IDENTIFICATION OF Fe_2 P IN PHOSPHIDE EUTECTIC OF CAST IRON

<正> 磷共晶是铸铁金相组织中的重要组成相之一,通常可分为二元和三元以及复合磷共晶。一般均认为磷共晶中的磷化物都是Fe_3P,即二元磷共晶是由Fe_3P+A组成;三元磷共晶是由Fe_3P_Fe_3C+A组成。 本文介绍在用热染法显示冷硬球铁轧辊的铸态组织时,发现二元磷共晶中的磷化铁呈白色,而三元磷共晶中的磷化铁呈紫色。这一差异表明,在两种共晶中磷化铁的组成是有区别的,为此有必要予以分析鉴定。 热染用样品的典型成分(％)如下:     

AZ91D合金SIMA形变组织与共晶熔化激活能的研究

研究了SIMA法制备半固态AZ91D镁合金坯料过程中形变率对形变组织的影响, 并采用DSC技术研究了形变率与共晶熔化激活能的关系.结果表明:随着形变率的增大,合金的原始组织由树枝晶演变为碎块晶,晶粒内存在位错、孪晶缺陷;合金的共晶熔化激活能随形变率的增大而变小,当形变率达到40%时,共晶熔化激活能下降很少;共晶熔化开始温度随形变率的增大略有下降.     

图像自适应分块的压缩感知采样算法

目的 在图像压缩感知过程中,不管是整体采样还是固定分块采样,都不能充分利用图像的稀疏性,存在采样率与图像重构质量的矛盾。提出了一种基于图像纹理变化的自适应分块感知采样算法ABCS(adaptive block compressed sensing),再结合JPEG量化思想,在不降低图像重构质量的前提下降低采样率,更大地提高压缩比。方法 首先进行图像预分块,计算分析各块纹理复杂度,当图像块纹理复杂度低于相应阈值,选择最佳采样率对各块观测采样,当图像块纹理复杂度高于相应阈值,需再分块,重复上述步骤,达到最小16×16块时停止分块。当最小块的纹理复杂度高于最大阈值采用JPEG量化编码,其他块选择匹配的采样率,以压缩感知方式压缩。结果 ABCS算法与典型的压缩感知重构算法结合并与其原始算法比较,在相近采样率条件下,图像重构质量提高明显,尤其在低采样率下性能更佳,如20%采样率下重构图像PSNR值达到30 dB左右。结论 提出的自适应的分块采样充分利用图像的稀疏分布,提高压缩感知的效率;高复杂纹理块采用JPEG编码处理,避免了重构质量差的缺点,同时减少了重构时间。     

Synchronization of a class of nonlinear network flow systems

In this paper, we consider the synchronization of a class of nonlinear network flow systems. Motivated by air distribution problem in air conditioning and mechanical ventilation (ACMV) systems, we propose a class of coupled nonlinear multi‐agent systems that can model a wide class of network flow systems, including air flow in ACMV systems, water flow in irrigation systems, traffic flow in transportation systems, and so on. Then we consider the synchronization problem for the class of nonlinear multi‐agent systems and propose cooperative controllers for the system. Based on graph theory, we derive conditions on the initial values of the state and the control input such that synchronization can be achieved. An application to air ventilation is provided to demonstrate the effectiveness of the cooperative controllers. Copyright © 2015 John Wiley & Sons, Ltd.     

A simulation framework for measuring robustness of incentive mechanisms and its implementation in reputation systems

In game theoretical analysis of incentive mechanisms, all players are assumed to be rational. Since it is likely that mechanism participants in the real world may not be fully rational, such mechanisms may not work as effectively as in the idealized settings for which they were designed. Therefore, it is important to evaluate the robustness of incentive mechanisms against various types of agents with bounded rational behaviors. Such evaluations would provide us with the information needed to choose mechanisms with desired properties in real environments. In this article, we first propose a general robustness measure, inspired by research in evolutionary game theory, as the maximal percentage of invaders taking non-equilibrium strategies such that the agents sustain the desired equilibrium strategy. We then propose a simulation framework based on evolutionary dynamics to empirically evaluate the equilibrium robustness. The proposed simulation framework is validated by comparing the simulated results with the analytical predictions based on a modified simplex analysis approach. Finally, we implement the proposed simulation framework for evaluating the robustness of incentive mechanisms in reputation systems for electronic marketplaces. The results from the implementation show that the evaluated mechanisms have high robustness against a certain non-equilibrium strategy, but is vulnerable to another strategy, indicating the need for designing more robust incentive mechanisms for reputation management in e-marketplaces.     

Multi-label classification via learning a unified object-label graph with sparse representation

Automatic annotation is an essential technique for effectively handling and organizing Web objects (e.g., Web pages), which have experienced an unprecedented growth over the last few years. Automatic annotation is usually formulated as a multi-label classification problem. Unfortunately, labeled data are often time-consuming and expensive to obtain. Web data also accommodate much richer feature space. This calls for new semi-supervised approaches that are less demanding on labeled data to be effective in classification. In this paper, we propose a graph-based semi-supervised learning approach that leverages random walks and ? ₁ sparse reconstruction on a mixed object-label graph with both attribute and structure information for effective multi-label classification. The mixed graph contains an object-affinity subgraph, a label-correlation subgraph, and object-label edges with adaptive weight assignments indicating the assignment relationships. The object-affinity subgraph is constructed using ? ₁ sparse graph reconstruction with extracted structural meta-text, while the label-correlation subgraph captures pairwise correlations among labels via linear combination of their co-occurrence similarity and kernel-based similarity. A random walk with adaptive weight assignment is then performed on the constructed mixed graph to infer probabilistic assignment relationships between labels and objects. Extensive experiments on real Yahoo! Web datasets demonstrate the effectiveness of our approach.     

面向智能家居/智慧生活的服务机器人技术与系统

随着机器人技术的发展以及服务机器人形态的日益丰富,智能家居/智慧生活逐渐成为一种未来的生活方式。文章探索了智能家居和智慧生活的服务机器人技术与系统,在其众多的关键技术中,重点探讨了面向服务机器人的云端融合技术以及高用户体验度的人-机器人交互技术。并以家庭服务机器人为例,实现了基于微信和语音云的人-机器人交互方式,验证了基于云架构的家庭服务机器人体系结构的可行性。文章所提出的服务机器人技术与系统是智能家居、智慧生活的一种实现方式,为未来形形色色的服务机器人技术方案提供了一些思路。     

静水压力下海底隧道安全稳定性研究

将强度折减法引入静水压力下海底隧道衬砌的安全稳定性研究,利用Flac3d软件建立了海底隧道-岩土体-海水相互作用的强度折减法数值分析模型,对比判定了强度折减法的两种折减方式,考虑海底隧道在静水压力作用下的位移变化、剪应变增量变化和塑性区变化情况,确定了衬砌局部破坏的极限平衡状态和整体破坏的极限平衡状态,分析了海底隧道在静水压力作用下的破坏机理。研究结果表明:海底隧道采用同时折减衬砌和围岩的折减方式进行计算较为合理;衬砌局部破坏的安全系数为1.83,整体破坏的安全系数为2.125,衬砌主要因剪应力产生破坏。     

Trajectory linearization control for a miniature unmanned helicopter

Trajectory linearization control (TLC) approach is applied to design a nonlinear trajectory tracking controller for a miniature unmanned helicopter. The controller is based on nonlinear model derived from Newton-Euler equations, with collective and cyclic pitches being regarded as actual controls. Via model simplifications, the nonlinear helicopter model can be transformed into a cascaded form including four subsystems. Corresponding with the simplified cascaded structure, the proposed controller is constructed by synthesizing TLC designs for subsystems. Each of them includes designs of a pseudo-inversion and an error regulator. A summarized TLC algorithm for the unmanned helicopter is listed briefly after the detailed controller design process. Simulation results are provided to demonstrate performances of the closed-loop system.