Optimal control and operation of drum granulation processes

Process optimisation and optimal control of batch and continuous drum granulation processes are studied in this paper. The main focus of the current research has been: (i) construction of optimisation and control relevant, population balance models through the incorporation of moisture content, drum rotation rate and bed depth into the coalescence kernels; (ii) investigation of optimal operational conditions using constrained optimisation techniques; (iii) development of optimal control algorithms based on discretized population balance equations; and (iv) comprehensive simulation studies on optimal control of both batch and continuous granulation processes. The objective of steady state optimisation is to minimise the recycle rate with minimum cost for continuous processes. It has been identified that the drum rotation-rate, bed depth (material charge), and moisture content of solids are practical decision (design) parameters for system optimisation. The objective for the optimal control of batch granulation processes is to maximize the mass of product-sized particles with minimum time and binder consumption. The objective for the optimal control of the continuous process is to drive the process from one steady state to another in a minimum time with minimum binder consumption, which is also known as the state-driving problem. It has been known for some time that the binder spray-rate is the most effective control (manipulative) variable. Although other possible manipulative variables, such as feed flow-rate and additional powder flow-rate have been investigated in the complete research project, only the single input problem with the binder spray rate as the manipulative variable is addressed in the paper to demonstrate the methodology. It can be shown from simulation results that the proposed models are suitable for control and optimisation studies, and the optimisation algorithms connected with either steady state or dynamic models are successful for the determination of optimal operational conditions and dynamic trajectories with good convergence properties. (c) 2005 Elsevier Ltd. All rights reserved.

Modelling Java concurrency with Object-Z

In this paper, we present a formal model of Java concurrency using the Object-Z specification language. This model captures the Java thread synchronization concepts of locking, blocking, waiting and notification. In the model, we take a viewpoints approach, first capturing the role of the objects and threads, and then taking a system view where we capture the way the objects and threads cooperate and communicate. As a simple illustration of how the model can, in general be applied, we use Object-Z inheritance to integrate the model with the classical producer-consumer system to create a specification directly incorporating the Java concurrency constructs.

UML approach to the generation of test sequences for Java-based concurrent systems

Starting with a UML specification that captures the underlying functionality of some given Java-based concurrent system, we describe a systematic way to construct, from this specification, test sequences for validating an implementation of the system. The approach is to first extend the specification to create UML state machines that directly address those aspects of the system we wish to test. To be specific, the extended UML state machines can capture state information about the number of waiting threads or the number of threads blocked on a given object. Using the SAL model checker we can generate from the extended UML state machines sequences that cover all the various possibilities of events and states. These sequences can then be directly transformed into test sequences suitable for input into a testing tool such as ConAn. As an illustration, the methodology is applied to generate sequences for testing a Java implementation of the producer-consumer system. © 2005 IEEE

Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

Concurreny based transition refinement for the verification of distributed algorithms

We suggest a new notion of behaviour preserving transition refinement based on partial order semantics. This notion is called transition refinement. We introduced transition refinement for elementary (low-level) Petri Nets earlier. For modelling and verifying complex distributed algorithms, high-level (Algebraic) Petri nets are usually used. In this paper, we define transition refinement for Algebraic Petri Nets. This notion is more powerful than transition refinement for elementary Petri nets because it corresponds to the simultaneous refinement of several transitions in an elementary Petri net. Transition refinement is particularly suitable for refinement steps that increase the degree of distribution of an algorithm, e.g. when synchronous communication is replaced by asynchronous message passing. We study how to prove that a replacement of a transition is a transition refinement.

Genetic algorithms with applications in wireless communications

Genetic algorithms (GAs) are known to locate the global optimal solution provided sufficient population and/or generation is used. Practically, a near-optimal satisfactory result can be found by Gas with a limited number of generations. In wireless communications, the exhaustive searching approach is widely applied to many techniques, such as maximum likelihood decoding (MLD) and distance spectrum (DS) techniques. The complexity of the exhaustive searching approach in the MLD or the DS technique is exponential in the number of transmit antennas and the size of the signal constellation for the multiple-input multiple-output (MIMO) communication systems. If a large number of antennas and a large size of signal constellations, e.g. PSK and QAM, are employed in the MIMO systems, the exhaustive searching approach becomes impractical and time consuming. In this paper, the GAs are applied to the MLD and DS techniques to provide a near-optimal performance with a reduced computational complexity for the MIMO systems. Two different GA-based efficient searching approaches are proposed for the MLD and DS techniques, respectively. The first proposed approach is based on a GA with sharing function method, which is employed to locate the multiple solutions of the distance spectrum for the Space-time Trellis Coded Orthogonal Frequency Division Multiplexing (STTC-OFDM) systems. The second approach is the GA-based MLD that attempts to find the closest point to the transmitted signal. The proposed approach can return a satisfactory result with a good initial signal vector provided to the GA. Through simulation results, it is shown that the proposed GA-based efficient searching approaches can achieve near-optimal performance, but with a lower searching complexity comparing with the original MLD and DS techniques for the MIMO systems.

System for foreign exchange trading using genetic algorithms and reinforcement learning

Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

Improved algorithms for rare event simulation with heavy tails

The estimation of P(S-n > u) by simulation, where S, is the sum of independent. identically distributed random varibles Y-1,..., Y-n, is of importance in many applications. We propose two simulation estimators based upon the identity P(S-n > u) = nP(S, > u, M-n = Y-n), where M-n = max(Y-1,..., Y-n). One estimator uses importance sampling (for Y-n only), and the other uses conditional Monte Carlo conditioning upon Y1,..., Yn-1. Properties of the relative error of the estimators are derived and a numerical study given in terms of the M/G/1 queue in which n is replaced by an independent geometric random variable N. The conclusion is that the new estimators compare extremely favorably with previous ones. In particular, the conditional Monte Carlo estimator is the first heavy-tailed example of an estimator with bounded relative error. Further improvements are obtained in the random-N case, by incorporating control variates and stratification techniques into the new estimation procedures.

A randomised control trial of exercise and manipulative therapy for cervicogenic headache

Study Design. A multicenter, randomized controlled trial with unblinded treatment and blinded outcome assessment was conducted. The treatment period was 6 weeks with follow-up assessment after treatment, then at 3, 6, and 12 months. Objectives. To determine the effectiveness of manipulative therapy and a low-load exercise program for cervicogenic headache when used alone and in combination, as compared with a control group. Summary of Background Data. Headaches arising from cervical musculoskeletal disorders are common. Conservative therapies are recommended as the first treatment of choice. Evidence for the effectiveness of manipulative therapy is inconclusive and available only for the short term. There is no evidence for exercise, and no study has investigated the effect of combined therapies for cervicogenic headache. Methods. In this study, 200 participants who met the diagnostic criteria for cervicogenic headache were randomized into four groups: manipulative therapy group, exercise therapy group, combined therapy group, and a control group. The primary outcome was a change in headache frequency. Other outcomes included changes in headache intensity and duration, the Northwick Park Neck Pain Index, medication intake, and patient satisfaction. Physical outcomes included pain on neck movement, upper cervical joint tenderness, a craniocervical flexion muscle test, and a photographic measure of posture. Results. There were no differences in headache-related and demographic characteristics between the groups at baseline. The loss to follow-up evaluation was 3.5%. At the 12-month follow-up assessment, both manipulative therapy and specific exercise had significantly reduced headache frequency and intensity, and the neck pain and effects were maintained (P < 0.05 for all). The combined therapies was not significantly superior to either therapy alone, but 10% more patients gained relief with the combination. Effect sizes were at least moderate and clinically relevant. Conclusion. Manipulative therapy and exercise can reduce the symptoms of cervicogenic headache, and the effects are maintained.

A Research Agenda for Assessing the Potential Contribution of Genomic Medicine to Tobacco Control

This paper identifies research priorities in evaluating the ways in which "genomic medicine"-the use of genetic information to prevent and treat disease-may reduce tobacco-related harm by: (1) assisting more smokers to quit; (2) preventing non-smokers from beginning to smoke tobacco; and (3) reducing the harm caused by tobacco smoking. The method proposed to achieve the first aim is pharmacogenetics", the use of genetic information to optimise the selection of smoking-cessation programmes by screening smokers for polymorphisms that predict responses to different methods of smoking cessation. This method competes with the development of more effective forms of smoking cessation that involve vaccinating smokers against the effects of nicotine and using new pharmaceuticals (such as cannabinoid antagonists and nicotine agonists). The second and third aims are more speculative. They include: screening the population for genetic susceptibility to nicotine dependence and intervening (eg, by vaccinating children and adolescents against the effects of nicotine) to prevent smoking uptake, and screening the population for genetic susceptibility to tobacco-related diseases. A framework is described for future research on these policy options. This includes: epidemiological modelling and economic evaluation to specify the conditions under which these strategies are cost-effective; and social psychological research into the effect of providing genetic information on smokers' preparedness to quit, and the general views of the public on tobacco smoking.

An unexpected role for visual feedback in vehicle steering control

Some motor tasks can be completed, quite literally, with our eyes shut. Most people can touch their nose without looking or reach for an object after only a brief glance at its location. This distinction leads to one of the defining questions of movement control: is information gleaned prior to starting the movement sufficient to complete the task (open loop), or is feedback about the progress of the movement required (closed loop)? One task that has commanded considerable interest in the literature over the years is that of steering a vehicle, in particular lane-correction and lane-changing tasks. Recent work has suggested that this type of task can proceed in a fundamentally open loop manner [1 and 2], with feedback mainly serving to correct minor, accumulating errors. This paper reevaluates the conclusions of these studies by conducting a new set of experiments in a driving simulator. We demonstrate that, in fact, drivers rely on regular visual feedback, even during the well-practiced steering task of lane changing. Without feedback, drivers fail to initiate the return phase of the maneuver, resulting in systematic errors in final heading. The results provide new insight into the control of vehicle heading, suggesting that drivers employ a simple policy of “turn and see,” with only limited understanding of the relationship between steering angle and vehicle heading.

Modifying insect population age structure to control vector-borne disease

Age is a critical determinant of the ability of most arthropod vectors to transmit a range of human pathogens. This is due to the fact that most pathogens require a period of extrinsic incubation in the arthropod host before pathogen transmission can occur. This developmental period for the pathogen often comprises a significant proportion of the expected lifespan of the vector. As such, only a small proportion of the population that is oldest contributes to pathogen transmission. Given this, strategies that target vector age would be expected to obtain the most significant reductions in the capacity of a vector population to transmit disease. The recent identification of biological agents that shorten vector lifespan, such as Wolbachia, entomopathogenic fungi and densoviruses, offer new tools for the control of vector-borne diseases. Evaluation of the efficacy of these strategies under field conditions will be possible due to recent advances in insect age-grading techniques. Implementation of all of these strategies will require extensive field evaluation and consideration of the selective pressures that reductions in vector longevity may induce on both vector and pathogen.

The future of tobacco control: project summary

The National Health and Medical Research Council has funded Professor Wayne Hall (University of Queensland) and Professor Simon Chapman (University of Sydney) for three years 2006-2008, to research aspects of the future of tobacco control, particularly in nations with advanced tobacco control programs like Australia. Dr Coral Gartner (UQ) and Ms Becky Freeman (USyd) are also working on the project. The University of Queensland's eSpace site provides links to papers and data appendices produced by the University of Queensland team on the project. Materials relevant to this project produced by the University of Sydney group are available at the link provided.