Sensory analysis of polystyrene packaging material taint in cocoa powder for drinks and chocolate flakes

Polystyrene packaging material taint was sensorily evaluated in cocoa powder for drinks and chocolate flakes using short-cut signal detection measures on differences between control and test samples and on recognition of styrene. No differences were observed in cocoa powder for drinks and plain chocolate flakes treated with 0.5 dm2 polystyrene of 1 mm thickness. However, differences were detected in milk chocolate flakes and plain chocolate flakes, which were in contact with a larger area or thicker polystyrene packaging material. The latter results were confirmed by the styrene recognition test, so polystyrene is a potential source of off-flavour for chocolate products. The amount of residual styrene in the polystyrene used was about 320 ppm, while the amounts of styrene ranged from 7 to 132 ppb in cocoa drinks and from 414 to 1447 ppb in chocolate flakes.     

An Analysis of Scheduling Policies In Multiechelon Production Systems

Results of a simulation study of the economics of frequency of rescheduling Material Requirements Planning (MRP) systems are presented for a single-product, two-stage system in which demand is uncertain. The results indicate that for systems with moderate demand uncertainty, frequent rescheduling to maintain customer service may be uneconomical when compared with the alternative of more stable schedules in conjunction with safety stock. This result arises primarily because the cost of “emergency” production setups which occur when rescheduling is frequent exceeds the cost of safety stock required to “protect” stable schedules.     

Online and Offline Rotary Regression Analysis of Torque Estimator for Switched Reluctance Motor Drives

A new torque estimator for switched reluctance motor (SRM) drives based on 2-D rotary regression analysis is presented in this paper. The proposed torque estimator is composed of a bicubic regressive polynomial as a function of rotor position and input current. The regressive coefficients can be computed offline or online from the torque characteristics acquired either experimentally or from numerical computation. Furthermore, a torque estimation method by taking mutual coupling into consideration is proposed. It can be seen that the estimated and experimentally obtained self-coupling and mutual-coupling torque characteristics are in good agreement with each other. In addition, the dynamic torque waveforms with and without the mutual coupling, estimated by the proposed estimator, are found to be virtually the same as those obtained from the bicubic spline interpolation for SRM drives with single-pulse voltage, hysteresis current chopping, as well as with voltage pulse width modulation control. The success of all the case studies being reported is a good validation of the usefulness and accuracy of the proposed real-time torque estimator that, as described in this paper, can be used to quickly estimate the instantaneous output torque of SRM drives.     

3D velocity from 3D Doppler radial velocity

We present local least squares and regularization frameworks for computing 3D velocity (3D optical flow) from 3D radial velocity measured by a Doppler radar. We demonstrate the performance of our algorithms quantitatively on synthetic radial velocity data and qualitatively on real radial velocity data, obtained from the Doppler radar at Kurnell Radar station, Botany Bay, New South Wales, Australia. Radial velocity can be used to predict the future positions of storms in sequences of Doppler radar datasets.© 2005 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 15, 189–198, 2005     

Ennoblement of stainless steel in natural seawater – A new explanation

The ennoblement of corrosion potential (E_corr) of passive metal immersed in seawater was investigated with electrochemical technology and epifluorescence microscopy. The in situ observation showed that the bacteria number increased on the metal surface according to an exponential law which was in the same way with the ennoblement of E_corr. At the same time, the anodic polarization current of high‐Mo stainless steel decreased in the initial days. According to the mix‐potential theory and the characteristics of polarization curves of high‐Mo steel in natural seawater, the ennoblement of corrosion potential may be induced by the decrease of the passive current density.     

智能化使汽车更安全

新的特性必须更加智能,在增加价值的同时不会分散驾驶者的注意力和增加事故的风险。     

Entropy of multidimensional cellular automata

Since the topological entropy of a vast class of two-dimensional cellular automata (CA) is infinite, of interest is the possibility to renormalize it so that to obtain a positive finite value. We find the asymptotics of the information function of a multidimensional CA and, accordingly, introduce the renormalized topological entropy as a coefficient of this asymptotics. We describe some properties of the introduced quantity, in particular, its positivity for CA of the type of “The Game of Life.” Also, we give an example of an explicit evaluation of this parameter for a particular cellular automaton.     

Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification E-Algorithm

Power distribution systems have been significantly affected by many outage-causing events. Good fault cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real-world data sets often degrades the fault cause identification performance. In this paper, the E-algorithm, which is extended from the fuzzy classification algorithm by Ishibuchi to alleviate the effect of imbalanced data constitution, is applied to Duke Energy outage data for distribution fault cause identification. Three major outage causes (tree, animal, and lightning) are used as prototypes. The performance of E-algorithm on real-world imbalanced data is compared with artificial neural network. The results show that the E-algorithm can greatly improve the performance when the data are imbalanced