Optimal photons for quantum-information processing

Photonic quantum-information processing schemes, such as linear optics quantum computing, and other experiments relying on single-photon interference, inherently require complete photon indistinguishability to enable the desired photonic interactions to take place. Mode-mismatch is the dominant cause of photon distinguishability in optical circuits. Here we study the effects of photon wave-packet shape on tolerance against the effects of mode mismatch in linear optical circuits, and show that Gaussian distributed photons with large bandwidth are optimal. The result is general and holds for arbitrary linear optical circuits, including ones which allow for postselection and classical feed forward. Our findings indicate that some single photon sources, frequently cited for their potential application to quantum-information processing, may in fact be suboptimal for such applications.

Prediction of subcellular localization using sequence-biased recurrent networks

Motivation: Targeting peptides direct nascent proteins to their specific subcellular compartment. Knowledge of targeting signals enables informed drug design and reliable annotation of gene products. However, due to the low similarity of such sequences and the dynamical nature of the sorting process, the computational prediction of subcellular localization of proteins is challenging. Results: We contrast the use of feed forward models as employed by the popular TargetP/SignalP predictors with a sequence-biased recurrent network model. The models are evaluated in terms of performance at the residue level and at the sequence level, and demonstrate that recurrent networks improve the overall prediction performance. Compared to the original results reported for TargetP, an ensemble of the tested models increases the accuracy by 6 and 5% on non-plant and plant data, respectively.

The applicability of recurrent neural networks for biological sequence analysis

Selection of machine learning techniques requires a certain sensitivity to the requirements of the problem. In particular, the problem can be made more tractable by deliberately using algorithms that are biased toward solutions of the requisite kind. In this paper, we argue that recurrent neural networks have a natural bias toward a problem domain of which biological sequence analysis tasks are a subset. We use experiments with synthetic data to illustrate this bias. We then demonstrate that this bias can be exploitable using a data set of protein sequences containing several classes of subcellular localization targeting peptides. The results show that, compared with feed forward, recurrent neural networks will generally perform better on sequence analysis tasks. Furthermore, as the patterns within the sequence become more ambiguous, the choice of specific recurrent architecture becomes more critical.

The multimodal world of medical monitoring displays

A vision of the future of intraoperative monitoring for anesthesia is presented-a multimodal world based on advanced sensing capabilities. I explore progress towards this vision, outlining the general nature of the anesthetist's monitoring task and the dangers of attentional capture. Research in attention indicates different kinds of attentional control, such as endogenous and exogenous orienting, which are critical to how awareness of patient state is maintained, but which may work differently across different modalities. Four kinds of medical monitoring displays are surveyed: (1) integrated visual displays, (2) head-mounted displays, (3) advanced auditory displays and (4) auditory alarms. Achievements and challenges in each area are outlined. In future research, we should focus more clearly on identifying anesthetists' information needs and we should develop models of attention in different modalities and across different modalities that are more capable of guiding design. (c) 2006 Elsevier Ltd. All rights reserved.

Bayesian methods for neural networks

Bayesian techniques have been developed over many years in a range of different fields, but have only recently been applied to the problem of learning in neural networks. As well as providing a consistent framework for statistical pattern recognition, the Bayesian approach offers a number of practical advantages including a potential solution to the problem of over-fitting. This chapter aims to provide an introductory overview of the application of Bayesian methods to neural networks. It assumes the reader is familiar with standard feed-forward network models and how to train them using conventional techniques.

Bayesian methods for neural networks

Bayesian techniques have been developed over many years in a range of different fields, but have only recently been applied to the problem of learning in neural networks. As well as providing a consistent framework for statistical pattern recognition, the Bayesian approach offers a number of practical advantages including a potential solution to the problem of over-fitting. This chapter aims to provide an introductory overview of the application of Bayesian methods to neural networks. It assumes the reader is familiar with standard feed-forward network models and how to train them using conventional techniques.

Transients and asymptotics of natural gradient learning

We analyse natural gradient learning in a two-layer feed-forward neural network using a statistical mechanics framework which is appropriate for large input dimension. We find significant improvement over standard gradient descent in both the transient and asymptotic phases of learning.

Sympathetic inhibition of accommodation after sustained nearwork in subjects with myopia and emmetropia

PURPOSE. The purposes of the present study were to assess the effect of a sympathetic inhibitory pharmacologic agent, timolol maleate, on the magnitude of nearwork-induced transient myopia (NITM) and its decay in different refractive groups for an extended near task duration and to determine the proportion of the young adult population manifesting effective sympathetic access under naturalistic closed-loop viewing conditions. METHODS. Ten subjects with emmetropia and 10 with myopia were tested. They read binocularly for 1 hour at a distance of 35 to 40 cm. NITM was calculated as the difference in distance refractive state after task as compared with before task immediately after reading. All subjects received timolol maleate to block the sympathetic nervous system and betaxolol as a control agent in independent test sessions separated by at least 3 days. Forty minutes after drug instillation, the NITM measurement procedure was repeated. RESULTS. Initial NITM magnitude was larger in subjects with myopia than in subjects with emmetropia before and after timolol instillation. Furthermore, NITM magnitude in subjects with sympathetic access was increased after timolol instillation. In contrast, with the control agent betaxolol, there was no increase. NITM decay duration to baseline was increased after timolol instillation in the subjects with myopia only. Only 15% of the subjects (n = 3 subjects with myopia) demonstrated effective and significant access to sympathetic facility. CONCLUSIONS. Subjects with myopia demonstrated an increase in decay duration with timolol, thus suggesting impaired sympathetic inhibition of accommodation. This may be a precursor for myopia progression in some persons.

Effect of β-adrenoceptor antagonists on autonomic control of ciliary smooth muscle

Purpose: Pharmacological intervention with peripheral sympathetic transmission at ciliary smooth muscle neuro-receptor junctions has been used against a background of controlled parasympathetic activity to investigate the characteristics of autonomic control of ocular accommodation. Methods: A continuously recording infrared optometer was used to measure accommodation on a group of five visually normal emmetropic subjects under open- and closed-loop conditions. A double-blind protocol between saline, timolol and betaxolol was used to differentiate between the localised action on ciliary smooth muscle and effects induced by changes in stimulus conditions. Data were collected before and 45 min following the instillation of saline, timolol or betaxolol. Open-loop post-task decay was investigated following 3 min sustained near fixation of a stimulus placed 3 D above the subject's pre-task tonic accommodation level. Closed-loop dynamic responses were recorded for each treatment condition while subjects viewed sinusoidally (0.05-0.6 Hz) or stepwise vergence-modulated targets over a 2 D range (2-4 D). Results: Open-loop data demonstrate a rapid post-task regression to pre-task tonic accommodation levels for saline and betaxolol control conditions. A slow positive post-task shift was induced by timolol indicating that sympathetic inhibition contributes to accommodative adaptation during sustained near vision. Closed-loop accommodation responses to temporally modulated sinusoidal stimuli showed characteristic features for both saline and betaxolol control conditions. Timolol induced a reduced gain for low- and mid-temporal frequencies (< 0.3 Hz) but did not affect the response at higher temporal frequencies. Response times to stepwise stimuli increased following the instillation of timolol for the near-to-far fixation condition compared with the controls and was related to the period of sustained prior fixation. Conclusions: Modulation of accommodation under open- and closed-loop conditions by a non-selective β-blocker is consistent with the temporal and inhibitory features of sympathetic innervation to ciliary smooth muscle. Although parasympathetic innervation predominates there is evidence to support a role for sympathetic innervation in the control of ocular accommodation. © 2002 The College of Optometrists.

Fast response static var generator for improving the power system performance of an electric arc furnace (EAF)

Cascaded multilevel inverters-based Static Var Generators (SVGs) are FACTS equipment introduced for active and reactive power flow control. They eliminate the need for zigzag transformers and give a fast response. However, with regard to their application for flicker reduction in using Electric Arc Furnace (EAF), the existing multilevel inverter-based SVGs suffer from the following disadvantages. (1) To control the reactive power, an off-line calculation of Modulation Index (MI) is required to adjust the SVG output voltage. This slows down the transient response to the changes of reactive power; and (2) Random active power exchange may cause unbalance to the voltage of the d.c. link (HBI) capacitor when the reactive power control is done by adjusting the power angle d alone. To resolve these problems, a mathematical model of 11-level cascaded SVG, was developed. A new control strategy involving both MI (modulation index) and power angle (d) is proposed. A selected harmonics elimination method (SHEM) is taken for switching pattern calculations. To shorten the response time and simplify the controls system, feed forward neural networks are used for on-line computation of the switching patterns instead of using look-up tables. The proposed controller updates the MI and switching patterns once each line-cycle according to the sampled reactive power Qs. Meanwhile, the remainder reactive power (compensated by the MI) and the reactive power variations during the line-cycle will be continuously compensated by adjusting the power angles, d. The scheme senses both variables MI and d, and takes action through the inverter switching angle, qi. As a result, the proposed SVG is expected to give a faster and more accurate response than present designs allow. In support of the proposal there is a mathematical model for reactive powered distribution and a sensitivity matrix for voltage regulation assessment, MATLAB simulation results are provided to validate the proposed schemes. The performance with non-linear time varying loads is analysed and refers to a general review of flicker, of methods for measuring flickers due to arc furnace and means for mitigation.

Mathematical modelling and optimal multivariable control of chemical processes

This work reports the developnent of a mathenatical model and distributed, multi variable computer-control for a pilot plant double-effect climbing-film evaporator. A distributed-parameter model of the plant has been developed and the time-domain model transformed into the Laplace domain. The model has been further transformed into an integral domain conforming to an algebraic ring of polynomials, to eliminate the transcendental terms which arise in the Laplace domain due to the distributed nature of the plant model. This has made possible the application of linear control theories to a set of linear-partial differential equations. The models obtained have well tracked the experimental results of the plant. A distributed-computer network has been interfaced with the plant to implement digital controllers in a hierarchical structure. A modern rnultivariable Wiener-Hopf controller has been applled to the plant model. The application has revealed a limitation condition that the plant matrix should be positive-definite along the infinite frequency axis. A new multi variable control theory has emerged fram this study, which avoids the above limitation. The controller has the structure of the modern Wiener-Hopf controller, but with a unique feature enabling a designer to specify the closed-loop poles in advance and to shape the sensitivity matrix as required. In this way, the method treats directly the interaction problems found in the chemical processes with good tracking and regulation performances. Though the ability of the analytical design methods to determine once and for all whether a given set of specifications can be met is one of its chief advantages over the conventional trial-and-error design procedures. However, one disadvantage that offsets to some degree the enormous advantages is the relatively complicated algebra that must be employed in working out all but the simplest problem. Mathematical algorithms and computer software have been developed to treat some of the mathematical operations defined over the integral domain, such as matrix fraction description, spectral factorization, the Bezout identity, and the general manipulation of polynomial matrices. Hence, the design problems of Wiener-Hopf type of controllers and other similar algebraic design methods can be easily solved.

Minimum description length, regularisation and multi-modal data

Conventional feed forward Neural Networks have used the sum-of-squares cost function for training. A new cost function is presented here with a description length interpretation based on Rissanen's Minimum Description Length principle. It is a heuristic that has a rough interpretation as the number of data points fit by the model. Not concerned with finding optimal descriptions, the cost function prefers to form minimum descriptions in a naive way for computational convenience. The cost function is called the Naive Description Length cost function. Finding minimum description models will be shown to be closely related to the identification of clusters in the data. As a consequence the minimum of this cost function approximates the most probable mode of the data rather than the sum-of-squares cost function that approximates the mean. The new cost function is shown to provide information about the structure of the data. This is done by inspecting the dependence of the error to the amount of regularisation. This structure provides a method of selecting regularisation parameters as an alternative or supplement to Bayesian methods. The new cost function is tested on a number of multi-valued problems such as a simple inverse kinematics problem. It is also tested on a number of classification and regression problems. The mode-seeking property of this cost function is shown to improve prediction in time series problems. Description length principles are used in a similar fashion to derive a regulariser to control network complexity.

Modelling and control of a hybrid stepping motor

The integration of a microprocessor and a medium power stepper motor in one control system brings together two quite different disciplines. Various methods of interfacing are examined and the problems involved in both hardware and software manipulation are investigated. Microprocessor open-loop control of the stepper motor is considered. The possible advantages of microprocessor closed-loop control are examined and the development of a system is detailed. The system uses position feedback to initiate each motor step. Results of the dynamic response of the system are presented and its performance discussed. Applications of the static torque characteristic of the stepper motor are considered followed by a review of methods of predicting the characteristic. This shows that accurate results are possible only when the effects of magnetic saturation are avoided or when the machine is available for magnetic circuit tests to be carried out. A new method of predicting the static torque characteristic is explained in detail. The method described uses the machine geometry and the magnetic characteristics of the iron types used in the machine. From this information the permeance of each iron component of the machine is calculated and by using the equivalent magnetic circuit of the machine, the total torque produced is predicted. It is shown how this new method is implemented on a digital computer and how the model may be used to investigate further aspects of the stepper motor in addition to the static torque.

Automatic control of attenuation in a digital communication network

This thesis describes the investigation of an adaptive method of attenuation control for digital speech signals in an analogue-digital environment and its effects on the transmission performance of a national telecommunication network. The first part gives the design of a digital automatic gain control, able to operate upon a P.C.M. signal in its companded form and whose operation is based upon the counting of peaks of the digital speech signal above certain threshold levels. A study was ma.de of a digital automatic gain control (d.a.g.c.) in open-loop configuration and closed-loop configuration. The former was adopted as the means for carrying out the automatic control of attenuation. It was simulated and tested, both objectively and subjectively. The final part is the assessment of the effects on telephone connections of a d.a.g.c. that introduces gains of 6 dB or 12 dB. This work used a Telephone Connection Assessment Model developed at The University of Aston in Birmingham. The subjective tests showed that the d.a.g.c. gives advantage for listeners when the speech level is very low. The benefit is not great when speech is only a little quieter than preferred. The assessment showed that, when a standard British Telecom earphone is used, insertion of gain is desirable if speech voltage across the earphone terminals is below an upper limit of -38 dBV. People commented upon the presence of an adaptive-like effect during the tests. This could be the reason why they voted against the insertion of gain at level only little quieter than preferred, when they may otherwise have judged it to be desirable. A telephone connection with a d.a.g.c. in has a degree of difficulty less than half of that without it. The score Excellent plus Good is 10-30% greater.

Autonomic correlates of ocular accommodation and cardiovascular function

PURPOSE: To evaluate the hypothesis that objective measures of open- and closed-loop ocular accommodation are related to systemic cardiovascular function, and ipso facto autonomic nervous system activity. METHODS: Sixty subjects (29 male; 31 female) varying in age from 18 to 33 years (average: 20.3 +/- 2.9 years) with a range of refractive errors [mean spherical equivalent (MSE): -7.12 to +1.82 D] participated in the study. Five 20-s continuous objective recordings of the accommodative response, measured with an open-view IR autorefractor (Shin-Nippon SRW-5000), were obtained for a variety of open- and closed-loop accommodative demands while simultaneous continuous measurement of heart rate was recorded with a finger-mounted piezo-electric pulse transducer for 5 min. Fast Fourier Transformation of cardiovascular function allowed the absolute and relative power of the autonomic components to be assessed in the frequency-domain, whereas heart period gave an indication of the time-domain response. RESULTS: Increasing closed-loop accommodative demand led to a concurrent increase in heart rate of approximately 2 beats/min for a 4.0 D increase in accommodative demand. The increase was attributable to a reduction in the absolute (p < 0.05) and normalised (p < 0.001) input of the systemic parasympathetic nervous system, and was unaffected by refractive group. The interaction with refractive group failed to reach significance. CONCLUSIONS: For sustained accommodation effort, the data demonstrate covariation between the oculomotor and cardiovascular systems which implies that a near visual task can significantly influence cardiovascular behaviour. Accommodative effort alone, however, is not a sufficient stimulus to induce autonomic differences between refractive groups. The data suggest that both the oculomotor and cardiovascular systems are predominantly attributable to changes in the systemic parasympathetic nervous system.