Scalable Approach to Uncertainty Quantification and Robust Design of Interconnected Dynamical Systems

Development of robust dynamical systems and networks such as autonomous aircraft systems capable of accomplishing complex missions faces challenges due to the dynamically evolving uncertainties coming from model uncertainties, necessity to operate in a hostile cluttered urban environment, and the distributed and dynamic nature of the communication and computation resources. Model-based robust design is difficult because of the complexity of the hybrid dynamic models including continuous vehicle dynamics, the discrete models of computations and communications, and the size of the problem. We will overview recent advances in methodology and tools to model, analyze, and design robust autonomous aerospace systems operating in uncertain environment, with stress on efficient uncertainty quantification and robust design using the case studies of the mission including model-based target tracking and search, and trajectory planning in uncertain urban environment. To show that the methodology is generally applicable to uncertain dynamical systems, we will also show examples of application of the new methods to efficient uncertainty quantification of energy usage in buildings, and stability assessment of interconnected power networks

Functional and Biomechanical Effects of the Edge-to-Edge Repair in the Setting of Mitral Regurgitation: Consolidated Knowledge and Novel Tools to Gain Insight into Its Percutaneous Implementation

Mitral regurgitation is the most prevalent heart valve disease in the western population. When severe, it requires surgical treatment, repair being the preferred option. The edge-to-edge repair technique treats mitral regurgitation by suturing the leaflets together and creating a double-orifice valve. Due to its relative simplicity and versatility, it has become progressively more widespread. Recently, its percutaneous version has become feasible, and has raised interest thanks to the positive results of the Mitraclip(\uae) device. Edge-to-edge features and evolution have stimulated debate and multidisciplinary research by both clinicians and engineers. After providing an overview of representative studies in the field, here we propose a novel computational approach to the most recent percutaneous evolution of the edge-to-edge technique. Image-based structural finite element models of three mitral valves affected by posterior prolapse were derived from cine-cardiac magnetic resonance imaging. The models accounted for the patient-specific 3D geometry of the valve, including leaflet compound curvature pattern, patient-specific motion of annulus and papillary muscles, and hyperelastic and anisotropic mechanical properties of tissues. The biomechanics of the three valves throughout the entire cardiac cycle was simulated before and after Mitraclip(\uae) implantation, assessing the biomechanical impact of the procedure. For all three simulated MVs, Mitraclip(\uae) implantation significantly improved systolic leaflets coaptation, without inducing major alterations in systolic peak stresses. Diastolic orifice area was decreased, by up to 58.9%, and leaflets diastolic stresses became comparable, although lower, to systolic ones. Despite established knowledge on the edge-to-edge surgical repair, latest technological advances make its percutanoues implementation a challenging field of research. The modeling approach herein proposed may be expanded to analyze clinical scenarios that are currently critical for Mitraclip(\uae) implantation, helping the search for possible solutions

The relation between magnetic and material arms in models for spiral galaxies

Context. Observations of polarized radio emission show that large-scale (regular) magnetic fields in spiral galaxies are not axisymmetric, but generally stronger in interarm regions. In some nearby galaxies such as NGC 6946 they are organized in narrow magnetic arms situated between the material spiral arms. Aims. The phenomenon of magnetic arms and their relation to the optical spiral arms (the material arms) call for an explanation in the framework of galactic dynamo theory. Several possibilities have been suggested but are not completely satisfactory; here we attempt a consistent investigation. Methods. We use a 2D mean-field dynamo model in the no-z approximation and add injections of small-scale magnetic field, taken to result from supernova explosions, to represent the effects of dynamo action on smaller scales. This injection of small scale field is situated along the spiral arms, where star-formation mostly occurs. Results. A straightforward explanation of magnetic arms as a result of modulation of the dynamo mechanism by material arms struggles to produce pronounced magnetic arms, at least with realistic parameters, without introducing new effects such as a time lag between Coriolis force and {\alpha}-effect. In contrast, by taking into account explicitly the small-scale magnetic field that is injected into the arms by the action of the star forming regions that are concentrated there, we can obtain dynamo models with magnetic structures of various forms that can be compared with magnetic arms. (abbrev). Conclusions. We conclude that magnetic arms can be considered as coherent magnetic structures generated by large-scale dynamo action, and associated with spatially modulated small-scale magnetic fluctuations, caused by enhanced star formation rates within the material arms.Comment: 13 pages, 8 figures, accepted for publication to A&

Studies for the Commissioning of the CERN CMS Silicon Strip Tracker

In 2008 the Large Hadron Collider (LHC) at CERN will start producing proton-proton collisions of unprecedented energy. One of its main experiments is the Compact Muon Solenoid (CMS), a general purpose detector, optimized for the search of the Higgs boson and super symmetric particles. The discovery potential of the CMS detector relies on a high precision tracking system, made of a pixel detector and the largest silicon strip Tracker ever built. In order to operate successfully a device as complex as the CMS silicon strip Tracker, and to fully exploit its potential, the properties of the hardware need to be characterized as precisely as possible, and the reconstruction software needs to be commissioned with physics signals. A number of issues were identified and studied to commission the detector, some of which concern the entire Tracker, while some are specific to the Tracker Outer Barrel (TOB): - the time evolution of the signals in the readout electronics need to be precisely measured and correctly simulated, as it affects the expected occupancy and the data volume, critical issues in high-luminosity running; - the electronics coupling between neighbouring channels affects the cluster size and hence the hit resolution, the tracking precision, the occupancy and the data volume; - the mechanical structure of the Rods (the sub-assemblies of the TOB) is mostly made of carbon fiber elements; aluminum inserts glued to the carbon fi ber frame provide efficient cooling contacts between the silicon detectors and the thin cooling pipe, made of a copper-nickel alloy; the different thermal expansion coefficients of the various components induce stresses on the structure when this is cooled down to the operating temperature, possibly causing small deformations; a detailed characterization of the geometrical precision of the rods and of its possible evolution with temperature is a valuable input for track reconstruction in CMS. These and other issues were studied in this thesis. For this purpose, a large scale test setup, designed to study the detector performance by tracking cosmic muons, was operated over several months. A dedicated trigger system was set up, to select tracks synchronous with the fast readout electronics, and to be able to perform a precise measurement of the time evolution of the front-end signals. Data collected at room temperature and at the Tracker operating temperature of -10°C were used to test reconstruction and alignment algorithms for the Tracker, as well as to perform a detailed qualification of the geometry and the functionality of the structures at different temperatures

Embedded dynamic programming networks for networks-on-chip

PhD ThesisRelentless technology downscaling and recent technological advancements in three dimensional integrated circuit (3D-IC) provide a promising prospect to realize heterogeneous system-on-chip (SoC) and homogeneous chip multiprocessor (CMP) based on the networks-onchip (NoCs) paradigm with augmented scalability, modularity and performance. In many cases in such systems, scheduling and managing communication resources are the major design and implementation challenges instead of the computing resources. Past research efforts were mainly focused on complex design-time or simple heuristic run-time approaches to deal with the on-chip network resource management with only local or partial information about the network. This could yield poor communication resource utilizations and amortize the benefits of the emerging technologies and design methods. Thus, the provision for efficient run-time resource management in large-scale on-chip systems becomes critical. This thesis proposes a design methodology for a novel run-time resource management infrastructure that can be realized efficiently using a distributed architecture, which closely couples with the distributed NoC infrastructure. The proposed infrastructure exploits the global information and status of the network to optimize and manage the on-chip communication resources at run-time. There are four major contributions in this thesis. First, it presents a novel deadlock detection method that utilizes run-time transitive closure (TC) computation to discover the existence of deadlock-equivalence sets, which imply loops of requests in NoCs. This detection scheme, TC-network, guarantees the discovery of all true-deadlocks without false alarms in contrast to state-of-the-art approximation and heuristic approaches. Second, it investigates the advantages of implementing future on-chip systems using three dimensional (3D) integration and presents the design, fabrication and testing results of a TC-network implemented in a fully stacked three-layer 3D architecture using a through-silicon via (TSV) complementary metal-oxide semiconductor (CMOS) technology. Testing results demonstrate the effectiveness of such a TC-network for deadlock detection with minimal computational delay in a large-scale network. Third, it introduces an adaptive strategy to effectively diffuse heat throughout the three dimensional network-on-chip (3D-NoC) geometry. This strategy employs a dynamic programming technique to select and optimize the direction of data manoeuvre in NoC. It leads to a tool, which is based on the accurate HotSpot thermal model and SystemC cycle accurate model, to simulate the thermal system and evaluate the proposed approach. Fourth, it presents a new dynamic programming-based run-time thermal management (DPRTM) system, including reactive and proactive schemes, to effectively diffuse heat throughout NoC-based CMPs by routing packets through the coolest paths, when the temperature does not exceed chip’s thermal limit. When the thermal limit is exceeded, throttling is employed to mitigate heat in the chip and DPRTM changes its course to avoid throttled paths and to minimize the impact of throttling on chip performance. This thesis enables a new avenue to explore a novel run-time resource management infrastructure for NoCs, in which new methodologies and concepts are proposed to enhance the on-chip networks for future large-scale 3D integration.Iraqi Ministry of Higher Education and Scientific Research (MOHESR)

Recent advances in petri nets and concurrency

CEUR Workshop Proceeding

Temporal workload-aware replicated partitioning for social networks

Most frequent and expensive queries in social networks involve multi-user operations such as requesting the latest tweets or news-feeds of friends. The performance of such queries are heavily dependent on the data partitioning and replication methodologies adopted by the underlying systems. Existing solutions for data distribution in these systems involve hashor graph-based approaches that ignore the multi-way relations among data. In this work, we propose a novel data partitioning and selective replication method that utilizes the temporal information in prior workloads to predict future query patterns. Our method utilizes the social network structure and the temporality of the interactions among its users to construct a hypergraph that correctly models multi-user operations. It then performs simultaneous partitioning and replication of this hypergraph to reduce the query span while respecting load balance and I/O load constraints under replication. To test our model, we enhance the Cassandra NoSQL system to support selective replication and we implement a social network application (a Twitter clone) utilizing our enhanced Cassandra. We conduct experiments on a cloud computing environment (Amazon EC2) to test the developed systems. Comparison of the proposed method with hash- and enhanced graph-based schemes indicate that it significantly improves latency and throughput