Hyperthermia based cancer treatments delivered under various modalities have the potential to become an effective option to eradicate the disease, maintain functionality of infected organs, and minimize complications and relapse. Moreover, hyperthermia therapies are a form of minimally invasive cancer treatment which are key to improving the quality of life post-treatment. Many modalities are available for delivering the heat source. However, the ability to control the energy deposition to prevent damage to adjacent healthy tissue is a limiting factor in all forms of thermal therapies, including cryotherapy, microwave, radio-frequency, ultrasound, and laser. The application of a laser heat source under the guidance of real-time treatment data has the potential to provide unprecedented control over the temperature field induced within the biological domain. The computational infrastructure developed in this work combines a computational model of bioheat transfer based on a nonlinear version of the Pennes equation for heterogeneous media with the precise timing and orchestration of the real-time solutions to the problems of calibration, optimal control, data transfer, registration, finite element mesh refinement, cellular damage prediction, and laser control; it is an example of Dynamic-Data-Driven Applications System (DDDAS) in which simulation models interact with measurement devices and assimilates data over a computational grid for the purpose of producing high-fidelity predictions of physical events. The tool controls the thermal source, provides a prediction of the entire outcome of the treatment and, using intra-operative data, updates itself to increase the accuracy of the prediction. A precise mathematical framework for the real-time finite element solution of the problems of calibration, optimal heat source control, and goal-oriented error estimation applied to the equations of bioheat transfer is presented. It is demonstrated that current finite element technology, parallel computer architecture, data transfer infrastructure, and thermal imaging modalities are capable of inducing a precise computer controlled temperature field within a biological domain. The project thus addresses a set of problems falling in the intersection of applied mathematics, imaging physics, computational science, computer science and visualizations, biomedical engineering, and medical science. The work involves contributions in the three component areas of the CAM program; A, Applicable Mathematics; B, Numerical Analysis and Scientific Computing; and C, Mathematical modeling and Applications. The ultimate goal of this research is to provide the medical community a minimally invasive clinical tool that uses predictive computational techniques to provide the optimal hyperthermia laser treatment procedure given real-time, patient specific data. / text

Namao virus (NV) was associated with mortality in lake sturgeon Acipenser fulvescens reared as part of a conservation stocking program for this endangered species in Manitoba, Canada. The virus itself was large, doubly encapsidated and icosahedral-shaped. Phylogenetic analyses using the major capsid protein showed that NV and other epitheliotropic sturgeon nucleo-cytoplasmic large DNA viruses shared a common evolutionary past and formed a distinct evolutionary lineage within Megavirales. Three PCR tests were developed and their analytical performance was validated for detection of these viruses. Testing of wild sturgeon revealed that NV is endemic in the Nelson River water basin in Manitoba. Bath exposure resulted in transmission of NV to healthy sturgeon. The gills appeared to be the initial site of infection with virus persisting in the head skin tissue for up to 62 days. The molecular tests will be useful tools for disease management in sturgeon conservation stocking programs. / October 2015

ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / High speed real-time data transportation is most important for telemetry systems, especially for large-scale distributed systems. This paper introduces a STDM (Sync Time Division Multiplexing) network structure for data transportation between devices in telemetry systems. The data in these systems is transported through virtual channels between devices. In addition, a proper frame format is designed based on PCM format to meet the needs of synchronization and real-time transportation in large-scale distributed telemetry systems.

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The timely delivery of inter-task real-time messages over a communication network is the key to successfully developing distributed real-time computer systems. These systems are rapidly developed and increasingly used in many areas such as automation industry. This work concentrates on the timed-token Medium Access Control (MAC) protocol, which is one of the most suitable candidates to support real-time communication due to its inherent timing property of bounded medium access time. The support of real-time communication with the timed-token MAC protocol has been studied using a rigorous mathematical analysis. Specifically, to guarantee the deadlines of synchronous messages (real-time messages defined in the timed-token MAC protocol), a novel and practical approach is developed for allocating synchronous bandwidth to a general message set with the minimum deadline (Dmin) larger than the Target Token Rotation Time (TTRT). Synchronous bandwidth is defined as the maximum time for which a node can transmit its synchronous messages every time it receives the token. It is a sensitive paramater in the control of synchronous message transmission and must be properly allocated to individual nodes to guarantee deadlines of real-time messages. Other issues related to the schedulability test, including the required buffer size and the Worst Case Achievable Utilisation (WCAU) of the proposed approach, are then discussed. Simulations and numerical examples demonstrate that this novel approach performs better than any previously published local synchronous bandwidth allocation (SBA) schemes, in terms of its ability to guarantee the real-time traffic. A proper selection of the TTRT, which can maximise the WCAU of the proposed SBA scheme, is addressed. The work presented in this thesis is compatible with any network standard where timed-token MAC protocol is employed and therefore can be applied by engineers building real-time systems using these standards.

Extremely large telescopes (ELTs) are the next generation of ground-based reflecting telescopes of optical wavelengths. ELTs possess an aperture of more than 20 meters and share a number of common features, particularly the use of a segmented primary mirror and the use of adaptive optics systems. In 2005, the European Southern Observatory introduced a new giant telescope concept, named the European Extremely Large Telescope (E-ELT), which is scheduled for operation in 2018. The E-ELT will address key scientific challenges and will aim for a number of notable firsts, including discovering Earth-like planets around other stars in the ``habitable zones'' where life could exist, attempting to uncover the relationship between black holes and galaxies, measuring the properties of the first stars and galaxies, and probing the nature of dark matter and dark energy. In 2009, a feasibility study, conducted by National Instruments, proved the feasibility of the real-time (RT) control system architecture for the E-ELT's nearly 1,000 mirror segments with 3,000 actuators and 6,000 sensors. The goal of the RT control system was to maintain a perfectly aligned field of mirrors at all times with a loop-time of 1 ms. The study assumed a prescribed controller algorithm. This research report prescribes the optimal controller algorithms for large segmented telescopes. In this respect, optimal controller designs for the primary mirror of the E-ELT, where optimality is formulated in the [H-2] and [H-infinity] frameworks are derived. Moreover, the designed controllers are simulated to show that the desired performance metrics are met. / text

published_or_final_version / abstract / toc / Physics / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

Visualization of large scale time-varying volumetric datasets is an active topic of research. Technical limitations in terms of bandwidth and memory usage become a problem when visualizing these datasets on commodity computers at interactive frame rates. The overall objective is to overcome these limitations by adapting the methods of an existing Direct Volume Rendering pipeline. The objective is considered to be a proof of concept to assess the feasibility of visualizing large scale time-varying datasets using this pipeline. The pipeline consists of components from previous research, which make extensive use of graphics hardware to visualize large scale static data on commodity computers. This report presents a diploma work, which adapts the pipeline to visualize flow features concealed inside the large scale Computational Fluid Dynamics dataset. The work provides a foundation to address the technical limitations of the commodity computer to visualize time-varying datasets. The report describes the components making up the Direct Volume Rendering pipeline together with the adaptations. It also briefly describes the Computational Fluid Dynamics simulation, the flow features and an earlier visualization approach to show the system’s limitations when exploring the dataset.

Medizinische Volumenvisualisierung ist ein wertvolles Werkzeug zur Betrachtung von Volumen- daten in der medizinischen Praxis und Lehre. Eine interaktive, stereoskopische und kollaborative Darstellung in Echtzeit ist notwendig, um die Daten vollständig und im Detail verstehen zu können. Solche Visualisierung von hochauflösenden Daten ist jedoch wegen hoher Hardware- Anforderungen fast nur an speziellen Visualisierungssystemen möglich. Remote-Visualisierung wird verwendet, um solche Visualisierung peripher nutzen zu können. Dies benötigt jedoch fast immer komplexe Software-Deployments, wodurch eine universelle ad-hoc Nutzbarkeit erschwert wird. Aus diesem Sachverhalt ergibt sich folgende Hypothese: Ein hoch performantes Remote- Visualisierungssystem, welches für Stereoskopie und einfache Benutzbarkeit spezialisiert ist, kann für interaktive, stereoskopische und kollaborative medizinische Volumenvisualisierung genutzt werden. Die neueste Literatur über Remote-Visualisierung beschreibt Anwendungen, welche nur reine Webbrowser benötigen. Allerdings wird bei diesen kein besonderer Schwerpunkt auf die perfor- mante Nutzbarkeit von jedem Teilnehmer gesetzt, noch die notwendige Funktion bereitgestellt, um mehrere stereoskopische Präsentationssysteme zu bedienen. Durch die Bekanntheit von Web- browsern, deren einfach Nutzbarkeit und weite Verbreitung hat sich folgende spezifische Frage ergeben: Können wir ein System entwickeln, welches alle Aspekte unterstützt, aber nur einen reinen Webbrowser ohne zusätzliche Software als Client benötigt? Ein Proof of Concept wurde durchgeführt um die Hypothese zu verifizieren. Dazu gehörte eine Prototyp-Entwicklung, deren praktische Anwendung, deren Performanzmessung und -vergleich. Der resultierende Prototyp (CoWebViz) ist eines der ersten Webbrowser basierten Systeme, welches flüssige und interaktive Remote-Visualisierung in Realzeit und ohne zusätzliche Soft- ware ermöglicht. Tests und Vergleiche zeigen, dass der Ansatz eine bessere Performanz hat als andere ähnliche getestete Systeme. Die simultane Nutzung verschiedener stereoskopischer Präsen- tationssysteme mit so einem einfachen Remote-Visualisierungssystem ist zur Zeit einzigartig. Die Nutzung für die normalerweise sehr ressourcen-intensive stereoskopische und kollaborative Anatomieausbildung, gemeinsam mit interkontinentalen Teilnehmern, zeigt die Machbarkeit und den vereinfachenden Charakter des Ansatzes. Die Machbarkeit des Ansatzes wurde auch durch die erfolgreiche Nutzung für andere Anwendungsfälle gezeigt, wie z.B. im Grid-computing und in der Chirurgie.