Effect of magnesium on the composition,microstructure and mechanical properties of carbon fibres

This work was undertaken in order to provide more detailed information on the chemical and mechanical behaviour of carbon fibres during the elaboration of graphite-magnesium composite materials. For this purpose, PAN-based T300, pitch-based P55 and P100 carbon fibres were isothermally heat treated, at temperatures ranging from 450 to 700 °C, under a saturated vapour pressure of magnesium. The composition, microstructure and tensile strength of the resulting samples were characterized by chemical and electron probe microanalysis, Raman spectrometry, X-ray diffraction and mechanical test of single filaments. From the results obtained, it has been concluded that highly graphitized fibres such as pitch-based P55 or P100 are not affected by long-time annealing in the presence of magnesium vapour, whereas impure and disorded fibres such as PAN-based T300 undergo some chemical and microstructural modifications decreasing their mechanical properties.     

Orbital volume measurement in the management of pure blowout fractures of the orbital floor

With the recent advent of accurate orbital volume assessment by computed tomography, a retrospective analysis was made of 31 patients with 'pure' blowout fracture of the orbital floor, managed either surgically or conservatively, to determine whether orbital volume measurement could provide an additional parameter of use in the management of such fractures. There was a significant difference in orbital volume discrepancy between patients managed surgically or conservatively suggesting that this investigation may be of use in decision making on surgical intervention in patients with orbital blowout fractures.     

Error Concealment Based on Semantic Prioritization with Hardware‐Based Face Tracking

With video compression standards such as MPEG‐4, a transmission error happens in a video‐packet basis, rather than in a macroblock basis. In this context, we propose a semantic error prioritization method that determines the size of a video packet based on the importance of its contents. A video packet length is made to be short for an important area such as a facial area in order to reduce the possibility of error accumulation. To facilitate the semantic error prioritization, an efficient hardware algorithm for face tracking is proposed. The increase of hardware complexity is minimal because a motion estimation engine is efficiently re‐used for face tracking. Experimental results demonstrate that the facial area is well protected with the proposed scheme.     

Birefringence in benzocyclobutene strip optical waveguides

We report the fabrication of benzocyclobutene strip optical waveguides and the measurement of their birefringence properties. To take into account the stress-induced birefringence in the waveguide, we generalize the formulas reported previously for the analysis of strip waveguides. Our experimental results are shown to agree closely with the theoretical calculation. The condition for achieving zero modal birefringence by control of the aspect ratio of the strip of the waveguide is highlighted. The dependence of the birefringence in the waveguides on the temperature is also measured and discussed.     

Reliability evaluation and optimisation of imperfect inspections for a component with multi-defects

In this paper, a model is developed to evaluate the reliability and optimise the inspection schedule for a multi-defect component. The model uses a non-homogeneous Poisson process (NHPP) method in conjunction with a delay time approach. The inspections are designed to detect any defects in the component, however it can be imperfect. The defect is a definable state before a functional failure happens to the component. Occurrences of defects are assumed to follow an NHPP and a defect will be minimally repaired if it is identified during an inspection. It is shown that the failures occurring in an interval of inspection will also follow an NHPP. The situation of imperfect inspections and non-constant inspection intervals are considered. An algorithm is presented to optimise the intervals of inspections in order to maximise the reliability of the component, and the properties of the algorithm are shown. A numerical example with parametric study is given to show the performance of the model and the algorithm.     

Signal classification through multifractal analysis and complex domain neural networks

This paper describes a system capable of classifying stochastic self-affine nonstationary signals produced by nonlinear systems. The classification and the analysis of these signals are important because these are generated by many real-world processes. The first stage of the signal classification process entails the transformation of the signal into the multifractal dimension domain, through the computation of the variance fractal dimension trajectory (VFDT). Features can then be extracted from the VFDT using a Kohonen self-organizing feature map. The second stage involves the use of a complex domain neural network and a probabilistic neural network to determine the class of a signal based on these extracted features. The results of this paper show that these techniques can be successful in creating a classification system which can obtain correct classification rates of about 87% when performing classification of such signals without knowing the number of classes.     

Managing Clinical Use of High-Alert Drugs: A Supervised Learning Approach to Pharmacokinetic Data Analysis

Drug-related problems, particularly those that result from sub- or overtherapeutic doses of high-alert medications, have become a growing concern in clinical medicine. In this paper, we use a model-tree-based regression technique (namely, M5) and support vector machine (SVM) for regression to develop learning-based systems for predicting the adequacy of a vancomycin regimen. We empirically evaluate each system's accuracy in predicting patients' peak and trough concentrations in different clinical scenarios characterized by renal functions and regimen types. Our data consist of 1099 clinical cases that were collected from a major tertiary medical center in southern Taiwan. We also examine the use of bagging for enhancing the prediction power of the respective systems and include in our evaluation a salient one-compartment model for performance benchmark purposes. Overall, our evaluation results suggest that both M5 and SVM are significantly more accurate than the benchmark one-compartment model in predicting patients' peak and trough concentrations across all investigated clinical scenarios. M5 appears to benefit considerably from bagging, which has a positive but seemingly smaller effect on SVM. Taken together, our findings indicate supervised learning techniques that are capable of effectively supporting clinicians' use of vancomycin or similar high-alert drugs in their patient care and management.     

Effect of spray nozzle design on liquid-solid contact in fluidized beds

In industrial fluid cokers the feedstock, consisting of heavy bituminous hydrocarbons, is atomized with steam and injected into a hot fluidized bed of coke. Good and uniform contact of the liquid droplets with the solid particles is required to provide heat for the cracking reactions while minimizing mass transfer effects. Experiments in a pilot plant coker have suggested that the initial particle/liquid mixing, in the spray jet, is rather poor. Experiments in a X-ray scanner showed that liquid droplets and entrained particles accumulate just below the tip of the jet plume to form agglomerates.An experimental technique was used to quantitatively determine the quality of mixing with a variety of nozzle configurations including several novel designs. By improving spray stability, redistributing liquid droplets to the solids-rich region of the jet and increasing the surface area of the gas-liquid jet-fluidized bed interface, liquid/solid contact is improved.