Multidimensional ARKN methods for general oscillatory second-order initial value problems

Based on B-series theory, the order conditions of the multidimensional ARKN methods are presented for the general multi-frequency and multidimensional oscillatory second-order initial value problems by Wu et al. (2009). These multidimensional ARKN methods exactly integrate the multi-frequency and multidimensional unperturbed oscillators. In this paper, we pay attention to the analysis of the concrete multidimensional ARKN methods for the general multi-frequency oscillatory second-order initial value problems whose right-hand side functions depend on both  y$y$and  y^′$y^{\prime }$ (the class of physical problems which fall within its scope is broader). Numerical experiments are carried out to show that the new multidimensional ARKN methods are more efficient compared with some well-known methods for dealing with the oscillatory problems in the scientific literature.     

Analysis over factors of innovation in China’s fast economic growth since its beginning of reform and opening up

The technological progress makes great contribution to the rapid economic growth of China during its past three decades of reform and opening up. An empirical analysis conducted over China’s total factor productivity certifies this conclusion but it also reveals that China’s TFP growth rate is not very high. We further explore the various stages of change of China’s total factor productivity and the causes of these changes and finally take an analytical calculation over the present flaws of China’s innovation system and offer some advices.     

Muscular fatigue and maximum endurance time assessment for male and female industrial workers

A single arm pushing experiment was conducted in an electronic factory in Yantai, China to assess muscular fatigue using the theoretical models of muscular strength and maximum endurance time (MET) developed by Ma et al. (2009). Seventy seven workers, including 38 males and 39 females, participated in the study. The muscular strength of pushing was measured after the subject pushed a stick, with a force of 2.5 kgf, for 0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 min. Fatigue rate was determined based on a regression approach. In addition to the theoretical model, the MET for such a pushing task was also determined using four empirical models in the literature. The results indicated that females were more resistant to muscular fatigue than males in the pushing task. The results of the muscular strength prediction show that the predictability of the muscular strength model is acceptable. The prediction errors for muscular strength for female subjects were significantly lower than those of the male subjects. The predicted MET using the theoretical model, with a group constant k, was highly correlated with those using the empirical models compared in the current study.     

Kinetics of the methanation of carbon dioxide over a supported Ni-La2O3 catalyst

The kinetics of the methanation of carbon dioxide was investigated using an alumina supported Ni-La₂O₂ catalyst in a differential and integral reactor. In the differential reactor the molar ratio of H₂ to CO₂ was varied from 0.6 to 30. In the integral reactor the rates were measured with up to 90% conversion. Both reactor tests were carried out at temperatures between 513 and 593 K. The experimental results were described by a Langmuir-Hinshelwood type equation. The kinetics can be explained by assuming equilibrium of dissociative carbon dioxide and hydrogen adsorption, and assuming hydrogenation of surface carbon as the rate determining step.     

Managing knowledge on communication and information flow in global software projects

Communication is a key success factor of distributed software projects. Poor communication has been identified as a main obstacle to successful collaboration. Global projects are especially endangered by information gaps between collaborating sites. Different communication styles, technical equipment, and missing awareness of each other can cause severe problems. Knowledge about actual and desired channels, paths, and modes of communication is required for improving communication in a globally distributed project. However, many project participants know little about communication and information flow in their projects. In this contribution, we focus on knowledge about communication and information flow. It is acquired by modelling on‐going and desired flows of information, including documented and non‐documented channels of information flow. We analyzed a distributed software project from the information flow perspective. Based on the findings, we developed specific techniques to improve information flow in distributed software development according to the FLOW Method. In a second distributed project, we evaluated one of the techniques. We found the FLOW mapping technique to be suitable for effectively spreading knowledge about communication and information flow in global software projects.     

Data-based adaptive online prediction model for plant-wide production indices

A data-based adaptive online prediction model is proposed for plant-wide production indices based on support vector regression, a general method which we customized specifically to model very large data sets that are generated dynamically and periodically. The proposed model can update its parameters online according to the statistical properties of the training samples. Further, in order to improve the prediction precision, each sample is weighted with a dynamic penalty factor that considers the effect of each sample on the prediction model accuracy. Moreover, a customized procedure is introduced to handle large training sets. After having been convincingly evaluated on benchmark data, effectiveness and performance of our approach for plant-wide production indices is demonstrated using industrial data from an operating ore dressing plant over a range of scale in training data set size. The higher accuracy and shorter computation times than existing methods suggest that it may prove advantageous in actual application to dynamic production processes.     

VOID FRACTION PROFILES IN PLANE-POISEUILLE FLOW OF VISCOELASTIC FOAMS

This investigation focuses on slow, isothermal, two-phase flow of gas bubble suspensions in Separan solutions, prepared with the help of a sodium borohydride blowing agent at room temperature. The total residence time in these experiments is much smaller than characteristic times for growth or rise of bubbles. The variation of bubble volume fraction across a narrow gap between two planes, is recorded at two locations along the flow direction. This is done with a Cesium gamma-radiation source focused on a region of area.012 cm² in the flow plane, and a Sodium iodide detector across the channel yielding a resolution of.01 over the range of void fractions investigated from.02 to.08. This measurement allows us to identify conditions under which the two-phase flow may be described by a two fluid model with a uniform bubbly core and a bubble free wall layer. With this two phase flow structure, a relative viscosity equation for the suspension is used to compute an apparent viscosity. Such calculations indicate that the observed reduction in apparent viscosity for the two phase flow may be attributed to a bubbly core which is more shear thinning than the medium. The additional shear thinning factor for the suspension is related to the elasticity of the medium.     

Safe Landing Analysis of a Quadrotor Aircraft With Two Legs

We proposed a multi-propeller multifunction aerial robot (MMAR) that is composed of a quadrotor with two legs. The legs can increase the function of the robot. We found that the legs can increase the safety region of the robot during the landing. To study the safety problem, the dynamics of MMAR interacting with environment should be solved. On the basis of the interaction dynamics, this paper investigates the velocity constraint for safe landing of MMAR. The investigation begins from the kinematics and dynamics of MMAR in flight mode. Then the impact dynamics of MMAR during landing is developed. Furthermore, the landing safety problem is formulated by a series of constraint equations which can give a safety region of the velocity during landing. The safety region can give the safe velocity of the aerial robot before landing. Finally, simulation examples are presented using the proposed methodology. In the examples, a detailed safety region of a simulated MMAR is constructed and shown.     

A novel self-adaptive extreme learning machine based on affinity propagation for radial basis function neural network

In this paper, a novel self-adaptive extreme learning machine (ELM) based on affinity propagation (AP) is proposed to optimize the radial basis function neural network (RBFNN). As is well known, the parameters of original ELM which developed by G.-B. Huang are randomly determined. However, that cannot objectively obtain a set of optimal parameters of RBFNN trained by ELM algorithm for different realistic datasets. The AP algorithm can automatically produce a set of clustering centers for the different datasets. According to the results of AP, we can, respectively, get the cluster number and the radius value of each cluster. In that case, the above cluster number and radius value can be used to initialize the number and widths of hidden layer neurons in RBFNN and that is also the parameters of coefficient matrix H of ELM. This may successfully avoid the subjectivity prior knowledge and randomness of training RBFNN. Experimental results show that the method proposed in this thesis has a more powerful generalization capability than conventional ELM for an RBFNN.