Whole wafer magnetostriction metrology for magnetic films and multilayers

The requirements for metrology of magnetostriction in complex multilayers and on whole wafers present challenges. An elegant technique based on radius of curvature deformation of whole wafers in a commercial metrology tool is described. The method is based on the Villari effect through application of strain to a film by introducing a radius of curvature. Strain can be applied tensilely and compressively depending on the material. The design, while implemented on 3'' wafers, is scalable. The approach removes effects arising from any shape anisotropy that occurs with smaller samples, which can lead to a change in magnetic response. From the change in the magnetic anisotropy as a function of the radius, saturation magnetostriction ?s can be determined. Dependence on film composition and film thickness was studied to validate the radius of curvature approach with other techniques. ?s decreases from positive values to negative values through an increase in Ni concentration around the permalloy composition, and ?s also increases with a decrease in film thickness, in full agreement with previous reports. We extend the technique by demonstrating the technique applied to a multi-layered structure. These results verify the validity of the method and are an important step to facilitate further work in understanding how manipulation of multilayered films can offer tailored magnetostriction.

Direct assembly of three-dimensional mesh plasmonic rolls

A direct-assembly method to construct three-dimensional (3D) plasmonic nanostructures yields porous plasmonic rolls through the strain-induced self-rolling up of two-dimensional metallic nanopore films. This route is scalable to different hole sizes and film thicknesses, and applicable to a variety of materials, providing general routes towards a diverse family of 3D metamaterials with nano-engineerable optical properties. These plasmonic rolls can be dynamically driven by light irradiation, rolling or unrolling with increasing or decreasing light intensity. Such dynamically controllable 3D plasmonic nanostructures offer opportunities both for sensing and feedback in active nano-actuators. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4711923]

Generic low-latency NoC router architecture for FPGA computing systems

A novel cost-effective and low-latency wormhole router for packet-switched NoC designs, tailored for FPGA, is presented. This has been designed to be scalable at system level to fully exploit the characteristics and constraints of FPGA based systems, rather than custom ASIC technology. A key feature is that it achieves a low packet propagation latency of only two cycles per hop including both router pipeline delay and link traversal delay - a significant enhancement over existing FPGA designs - whilst being very competitive in terms of performance and hardware complexity. It can also be configured in various network topologies including 1-D, 2-D, and 3-D. Detailed design-space exploration has been carried for a range of scaling parameters, with the results of various design trade-offs being presented and discussed. By taking advantage of abundant buildin reconfigurable logic and routing resources, we have been able to create a new scalable on-chip FPGA based router that exhibits high dimensionality and connectivity. The architecture proposed can be easily migrated across many FPGA families to provide flexible, robust and cost-effective NoC solutions suitable for the implementation of high-performance FPGA computing systems. © 2011 IEEE.

Adaptive Measurement-Based Policy-Driven QoS Management with Fuzzy-Rule-based Resource Allocation

Fixed and wireless networks are increasingly converging towards common connectivity with IP-based core networks. Providing effective end-to-end resource and QoS management in such complex heterogeneous converged network scenarios requires unified, adaptive and scalable solutions to integrate and co-ordinate diverse QoS mechanisms of different access technologies with IP-based QoS. Policy-Based Network Management (PBNM) is one approach that could be employed to address this challenge. Hence, a policy-based framework for end-to-end QoS management in converged networks, CNQF (Converged Networks QoS Management Framework) has been proposed within our project. In this paper, the CNQF architecture, a Java implementation of its prototype and experimental validation of key elements are discussed. We then present a fuzzy-based CNQF resource management approach and study the performance of our implementation with real traffic flows on an experimental testbed. The results demonstrate the efficacy of our resource-adaptive approach for practical PBNM systems

Implementation and Evaluation of Measurement-Based Admission Control Schemes Within a Converged Networks QoS Management Framework

Policy-based network management (PBNM) paradigms provide an effective tool for end-to-end resource
management in converged next generation networks by enabling unified, adaptive and scalable solutions
that integrate and co-ordinate diverse resource management mechanisms associated with heterogeneous
access technologies. In our project, a PBNM framework for end-to-end QoS management in converged
networks is being developed. The framework consists of distributed functional entities managed within a
policy-based infrastructure to provide QoS and resource management in converged networks. Within any
QoS control framework, an effective admission control scheme is essential for maintaining the QoS of
flows present in the network. Measurement based admission control (MBAC) and parameter basedadmission control (PBAC) are two commonly used approaches. This paper presents the implementationand analysis of various measurement-based admission control schemes developed within a Java-based
prototype of our policy-based framework. The evaluation is made with real traffic flows on a Linux-based experimental testbed where the current prototype is deployed. Our results show that unlike with classic MBAC or PBAC only schemes, a hybrid approach that combines both methods can simultaneously result in improved admission control and network utilization efficiency

Design and Implementation of a Measurement-Based Policy-Driven Resource Management Framework For Converged Networks

This paper presents the design and implementation of a measurement-based QoS and resource management framework, CNQF (Converged Networks’ QoS Management Framework). CNQF is designed to provide unified, scalable QoS control and resource management through the use of a policy-based network
management paradigm. It achieves this via distributed functional entities that are deployed to co-ordinate the resources of the transport network through centralized policy-driven decisions supported by measurement-based control architecture. We present the CNQF architecture, implementation of the
prototype and validation of various inbuilt QoS control mechanisms using real traffic flows on a Linux-based experimental test bed.

A Framework for Context-Driven End-to-End QoS Control in Converged Next Generation Networks”

This paper presents a framework for context-driven policy-based QoS control and end-to-end resource management in converged next generation networks. The Converged Networks QoS Framework (CNQF) is being developed within the IU-ATC project, and comprises distributed functional entities whose instances co-ordinate the converged network infrastructure to facilitate scalable and efficient end-to-end QoS management. The CNQF design leverages aspects of TISPAN, IETF and 3GPP policy-based management architectures whilst also introducing important innovative extensions to support context-aware QoS control in converged networks. The framework architecture is presented and its functionalities and operation in specific application scenarios are described.

Perceptual investigation of image placement with Ambisonics for non-centred listeners

Ambisonics is a scalable spatial audio technique that attempts to present a sound scene to listeners over as large an area as possi- ble. A localisation experiment was carried out to investigate the performance of a first and third order system at three listening positions - one in the centre and two off-centre. The test used a reverse target-pointer adjustment method to determine the error, both signed and absolute, for each combination of listening posi- tion and system. The signed error was used to indicate the direc- tion and magnitude of the shifts in panning angle introduced for the off-centre listening positions. The absolute error was used as a measure of the performance of the listening position and systems combinations for a comparison of their overall performance. A comparison was made between the degree of image shifting be- tween the two systems and the robustness of their off-centre per- formance.

Understanding the synthesis of directly spinnable carbon nanotube forests

Carbon nanotube forests that can be spun directly from the growth substrate into pure, highly aligned webs, ribbons or yarn promise novel applications that capture the strength and other characteristics of this material. The precise conditions for high spinnability over a maximum proportion of the reactor space are extremely sensitive. The roles of catalyst, substrate, temperature, gas flow rates, reaction time with acetylene etc. were studied to identify and understand the key parameters and develop a robust, scalable process. Using a 44 mm (id) reactor, the optimum values for these variables were determined as comprising a 2.3 nm thick iron catalyst layer on a silicon substrate with 50 nm of thermal oxide; 670 °C running temperature; 650 sccm helium and 34 sccm acetylene for 20 min. The effects of deviating from these optima were explored and the role of amorphous carbon deposition clarified. Crown Copyright © 2009.

An Improvement of Subject Reacquisition by Reasoning and Revision

CCTV systems are broadly deployed in the present world. Despite this, the impact on anti-social and criminal behaviour has been minimal. Subject reacquisition is a fundamental task to ensure in-time reaction for intelligent surveillance. However, traditional reacquisition based on face recognition is not scalable, hence in this paper we use reasoning techniques to reduce the computational effort which deploys the time-of-flight information between interested zones such as airport security corridors. Also, to improve accuracy of reacquisition, we introduce the idea of revision as a method of post-processing.We demonstrate the significance and usefulness of our framework with an experiment which shows much less computational effort and better accuracy.

Analysis of Dependence Tracking Algorithms for Task Dataflow Execution

Processor architectures has taken a turn towards many-core processors, which integrate multiple processing cores on a single chip to increase overall performance, and there are no signs that this trend will stop in the near future. Many-core processors are harder to program than multi-core and single-core processors due to the need of writing parallel or concurrent programs with high degrees of parallelism. Moreover, many-cores have to operate in a mode of strong scaling because of memory bandwidth constraints. In strong scaling increasingly finer-grain parallelism must be extracted in order to keep all processing cores busy.

Task dataflow programming models have a high potential to simplify parallel program- ming because they alleviate the programmer from identifying precisely all inter-task de- pendences when writing programs. Instead, the task dataflow runtime system detects and enforces inter-task dependences during execution based on the description of memory each task accesses. The runtime constructs a task dataflow graph that captures all tasks and their dependences. Tasks are scheduled to execute in parallel taking into account dependences specified in the task graph.

Several papers report important overheads for task dataflow systems, which severely limits the scalability and usability of such systems. In this paper we study efficient schemes to manage task graphs and analyze their scalability. We assume a programming model that supports input, output and in/out annotations on task arguments, as well as commutative in/out and reductions. We analyze the structure of task graphs and identify versions and generations as key concepts for efficient management of task graphs. Then, we present three schemes to manage task graphs building on graph representations, hypergraphs and lists. We also consider a fourth edge-less scheme that synchronizes tasks using integers. Analysis using micro-benchmarks shows that the graph representation is not always scalable and that the edge-less scheme introduces least overhead in nearly all situations.

Algorithms for Self-Healing Networks

Many modern networks are \emph{reconfigurable}, in the sense that the topology of the network can be changed by the nodes in the network. For example, peer-to-peer, wireless and ad-hoc networks are reconfigurable. More generally, many social networks, such as a company's organizational chart; infrastructure networks, such as an airline's transportation network; and biological networks, such as the human brain, are also reconfigurable. Modern reconfigurable networks have a complexity unprecedented in the history of engineering, resembling more a dynamic and evolving living animal rather than a structure of steel designed from a blueprint. Unfortunately, our mathematical and algorithmic tools have not yet developed enough to handle this complexity and fully exploit the flexibility of these networks. We believe that it is no longer possible to build networks that are scalable and never have node failures. Instead, these networks should be able to admit small, and maybe, periodic failures and still recover like skin heals from a cut. This process, where the network can recover itself by maintaining key invariants in response to attack by a powerful adversary is what we call \emph{self-healing}. Here, we present several fast and provably good distributed algorithms for self-healing in reconfigurable dynamic networks. Each of these algorithms have different properties, a different set of gaurantees and limitations. We also discuss future directions and theoretical questions we would like to answer. %in the final dissertation that this document is proposed to lead to.

Risk assessment of neonatal excipient exposure:Lessons from food safety and other areas

Newborn babies can require significant amounts of medication containing excipients intended to improve the drug formulation. Most medicines given to neonates have been developed for adults or older children and contain excipients thought to be safe in these age groups. Many excipients have been used widely in neonates without obvious adverse effects. Some excipients may be toxic in high amounts in which case they need careful risk assessment. Alternatively, it is conceivable that ill-founded fears about excipients mean that potentially useful medicines are not made available to newborn babies. Choices about excipient exposure can occur at several stages throughout the lifecycle of a medicine, from product development through to clinical use. Making these choices requires a scalable approach to analysing the overall risk. In this contribution we examine these issues.