Tungsten(VI) oxide supported rhodium nanoparticles: Highly active catalysts in hydrogen generation from ammonia borane

Herein, we report the use of tungsten(VI) oxide (WO₃) as support for Rh⁰ nanoparticles. The resulting Rh⁰/WO₃ nanoparticles are highly active and stable catalysts in H₂ generation from the hydrolysis of ammonia borane (AB). We present the results of our investigation on the particle size distribution, catalytic activity and stability of Rh⁰/WO₃ catalysts with 0.5%, 1.0%, 2.0% wt. Rh loadings in the hydrolysis reaction. The results reveal that Rh⁰/WO₃ (0.5% wt. Rh) is very promising catalyst providing a turnover frequency of 749 min^?1 in releasing 3.0 equivalent H₂ per mole of AB from the hydrolysis at 25.0 °C. The high catalytic activity of Rh⁰/WO₃ catalyst is attributed to the reducible nature of support. The report covers the results of kinetics study as well as comparative investigation of activity, recyclability, and reusability of colloidal(0) nanoparticles and Rh⁰/WO₃ (0.5 % wt. Rh) catalyst in the hydrolysis reaction.     

Sediment Concentration and Its Prediction by Perceptron Kalman Filtering Procedure

Predictions of the discharge and the associated sediment concentration are very useful ingredients in any water resources reservoir design, planning, maintenance, and operation. Although there are many empirical relationships between the discharge and sediment concentration amounts, they need estimation of model parameters. Generally, parameter estimations are achieved through the regression method (RM), which has several restrictive assumptions. Such models are locally valid and their structures and parameter values are questionable from region to others. This paper proposes a new approach for sediment concentration prediction provided that there are measurements of discharge and sediment concentration. The basis of the methodology is a dynamic transitional model between successive time instances based on two variables, namely, discharge and sediment concentration measurements. The transition matrix elements are estimated from the measurements through a special form of the artificial neural networks as perceptrons. The sediment concentration predictions from discharge measurements are achieved through a perceptron Kalman filtering (PKF) technique. In the meantime, this technique also provides temporal predictions. A certain portion of the measurement sequence is employed for the model parameter estimations through training and the remaining part is used for the model verification. Detailed comparisons between RM and PKF approaches are presented and, finally, it is shown that the latter model works dynamically by simulating the observation scatter diagram in the best possible manner with smaller prediction errors. The application of the methodology is performed for the discharge and sediment concentration measurements obtained from the Mississippi River basin at St. Louis, Missouri. It is found that the PKF methodology has smaller average relative, root-mean-square, and absolute errors than RM. Furthermore, graphical representation, such as the scatter and frequency diagrams, indicated that the PKF approach has superiority over the RM.     

基于软件定义网络和移动边缘计算的车联网高效任务卸载方案

随着车联网(IoV)中车辆和智能应用数目的增加使计算密集型任务激增,传统架构难以满足用户需求。为解决车联网计算资源不足且分配不均匀、应用时延需求无法满足、任务能耗成本较高的问题,结合移动边缘计算(MEC)和软件定义网络(SDN),设计了一种从宏基站到MEC服务器到车辆的车联网架构中的高效任务卸载方案,并提出一种改进的低复杂度非支配排序遗传算法,优化任务卸载成本和MEC服务器的负载均衡率。实验仿真结果表明,相比于随机卸载,NO-MEC卸载,NO-I卸载,传统NSGA、NSGA-Ⅱ卸载,GA卸载,Q-learning卸载,DQN卸载方案,所提方案有着更低的卸载成本,更优的负载均衡率,得到近似最高的系统效用,能够给车联网中的车辆用户带来更优质的网络服务。     

Graphene oxide-containing isocyanate-based polyimide foams: Enhanced thermal stability and flame retardancy

Isocyanate-based graphene oxide-containing polyimide foams were synthesized by a semi-prepolymer method. In this method, while the first solution containing pre-polymer was derived from pyromellitic dianhydride and excess polymethylene polyphenylene isocyanate (PM200), the second solution contains dianhydride derivatives, water, catalysts, surfactants, and graphene oxide. PIFs were prepared with 0%, 0.25%, 0.50%, 0.75%, and 1% graphene oxide by weight, respectively. PIFs exhibited a minimum side reaction and urea generation was not seen for all PIFs instead of imide bonding. The addition of graphene oxide (GO) leads to a more close-packed structure. Therefore, crosslinking density and thermal stability of graphene oxide-containing polyimide foams increased. Upon the addition of 1% GO, almost seven times higher compression strength was obtained compared to neat PIFs. Also, LOI values supported the theory that thermally stable and flame retardant PIFs can be synthesized via the isocyanate-based process with GO.     

Some results on disturbance attenuation for Hamiltonian systems via direct discrete‐time design

The disturbance attenuation and robust disturbance attenuation problems for Hamiltonian systems in the discrete‐time setting are considered and some new results are presented. The new results are derived utilizing the recently presented dissipativity equality obtained by adding the dissipation rate function to the classical dissipativity inequality. A selection of the dissipation rate function yields new results. These results include a condition on the dissipation structure of the system to achieve the desired disturbance attenuation level and gives direct construction of optimal control laws for any desired disturbance attenuation level. The results remove the need to solve Hamilton–Jacobi–Isaacs inequalities. Copyright © 2014 John Wiley & Sons, Ltd.     

Robust delay‐dependent guaranteed cost controller design for uncertain nonlinear neutral systems with time‐varying state delays

In this paper, the problem of robust delay‐dependent guaranteed cost control for uncertain nonlinear neutral systems with time‐varying state delay is investigated. The control law is chosen to be a memoryless type one. Neither any model transformation nor bounding of any cross terms are utilized. The system under consideration may be subjected to both norm‐bounded uncertainties and nonlinear parameter perturbations. A delay‐dependent sufficient condition is obtained in terms of a matrix inequality for which a cone complementarity problem is introduced to provide a feasible solution set. Two numerical examples have been demonstrated to show the effective application of the proposed method. Copyright © 2009 John Wiley & Sons, Ltd.     

Functional Diversity,Absorptive Capability and Product Success: The Moderating Role of Project Complexity in New Product Development Teams

Absorptive capability appears to be an appealing concept in the technology and innovation management literature. Though absorptive capability attracts researchers from a variety of disciplines, team‐level empirical research on it is scant. In this study, we operationalized team absorptive capability as a multidimensional construct involving knowledge acquisition, assimilation and exploitation. This study also explores the moderating effect of project complexity between team absorptive capability and new product success. In studying the data from 239 new product development projects using partial least squares structural equation modelling, we found that team functional diversity is a significant determinant of team absorptive capability. Moreover, regarding the relationships between team absorptive capability and new product success, we uncovered that (i) new product success is dependent on the ability to understand the acquired knowledge, and (ii) the teams appear to be more cautious in putting the assimilated knowledge into practice to the extent that project complexity increases.     

A sliding mode observer for uncertain nonlinear systems based on multiple models approach

This paper presents a method of state estimation for uncertain nonlinear systems described by multiple models approach. The uncertainties, supposed as norm bounded type, are caused by some parameters’ variations of the nonlinear system. Linear matrix inequalities (LMIs) have been established in order to ensure the stability conditions of the multiple observer which lead to determine the estimation gains. A sliding mode gain has been added in order to compensate the uncertainties. Numerical simulations through a state space model of a real process have been realized to show the robustness of the synthesized observer.