Synthesis and Characterization of Segmented Block Copolymers Based on Hydroxyl‐Terminated Liquid Natural Rubber and α,ω‐Diisocyanato Telechelics

Summary: Segmented block copolymers, consisting of non‐polar soft segments from hydroxyl‐terminated liquid natural rubber (HTNR) and polar hard segments from α,ω‐diisocyanato telechelics obtained by “criss‐cross”‐cycloaddition, have been synthesized. The block copolymer formation took place under relatively mild reaction conditions at 80 °C in dichloroethane in the presence of dibutyltin dilaurate as a catalyst. The resulting block copolymers were characterized by spectroscopic techniques (¹H NMR, FTIR, UV‐vis spectroscopy) as well as GPC for molar mass determination. The block copolymers were compression molded in a hot stage press, and the resulting samples were characterized by DSC and stress‐strain measurement. The solubility and phase morphology of the materials have also been studied.

Segmented block copolymer from HTNR and α,ω‐diisocyanato telechelics     

Modélisation Mathématique de la Décantation de la Boue Rouge

A good performance of the solid‐liquid unit operation is required for the economical exploitation of the Bayer process. A computational fluid dynamics (CFD) model simulating the operation of the last washing stage mud thickener of a large Canadian alumina plant is presented. The parametric study of the impact of changes in four parameters shows that the diameter of flocculated red mud particles, the feed flow rate and the radius of the feed well are critical parameters for the operation of the thickener.     

How the environment determines banking efficiency: a comparison of banking firms in Taiwan,Hong Kong,and Mainland China

This study uses the three‐stage data envelopment analysis (DEA) model to explore the true managerial efficiency of the banking firms in Taiwan, Hong Kong, and Mainland China. The empirical results indicate that the environmental conditions have a significant impact on banking efficiency. When the country‐specific situations are important factors in explaining efficiency difference, the common frontier estimates obtained by neglecting those factors can generate biased and overestimated inefficiency levels. With findings obtained from the slack variable analyses, the current study can provide inefficient banks with ways to reduce their input waste through the adjustment of input allocations. The findings also confirm the importance of the three‐stage DEA and its applications in determining the true managerial efficiencies of banks. Without the three‐stage DEA, the management could be misguided when making strategic decisions and conducting inappropriate resource allocation.     

M/M/1 retrial queue with working vacations

In this paper we introduce the new M/M/1 retrial queue with working vacations which is motivated by the performance analysis of a Media Access Control function in wireless systems. We give a condition for the stability of the model, which has an important impact on setting the retrial rate for such systems. We derive the closed form solution in equilibrium for the retrial M/M/1 queue with working vacations, and we also show that the conditional stochastic decomposition holds for this model as well.     

Predictive models for emission of hydrogen powered car using various artificial intelligent tools

This paper investigates the use of artificial intelligent models as virtual sensors to predict relevant emissions such as carbon dioxide, carbon monoxide, unburnt hydrocarbons and oxides of nitrogen for a hydrogen powered car. The virtual sensors are developed by means of application of various Artificial Intelligent (AI) models namely; AI software built at the University of Tasmania, back-propagation neural networks with Levenberg–Marquardt algorithm, and adaptive neuro-fuzzy inference systems. These predictions are based on the study of qualitative and quantitative effects of engine process parameters such as mass airflow, engine speed, air-to-fuel ratio, exhaust gas temperature and engine power on the harmful exhaust gas emissions. All AI models show good predictive capability in estimating the emissions. However, excellent accuracy is achieved when using back-propagation neural networks with Levenberg–Marquardt algorithm in estimating emissions for various hydrogen engine operating conditions with the predicted values less than 6% of percentage average root mean square error.     

Automated thermal fuse inspection using machine vision and artificial neural networks

Machine vision is an excellent tool for inspecting a variety of items such as textiles, fruit, printed circuit boards, electrical components, labels, integrated circuits, machine tools, etc. This paper presents an intelligent system that incorporates machine vision with artificial intelligent networks to automatically inspect thermal fuses. An effective inspection flow is proposed to detect four commonly seen defects, including black-dot, small-head, bur, and flake during the production of thermal fuses. Backpropagation neural networks and learning vector quantization performance is compared in detecting the bur defect because of its illegibility. Different numbers of defective samples were screened out from a production line in a case study company and used to demonstrate the efficacy of the proposed system. Currently, the proposed inspection system is operating at the case study company, replacing four to six human inspectors. The system not only ensures the quality of the thermal fuses produced, but also reduced the cost of manual visual inspection.     

A new solution for a queueing model of a manufacturing cell with negative customers under a rotation rule

In this paper, we consider a queueing model extension for a manufacturing cell composed of a machining center and several parallel downstream production stations under a rotation rule. A queueing model is extended with the arrival processes of negative customers to capture failures of production stations, reorganization of works and disasters in the manufacturing cell. We present an exact solution for the steady-state probabilities of the proposed queueing model. The solution does not require the approximation of the infinite sum. In addition, it provides an alternative way to compute the rate matrix for the matrix-geometric method as well.     

Electrostatic model for an asymmetric combdrive

This paper presents an analytical solution to the electrostatic actuation of an asymmetric combdrive in out-of-plane and torsional motions. The exact solutions to force in the out-of-plane motion and the integral for torque in the torsional motion are obtained. The dependence of the peak force on the thickness of the movable fingers and the amount of overlap of the combs is given in closed form. Using our model, the shift of the natural resonant frequency due to a dc bias is analyzed. Furthermore, our solution also applies to the in-plane motion of an in-plane interdigitated combdrive. We found that an in-plane interdigitated combdrive generates a constant force within 0.1% when the minimum initial engagement length of the combs is twice the separation gap     

A new procedure for determining specific filter cake resistance from filtration data

A new procedure has been developed for the determination of specific filter cake resistance from experimental filtration data. Unlike the conventional procedure which treats constant-pressure filtration data through the t/V vs. V plot and yields a single value of the average specific cake resistance (α_av) from a given experiment, this new procedure allows the establishment of the relationship of α_av vs. the cake compressive stress (p_s) over a range of p_s values. Results from the new procedures were compared with those obtained from the procedure based on the t/V vs. V plot as well as those from compression-permeability (C-P) measurements. Discussions on the possible improvement of the new procedure are also presented.