Optical waveguiding and birefringence properties of sputtered zinc oxide (ZnO) thin films on glass

Thin (≈1 μm), waveguiding and c-axis oriented ZnO films of good optical quality have been fabricated on corning glass substrates by r.f. magnetron reactive sputtering without substrate heating. The optical parameters of the films deposited in different O₂:Ar sputtering gas mixtures were found to vary. The extraordinary and ordinary refractive indices (n_e and n_o respectively) of the ZnO film grown in 60% O₂ and 40% Ar were found to be the highest (n_e=1.9876, n_o=1.9692) and closest to bulk single crystal values, and the birefringence of the film was ≈0.018. The films were annealed at 380 °C in air for 1 h, as a result of which the crystalline quality of the films was found to improve with increase in X-ray density and decrease in stress. While the refractive index decreased, the propagation loss was lowered substantially (3–5 dB/cm) as a result of annealing. The annealed zinc oxide film with minimum stress exhibited lowest loss (3 dB/cm) and highest birefringence (≈0.018). This indicated a correlation between propagation loss and stress.     

Mono- and oligosaccharides in fifteen Vicia faba L. cultivars

Fresh and dry mature seeds of fifteen cultivars or lines of faba bean were compared with respect to their mono- and oligosaccharide contents, in an attempt to determine the possibilities for selection in a breeding programme on the basis of some chemical characteristics. The raffinose content of the whole dry seed ranged from 0·12% to 0·29%, the stachyose content between 0·46% and 1·02%, the verbascose content, the principal α-galactoside, from 0·82% to 1·61% on a dry matter basis. These components occurred in seeds with more than 30% of dry matter, while fructose, glucose and sucrose regularly decreased during seed development.     

Improving the integration of piece wise linear representation and weighted support vector machine for stock trading signal prediction

The integrated piecewise linear representation (PLR) and weighted support vector machine (PLR-WSVM) has shown success in the prediction of stock trading signals. Meanwhile drawbacks of PLR-WSVM exist particularly in a real world setting. For example, the profitability using PLR-WSVM is unstable, it is not reasonable to specify same threshold value for all stocks in PLR, and critical errors in trading signals may significantly reduce the profit. In this paper, we conduct a set of improvements to PLR-WSVM. First, most of absolute technical indicators in input variables are substituted with relative indicators since the relative indicators are generally more helpful in predicting trading signals. Second, a four-class prediction problem is converted into a two-class problem in which one class is a turning point (TP) and the other is an ordinary point. And prior domain knowledge is exploited to identify either buying or selling signals from TPs. Thirdly, a delay-one-day strategy (DODS) is proposed to further correct the predicted trading signals. DODS reduces the critical errors occurring to PLR-WSVM. Finally, a procedure for selecting a threshold in PLR is provided. The threshold is automatically selected by a given percentage of TPs in a training set. The percentage of TPs is easier to understand by investor compared with the threshold. We conduct experimental study over 20 stocks, and the results confirm the expected performance of the improved PLR-WSVM. More importantly, the improved PLR-WSVM provides steady profits in average over the stocks of interest with accepted retracements.     

Learning machines: Rationale and application in ground-level ozone prediction

Multilayer perceptron (MLP) and support vector machine (SVM), two popular learning machines, are increasingly being used as alternatives to classical statistical models for ground-level ozone prediction. However, employing learning machines without sufficient awareness about their limitations can lead to unsatisfactory results in modeling the ozone evolving mechanism, especially during ozone formation episodes. With the spirit of literature review and justification, this paper discusses, with respect to the concerning of ozone prediction, the recently developed algorithms/technologies for treating the most prominent model-performance-degradation limitations. MLP has the “black-box” property, i.e., it hardly provides physical explanation for the trained model, overfitting and local minima problems, and SVM has parameters identification and class imbalance problems. This commentary article aims to stress that the underlying philosophy of using learning machines is by no means as trivial as simply fitting models to the data because it causes difficulties, controversies or unresolved problems. This article also aims to serve as a reference point for further technical readings for experts in relevant fields.     

保证闭环系统鲁棒稳定性的干扰观测器系统性设计方法

研究带有干扰观测器(Disturbance observer,DOB)的反馈控制系统对模型不确定性鲁棒稳定的充分条件,在此基础上,选取满足此充分条件的加权函数,使得标准H∞干扰观测器设计方法保证对受控对象参数变化的鲁棒稳定性.提出了在H∞干扰观测器设计中兼顾鲁棒性设计指标和结构约束的频率加权函数的选取方法.利用加权函数选取的自由度,在干扰观测器低通滤波器设计中,实现Q—滤波器在截止频率上的高峰幅度与干扰抑制性能之间的最佳折中,使得干扰观测器在满足其幅度指标的条件下,具有最优干扰抑制性能.实验结果表明该方法保证了闭环反馈系统的鲁棒稳定性,同时,具有实现其他设计指标的自由度.     

Characterization of (CoCr/Pt)20 Namomultilayers Preparation by Magnetron Sputtring

(CoCr/Pt) 20 nanomultilayers with Pt underlayers are prepared by DC magnetron sputtering and the effect of sputtering Ar gas pressure on microstructure and magnetic properties of (CoCr/Pt)20 nanomultilayers is studied.The results show that sputtering Ar gas pressure has a great effect on microstructure,perpendicular magnetic anisotropy,and coercivity of (CoCr/Pt)20 nanomultilayers.For all samples,the effective magnetic anisotropy constant Keff＞0 and all samples have perpendicular magnetic anisotropy.The X-ray diffraction patterns show that low angle X-ray diffraction peaks are very sharp.This confirms the good quality of the multilayers and the bilayer periodicity of films.With increasing of sputtering Ar gas pressure,perpendicular and in-plane coercivity of the samples increase,but the effective magnetic anisotropy constant decreases.The images of atomic force microscopy show that when the sputtering Ar gas pressure is increased,both average grain size and the surface roughness are increased,which lead to the increase of perpendicular coercivity and the decrease of effective magnetic anisotropy constant.     

On the capabilities and limitations of predictive,multi-zone combustion models for hydrogen-diesel dual fuel operation

Compared with traditional hydrocarbon fuels, hydrogen provides a high-energy content and carbon-free source of energy rendering it an attractive option for internal combustion engines. Co-combusting hydrogen with other fuels offers significant advantages with respect to thermal efficiency and carbon emissions.This study seeks to investigate the potential and limitations of multi-zone combustion models implemented in the GT-Power software package to predict dual fuel operation of a hydrogen-diesel common rail compression ignition engine. Numerical results for in-cylinder pressure and heat release rate were compared with experimental data. A single cylinder dual-fuel model was used with hydrogen being injected upstream of the intake manifold. During the simulations low (20 kW), medium (40 kW) and high (60 kW) load conditions were tested with and without exhaust gas recirculation (EGR) and at a constant engine speed of 1500 rpm. Both single and double diesel injection strategies were examined with hydrogen energy share ratio being varied from 0 to 57% and 0–42 respectively. This corresponds to a range in hydrogen air-equivalence ratios of approximately 0–0.29.The results show that for the single-injection strategy, the model captures in-cylinder pressure and heat release rate with good accuracy across the entire load and hydrogen share ratio range. However, it appears that for high hydrogen content in the charge mixture and equivalence ratios beyond the lean flammability limit, the model struggles to accurately predict hydrogen entrainment leading to underestimated peak cylinder pressures and heat release rates. For double-injection cases the model shows good agreement for hydrogen share ratios up to 26%. However, for higher energy share ratios the issue of erroneous hydrogen entrainment into the spray becomes more accentuated leading to significant under-prediction of heat release rate and in-cylinder pressure.