Fabrication of advanced Bragg gratings with complex apodization profiles by use of the polarization control method

The polarization control method offers a flexible, robust, and low-cost route for the parallel fabrication of gratings with complex apodization profiles including several discrete phase shifts and chirp. The performance of several test gratings is evaluated in terms of their spectral response and compared with theoretical predictions. Short gratings with sidelobe-suppression levels in excess of 32 dB and transmission dips lower than 80 dB have been realized. Finally, most of the devices fabricated by the polarization control method show comparable quality to gratings manufactured by far more complex methods.     

Multilevel optimization algorithms in computer aided production control in process industry

The use of optimization techniques in production control is discussed. Two optimization problems in relation to typical process industry complexes are formulated. A modified version of Tamura's algorithm is reviewed. The promising performance of the computerised algorithms is illustrated by numerical results. DISPATCHER, a practical operative decision support system, is described.     

Experimental investigation of a pilot-scale jet bubbling reactor for wet flue gas desulphurisation

In the present work, an experimental parameter study was conducted in a pilot-scale jet bubbling reactor for wet flue gas desulphurisation (FGD). The pilot plant is downscaled from a limestone-based, gypsum producing full-scale wet FGD plant. Important process parameters, such as slurry pH, inlet flue gas concentration of SO₂, reactor temperature, and slurry concentration of Cl⁻ have been varied. The degree of desulphurisation, residual limestone content of the gypsum, liquid phase concentrations, and solids content of the slurry were measured during the experimental series.The SO₂ removal efficiency increased from 66.1% to 71.5% when the reactor slurry pH was changed from 3.5 to 5.5. Addition of Cl⁻ (in the form of CaCl₂·2H₂O) to the slurry increased the degree of desulphurisation to above 99%, due to the onset of extensive foaming, which substantially increased the gas-liquid contact area. An increase in the inlet flue gas SO₂ concentration from 502 to led to a decrease in the SO₂ removal efficiency from 80.1% to 69.4%. A temperature increase from 296 to caused a reduction in the degree of desulphurisation from 69.4% to 68.1%, but this result is almost within the experimental uncertainty. The residual limestone level in the gypsum formed increased with increasing values of reactor slurry pH, inlet flue gas SO₂ concentration, and slurry concentration of Cl⁻.     

薄膜晶体硅太阳能电池的潜力

如果效率和成本目标能够实现，薄膜晶体硅太阳能电池有潜力替代目前在光伏市场上占主导地位的多晶硅太阳能电池。     

Time series classification for the prediction of dialysis in critically ill patients using echo statenetworks

Objective: Time series often appear in medical databases, but only few machine learning methods exist that process this kind of data properly. Most modeling techniques have been designed with a static data model in mind and are not suitable for coping with the dynamic nature of time series. Recurrent neural networks (RNNs) are often used to process time series, but only a few training algorithms exist for RNNs which are complex and often yield poor results. Therefore, researchers often turn to traditional machine learning approaches, such as support vector machines (SVMs), which can easily be set up and trained and combine them with feature extraction (FE) and selection (FS) to process the high-dimensional temporal data. Recently, a new approach, called echo state networks (ESNs), has been developed to simplify the training process of RNNs. This approach allows modeling the dynamics of a system based on time series data in a straightforwardway.The objective of this study is to explore the advantages of using ESN instead of other traditional classifiers combined with FE and FS in classification problems in the intensive care unit (ICU) when the input data consists of time series. While ESNs have mostly been used to predict the future course of a time series, we use the ESN model for classification instead. Although time series often appear in medical data, little medical applications of ESNs have been studiedyet.Methods and material: ESN is used to predict the need for dialysis between the fifth and tenth day after admission in the ICU. The input time series consist of measured diuresis and creatinine values during the first 3days after admission. Data about 830 patients was used for the study, of which 82 needed dialysis between the fifth and tenth day after admission. ESN is compared to traditional classifiers, a sophisticated and a simple one, namely support vector machines and the naive Bayes (NB) classifier. Prior to the use of the SVM and NB classifier, FE and FS is required to reduce the number of input features and thus alleviate the curse dimensionality. Extensive feature extraction was applied to capture both the overall properties of the time series and the correlation between the different measurements in the time series. The feature selection method consists of a greedy hybrid filter-wrapper method using a NB classifier, which selects in each iteration the feature that improves prediction the best and shows little multicollinearity with the already selected set. Least squares regression with noise was used to train the linear readout function of the ESN to mitigate sensitivity to noise and overfitting. Fisher labeling was used to deal with the unbalanced data set. Parameter sweeps were performed to determine the optimal parameter values for the different classifiers. The area under the curve (AUC) and maximum balanced accuracy are used as performance measures. The required execution time was also measured.Results: The classification performance of the ESN shows significant difference at the 5% level compared to the performance of the SVM or the NB classifier combined with FE and FS. The NB+FE+FS, with an average AUC of 0.874, has the best classification performance. This classifier is followed by the ESN, which has an average AUC of 0.849. The SVM+FE+FS has the worst performance with an average AUC of 0.838. The computation time needed to pre-process the data and to train and test the classifier is significantly less for the ESN compared to the SVM andNB.Conclusion: It can be concluded that the use of ESN has an added value in predicting the need for dialysis through the analysis of time series data. The ESN requires significantly less processing time, needs no domain knowledge, is easy to implement, and can be configured using rules ofthumb.     

The effect of pressure on GRIN lenses

The changes of the optical power of Gradient Index (GRIN) lenses occurring in hydrostatic pressures of the range of 0-2 GPa are investigated. The measurements of the position of the waist of the semiconductor laser beam revealed the increase of the optical power of the lenses with increasing pressure. The use of the special plano-concave lenses insensitive to the changes of the refractive index of the pressure medium allowed to attribute the changes to the increasing index gradient in GRIN material. The effect has been explained within the frame of Mueller’s theory of photoelasticity. The findings have been then confirmed in experiments with the plano-planar and plano-convex lenses of the same materials.     

Emission control of nitrogen oxides in the oxy-fuel process

The interest in oxy-combustion as a method to capture carbon dioxide has increased drastically during recent years. The oxy-fuel process offers new process conditions and may take advantage of innovative techniques as well as of new ways to apply conventional measures for emission control. The present work reviews available techniques for controlling both the emission of nitrogen oxides (NO_x) to the atmosphere and the content of NO_x in the captured carbon dioxide. The results indicate that for a first generation of oxy-fuel power plants, conventional primary NO_x control should be sufficient to meet today's emission regulations, if based on emission per unit of fuel supplied. However, there are several opportunities for new methods of NO_x control in oxy-fuel plants, depending on future emission and storage legislation for carbon capture schemes. Improved understanding of the behaviour of nitric oxide and nitrogen dioxide during compression and condensation of carbon dioxide is needed, as well as improved knowledge on the influence of the parameters of oxy-combustion on nitrogen chemistry.