Effect of polymeric properties on the operation of gel-type audio transducers.

A novel design of a moving-coil transducer coupled with a low-hardness elastomer called “the gel surround” is presented in this thesis. This device is termed a “gel-type audio transducer”. The gel-type audio transducer has been developed to overcome the problems that conventional loudspeakers have suffered - that is, the problem with size of the audio device against the quality of sound at low frequency range. Therefore the research work presented herein aims to develop the “gel-type audio transducer” as a next-generation audio transducer for miniaturized woofers. The gel-type audio transducer consists of the magnetic and coil-drive plate assembly, and these parts are coupled by the gel surround. The transducer is driven by the electromagnetic conversion mechanism (a moving-coil transducer) and its output driving force can be greatly enhanced by applying the novel mechanism of the gel surround especially at low frequency range, resulting in the enhanced acoustic efficiency. The transducer can be attached to a stiff and light panel with both the optimized impedance matching and minimised wave collisions. The performance of the gel-type audio transducer is greatly influenced by the mass of the magnetic assembly and compliance of the “gel surround”. But as the size of the magnet and its weight have to be kept minimal for a miniaturisation of the device, the focus of the research is on the effect of the of the gel surround. As a result, the effect of the gel surround, made of the RTV (room-temperature vulcanising) silicone elastomer, TPE (thermoplastic elastomer), and the silicone foam, on generation of the output driving force, the energy transfer from the transducer to a panel to which the transducer is attached, and sound radiation from the vibrating panel, was investigated. This effect was studied by COMSOL multiphysics (FE analysis) and thereby, the simulated results were verified by experiments such as the laser scanning measurement, DMA (dynamic mechanical analyzer), and the acoustic test. Successful development of prototypes of the gel-type audio transducers, with an enhanced acoustic efficiency at reduced size and weight, was achieved. Implementation of the transducers into consumer applications was also demonstrated with their commercial values.

Library co-operation and ICT in the UK: an overview

Tedd, L.A. (2003). Library co-operation and ICT in the UK: an overview. Information Services and Use, 23(4), 199-210

The Organization for Security and Co-operation in Europe and European Security Law

Odello, Marco, The Organization for Security and Co-operation in Europe and European Security Law, In: European Security Law, Oxford University Press, pp. 295-328, 2007. RAE2008

Judicial Perspectives on the Operation of s.41 and the Relevance and Admissibility of Prior Sexual History Evidence: Four Scenarios

Judicial Perspectives on the Operation of s.41 and the Relevance and Admissibility of Prior Sexual History Evidence: Four scenarios. N.Kibble. Crim.L.R. 2005 190. RAE2008

Missionary survey as an aid to intelligent co-operation in foreign missions, by Roland Allen, and Thomas Cochrane.

http://www.archive.org/details/missionarysurvey13360gut

The operation of multiquantum-well barriers

The multiquantum barrier (MQB), proposed by Iga et al in 1986, has been shown by several researchers to be an effective structure for improving the operating characteristics of laser diodes. These improvements include a reduction in the laser threshold current and increased characteristic temperatures. The operation of the MQB has been described as providing an increased barrier to electron overflow by reflecting high energy electrons trying to escape from the active region of the laser.This is achieved in a manner analogous to a Bragg reflector in optics. This thesis presents an investigation of the effectiveness of the MQB as an electron reflector. Numerical models have been developed for calculating the electron reflection due to MQB. Novel optical and electrical characterisation techniques have been used to try to measure an increase in barrier height due to the MQB in AlGaInP.It has been shown that the inclusion of MQB structures in bulk double heterostructure visible laser diodes can halve the threshold current above room temperature and the characteristic temperature of these lasers can be increased by up to 20K.These improvements are shown to occur in visible laser diodes even with the inclusion of theoretically ineffective MQB structures, hence the observed improvement in the characteristics of the laser diodes described above cannot be uniquely attributed to an increased barrier height due to enhance electron reflection. It is proposed here that the MQB improves the performance of laser diodes by proventing the diffusion of zinc into the active region of the laser. It is also proposed that the trapped zinc in the MQB region of the laser diode locally increases the p-type doping bringing the quasi-Fermi level for holes closer to the valence band edge thus increasing the barrier to electron overflow in the conduction band.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Continuous-wave operation of a modulational instability laser

post-deadline paper

Upgrading automation for nuclear fuel in-core management: from the symbolic generation of configurations to the neural adaptation of heuristics

FUELCON is an expert system in nuclear engineering. Its task is optimized refueling-design, which is crucial to keep down operation costs at a plant. FUELCON proposes sets of alternative configurations of fuel-allocation; the fuel is positioned in a grid representing the core of a reactor. The practitioner of in-core fuel management uses FUELCON to generate a reasonably good configuration for the situation at hand. The domain expert, on the other hand, resorts to the system to test heuristics and discover new ones, for the task described above. Expert use involves a manual phase of revising the ruleset, based on performance during previous iterations in the same session. This paper is concerned with a new phase: the design of a neural component to carry out the revision automatically. Such an automated revision considers previous performance of the system and uses it for adaptation and learning better rules. The neural component is based on a particular schema for a symbolic to recurrent-analogue bridge, called NIPPL, and on the reinforcement learning of neural networks for the adaptation.

Refueling in nuclear engineering: the FUELCON project

Over a time span of almost a decade, the FUELCON project in nuclear engineering has led to a fully functional expert system and spawned sequel projects. Its task is in-core fuel management, also called `refueling', i.e., good fuel-allocation for reloading the core of a given nuclear reactor, for a given operation cycle. The task is crucial for keeping down operation costs at nuclear power plants. Fuel comes in different types and is positioned in a grid representing the core of a reactor. The tool is useful for practitioners but also helps the expert in the domain to test his or her rules of thumb and to discover new ones.

Optimizing the operation of straight-grate iron-ore pellet induration systems using process models

Mathematical models of straight-grate pellet induration processes have been developed and carefully validated by a number of workers over the past two decades. However, the subsequent exploitation of these models in process optimization is less clear, but obviously requires a sound understanding of how the key factors control the operation. In this article, we show how a thermokinetic model of pellet induration, validated against operating data from one of the Iron Ore Company of Canada (IOCC) lines in Canada, can be exploited in process optimization from the perspective of fuel efficiency, production rate, and product quality. Most existing processes are restricted in the options available for process optimization. Here, we review the role of each of the drying (D), preheating (PH), firing (F), after-firing (AF), and cooling (C) phases of the induration process. We then use the induration process model to evaluate whether the first drying zone is best to use on the up- or down-draft gas-flow stream, and we optimize the on-gas temperature profile in the hood of the PH, F, and AF zones, to reduce the burner fuel by at least 10 pct over the long term. Finally, we consider how efficient and flexible the process could be if some of the structural constraints were removed (i.e., addressed at the design stage). The analysis suggests it should be possible to reduce the burner fuel lead by 35 pct, easily increase production by 5+ pct, and improve pellet quality.

Scheduling three-operation jobs in a two-machine flow shop to minimize makespan

This paper considers a variant of the classical problem of minimizing makespan in a two-machine flow shop. In this variant, each job has three operations, where the first operation must be performed on the first machine, the second operation can be performed on either machine but cannot be preempted, and the third operation must be performed on the second machine. The NP-hard nature of the problem motivates the design and analysis of approximation algorithms. It is shown that a schedule in which the operations are sequenced arbitrarily, but without inserted machine idle time, has a worst-case performance ratio of 2. Also, an algorithm that constructs four schedules and selects the best is shown to have a worst-case performance ratio of 3/2. A polynomial time approximation scheme (PTAS) is also presented.

The impact of powder flowing properties on dosator filling system operation

Purpose: To study the impact of powder flow properties on dosator filling systems, with particular focus on improvements in dose weight accuracy and repeatability. Method: This study evaluates a range of critical powder flow properties such as: flow function, cohesion, wall friction, adhesion to wall surfaces, density/compressibility data, stress ratio “K” and gas permeability. The characterisations of the powders considered in this study were undertaken using an annular shear cell using a sample size of 0.5 litres. This tester also incorporated the facility to measure bed expansion during shear in addition to contraction under consolidation forces. A modified Jenike type linear wall friction tester was used to develop the failure loci for the powder sample in conjunction with multiple wall samples (representing a variety of material types and surface finishes). Measurements of the ratio of applied normal stress versus lateral stress were determined using a piece of test equipment specifically designed for the purpose. Results: The correct characterisation of powders and the incorporation of this data into the design of process equipment are recognised as critical for reliable and accurate operation. An example of one aspect of this work is the stress ratio “K”. This characteristic is not well understood or correctly interpreted in many cases – despite its importance. Fig 1 [Omitted] (illustrates a sample of test data. The slope of the line gives the stress ratio in a uniaxial compaction system – indicating the behaviour of the material under compaction during dosing processes. Conclusions: A correct assessment of the bulk powder properties for a given formulation can allow prediction of: cavity filling behaviour (and hence dosage), efficiency of release from dosator, and strength and stability of extruded dose en route to capsule filling Influences over the effectiveness of dosator systems have been shown to be impacted upon by: bed pre-compaction history, gas permeability in the bed (with respect to local density effects), and friction effects for materials of construction for dosators

Modelling of dosator operation for improved manufacturing performance

Purpose: To develop an improved mathematical model for the prediction of dose accuracy of Dosators - based upon the geometry of the machine in conjunction with measured flow properties of the powder. Methods: A mathematical model has been created, based on a analytical method of differential slices - incorporating measured flow properties. The key flow properties of interest in this investigation were: flow function, effective angle of wall friction, wall adhesion, bulk density, stress ratio K and permeability. To simulate the real process and (very importantly) validate the model, a Dosator test-rig has been used to measure the forces acting on the Dosator during the filling stage, the force required to eject the dose and the dose weight. Results: Preliminary results were obtained from the Dosator test-rig. Figure 1 [Omitted] shows the dose weight for different depths to the bottom of the powder bed at the end of the stroke and different levels of pre-compaction of the powder bed. A strong influence over dose weight arising from the proximity between the Dosator and the bottom of the powder bed at the end of the stroke and the conditions of the powder bed has been established. Conclusions: The model will provide a useful tool to predict dosing accuracy and, thus, optimise the future design of Dosator based equipment technology – based on measured bulk properties of the powder to be handled. Another important factor (with a significant influence) on Dosator processes, is the condition of the powder bed and the clearance between the Dosator and the bottom of the powder bed.