Robotic motion planning aspires to match the ease and efficiency with which humans move through and interact with their environment. Yet state of the art robotic planners fall short of human abilities; they are slower in computation, and the results are often of lower quality. One stumbling block in traditional motion planning is that points and paths are often considered in isolation. Many planners fail to recognize that substantial shared information exists among path alternatives. Exploitation of the geometric and topological relationships among path alternatives can therefore lead to increased efficiency and competency. These benefits include: better-informed path sampling, dramatically faster collision checking, and a deeper understanding of the trade-offs in path selection. In path sampling, the principle of locality is introduced as a basis for constructing an adaptive, probabilistic, geometric model to influence the selection of paths for collision test. Recognizing that collision testing consumes a sizable majority of planning time and that only collision-free paths provide value in selecting a path to execute on the robot, this model provides a significant increase in efficiency by circumventing collision testing paths that can be predicted to collide with obstacles. In the area of collision testing, an equivalence relation termed local path equivalence, is employed to discover when the work of testing a path has been previously performed. The swept volumes of adjoining path alternatives frequently overlap, implying that a continuum of intermediate paths exists as well. By recognizing such neighboring paths with related shapes and outcomes, up to 90% of paths may be tested implicitly in experiments, bypassing the traditional, expensive collision test and delivering a net 300% boost in collision test performance. Local path equivalence may also be applied to the path selection problem in order to recognize higher-level navigation options and make smarter choices. This thesis presents theoretical and experimental results in each of these three areas, as well as inspiration on the connections to how humans reason about moving through spaces.

A real-time system is a system such that the correctness of operations depends not only on the logical results, but also on the time at which these results are available. A fundamental problem in designing real-time systems is to analyze response time of operations, which is defined as the time elapsed from the moment when the operation is requested to the moment when the operation is completed. Response time analysis is challenging due to the complex dynamics among operations. A common technique is to study response time under worst-case scenario. However, using worst-case response time may lead to the conservative real-time system designs. To improve the real-time system design, we analyze the non-worst-case response time of operations and apply these results in the design process. The main contribution of this thesis includes mathematical modeling of real-time systems, calculation of non-worst-case response time, and improved real-time system design. We perform analysis and design on three common types of real-time systems as the real-time computing system, real-time communication network, and real-time energy management. For the real-time computing systems, our non-worst-response time analysis leads a necessary and sufficient online schedulability test and a measure of robustness of real-time systems. For the real-time communication network, our non-worst-response time analysis improves the performance for the model predictive control design based on the real-time communication network. For the real-time energy management, we use the non-worst-case response time to check whether the micro-grid can operate independently from the main grid.

Toxic cyanobacterial blooms constitute a threat to the safety and ecological quality of aquatic environments worldwide. Cyclic hepatotoxin, especially microcystin, is the most widely occurring of the cyanotoxins. The aim of this study was to identify the cyanobacterial genotypes present including how many toxic genotypes were present in two North American lakes and one African Lake. All three lakes are prone to cyanobacterial blooms and were sampled in 2005 and 2006: Lake Ontario (Bay of Quinte, Canada), Lake Erie (Maumee Bay, Canada) and Lake Victoria (Nyanza Gulf, Kenya). The cyanobacterial genotypic community was assessed using DNA based analyses of the hypervariable V3 region of the 16S rRNA gene. In addition, the aminotransferase (AMT) domain in modules mcyE and ndaF of the microcystin and nodularin gene cluster respectively was used to detect the presence of hepatotoxic genotypes. Denaturing gradient gel electrophoresis (DGGE) results from this study suggested that hepatotoxin producers were present in all study sites sampled and were most likely members of the genus Microcystis. This study was the first to report the potential for microcystin production in the in-shore and off-shore open lake of Nyanza Gulf in Kenya. A seasonal study of the Bay of Quinte and Maumee Bay showed differences in the cyanobacterial genotypic community from early to late summer. In addition, the cyanobacterial genotypic community from the Bay of Quinte differed from 2005 to 2006 and quantification of the North American samples revealed an increase in cyanobacterial cells from early to late summer. The Bay of Quinte saw relatively no change in hepatotoxic cells from early to late summer but in Maumee Bay hepatotoxic cells increased from undetectable in early summer to dominating the cyanobacterial community by late summer. This study demonstrated the use of DGGE and qPCR of the 16S rRNA-V3 and AMT gene region in monitoring the cyanobacterial community of waterbodies susceptible to toxic cyanobacterial blooms.

I dagens samhälle används internet för kommunikation mellan människor runtom i världen. Det första videosamtalet gjordes runt år 1940 och det är dags fören utveckling, där 3D är något som skulle kunna göra videomöten mer verkliga.För att möjliggöra detta så konstruerades ett system som skulle kunna ta in datafrån olika time-of-flight- och färgkameror och en ljudenhet. Denna data ska sedankomprimeras och sändas över internet för att kunna spelas upp på någonannans 3D-skärm. För att samtalet inte ska kännas fördröjt måste samtliga delartillsammans ske inom realtid. De utvecklingsmetoder som har använts är parprogrammeringoch en variant utav testdriven utveckling. Systemet har utvärderatsutifrån tidmätningar, bildkvalitet och datastorlek för att hitta en bra balansmellan tid och kvalitet. Systemet konstruerades med fem delar: insamling avbilder och ljud, bilduppskalning, komprimering och avkomprimering, internetöverföringsamt rendering. Resultatet visade att de delar som berörs av datastorlekoch bildkvalitet kunde uppnå en bra balans mellan tid och kvalitet. Dockkunde inte alla mål uppnås då vissa delar tog upp mer tid än realtidsmålet samtatt alla delar inte han konstrueras. Eftersom systemet byggdes upp modulärt såkan de delar som inte uppnådde målen förbättras eller bytas ut. Utifrån resultatetkunde sedan lösningsförslag ges för att förbättra resultaten för en eventuell vidareutveckling. / In todays society internet is used for communication between each other aroundthe world. The first video call was made around the year 1940 and it is time fora development, where 3D is something that can make video calls more real. Tomake this possible a system was constructed that would be able to get data fromdifferent time-of-flight cameras and color cameras and audio devices. That datashould later on be compressed and transmitted over internet to be able to play iton someone else’s 3D-display. To prevent the feeling of delay in the call, allparts together must happen in real time. The development methods that havebeen used is pair programming and a variation of test-driven development. Thesystem has been evaluated by time messurements, image quality and data sizeto find a good balance between time and quality. The system was constructedby five parts: capturing of images and audio, image upscaling, compression anddecompression, network streaming and also rendering. The result showed thatthe parts affected by data size and image quality could achieve a good balancebetween time and quality. However, all goals could not be achieved becausesome parts where too slow for the real time goal to be achieved and also someparts could not be constructed in time. Since the system was built up modularlythe parts that did not achieve the goals can be improved or replaced. Based onthe results, solution proposals was made to improve the results for a possiblefurther development.

Scheduling of aperiodic and independent tasks in hard real-time symmetric multiprocessing systems is an NP-complete problem that is often solved using heuristics like particle swarm optimization (PSO). The performance of these class of heuristics, known as evolutionary algorithms, are often evaluated based on the number of iterations it takes to find a solution. Such metrics provide limited information on how the algorithm reaches a solution and how the process could be accelerated. This thesis presents a methodology to analyze the trajectory formed by candidate solutions in order to analyze them in both the time and frequency domains at a single scale. The analysis entails (i) the impact of different parameters for the PSO algorithm, and (ii) the evolutionary processes in the swarm. The work reveals that particles have a directed movement towards a solution during a transient phase, and then enter a steady state where they perform an unguided local search. The scheduling algorithm presented in this thesis uses a variation of the minimum total tardiness with cumulative penalties cost function, that can be extended to suit different system needs. The experimental results show that the scheduler is able to distribute tasks to meet the real-time deadlines over 1, 2, and 4 processors and up to 30 tasks with overall system loads of up to 50\% in fewer than 1,000 iterations. When scheduling greater loads, the scheduler reaches local solutions with 1 to 2 missed deadlines, while larger tasks sets take longer to converge. The trajectories of the particles during the scheduling algorithm are examined as a means to emphasize the impact of the behaviour on the application performance and give insight into ways to improve the algorithm for both space and terrestrial applications.

OBJECTIVES: Measles and rubella are nationally notifiable, vaccine-preventable diseases targeted for elimination by the Pan American Health Organization (PAHO). To support national and international elimination efforts, surveillance optimization is important to ensure rapid case detection, document endemic transmission interruption, identify susceptible populations and inform immunization strategies. While current national surveillance captures confirmed-case data, its performance cannot be assessed using PAHO-recommended surveillance indicators as suspect-case investigation data are required for their estimation. In Canada, the investigation of clinically-suspect measles-like illness (MLI) is highly dependent on laboratory evidence, providing an opportunity to use laboratory data to estimate MLI investigation rates. The Measles and Rubella Surveillance (MARS) pilot project was developed to address existing surveillance challenges with the central hypothesis that (I) ‘it is feasible to develop and implement a real‐time, web‐based measles and rubella surveillance system in the Canadian setting’, and the following sub‐hypotheses: (II) ‘implementation of real‐time surveillance in MARS pilot provinces will result in increased timeliness of national measles and rubella surveillance when compared with established confirmed-case surveillance’, and (III) ‘it is possible to use augmented laboratory data to estimate the performance of national measles and rubella surveillance using adapted PAHO indicators’. METHODS: A MARS application was designed to support centralized real-time measles/ rubella investigation reporting and alerting with integration of non-nominal laboratory and epidemiological data, then developed and piloted using the web-based Canadian Network for Public Health Intelligence platform in British Columbia, Alberta and Newfoundland from June/2011-May/2012. Pre- and post-pilot laboratory surveys were conducted to retrospectively assess national surveillance performance in ‘outbreak’ and ‘non-outbreak’ settings during the 2005‐2011 and pilot years using various surveillance indicators and attributes. Measles IgM serology testing was used as a laboratory-based proxy for MLI investigation to support indicator estimation. RESULTS: Real-time, integrated surveillance was successfully implemented in MARS pilot provinces as modeled within the context of established reporting roles, and surveillance indicators and attributes were estimated using augmented laboratory data. MARS surveillance was more timely than confirmed-case surveillance, and real-time MARS reports exceeded all laboratory-related PAHO targets evaluated: 100% met ‘sample collection’ and ‘receipt’ timelines, and 91.7% met ‘result' timelines (Targets:≥80%); 99.8% of all MLI investigations were discarded (Target:≥95%). A national ‘non-outbreak’ baseline rate of 14 MLI investigations/100 000 population was estimated, whereas MARS pilot sites averaged 22 MLI investigations/100 000 population during the pilot year. While ‘non-outbreak’ investigation rates varied between provinces, all annual provincial and national rates estimated for the 2005‐2011 and MARS pilot years exceeded the PAHO investigation target of ≥2 suspected cases/100 000 population in settings attempting elimination. CONCLUSIONS: The MARS model supported more timely and integrated national measles and rubella surveillance, and enabled indicator‐based performance assessment. Results underscore the importance of laboratory data when evaluating and documenting surveillance performance to support elimination efforts. Consideration should be given to national MARS implementation and its use as a model adaptable to the case-based surveillance of other nationally notifiable diseases.

This dissertation will present several novel techniques that use cooperation and diversity to improve the performance of multihop Wireless Sensor Networks, as measured by throughput, delay, and reliability, beyond what is achievable with conventional error control technology. We will investigate the applicability of these new technologies to Wireless Body Area Networks (WBANs) an important emerging class of wireless sensor networks. WBANs, which promise significant improvement in the reliability of monitoring and treating people's health, comprise a number of sensors and actuators that may either be implanted in vivo or mounted on the surface of the human body, and which are capable of wireless communication to one or more external nodes that are in close proximity to the human body. Our focus in this research is on enhancing the performance of WBANs, especially for emerging real-time in vivo traffic such as streaming real-time video during surgery. Because of the nature of this time-sensitive application, retransmissions may not be possible. Furthermore, achieving minimal energy consumption, with the required level of reliability is critical for the proper functioning of many wireless sensor and body area networks. Additionally, regardless of the traffic characteristics, the techniques we introduce strive to realize reliable wireless sensor networks using (occasionally) unreliable components (wireless sensor nodes). To improve the performance of wireless sensor networks, we introduce a novel technology Cooperative Network Coding, a technology that synergistically integrates the prior art of Network Coding with Cooperative Communications. With the additional goal of further minimizing the energy consumed by the network, another novel technology Cooperative Diversity Coding was introduced and is used to create protection packets at the source node. For representative applications, optimized Cooperative Diversity Coding or Cooperative Network Coding achieves ≥ 25% energy savings compared to the baseline Cooperative Network Coding scheme. Cooperative Diversity Coding requires lees computational complexity at the source node compared to Cooperative Network Coding. To improve the performance and increase the robustness and reliability of WBANs, two efficient feedforward error-control technologies, Cooperative Network Coding (CDC) and Temporal Diversity Coding (TDC), are proposed. Temporal Diversity Coding applies Diversity Coding in time to improve the WBAN's performance. By implementing this novel technique, it is possible to achieve significant improvement (50%) in throughput compared to extant WBANs. An example of an implementation of in vivo real-time application, where TDC can improve the communications performance, is the MARVEL (Miniature Anchored Robotic Videoscope for Expedited Laparoscopy) research platform developed at USF. The MARVEL research platform requires high bit rates (100 Mbps) for high-definition transmission. Orthogonal Frequency Division Multiplexing (OFDM), a widely used technology in fourth generation wireless networks (4G) that achieves high transmission rates over dispersive channels by transmitting serial information through multiple parallel carriers. Combining Diversity Coding with OFDM (DC-OFDM) promises high reliability communications while preserving high transmission rates. Most of the carriers transport original information while the remaining (few) carriers transport diversity coded (protection) information. The impact of DC-OFDM can extend far beyond in vivo video medical devices and other special purpose wireless systems and may find significant application in a broad range of ex vivo wireless systems, such as LTE, 802.11, 802.16.

Increased reactive oxygen species (ROS) have been reported to be at the centre of various diseases. Although several reports have implicated elevated levels of ROS in the pathogenesis of diabetes mellitus, the early detection of ROS is still not attainable. This limitation causes difficulty in the early diagnosis of ROS related disorders. The presence of high levels of ROS was reported to result in differential expression of antioxidant genes involved in protecting cells from their deleterious effects. Among the antioxidant genes that are expressed, it was postulated that expression of metallothioneins (MTs) are also induced. MTs are low molecular weight, cysteine-rich proteins involved in metal homeostasis and reported to harbour antioxidant function. The aim of this investigation was to explore MTs as biomarkers for elevated levels of ROS in whole blood of type 2 diabetic (T2D) individuals. The level of ROS in diabetic, non-diabetic as well as individuals at risk of developing T2D was determined via the use of biochemical assays. Real-Time PCR was utilised to analyse the expression of MTs and the presence of MT proteins was analysed via the ELISA. In this study it was observed that diabetic individuals had elevated levels of ROS. However, no significant difference in the expression of MTs and the presence of MT proteins between the diabetic and non-diabetic individuals was observed. In vitro experimental conditions indicated that MT expression is induced by elevated levels of ROS. In pathological conditions the ROS-dependent induction of MT expression needs to be elucidated further. It therefore can be suggested that MTs can not yet be utilised as biomarkers for the detection of elevated levels of ROS in pathological conditions with ROS aetiology. This investigation also highlights the fact that blood is not an optimal medium in which this objective can be attained. / Thesis (Ph.D. (Biochemistry))--North-West University, Potchefstroom Campus, 2005.

As demand for real-time image processing increases, the need to improve the efficiency of image processing systems is growing. The process of image segmentation is often used in preprocessing stages of computer vision systems to reduce image data and increase processing efficiency. This dissertation introduces a novel image segmentation approach known as leap segmentation, which applies a flexible definition of adjacency to allow groupings of pixels into segments which need not be spatially contiguous and thus can more accurately correspond to large surfaces in the scene. Experiments show that leap segmentation correctly preserves an average of 20% more original scene pixels than traditional approaches, while using the same number of segments, and significantly improves execution performance (executing 10x - 15x faster than leading approaches). Further, leap segmentation is shown to improve the efficiency of a high-level vision application for scene layout analysis within 3D scene reconstruction. The benefits of applying image segmentation in preprocessing are not limited to single-frame image processing. Segmentation is also often applied in the preprocessing stages of video analysis applications. In the second contribution of this dissertation, the fast, single-frame leap segmentation approach is extended into the temporal domain to develop a highly-efficient method for multiple-frame segmentation, called video leap segmentation. This approach is evaluated for use on mobile platforms where processing speed is critical using moving-camera traffic sequences captured on busy, multi-lane highways. Video leap segmentation accurately tracks segments across temporal bounds, maintaining temporal coherence between the input sequence frames. It is shown that video leap segmentation can be applied with high accuracy to the task of salient segment transformation detection for alerting drivers to important scene changes that may affect future steering decisions. Finally, while research efforts in the field of image segmentation have often recognized the need for efficient implementations for real-time processing, many of today’s leading image segmentation approaches exhibit processing times which exceed their camera frame periods, making them infeasible for use in real-time applications. The third research contribution of this dissertation focuses on developing fast implementations of the single-frame leap segmentation approach for use on both single-core and multi-core platforms as well as on both high-performance and resource-constrained systems. While the design of leap segmentation lends itself to efficient implementations, the efficiency achieved by this algorithm, as in any algorithm, is can be improved with careful implementation optimizations. The leap segmentation approach is analyzed in detail and highly optimized implementations of the approach are presented with in-depth studies, ranging from storage considerations to realizing parallel processing potential. The final implementations of leap segmentation for both serial and parallel platforms are shown to achieve real-time frame rates even when processing very high resolution input images. Leap segmentation’s accuracy and speed make it a highly competitive alternative to today’s leading segmentation approaches for modern, real-time computer vision systems.

Group A rotaviruses are a major cause of acute gastroenteritis in children. Almost all children are infected by the age of 5 years old. Rotavirus disease causes around 600,000 deaths per year. VP4 (P) and VP7 (G) genotypes were analyzed for prevalence and potential antigenicity, as they are known to elicit a neutralizing antibody response during infection. This study predicted the effectiveness of two recently licensed rotavirus vaccines based on Canadian surveillance. 271 out of 348 diarrhea samples from 8 paediatric hospital were successfully genotyped by PCR. Canadian rotavirus genotypes were found to be mostly G1P[8] followed by G3P[8], G2P[4], G9P[8], G4P[8], and G9P[4], between 2007 and 2010. Reassortment and motif analysis was done with a subset of rotavirus-positive samples. There were no unusual reassortment events found in Canadian strains. Variations amongst strains were commonly genotype-specific, but otherwise rare. In conclusion, rotavirus vaccine escape is presently unlikely amongst Canadian strains.