城市轨道交通车辆牵引逆变器的技术性发展路径分析

城市化进程的快速推进,城市轨道交通作为构成城市整体结构的重要组成,在城市发展的过程中具有重要作用。在城市轨道交通当中,构成的环节有很多,牵引逆变器是其中最为关键的一个环节。为了对城市轨道交通更好的了解,本文对城市轨道交通车辆牵引逆变器的技术性发展路径进行了分析,对各个基础模块进行分析。并最终通过实际装车考核,为我国城市轨道交通更好的发展贡献出自己的一份力量。

Predicting Resting-state Functional Connectivity With Efficient Structural Connectivity

The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible(SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field(DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that i) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ii) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; iii) in comparison with the DMF model,the dynamic model embedded in the shortest paths is found to perform better to predict FC.

Bio-inspired computational techniques based on advanced condition monitoring

The application of bio-inspired computational techniques to the field of condition monitoring is addressed. First, the bio-inspired computational techniques are briefly addressed; the advantages and disadvantages of these computational methods are made clear. Then, the roles of condition monitoring in the predictive maintenance and failures prediction and the development trends of condition monitoring are discussed. Finally, a case study on the condition monitoring of grinding machine is described, which shows the application of bio-inspired computational technique to a practical condition monitoring system.

Development and Future Challenges of Bio-Syncretic Robots

Bio-syncretic robots consisting of both living biological materials and non-living systems possess desirable attributes such as high energy efficiency, intrinsic safety, high sensitivity, and self-repairing capabilities. Compared with living biological materials or non-living traditional robots based on elec- tromechanical systems, the combined system of a bio-syncretic robot holds many advantages. Therefore, developing bio-syncretic robots has been a topic of great interest, and significant progress has been achieved in this area over the past decade. This review systematically summarizes the development of bio-syncretic robots. First, potential trends in the development of bio-syncretic robots are discussed. Next, the current performance of bio-syncretic robots, including simple movement and controllability of velocity and direction, is reviewed. The living biological materials and non-living materials that are used in bio-syncretic robots, and the corresponding fabrication methods, are then discussed. In addition, recently developed control methods for bio-syncretic robots, including physical and chemical control methods, are described. Finally, challenges in the development of bio-syncretic robots are discussed from multiple viewpoints, including sensing and intelligence, living and non-living materials, control approaches, and information technology.

Analysis on Evaluating Comprehensive Efficiency of Enterprise Leaders＇ Performance Based on Scientific Development Outlook

In former researches there are primary theoretical studies and qualitative analyses on enterprise leaders＇ effectiveness and performance, and there are a few studies on quantitative analyses which mostly relies on the method of comparing differences and ratio of divergence to evaluate leaders＇ performance by stage statistics. This paper illustrates how to evaluate Comprehensive Efficiency （CE） based on Scientific Development Outlook, which reflects overall development of enterprise leaders＇ performance, depends on measuring Output Efficiency Index （OEI） and Cost Efficiency Index （CEI） of enterprise leaders＇ performance, and adopts the C^2R model in Data Envelopment Analysis （DEA）.

Investigation of Eddy Current Nondestructive Testing for Carbon Fiber-Reinforced Plastic （CFRP） Based on Electromagnetic Field Analysis

CFRP （carbon fiber reinforced plastic） is used extensively in aircraft and spacecraft structures, because of its excellent mechanical properties. Ultrasonic testing, which is used as a non-destructive testing technique for CFRP, requires a contact medium. In contrast, eddy current testing does not require a contact medium, and when used for CFRP testing it has advantages not available with other techniques. CFRP is a laminate, with each layer being anisotropically conductive, and the distribution of the induced eddy current is yet to be determined. Here, to determine the eddy current distribution in the detection of flaws in cross-ply CFRP （0°/90°） by using a cross-point probe, we performed an FEM （finite element method） analysis of electromagnetic fields. We investigated the nature of the flaw signals and the differences in eddy current distributions between materials with and without flaws.

Scene-adaptive hierarchical data association and depth-invariant part-based appearance model for indoor multiple objects tracking

Indoor multi-tracking is more challenging compared with outdoor tasks due to frequent occlusion, view-truncation, severe scale change and pose variation, which may bring considerable unreliability and ambiguity to target representation and data association. So discriminative and reliable target representation is vital for accurate data association in multi-tracking. Pervious works always combine bunch of features to increase the discriminative power, but this is prone to error accumulation and unnecessary computational cost, which may increase ambiguity on the contrary. Moreover, reliability of a same feature in different scenes may vary a lot, especially for currently widespread network cameras, which are settled in various and complex indoor scenes, previous fixed feature selection schemes cannot meet general requirements. To properly handle these problems, first, we propose a scene-adaptive hierarchical data association scheme, which adaptively selects features with higher reliability on target representation in the applied scene, and gradually combines features to the minimum requirement of discriminating ambiguous targets; second, a novel depth-invariant part-based appearance model using RGB-D data is proposed which makes the appearance model robust to scale change, partial occlusion and view-truncation. The introduce of RGB-D data increases the diversity of features, which provides more types of features for feature selection in data association and enhances the final multi-tracking performance. We validate our method from several aspects including scene-adaptive feature selection scheme, hierarchical data association scheme and RGB-D based appearance modeling scheme in various indoor scenes, which demonstrates its effectiveness and efficiency on improving multi-tracking performances in various indoor scenes.

Cyclonic Separation Technology:Researches and Developments

Centered on thetechniques and industrial applications of the reinforced cyclonic separation process, its principles and mechanism for separation ot ions, molecules and their aggregates using polyalsperse aroplets are discussed generally; the characteristics and influential factors of fish-hook phenomenon of the grade efficiency curve in cyclonic separation for both gas and liquid are analyzed; and the influence of shear force on particle be- havior （or that of particle swarm） is also summarized. A novel idea for cyclonic separation is presented here： enhancing the cyclonic seoaration process of ions, molecules and their aggregates with monodisperse microspheres and their surface grafting, rearranging the distribution of particles by size using centrifugal field, reinforcing the cyclonic separation performance with orderly arranged particle swarm. Also the investigation of the shortcut flow, recirculation flow, the asymmetric structure and non-linear characteristics of the cyclonic flow field with a com-bined method of Volumetric 3-component Velocimetry （V3V） and Phase-Doppler Particle Anemometer （PDPA） are elaborated. It is recommended to develop new systems for the separation of heterogeneous phases with cyclonic technology, in accordance with the capture and reuse of CO2, methanol to olefins （MTO） process, coal transfer, andthe exploitation of oil shale.

Fourier Locally Linear Soft Constrained MACE for facial landmark localization

This paper proposes a novel nonlinear correlation filter for facial landmark localization. Firstly, we prove that SVM as a classifier can also be used for localization. Then, soft constrained Minimum Average Correlation Energy filter （soft constrained MACE） is proposed, which is more resistent to overfittings to training set than other variants of correlation filter. In order to improve the performance for the multi-mode of the targets, locally linear framework is introduced to our model, which results in Fourier Locally Linear Soft Constraint MACE （FL^2 SC-MACE）. Furthermore, we formulate the fast implementation and show that the time consumption in test process is independent of the number of training samples. The merits of our method include accurate localization performance, desiring generalization capability to the variance of objects, fast testing speed and insensitivity to parameter settings. We conduct the cross-set eye localization experiments on challenging FRGC, FERET and BioID datasets. Our method surpasses the state-of-arts especially in pixelwise accuracy.

Recent biomedical applications of bio-sourced materials

Natural anisotropic nanostructures occurring in several organisms have gained more and more attention because of their obvious advantages in sensitivity, stability, security, miniaturization, portability, online use, and remote monitoring. Due to the development of research on nature-inspired bionic structures and the demand for highly efficient, low-cost microfabrication techniques, an understanding of and the ability to replicate the mechanism of structural coloration have become increasingly significant. These sophisticated structures have many unique functions and are used in many applications. Many sensors have been proposed based on their novel structures and unique optical properties. Several of these bio-inspired sensors have been used for infrared radiation/thermal, pH, and vapor techniques, among others, and have been discussed in detail, with an intense focus on several biomedical applications. However, many applications have yet to be discovered. In this review, we will describe these nanostructured materials based on their sources in nature and various structures, such as layered, hierarchical, and helical structures. In addition, we discuss the functions endowed by these structures, such as superhydrophobicity, adhesion, and high strength, enabling them to be employed in a number of applications in biomedical fields, including cell cultivation, biosensors, and tissue engineering.

Contribution for a Better Understanding of the Technological Sustainability in Electrical Energy Production through Photovoltaic Cells

The conversion of solar energyinto electricity reveals a huge importance in the production of＂clean＂ energy, mainly when applied to decentralized production systems （micro-generation）. However, there is the need to develop and optimize these processes in order to turn it more sustainable in economic and technological scoops. The main purpose of this work is to study the solar energy conversion into electricity through photovoltaic cells, characterizing the process efficiencies. This study intends to evaluate the energetic and exergetic efficiencies defining them as indicators in the formulation ofa sustainability index. All the procedures are in a theoretical scope with an illustrative example in the end of this work.

Soft error reliability in advanced CMOS technologies—trends and challenges

With the decrease of the device size,soft error induced by various particles becomes a serious problem for advanced CMOS technologies.In this paper,we review the evolution of two main aspects of soft error-SEU and SET,including the new mechanisms to induced SEUs,the advances of the MCUs and some newly observed phenomena of the SETs.The mechanisms and the trends with downscaling of these issues are briefly discussed.We also review the hardening strategies for different types of soft errors from different perspective and present the challenges in testing,modeling and hardening assurance of soft error issues we have to address in the future.

Recent developments in plastic forming technology of titanium alloys

Titanium alloys have been used extensively in industry fields including aviation,aerospace and automobile due to their excellent comprehensive properties.Research and development of advanced plastic forming technology are of great importance to manufacturing titanium products of high performance and lightweight with low cost and short cycle.This paper analyzes the development tendencies of titanium alloy forming technology.Recent achievements in precision forming,microstructure control and multi-scale simulation of titanium alloys are reviewed.The forming techniques of large-sale integral complex components are presented.