal transformation are promising. In the second part, an optimum mathematical morphology (MM) chain is obtained by applying GP to localize the object of interest in a binary image. Morphology operations use 27 regular structuring elements along with commonly used morphological operations (i.e., erosion, dilation, opening, and closing) to build an optimal MM chain. The obtained chains are tested against challenging test cases, such as, object translation, scaling, and rotation. In the third part, a hybrid genetic programming - di erential evolutionary (GP-DE) algorithm is proposed to optimize not only the morphology chain but also the utilized structuring elements. GP as an outer layer optimizer is responsible to optimize the morphology chain while the di erential evolutionary (DE) as an inner layer optimizer optimizes the structure elements. Similarly in the testing phase, the obtained morphology chain is applied on test images. In term of utilized test images, the two test cases have been employed : synthesis and music note images. The results indicate that the proposed method is able to locate the object of interest. For the music note images, the proposed approach is able to extract the head notes, sta s, and vertical lines correctly. The training phase is iii time consuming, but it is acceptable; because one time training is required to obtain an optimal chain for a speci c image processing task.

This thesis presents a method for a small, inexpensive mobile robot equipped with a single high resolution scintillation detector to quickly survey an area and convey information about local sources of gamma radiation to a remote human operator. This is achieved by surrounding the detector with a lead sheath that blocks all gamma rays except those incident along the detector???s axial direction. A horizontal scan is performed by rotating the detector and a directional profile of gamma radiation is constructed. In addition a visual panorama of the local area is assembled using a camera mounted on the detector. A plot of the detector signal versus angle is then overlaid on top of the visual panorama and visible peaks clearly indicate the direction of local gamma radiation sources. Moreover, measuring the energy spectrum of gamma rays in each direction produces a 2D count frequency histogram where distinct peaks indicate the energy and direction of local gamma ray sources allowing the identification of different radio-isotopes.

Taking into account the expected increase in global energy demands and increasing climate change issues, there is a pressing need to develop new environmentally sustainable energy systems. Nuclear energy will play a major role in being part of the energy mix since it offers a relatively clean, safe and reliable source of electrical energy. However, opportunities for building new generation nuclear systems will depend on their economic and safety attractiveness as well as their flexibility in design to adapt in different countries and situations. Keeping these objectives in mind, a framework for international cooperation was set forth in a charter of Generation IV International Forum (GIF) (GIF Charter, 2002) and six design concepts were selected for further development. To achieve high thermal efficiencies of up to 45 ??? 50%, the use of SuperCritical Fluids (SCFs) as working fluids in heat transfer cycles is proposed Generation IV designs. An important aspect towards development of SCF applications in novel Gen IV Nuclear Power Plant (NPP) designs is to understand the thermodynamic behavior and prediction of Heat Transfer Coefficients (HTCs) at supercritical (SC) conditions. In addition to the nuclear power industry applications; SCFs are also expected to play a vital role in a number of other important technologies such as refrigeration systems, and geothermal systems, to name a few. Given the potential for vast number of applications of SCFs in industry, the objective of this work was to gain an understanding on the behavior of SCFs and to develop a fundamental knowledge of the heat-transfer processes and correlations for SC Water and SC CO2 flowing in bare circular tubes. Experimental datasets for SC Water and SC CO2 were compiled and used to obtain a basic 1-D empirical correlation that can predict HTC in bare circular tubes during the transient phases. The accuracy of these correlations was also analyzed using statistical techniques. Limitations and applications for 1-D correlations are discussed as well. The new correlations showed promising results for HTC and Tw calculations for the reference dataset with uncertainty of about ??25% for HTC values and about ??10-15% for the calculated wall temperature.

Wireless Sensor Networks (WSNs) are typically used to monitor specific phenomena and gather the data to a gateway node, where the data is further processed. WSNs nodes have limited power resources, which require developing power efficient systems. Additionally, reaching the nodes after a deployment to correct any design flaws is very challenging due the distributed nature of the nodes. The current development of WSNs occurs at the coding layer, which prevent the design from going through a typical software design process. Designing and analyzing the software modules of a WSN system at a higher abstraction layer than at the coding level will enable the designer of a WSN to fix any design errors and improve the system for power consumption at an early design stage, before the actual deployment of the network. This thesis presents multiple Unified Modeling Language (UML) design patterns that enable the designer to capture the structure and the behavior of the design of a WSN at higher abstraction layers. The UML models are developed based on these design patterns that are capable of early validation of the functional requirements and the power consumption of the system hardware resources by leveraging animation and instrumentation of the UML diagrams. To support the analysis of power consumption of the communication components of a WSN node, the Avrora network simulator was integrated with the UML design environment such that designer is able to analyze the power consumption analysis of the communication process at the UML layer. The UML and the Avrora simulation integration is achieved through developing a code generator that produces the necessary configuration for Avrora simulator and through parsing the simulator results. The methodology presented in this thesis is evaluated by demonstrating the power analysis of a typical collector system.