工业机器人运用技术

工业机器人运用技术是指在现有工业机器人的基础上所研发的应用技术,其主要目的是增强工业机器人的感知适应能力、降低用户使用难度、缩短示教与编程时间、提高工业机器人的运动精度以及拓宽其应用范围。然而,工业机器人运用技术一直以来没有得到足够的重视,造成工业机器人的设计制造与应用需求脱节,不仅限制了工业机器人的应用和普及,也制约了工业机器人产业自身的大规模发展。文章针对现有工业机器人在制造自动化应用中所存在的问题,系统地归纳和分析了工业机器人运用技术的重点研发方向,主要包括:提高易用性的直觉示教与快捷编程、提高绝对定位精度的运动标定与误差补偿以及拓宽应用范围的力-运动混合控制等关键共性技术。部署和实施相关技术的研发对于提高我国工业机器人的运用水平、加快制造业向智能化升级的步伐具有重要的意义。     

基于ERDAS IMAGINE9.2操作平台的遥感图像融合概述

随着遥感技术的迅猛发展,各种遥感数据相应呈现。如何让数据得到充分的应用？数据融合在当今社会显得越来越重要;如何更好地对数据进行融合？我们必须了解各种融合方法的优缺点。本文介绍了ERDAS IMAGINE9.2操作平台上的几种遥感图像融合,分别是分辨率、小波变换、改进IHS、高通滤波融合,并通过实验比较几种融合方法的优缺点以及探讨未来可能研究方向。     

Lipid–oligonucleotide conjugates for bioapplications

Lipid–oligonucleotide conjugates (LONs) are powerful molecular-engineering materials for various applications ranging from biosensors to biomedicine. Their unique amphiphilic structures enable the self-assembly and the conveyance of information with high fidelity. In particular, LONs present remarkable potential in measuring cellular mechanical forces and monitoring cell behaviors. LONs are also essential sensing tools for intracellular imaging and have been employed in developing cell-surface-anchored DNA nanostructures for biomimetic-engineering studies. When incorporating therapeutic oligonucleotides or small-molecule drugs, LONs hold promise for targeted therapy. Moreover, LONs mediate the controllable assembly and fusion of vesicles based on DNA-strand displacements, contributing to nanoreactor construction and macromolecule delivery. In this review, we will summarize the general synthesis strategies of LONs, provide some characterization analysis and emphasize recent advances in bioanalytical and biomedical applications. We will also consider the relevant challenges and suggest future directions for building better functional LONs in nanotechnology and materials-science applications.     

辽东湾海冰资源量的遥感估算方法研究

该文提出了一种简单易行的海冰资源量遥感估算方法,包括提取海冰的结冰范围和反演冰厚分布。根据这种方法,利用2000年1月30日辽东湾NOAA/AVHRR资料,进行了海冰资源量遥感估算的尝试,得到了当天的海冰厚度分布图和海冰资源总量的数据,进而讨论了估算结果的合理性。研究得出的主要结论是：（1）NOAA/AVHRR资料的第一通道数据可以用于进行海陆分离和冰水分离;（2）基于反照率与海冰厚度指数关系的冰厚反演公式,可以用于海冰厚度的遥感估算;（3）得到的海冰资源量遥感估算结果,基本上符合辽东湾海冰分布的实际情况,可以为海冰资源的开发利用提供。     

多源遥感数据在植被识别和提取中的应用

不同类型的遥感数据有着自己独特的优势,如果综合应用,可以实现信息的互补,提高地物的识别精度。本文以福建省漳浦县为研究区域,利用SPOT5、ASTER和CBERS等多源遥感数据对植被的识别和提取方法进行研究,建立了基于多源遥感数据的专题信息提取流程。首先设计了基于不同植被专题信息自动提取的专家库,对单一遥感数据进行专题提取,然后基于专家知识进行决策级植被信息融合。多源遥感数据所提供的信息的优越性在于可以将不同传感器的光谱信息和时相特征进行互补,利用不同植被在不同遥感数据上的特征和专家知识,建立隶属度函数,判剐每个像元的归属,完成研究区不同植被类型的专题提取。结果表明,与单一传感器数据的结果相比,综合利用多源遥感数据能较大程度地提高植被的提取精度。     

试论政府过程再造

结合我国政府过程的实际和电子政府建设的实践,提出了政府过程再造概念。阐述了政府过程再造的特点、意义,建立了政府过程再造的初步理论框架。     

多源信息融合技术在干旱区盐渍地信息提取中的应用

土壤盐渍化是干旱区绿洲稳定与可持续发展面临的主要环境问题之一,因此借助遥感手段及时准确地提取盐渍地信息并掌握其空间分布有着重要的现实意义。本文以渭干河-库车河三角洲绿洲为例,使用RadarsatSAR与LandsatTM影像进行主成分融合,同时与HIS和Brovey变换的融合效果作定量比较,并利用BP神经网络模型,以相同的训练样本分别对融合前后的影像进行分类。结果表明：盐渍地主要分布在绿洲的和沙漠之间的交错带,盐渍地的分布在绿洲内部呈条形状分布,而在绿洲外部呈片状分布,且绿洲外部重度盐渍地交错分布在中轻度盐渍地中;主成份变换融合影像的光谱信息保持性、信息量都优于其它常用的融合方法,且分类精度比单一LANDSATTM多光谱影像有较大提高,是监测干旱区盐渍地变化的有效手段。     

浅谈基于稀疏表示的图像融合算法

图像融合已成为图像处理和计算机视觉领域的一项重要技术。随着压缩感知理论的发展,稀疏表示成为了压缩感知中的一个重要的研究内容。文章系统地阐述了当前图像融合技术的研究现状,重点介绍了稀疏表示在图像融合中的应用,并对目前图像融合算法存在的问题以及未来的发展进行了展望。     

QuickBird全色与多光谱影像融合方法比较研究

自从高分辨率卫星影像出现以来,遥感影像的融合一直是一个重要的研究领域。随着遥感影像获取手段的增加和分辨率的提高,影像的融合不仅仅要求增加空间信息而且在原始多光谱波段的光谱保持方面也有越来越高的要求。目前图像融合已研究出多种方法,如主成分变换法(PCA)、乘积法、Brovey变换法、IHS变换法、SVR变换法以及小波变换法等。这些方法在中低分辨率影像融合时效果较好但却不一定适用于像QuickBird、IKONOS等高分辨遥感影像的融合。本文应用Pansharp变换法和Gram-Schmidt变换法两种融合方法,对QuickBird影像进行融合试验,并与Brovey变换法、IHS变换法、PCA变换法的融合效果进行比较,以评价各算法的优缺点。研究结果表明,Gram-Schmidt变换和Pansharp变换在QuickBird影像融合时不仅能增加空间信息而且还能较好地保持原多光谱波段的光谱信息,其中以Gram-Schmidt变换法所获得的效果最好。     

浅议探地雷达在隧道检测中的应用

探地雷达技术是一种高分辨率的地球物理探测技术,具有无损,高效快捷,高分辨率等特征,本文介绍探地雷达在隧道检测中的应用,并对一些典型雷达波形进行解释和分析。     

用VC做探地雷达数据CAD矢量图

本文从探地雷达软件处理后的文件为出发点,经过读取显示,输出参数设置,导出DXF文件,从而实现CAD的矢量成图;文章提出了一种用矢量图来代替位图的方法,克服了探地雷达成果位图失真和不便引用等问题。     

Light-emitting self-assembled metallacages

Coordination-driven self-assembly of metallacages has garnered significant interest because of their 3D layout and cavity-cored nature. The well-defined, highly tunable metallacage structures render them particularly attractive for investigating the properties of luminophores, as well as for inducing novel photophysical characters that enable widespread applications. In this review, we summarize the recent advances in synthetic methodologies for light-emitting metallacages, and highlight some representative applications of these metallacages. In particular, we focus on the favorable photophysical properties—including high luminescence efficiency in various physical states, good modularity in photophysical properties and stimulus responsiveness—that have resulted from incorporating ligands displaying aggregation-induced emission (AIE) into metallacages. These features show that the synergy between carrying out coordination-driven self-assembly and using luminophores with novel photophysical characteristics like AIE could stimulate the development of supramolecular luminophores for applications in fields as diverse as sensing, biomedicine and catalysis.     

Sense through the wall system development and design considerations

This paper presents system design challenges and issues with sensing through walls at different standoff distances and wall types. Efforts for developing sense through the wall (STTW) systems, such as those undertaken by the US Army Technology Objective (ATO) program, aim at providing the soldier with situational awareness information before breaching a building in a military operations in urban terrain (MOUT) environment. STTW capabilities also support law enforcement and search and rescue applications. Since 2002, extensive evaluations of STTW technologies, most notably those performed by the Communications Electronics, Research, Development and Engineering Center (CERDEC) Intelligence and Information Warfare Directorate (I2WD), have been made to determine which technology could be the most viable solution. After conducting comprehensive studies, I2WD initiated several Phase I efforts and Phase II efforts. The purpose behind both efforts was to develop various STTW technology demonstrators under a 5 year ATO. Many lessons learned during the development of Phase I systems were incorporated into the considerations for Phase II developments. This paper discusses design challenges and issues with sensing through walls at different standoff distances and wall types through lessons learned and results from modeling and simulations performed by the Army Research Laboratory.     

Whose posts to read: Finding social sensors for effective information acquisition

In the era of big data, it is extremely challenging to decide what information to receive and filter out in order to effectively acquire high-quality information, particularly in social media where large-scale User Generated Contents (UGC) is widely and quickly disseminated. Considering that each individual user in social network can take actions to drive the process of information diffusion, it is naturally appealing to aggregate spreading information effectively at the individual level by regarding each user as a social sensor. Along this line, in this paper, we propose a framework for effective information acquisition in social media. To be more specific, we introduce a novel measurement, the preference-based Detection Ability to evaluate the ability of social sensors to detect diffusing events, and the problem of effective information acquisition is then reduced to achieving social sensing maximization through discovering valid social sensors. In pursuit of social sensing maximization, we propose two algorithms to resolve the longstanding problems in traditional greedy methods from the perspectives of efficiency and performance. On the one hand, we propose an efficient algorithm termed LeCELF, which resolves the redundant re-evaluations in the traditional Cost-Effective Lazy Forward (CELF) algorithm. On the other hand, we observe the participation paradox phenomenon in the social sensing network, and proceed to propose a randomized selection-based algorithm called FRIENDOM to choose social sensors to improve the effectiveness of information acquisition. Experiments on a disease spreading network and real-world microblog datasets have validated that LeCELF greatly reduces the running time, whereas FRIENDOM achieves a better detection performance. The proposed framework and corresponding algorithms can be applicable in many other settings in resolving information overload problems.     

On-chip pressure sensor using single-layer concentric chambers

A vision-based on-chip sensor for sensing local pressure inside a microfluidic device is proposed and evaluated in this paper. The local pressure is determined from the change of color intensity in the sensing chamber which is pre-filled with colored fluid. The working principle of the sensor is based on polydimethylsiloxane deformation. The pressure at the point of interest is guided into a deformation chamber, where the structural stiffness is softened by chamber geometry, and thus, the chamber deforms as a result of pressure changes. Such deformation is transmitted to the sensing chamber, a same-layer concentric inside the deformation chamber. The deformation in the sensing chamber causes the colored fluid flowing in or out the chamber and leads to different color intensity from the top view through a microscope. Experimental evaluations on static and dynamic responses by regulated input pressures were conducted. The correlation in static response is 0.97 while the dynamic responses are successfully observed up to 16 Hz. The greatest advantage is that the local pressure can be directly seen without any additional hardware or electricity. The whole sensor is on a single-layer microfluidic design, so that the fabrication is simple, consistent, and low-cost. The single-layer design also provides the convenience of easy integration for existing microfluidic systems.     

Flexible sample selection strategies for transfer learning in ranking

Ranking is a central component in information retrieval systems; as such, many machine learning methods for building rankers have been developed in recent years. An open problem is transfer learning, i.e. how labeled training data from one domain/market can be used to build rankers for another. We propose a flexible transfer learning strategy based on sample selection. Source domain training samples are selected if the functional relationship between features and labels do not deviate much from that of the target domain. This is achieved through a novel application of recent advances from density ratio estimation. The approach is flexible, scalable, and modular. It allows many existing supervised rankers to be adapted to the transfer learning setting. Results on two datasets (Yahoo’s Learning to Rank Challenge and Microsoft’s LETOR data) show that the proposed method gives robust improvements.     

Bicausal bond graphs for supervision: From fault detection and isolation to fault accommodation

Model-based fault detection and isolation (FDI) requires an analytical system model from which fault indicators can be derived by assigning proper computational causalities. Many bond graph (BG) model-based techniques for FDI have been developed in recent past. Furthermore, many other advances have been made in the field of control engineering applications of BG modelling. Supervision systems not only perform FDI, but also take the necessary steps for fault accommodation. Fault accommodation is done either through system reconfiguration or through fault tolerant control (FTC). In this paper, it is shown that bicausal BG modelling proves to be a unified approach for sensor placement from the FDI and FTC viewpoint, identification of hardware redundancies for system reconfiguration, generation of fault indicators, estimation of fault parameters for fault accommodation, inversion of systems and actuator sizing for FTC, etc. It is shown that the use of bicausalled BG helps to integrate many of the recently developed advances made in the field of control engineering into development of complex supervision systems.     

Microfluidic study of the chemotactic response of Escherichia coli to amino acids,signaling molecules and secondary metabolites

Quorum sensing and chemotaxis both affect bacterial behavior on the population level. Chemotaxis shapes the spatial distribution of cells, while quorum sensing realizes a cell-density dependent gene regulation. An interesting question is if these mechanisms interact on some level: Does quorum sensing, a density dependent process, affect cell density itself via chemotaxis? Since quorum sensing often spans across species, such a feedback mechanism may also exist between multiple species. We constructed a microfluidic platform to study these questions. A flow-free, stable linear chemical gradient is formed in our device within a few minutes that makes it suitable for sensitive testing of chemoeffectors: we showed that the amino acid lysine is a weak chemoattractant for Escherichia coli, while arginine is neutral. We studied the effect of quorum sensing signal molecules of Pseudomonas aeruginosa on E. coli chemotaxis. Our results show that N-(3-oxododecanoyl)-homoserine lactone (oxo-C12-HSL) and N-(butryl)-homoserine lactone (C4-HSL) are attractants. Furthermore, we tested the chemoeffector potential of pyocyanin and pyoverdine, secondary metabolites under a quorum sensing control. Pyocyanin is proved to be a weak attractant while pyoverdine are repellent. We demonstrated the usability of the device in co-culturing experiments, where we showed that various factors released by P. aeruginosa affect the dynamic spatial rearrangement of a neighboring E. coli population, while surface adhesion of the cells is also modulated.     

Dielectrophoretic cell trapping and parallel one-to-one fusion based on field constriction created by a micro-orifice array

Micro-orifice based cell fusion assures high-yield fusion without compromising the cell viability. This paper examines feasibility of a dielectrophoresis (DEP) assisted cell trapping method for parallel fusion with a micro-orifice array. The goal is to create viable fusants for studying postfusion cell behavior. We fabricated a microfluidic chip that contained a chamber and partition. The partition divided the chamber into two compartments and it had a number of embedded micro-orifices. The voltage applied to the electrodes located at each compartment generated an electric field distribution concentrating in micro-orifices. Cells introduced into each compartment moved toward the micro-orifice array by manipulation of hydrostatic pressure. DEP assisted trapping was used to keep the cells in micro-orifice and to establish cell to cell contact through orifice. By applying a pulse, cell fusion was initiated to form a neck between cells. The neck passing through the orifice resulted in immobilization of the fused cell pair at micro-orifice. After washing away the unfused cells, the chip was loaded to a microscope with stage top incubator for time lapse imaging of the selected fusants. The viable fusants were successfully generated by fusion of mouse fibroblast cells (L929). Time lapse observation of the fusants showed that fused cell pairs escaping from micro-orifice became one tetraploid cell. The generated tetraploid cells divided into three daughter cells. The fusants generated with a smaller micro-orifice (diameter∼2 μm) were kept immobilized at micro-orifice until cell division phase. After observation of two synchronized cell divisions, the fusant divided into four daughter cells. We conclude that the presented method of cell pairing and fusion is suitable for high-yield generation of viable fusants and furthermore, subsequent study of postfusion phenomena.     

Co-ordinated detection of microparticles using tunable resistive pulse sensing and fluorescence spectroscopy

Tunable resistive pulse sensing (TRPS) has emerged as a useful tool for particle-by-particle detection and analysis of microparticles and nanoparticles as they pass through a pore in a thin stretchable membrane. We have adapted a TRPS device in order to conduct simultaneous optical measurements of particles passing through the pore. High-resolution fluorescence emission spectra have been recorded for individual 1.9 μm diameter particles at a sampling period of 4.3 ms. These spectra are time-correlated with RPS pulses in a current trace sampled every 20 μs. The flow rate through the pore, controlled by altering the hydrostatic pressure, determines the rate of particle detection. At pressures below 1 kPa, more than 90% of fluorescence and RPS events were matching. At higher pressures, some peaks were missed by the fluorescence technique due to the difference in sampling rates. This technique enhances the particle-by-particle specificity of conventional RPS measurements and could be useful for a range of particle characterization and bioanalysis applications.