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Objectives Radiation dose variation within and among Computed Tomography (CT) centres is commonly reported. This work systematically reviewed published articles on adult Diagnostic Reference Levels (DRLs) for the brain, chest and abdomen to determine the causes and extent of variation. A systematic literature search and review was performed in selected databases containing leading journals in radiography, radiology and medical physics using carefully defined search terms related to CT and DRLs. The quality of the included articles was determined using the Effective Public Health Practise Project tool for quantitative studies. Key findings The 54 articles reviewed include: 45 studies using human data, 8 studies using phantom data, and one study with both human and phantom data. The main comparator in between studies was the dose indices used in reporting DRLs. DRL variations of up to a factor of 2 for the same procedure were noted in phantom studies, and up to a factor of 3 in human studies. Sources of variation include the type of scanner, the age of the scanner, differences in protocols, variations in patients, as well as variations in study design. Different combinations of dose indices were reported: volume computed tomography dose index (CTDIvol) and dose length product (DLP) (59%); DLP only (11%); weighted computed tomography dose index (CTDIw) and DLP (9%); CTDIvol only (7%); CTDIvol, DLP and effective dose (ED) (6%); CTDIw only (4%); CTDIvol, DLP and size specific dose estimate (SSDE) (1%) and CTDIw, CTDIvol and DLP (1%). The use of different dose indices limited dose comparison between studies. Conclusion The study noted a 2–3 fold variation in DRLs between studies for the same procedure. The causes of variation are reported and include study design, scanner technology and the use of different dose indices. Implications for practice There is a need for standardisation of CT DRLs in line with the International Commission on Radiological Protection recommendations to reduce dose variation and facilitate dose comparison.

The improvement of the robustness of the performance of electrical machines in presence of neglected features, such as manufacturing tolerances and deviations in material properties and parameters, is increasingly demanded. The available optimization procedures do not account for manufacturing tolerances, leaving the decision process incomplete. The article proposes a methodology for the selection of the more robust design towards manufacturing tolerances among the best candidates, detected by an optimization procedure. Statistical tools for tolerance analysis and worst-case analysis are discussed and adopted for the scope. The proposed methodology is used to select a robust design with respect to torque ripple deviations due to geometric tolerances in the laminations of a Synchronous Reluctance Motor with fluid shaped barriers. The statistical performance analysis and the worst-case analysis provide an estimation of the performance deterioration in the presence of the tolerances in the manufacturing process.

A novel dual adaptive controller for extremum control of stochastic and uncertain nonlinear Hammerstein systems is proposed. The design is based on the innovations dual control cost function originally developed for conventional adaptive control of linear systems. However, the design process is extensively modified and developed so as to cater for the extremum control scenario. This is a more challenging problem because the reference input is itself a nonlinear function of the unknown system parameters, rather than an independent and predefined external reference signal. As in all dual adaptive schemes, it leads to a control law that balances out the need for caution, due to parameter uncertainty, with the conflicting requirement of probing that acts to quickly reduce parameter uncertainty. The proposed controller's performance is analysed through extensive Monte Carlo simulation trials and compared with several other non-dual adaptive extremum controllers. It is shown that the novel extremum innovations ...

This work investigates the use of switching linear Gaussian state space models for the segmentation and automatic labelling of Stage 2 sleep EEG data characterised by spindles and K-complexes. The advantage of this approach is that it offers a unified framework of detecting multiple transient events within background EEG data. Specifically for the identification of background EEG, spindles and K-complexes, a true positive rate (false positive rate) of 76.04% (33.47%), 83.49% (47.26%) and 52.02% (7.73%) respectively was obtained on a sample by sample basis. A novel semi-supervised model allocation approach is also proposed, allowing new unknown modes to be learnt in real time.

Reliability is a fundamental requirement in aircraft safety-critical equipments. Its pursuing involves the adoption of protective design concepts such as fault-tolerant or redundant approaches, aiming to minimize mission failure probabilities. Multi-phase motor drives are gaining a growing interest to this extent, because they permit a boost in torque and power density, allowing the design of very compact high efficiency drives with intrinsic fault-tolerant capabilities. This paper presents a five-phase permanent magnet brushless motor drive developed for an aircraft flap actuator application. The motor is designed to satisfy the load specifications with one or two phases open or with a phase short circuited, while a failure in the rotor position sensors is remedied through a sensorless strategy. Design studies aiming to predict the faulty mode performance in case of different remedial strategies are presented. Experimental tests on the drive prototype are included, which confirm its capability to satisfy the planned degraded modes of operation.

Model order estimation is fundamental in the system identification process. In this paper, we generalize a previous multivariate autoregressive (AR) model order estimation method (J. Lardies and N. Larbi, ?A new method for model order selection and model parameter estimation in time domain,? J. Sound Vibr., vol. 245, no. 2, 2001) to include multivariate autoregressive moving average (ARMA) models and propose a modified model order selection criterion. We discuss the performance analysis of the proposed criterion and show that it has a lower error probability for model order selection when compared to the criterion of G. Liang ?ARMA model order estimation based on the eigenvalues of the covariance matrix,?IEEE Trans. Signal Process., vol. 41, no. 10, pp. 3009-03009, Oct. 1993). A Monte-Carlo (MC) analysis of the model order selection performance under different noise variations and randomized model parameters is performed, allowing the MC results to be generalized across model parameter values and various noise levels. Finally we validate the model for both simulated data and real electroencephalographic (EEG) data by spectral fitting, using the model order selected by the proposed technique as compared to that selected by Akaike's Information Criterion (AIC). We demonstrate that with the proposed technique a better fit is obtained.

Summarization: The back-projected independent components (BICs) of single-trial, auditory P300 and contingent negative variation (CNV) evoked potentials (EPs) were derived using independent component analysis (ICA) and cluster analysis. The method was tested in simulation including a study of the electric dipole equivalents of the signal sources. P300 data were obtained from healthy and Alzheimer's disease (AD) subjects. The BICs were of approximately 100 ms duration and approximated positive- and negative-going half-sinusoids. Some positively and negatively peaking BICs constituting the P300 coincided with known peaks in the averaged P300. However, there were trial-to-trial differences in their occurrences, particularly where a positive or a negative BIC could occur with the same latency in different trials, a fact which would be obscured by averaging them. These variations resulted in marked differences in the shapes of the reconstructed, artefact-free, single-trial P300s. The latencies of the BIC associated with the P3b peak differed between healthy and AD subjects (p < 0.01). More reliable evidence than that obtainable from single-trial or averaged P300s is likely to be found by studying the properties of the BICs over a number of trials. For the CNV, BICs corresponding to both the orienting and the expectancy components were found. Παρουσιάστηκε στο: Physiological Measurement

Much of the development in model-based fault detection techniques for dynamic stochastic systems has relied on the system model being linear and the noise and disturbances being Gaussian. Linearized approximations have been used in the non-linear systems case. However, linearization techniques, being approximate, tend to suffer from poor detection or high false alarm rates. A novel particle filtering based approach to fault detection in non-linear stochastic systems is developed here. One of the appealing advantages of the new approach is that the complete probability distribution information of the state estimates from particle filter is utilized for fault detection, whereas, only the mean and covariance of an approximate Gaussian distribution are used in a coventional extended Kalman filter-based approach. Another advantage of the new approach is its applicability to general non-linear system with non-Gaussian noise and disturbances. The effectiveness of this new method is demonstrated through Monte Car...

An adaptive control technique, using dynamic structure Gaussian radial basis function neural networks, that grow in time according to the location of the system's state in space is presented for the affine class of nonlinear systems having unknown or partially known dynamics. The method results in a network that is "economic" in terms of network size, for cases where the state spans only a small subset of state space, by utilizing less basis functions than would have been the case if basis functions were centered on discrete locations covering the whole, relevant region of state space. Additionally, the system is augmented with sliding control so as to ensure global stability if and when the state moves outside the region of state space spanned by the basis functions, and to ensure robustness to disturbances that arise due to the network inherent approximation errors and to the fact that for limiting the network size, a minimal number of basis functions are actually being used. Adaptation laws and sliding control gains that ensure system stability in a Lyapunov sense are presented, together with techniques for determining which basis functions are to form part of the network structure. The effectiveness of the method is demonstrated by experiment simulations.

This paper presents a five-phase switched reluctance motor designed to satisfy the requirements of flap actuators in medium size aircrafts, a real example of the more electric aircraft trend. In normal conditions the machine operates with two phases conducting simultaneously but it is designed to satisfy the load specifications also with one or two phases open as consequence of fault remedial strategies. A finite-element study, aiming to predict both the healthy and faulty-mode performance, is presented. The mean torque vs. current capability and the torque ripple are investigated and optimum commutation angles are evaluated in static conditions. Experimental tests on the motor prototype are included, which confirm its capability to satisfy the planned degraded modes of operation and validate the design.

This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot., peer-reviewed

In this primer, we give a review of the inverse problem for EEG source localization. This is intended for the researchers new in the field to get insight in the state-of-the-art techniques used to find approximate solutions of the brain sources giving rise to a scalp potential recording. Furthermore, a review of the performance results of the different techniques is provided to compare these different inverse solutions. The authors also include the results of a Monte-Carlo analysis which they performed to compare four non parametric algorithms and hence contribute to what is presently recorded in the literature. An extensive list of references to the work of other researchers is also provided. This paper starts off with a mathematical description of the inverse problem and proceeds to discuss the two main categories of methods which were developed to solve the EEG inverse problem, mainly the non parametric and parametric methods. The main difference between the two is to whether a fixed number of dipoles is assumed a priori or not. Various techniques falling within these categories are described including minimum norm estimates and their generalizations, LORETA, sLORETA, VARETA, S-MAP, ST-MAP, Backus-Gilbert, LAURA, Shrinking LORETA FOCUSS (SLF), SSLOFO and ALF for non parametric methods and beamforming techniques, BESA, subspace techniques such as MUSIC and methods derived from it, FINES, simulated annealing and computational intelligence algorithms for parametric methods. From a review of the performance of these techniques as documented in the literature, one could conclude that in most cases the LORETA solution gives satisfactory results. In situations involving clusters of dipoles, higher resolution algorithms such as MUSIC or FINES are however preferred. Imposing reliable biophysical and psychological constraints, as done by LAURA has given superior results. The Monte-Carlo analysis performed, comparing WMN, LORETA, sLORETA and SLF, for different noise levels and different simulated source depths has shown that for single source localization, regularized sLORETA gives the best solution in terms of both localization error and ghost sources. Furthermore the computationally intensive solution given by SLF was not found to give any additional benefits under such simulated conditions.

A measurement of the drift velocity versus electric field in GaAs has been determined for electric fields between 15 and 90 kV/cm. The experimental values were obtained from the measurement of the current‐voltage characteristic of a Gunn diode, done during the transit time of a domain.

Ion implantation of indium in silicon has been studied at 30 keV both in random and in channeling conditions. Implantations were performed at room temperature with doses ranging from 1×1012 to 1×1015 ions/cm2; surface carrier concentration versus anneal temperature curves were obtained and compared with the behavior of other group III elements. The anneal behavior of the above‐mentioned implants after anneal at 700°C and subsequent tin implantation is also discussed.

The possible contribution to urinary mutagenicity of occupational exposures in the rubber industry was studied by assaying the urine concentrates of 72 workmen (44 smokers) employed in a tyre plant. Twenty three clerks (16 smokers) engaged in the administrative department of the same factory served as presumptive unexposed controls. XAD-2 resin concentrates of urine samples were assayed in the plate incorporation test and in the microtitre fluctuation assay with Salmonella typhimurium strains TA1535, TA98, and TA100. Furthermore, the in vitro mutagenicity of the major raw materials in use at the plant was determined in the plate incorporation assay with S typhimurium strains TA1535, TA1537, TA98, and TA100. The results obtained from the urinary mutagenicity study show that smoking habits, but not occupation, were statistically significantly related to the appearance of a urinary mutagenicity that was detectable with strain TA98. A possible synergistic effect of occupation with smoking was observed among tyre builders who were also smokers. The study of the raw materials showed that three technical grade materials were weakly active as mutagens in strain TA98 in the absence (poly-p-dinitrosobenzene) or in the presence of metabolic activation (mixed diaryl-p-phenylendiamines and tetramethyltiuram disulphide). The latter chemical was also weakly active in strain TA100.