Photo-Chemically-Deposited and Industrial Cu/ZnO/Al2O3 Catalyst Material Surface Structures During CO2 Hydrogenation to Methanol: EXAFS,XANES and XPS Analyses of Phases After Oxidation,Reduction, and Reaction

Catalysis Letters - Industrial Cu/ZnO/Al2O3 or novel rate catalysts, prepared with a photochemical deposition method, were studied under functional CH3OH synthesis conditions at the set temperature...     

轮辐翻边成形冲模参数优化

应用有限元成形分析软件，对轮辐翻边成形过程进行了模拟分析，探讨了不同冲模斜角对翻边变形的影响，以控制变形冲力和轮辐变形区应变分布为目标，对冲模斜角参数进行优化。     

Functionalized oligopolysiloxanes by heterogeneously catalyzed equilibration polymerization reactions

Summary A new general procedure for preparation of functionalized oligopolysiloxanes of predetermined molecular weight is described. It utilizes heterogeneously catalyzed siloxane equilibration polymerization reactions which do not require troublesome and sometimes difficult post-preparative work-up procedures usually encountered with the well known homogeneously catalyzed corresponding reactions. The method is described using as example the preparation of , -telechelic vinyldimethylsiloxy-oligopolydimethylsiloxanes from octamethylcyclotetrasiloxane and 1,3-divinyltetramethyldisiloxane, but reference to the preparations of trimethylsiloxy-, dimethylsiloxy-and carboxypropyldimethylsiloxyoligopolydimethylsiloxanes, oligopolymethylhydridosiloxanes or their copolymers is also made.     

An e-Learning tool considering similarity measures for manufacturing cell formation

Manufacturing cell formation is the first step in the design of cellular manufacturing system. The primary objective of this step is to cluster machines into machine cells and parts into part families so that the minimum of intercell trips will be achieved. This paper will be focused on the configuration of machine cells considering three types of initial machine-part matrix: binary (zero-one) matrix, production volume matrix, and operation time matrix. The similarity measure uses only information from these types of matrix. A pure combinatorial programming formulation will be developed to maximize the sum of similarity coefficients between machine/part pairs. An e-Learning tool/application to help industrial students and engineers for enhancing their cell formation capability is proposed. This tool is designed to include a novel similarity coefficient-based heuristic algorithm for solving the cell formation problem. To determine the performance of the proposed tool, comparison is made with a well-known tool along a case study.     

Nature-Inspired Meta-Heuristics on Modern GPUs: State of the Art and Brief Survey of Selected Algorithms

Graphic processing units (GPUs) emerged recently as an exciting new hardware environment for a truly parallel implementation and execution of Nature and Bio-inspired Algorithms with excellent price-to-power ratio. In contrast to common multicore CPUs that contain up to tens of independent cores, the GPUs represent a massively parallel single-instruction multiple-data devices that can nowadays reach peak performance of hundreds and thousands of giga floating-point operations per second. Nature and Bio-inspired Algorithms implement parallel optimization strategies in which a single candidate solution, a group of candidate solutions (population), or multiple populations seek for optimal solution or set of solutions of given problem. Genetic algorithms (GA) constitute a family of traditional and very well-known nature-inspired populational meta-heuristic algorithms that have proved its usefulness on a plethora of tasks through the years. Differential evolution (DE) is another efficient populational meta-heuristic algorithm for real-parameter optimization. Particle swarm optimization (PSO) can be seen as nature-inspired multiagent method in which the interaction of simple independent agents yields intelligent collective behavior. Simulated annealing (SA) is global optimization algorithm which combines statistical mechanics and combinatorial optimization with inspiration in metallurgy. This survey provides a brief overview of the latest state-of-the-art research on the design, implementation, and applications of parallel GA, DE, PSO, and SA-based methods on the GPUs.     

Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.     

Electrochemical study of the chromium electrode behaviour in borate buffer solution

The electrochemical behaviour of the chromium electrode in borate buffer solution (pH 9.3) was studied by cyclic voltammetry and electrochemical impedance spectroscopy. Chromium passivity was observed over a broad potential region, from –1.0 to 0.5 V vs SCE. The passivation process took place in two steps: formation of a chromium oxide monolayer and transition of chromium to a higher valence state. The anodic film exhibited the properties of a p-type semiconductor. Transpassive dissolution of chromium occurred at 0.5 V vs SCE, with two reaction intermediates present, Cr_Cr ^III and Cr_ad ⁴⁺.     

Towards a Trajectory Planning Concept: Augmenting Path Planning Methods by Considering Speed Limit Constraints

Trajectory planning is an essential part of systems controlling autonomous entities such as vehicles or robots. It requires not only finding spatial curves but also that dynamic properties of the vehicles (such as speed limits for certain maneuvers) must be followed. In this paper, we present an approach for augmenting existing path planning methods to support basic dynamic constraints, concretely speed limit constraints. We apply this approach to the well known A* and state-of-the-art Theta* and Lazy Theta* path planning algorithms. We use a concept of trajectory planning based on a modular architecture in which spatial and dynamic parts can be easily implemented. This concept allows dynamic aspects to be processed during planning. Existing systems based on a similar concept usually add dynamics (velocity) into spatial curves in a post-processing step which might be inappropriate when the curves do not follow the dynamics. Many existing trajectory planning approaches, especially in mobile robotics, encode dynamic aspects directly in the representation (e.g. in the form of regular lattices) which requires a precise knowledge of the environmental and dynamic properties of particular autonomous entities making designing and implementing such trajectory planning approaches quite difficult. The concept of trajectory planning we implemented might not be as precise but the modular architecture makes the design and implementation easier because we can use (modified) well known path planning methods and define models of dynamics of autonomous entities separately. This seems to be appropriate for simulations used in feasibility studies for some complex autonomous systems or in computer games etc. Our basic implementation of the augmented A*, Theta* and Lazy Theta* algorithms is also experimentally evaluated. We compare (i) the augmented and basic A*, Theta* and Lazy Theta* algorithms and (ii) optimizing of augmented Theta* and Lazy Theta* for distance (the trajectory length) and duration (time needed to move through the trajectory).