Characteristics of tiger nut milk: effects of milling

A standard method for the extraction of tiger nut milk has been introduced. It has been shown that, although milling duration improves the yield of tiger nut milk solids and its nutrient composition, there is a quantifiable loss of nutrient in the pressing residue during milk extraction. Milling duration improved the colloidal stability of the milk against creaming during 16 h of storage. A higher milling intensity resulted in the aggregation of biological polymers which resulted in colloidal destabilisation. Milling improved the lightness and stability and reduced browning rate of the tiger nut milk during storage. This report is important for the production of tiger nut milk of consistent and comparable characteristics. Milling has been introduced as a processing method for the qualitative and quantitative modulation of the properties of tiger nut milk. It is recommended to develop further strategies to improve the colloidal stability of tiger nut milk as a beverage.     

Quality and Emulsion Stability of Milk from Ettawah Crossed Bred Goat During Frozen Storage

Goat milk has specific chemical composition and physical properties. The purpose of this study was to investigate the change of milk quality and emulsion stability during 60 d frozen storage. Milk sample was taken from three Ettawah Crossedbred goats that were divided into three groups. Samples were frozen and stored for 0, 30 and 60 days. At the end of each storage periode, milk sample was thawed in the refrigerator and analyzed for total number of bacteria, chemical (acidity, pH, free fatty acids), physical (alcohol test, clot on boiling test) quality, and emulsion stability. The microbiological and chemical data were analyzed statistically using one way ANOVA, whereas physical quality and emulsion stabilty were expressed qualitatively. There were no change in the total bacteria, acidity, pH and free fatty acid (FFA) of milk during storage, whereas the assessment by 70% alcohol showed positive since 0 d. Emulsions stability changed after 30 d of storage. While, the clot on boiling (COB) test of milk was positive at 60 d of storage. Recommendation is frozen storage of goat milk should not longer than 30 d.     

LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

一种基于空间到达角的卫星电子侦察信号分选方法

在建立简化的卫星电子侦察空间模型的基础上，提出了一种利用空间到达角分选卫星电子侦察信号的新方法。通过仿真实验验证了这种方法的可行性。该方法可用于密集信号的预处理。     

低密度微泡沫压井液的研究与应用

吐哈油田部分区块地层压力系数小于0.9,常规水基压井液对储层伤害大,若使用油基压井液成本高,环境污染严重。通过实验优选出了一种低密度水基微泡沫压井液。该压井液具有密度低、泡沫强度高、稳定性好、携砂能力强等优点。现场应用表明,低密度微泡沫压井液稳定时间大于48 h,密度在0.70~0.99 g/cm3之间可调,抗油污染能力强,抗油大于8%,抗温在100℃以上,岩心污染后渗透率恢复值大于80%;并且施工方便,成本低,具有储层保护能力,使用微泡沫压井液的井表皮系数在0.20~2.34之间。     

NSA-500-1型氩弧焊机VD9不同接法对引弧和稳弧的影响

从一起NSA－500－1型氩弧焊机故障，分析其高压脉冲旁路二极管VD9不同接法对引弧、稳弧及设备安全的影响。     

T8钢－聚有机硅氧烷仿生减粘降阻复合涂层的特性

研究了Ｔ８钢－聚有机硅氧烷仿生减粘降阻复合涂层的表面润湿性、磨料磨损特性及对土壤的减粘降阻性能与金属材料相比，仿生复合涂层的表面憎水性显著提高，水在其表面上的接触角达９２°；与４５钢相比，其磨料磨损的体积相对耐磨系数为６３％，降阻率达１５．２２％～２２．２７％     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Breakdown characteristics of oil and paper insulation for a very fast transient voltage

This paper describes the dielectric breakdown characteristics of oil and oil‐impregnated paper for very fast transient (VFT) voltages. Blumlein circuits generate VFT voltages of 60 and 300 ns in a pulse width that simulates disconnecting switching surges in gas‐insulated switch gears. We measured the breakdown voltages of needle‐to‐plane, plane‐to‐plane oil gaps and several pieces of paper between plane electrodes for VFT and lightning impulse voltages. The measured data were formulated in V‐t characteristics and Weibull probability distributions. The inclination n of V‐t characteristics of insulating paper is 150, which is less than n = 13.7 of the plane‐to‐plane oil gap in the VFT time range. The shape parameters of Weibull distribution obtained in this study show that the scattering of breakdown voltages of paper is much less than that of oil. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 141(4): 16–24, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10043