PtRu/C and PtNi/C catalysts were prepared by microwave-assistant polyol process, and their microstructure and morphology were characterized by transmission electron microscopy (TEM) and X-ray diffraction (XRD). The results showed that the average diameters of PtRu and PtNi alloy nanoparticles in the catalysts are 2.7 nm and 3.0 nm respectively, and the alloy nanoparticles are homogeneous in size and highly dispersed on the carbon support. Compared with the Pt/C catalyst, the synthesized PtRu/C and PtNi/C catalysts exhibit lower onset oxidation potential and more stable polarization current for methanol electrooxidation. The facts indicate that the PtRu/C and PtNi/C catalysts have more durable electrocatalytic performance for methanol oxidation and better resistance to CO-poisoning than Pt/C catalyst. Because the Ru and Ni metals in the alloys can form oxygen-containing species with their surface adsorbed water under low potential, the adsorbed intermediates such as CO on Pt metal surface can be oxidized to CO2 and the CO-poisoning of the catalysts is avoided.
Impact prediction was incorporated with the dynamic expression of network in order to realize the impact prediction of design change in network flow system, and a dynamic model based on network flow Petri net (NFPN) was proposed to predict these impacts. Petri net was utilized to describe network flow and its design changes, and the NFPN dynamic model was established. The construction of full reachable graph of Petri net was associated with the impact prediction of change based on the analysis of hierarchical network flow. The analysis of the integral network was recursively accomplished through the simplification of reachable graph by multi-level abstraction. Application to the reconstruction and design of distribution network verified the feasibility and validity of the method. The method greatly reduces the complexity of state space, and is applicable to large scale and complicated network．
Effect of different reaction conditions on properties of DBBF-modified porcine hemoglobin products
A new scheme of the power system was proposed in order to meet the microminiaturization need of ZDPS-1A. To improve the power level of the satellite and to obtain a high efficiency power system, high efficient and high-tech devices such as GaInP2/GaAs/Ge solar cells, Li-ion batteries were adopted, and industrial power management ICs were widely used in the design of the power conversion and distribution circuit. Besides, the electric system was optimized and the operation mode of the satellite was reasonably planned to improve the reliability of the power system. Furthermore, a simulation model of the power system based on Matlab/Simulink was established to study the energy balance performance of the satellite. Analysis of the simulation, ground test and onorbit data for nearly one year of the power system, show that the solar cells can output 3.7 W in the case of simulation and 4.5 W under actual operating conditions, that the performance of the battery has deteriorated along time, and that the power dissipation of some loads has increased along time while the energy balance of the satellite is sustained.
The confidentiality of information in e-commerce activities leads to negotiation participants are unable to get the opponent’s utility function, thereby affecting the negotiation performance. To solve this, a bilateral and multi-issue negotiation model based on transductive support vector machine (TSVM-NM) was proposed. In this model, the proposals generated in the procedure of negotiation are stored in negotiation history database. The model constructs labeled data and unlabeled data by making full use of the implicit information in negotiation history and analyzing that whether those proposals fall in opponent’s acceptable utility zone. Those data become the training samples of TSVM. Then the estimation of opponent’s utility function was obtained by learning the training samples. With the combination of self’s utility function and the estimation of opponent’s utility function, a constrained optimization problem is formed, which is to be resolved by particle swarm optimization (PSO). The optimal solution is the self’s counter-offer. Experimental results show that this model can shorten the negotiation time and increase both the success rate of negotiation and the joint utility, in the environments where information is private and the prior knowledge is not available.
A method of measuring and evaluating color motion artifacts which combined a flash spectroradiometer with simulation method was presented. Alternative patterns step response curves which show the difference between different colors were obtained with flash spectrum SPR-3000. Perceived response curve was obtained after doing Fourier transformation, weighting contrast sensitivity function and counter-Fourier transformation. Extended blur edge width (EBEW) and perceived blur edge width (PBEW) were introduced here. And PBEW was used to evaluate color motion artifacts. In the experiment, monochromatic patterns with different wavelengths were tested. And the result proved that under the same moving conditions, motion artifacts will chang in different degrees while the testing colors are changing．
According to characteristics of moving dynamic loads on bridges and tracking the time domain method (TDM), the moving dynamic axle loads were identified from bridge bending responses, acceleration responses or their combination based on a preconditioned conjugate gradient method (PCGM). It aimed at obtaining the most accurate preconditioned matrix by comparing effect of preconditioned matrixes on identification accuracy. Simulation results showed that the PCGM could accurately identify the dynamic axle loads on bridges in most cases. However, there was different identification accuracy and immunity to measured noise and to the ill-posed problems of the system equation if different preconditioned matrixes were used. Meanwhile, choosing proper preconditioned matrix could effectively improve both of identification accuracy and efficiency of the PCGM. Key words: preconditioned matrix|moving force
The force feedback technology was introduced in the virtual painting process;a novel hairy brush modeling method was proposed. During Chinese calligraphy and painting process, the brush deformation, ink transfer process between hairy brush and paper were simulated in real time. Firstly, the geometry model of the hairy brush was represented with the two-layer structure of skeleton and surface. Then,a spring-mass model was adopted to simulate hairy brush skeleton and surface deformation when force was exerted on hairy brush, and the dynamic control of force to hairy brush deformation was realized in real time. A real time algorithm of the ink quantity of hairy brush was put forward to simulate ink transfer process between hairy brush and paper. The virtual painting system with force feedback technology was established based on the hardware components HP xw 8600 workstation and PHANTOM Desktop haptic device. In this system, users realize real time painting with the Phantom Desktop haptic device, which can effectively enhance the reality of virtual painting process to users.
Shadow pixels in images can lead to the uncertainty of image content, which is harmful to computer vision tasks. Therefore, shadow detection is often used as a preprocessing step of computer vision algorithm. A shadow detection network was proposed by combining semantic information contained in input images and correlation between pixels. Pre-trained deep network ResNeXt101 was used as feature extraction front-end module to extract semantic information of the image. The baseline structure of the network was built to up-sample feature layers, encouraged by the design idea of U-Net. Non-local operations were added before the output layer to provide global information for each pixel and establish the relationship between pixels. At the same time, an attention generation module and an attention fusion module were developed to further improve shadow detection accuracy. Two common shadow detection datasets named SBU and UCF were utilized for verification. Experiment results showed that the proposed network outperformed previous methods in both visual effect and objective indicator. The proposed network showed 14.4% reduction on SBU and 14.9% reduction on UCF for the balance error rate, compared with the state-of-the-art framework.
A method of proactive self-adaptation (PSA) was proposed to address the unanticipated adaptation of the traditional reactive self-adaptation (RSA) model. The PSAmethod presented an important problem to be resolved how the model learns from the environment. Hidden Markov model (HMM) was employed to learn from history behavior of targetsystem, and then generated anticipatory actions. The PSA method can proactively adjust the runtime behaviors of the system to be adaptive to the new situations compared to thetraditional RSA model. The application system made sound decision by combining the observation from system administrators and the cognitive power of PSA. Then applicationsimplemented the proactive autonomic management and reduced manual operation. Experimental results show that the PSA method provides for application with proactive self-adaptivemanagement mechanism and improves the manageability and quality of service (QoS) of application.
The theory analysis and simulations were conducted to explain how the ultrasonic wave aberration affects second harmonic imaging in medical ultrasonic diagnosis. Simulation results indicate that in the case of aberration, the energy of second harmonic is mainly generated in the near field and the profile of second harmonic is nearly the same as the fundamental. Though second harmonic is generated deeply, it experiences serious aberration. When the back scattering acoustic beam goes through body wall, it makes pulse to generate worse aberration. The ability of nonlinear amplitude fluctuation is weakened and the aberration’s amplitude is larger with the increase of frequency.
A feature pyramid multi-scale network structure was constructed based on the region recommendation network, the small target and class-independent image target were detected by combining the full convolution operation. In order to improve the detection accuracy of small targets in images, a three-layer pyramid structure network based on side link fusion was constructed, which made full use of the convolution features of images with low semantic level. To improve the robustness of class-independent image target detection, a specific non-maximum suppression algorithm was proposed to eliminate redundant target windows in overlapping target filtering and to refine the location of the target windows. The experimental results on PASCAL VOC 2007, PASCAL VOC 2012 and ancient painting datasets show that the detection accuracy of the proposed algorithm for small targets, multi-scale targets and type-independent targets is higher than that of the existing algorithms.
An inverse kinematics procedure was proposed aimed at the developed 6 degreeoffreedom (DOF) modular manipulator. The kinematics of the manipulator was analyzed according to the structural characteristic and the kinematic constraint. A forward kinematics model of the maniputor was conducted, and the complete analytical solution of the inverse kinematics was obtained. The DenavitHartenberg (DH) method was used to describe the workspace of the manipulator, resulting in the forward kinematics model with angle variables under the kinematic constraint of the manipulator. The solvability of the forward kinematics model was analyzed. Then the complete analytical solution of the inverse kinematics can be acquired by solving the forward kinematics model with the inverse matrix analysis. Simulation results verified the correctness of the forward kinematics model and the inverse kinematics solution. The inverse kinematics results can be further used for the precise location of endeffector and the motion planning.
Employing phenylethyl phenyl ether (PPE) as a lignin model compound, tetralin as a solvent and hydrogen-donor, toluene-4-sulfonic acid (PTSA) as a catalyst, the regularity of decomposition of PPE was studied with the microwave and tetralin. The effect of microwave to the reaction was discussed and a possible mechanism on the degradation with the microwave and tetralin was presented. The HPLC results indicated that the conversion of PPE decreased with the increase of initial mass density of PPE and was improved with the increase of mass density of PSTA. Compared to reactions with traditional heat conduction, microwave irradiation promoted the decomposition reaction of PPE significantly, and the apparent activation energy for PPE decomposition with microwave decreased by 27.7%.