Si nanowire FET and its modeling

Because of its ability to effectively suppress off-leakage current with its gate-around conffguration, the Si nanowire FET is considered to be the ultimate structure for ultra-small CMOS devices to the extent that the devices would be approaching their downsized limits. Recently, several experimental studies of Si nanowire FETs with on-currents much larger than those of planar MOSFETs have been published. Consequently, Si nanowire FETs are now gaining significant attention as the most promising candidate fo...     

Vertical processing systems: a survey

Work with associative memories and associative-array processing has culminated in the development of fine-grained single-instruction, multiple-data computing systems, called vertical processing systems, that employ bit-slice sequential processing. After reviewing the engineering characteristics of various commercial and research models such as the DAP, MPP, and CM, this survey proposes a combined architecture that links a VPS with a set of highly specialized, homogenous coprocessors     

Adaptive Doppler processing technique

In this paper we have investigated the possibility of realizing an adaptive signal Doppler processing in stationary clutter regions by using modern spectral analysis technique. Burg's algorithm is chosen to update the whitening filter weights of the lattice. The coherent integration is realized by FFT processor. The computer simulation results are shown.     

Fabrication of AFM probe with CuO nanowire formed by stress-induced method

A novel method has been proposed to fabricate an atomic force microscope (AFM) probe using CuO nanowire and a stress-induced method that can form the nanowire easily. By heating a commercial AFM probe with a film coating of Ta and Cu, a Cu hillock with CuO nanowires on its surface could be formed at the end of the probe. The thickness of the coating films, the heating temperature, and the heating time were investigated to obtain CuO nanowires with a high aspect ratio for use as an AFM probe tip. It was found that a suitable probe tip can be fabricated using the a Cu film thickness of 700 nm, a heating temperature of 380 °C and a heating time of 6 h. Probe tips (~5 μm high) and nanowires of ~25 nm diameter were obtained successfully. In the range evaluated, the measurement resolution of the CuO nanowire probe was slightly worse than that of a commercial AFM probe. However, both probes had almost the same dimensional measurement precision.     

结合人类视觉系统的数字图像水印技术

小波变换已经被广泛的应用到数字图像处理的许多领域,利用小波变换的数字水印技术被认为是一种最有效的保护数字信息版权的技术.提出了一种结合人类视觉系统的数字图像盲水印技术,它利用小波变化和人类视觉系统的共通点,进行水印的嵌入.实验结果表明,基于此种方法对图像进行数字水印的处理会有很好的效果.     

硅纳米线制成的纳米传感器

最新的研究表明:采用硅纳米线作为检测部件,利用其自身所特有的电学性质及高表面活性可制成有实用前途的纳米传感器。介绍了硅纳米线在合成纳米传感器方面的最新应用进展,对检测NH3气、水蒸汽、pH值、Ca2+及DNA等方面的应用做了较详细地阐述。     

基于BOE硅腐蚀现象的硅纳米线制作

介绍一种硅纳米线制作方法.在SOI顶层硅上制作硅纳米梁,通过离子注入形成pnp结构,利用新发现的没有特殊光照时BOE溶液腐蚀pn结n型区域现象,结合BOE溶液氧化硅腐蚀,实现硅纳米线制作.制作完全采用传统MEMS工艺,具有工艺简单,成本低,可控,可靠性好,可批量制作等优点.利用该方法制作出了厚50 nm,宽100 nm的单晶硅纳米线,制作的纳米线可用于一维纳米结构电学性能研究、谐振器研究等.     

A combined heuristic optimization technique

Realistic problems of structural optimization are characterized by non-linearity, non-convexity and by continuous and/or discrete design variables. There are non-linear dependencies between the optimised parameters. Real-world problems are rarely decomposable or separable. In this contribution a combined heuristic algorithm is described which is well suited for problems, for which the application-requirements of gradient-based algorithms are not fulfilled. The present contribution describes a combination of the Threshold Accepting Algorithm with Differential Evolution with particular emphasis on structural optimization, it can be classified as a Hybrid Evolutionary Algorithm. The Threshold Accepting Algorithm is similar to Simulated Annealing. Differential Evolution is based on Genetic Algorithms.     

基于金硅腐蚀自停止技术的亚微米梁制作研究

提出了利用无电极电化学腐蚀自停止技术制作亚微米梁结构的新工艺方法。根据金硅腐蚀自停止现象发生的条件,结合硅材料的各向异性腐蚀特性,设计器件结构,利用腐蚀暴露面积变化实现了硅的选择性自停止腐蚀。在(111)型硅片上利用原电池钝化效应一次性腐蚀出与衬底绝缘,由约4μm厚的金电极支撑,厚度约为235 nm的亚微米梁结构,具有制作简单、成品率高、成本低等特点,应用前景广阔。     

数学形态学和LoG算子结合的边缘检测技术

提出了一种LoG算子与数学形态学结合的玻璃碎片边缘检测方法,该方法是建立在一个承载着各种各样玻璃碎片快速传输系统上的。这个传输系统需要对传送带上的玻璃碎片进行快速的边缘检测,因此要求图像处理速度既快又准。经过研究,LoG算子计算量少,边缘检测效率高,但对噪声敏感;而数学形态学恰恰能弥补这一缺点,而且易于硬件实现。实验结果表明先用形态学中的膨胀和腐蚀操作对含噪声的图像进行平滑处理,再用LoG算子进行边缘检测的效果很好。     

Partial evaluation technique for distributed image processing

In this paper, a partial evaluation technique to reduce communication costs of distributed image processing is presented. It combines application of incomplete structures and partial evaluation together with classical program optimization such as constant-propagation, loop unrolling and dead-code elimination. Through a detailed performance analysis, we establish conditions under which the technique is beneficial. Andrei Tchernykh received his Ph.D. degree in computer science from the Institute of Precise Mechanics and Computer Technology of the Russian Academy of Sciences (RAS), Russia in 1986. From 1975 to 1995 he was with the Institute of Precise Mechanics and Computer Technology of the RAS, Scientific Computer Center of the RAS, and at Institute for High Performance Computer Systems of the RAS, Moscow, Russia. Since 1995 he has been working at Computer Science Department at the CICESE Research Center, Ensenada, Baja California, Mexico. His main interests include cluster and Grid computing, incomplete information processing, and on-line scheduling. Vitaly Kober obtained his MS degree in Applied Mathematics from the Air-Space University of Samara (Russia) in 1984, and his PhD degree in 1992 and Doctoral degree in 2004 in Image Processing from the Institute of Information Transmission Problems, Russian Academy of Sciences. Now he is a titular researcher at the Centro de Investigation Cientifica y de Educatión Superior de Ensenada (Cicese), México. His research interests include signal and image processing, pattern recognition. Alfredo Cristóbal-Salas received his Ph.D. degree in computer science from the Computer Science Department at the CICESE Research Center, Ensenada, Baja California, México. Now he is a researcher at School of Chemistry Sciences and Engineering, University of Baja California, Tijuana, B.C. Mexico His main interests include cluster and Grid computing, incomplete information processing, and online scheduling. Iosif A. Ovseevich graduated from the Moscow Electrotechnical Institute of Telecommunications. Received candidate’s degree in 1953 and doctoral degree in information theory in 1972. At present he is Emeritus Professor at the Institute of Information Transmission Problems of the Russian Academy of Sciences. His research interests include information theory, signal processing, and expert systems. He is a Member of IEEE, Popov Radio Society.     

数据仓库与数据库相结合完善通风网络数据处理

数据仓库技术是信息产业的新兴技术之一,对大型企业的事务分析、决策等具有很大意义。将数据仓库技术、数据挖掘技术引入到矿井通风网络数据处理这一研究领域,介绍了数据仓库的概念、特征以及数据分析的相关技术,讨论了矿山企业通风网络数据仓库的建立过程,提出了一种数据仓库技术与数据库技术相结合的矿山企业通风网络管理系统。     

基于图像处理的太阳光矢量倾角测量方法

为了提高在轨太阳光谱辐射的绝对定标精度,提出了太阳光矢量和太阳光谱仪主光轴夹角的测量方法。以图像处理技术为基础,构造了太阳光矢量和太阳光谱仪主光轴夹角的测量系统。入射的太阳光经在成像器件上成像,然后经过图像处理,获取了太阳光像点中心的位置,进而计算了太阳光矢量和与太阳光谱仪主光轴的倾角。实验表明测量方法是有效的,测量系统工作可靠稳定,测量精度约为0.05°。     

基于视频处理的视线稳定技术

针对既有摄像机运动又有前景物体运动的图像稳定问题,提出了一种快速算法。该算法首先利用改进的 Harries 算子提取特征点,根据三级匹配策略实现特征点的三级匹配,并且利用基于块的去噪声点方法检测出前景区域,剔除存在于前景区域的角点;然后建立当前帧与参考帧的映射关系,利用最小二乘法求解出全局运动参数;最后利用 Kalman 滤波平滑运动参数,依据平滑后的参数对图像进行补偿。     

流水线处理技术在数据集成中的应用

在数据集成中,经常碰到大数据量的集成问题,基于数据仓库方式的数据集成技术是一种比较流行的集成模式,提高该集成模式的查询以及实化视图的初始化效率、响应速度,并防止内存溢出,是数据集成中非常关注的地方.在基于数据仓库方式的数据集成模式中,利用基于内存控制的流水线处理方法,提高查询以及实化视图的初始化效率.实验证明,以上方法较同步方法不仅提高了数据集成效率,而且实现了内存控制.     

自上而下注意图分割的细粒度图像分类

目的 针对细粒度图像分类中的背景干扰问题,提出一种利用自上而下注意图分割的分类模型。方法 首先,利用卷积神经网络对细粒度图像库进行初分类,得到基本网络模型。再对网络模型进行可视化分析,发现仅有部分图像区域对目标类别有贡献,利用学习好的基本网络计算图像像素对相关类别的空间支持度,生成自上而下注意图,检测图像中的关键区域。再用注意图初始化GraphCut算法,分割出关键的目标区域,从而提高图像的判别性。最后,对分割图像提取CNN特征实现细粒度分类。结果 该模型仅使用图像的类别标注信息,在公开的细粒度图像库Cars196和Aircrafts100上进行实验验证,最后得到的平均分类正确率分别为86.74%和84.70%。这一结果表明,在GoogLeNet模型基础上引入注意信息能够进一步提高细粒度图像分类的正确率。结论 基于自上而下注意图的语义分割策略,提高了细粒度图像的分类性能。由于不需要目标窗口和部位的标注信息,所以该模型具有通用性和鲁棒性,适用于显著性目标检测、前景分割和细粒度图像分类应用。     

An integrated MCDM technique combined with DEMATEL for a novel cluster-weighted with ANP method

Traditionally, most importance-assessing methods used to demonstrate the importance among criteria by preference weightings are based on the assumptions of additivity and independence. In fact, people have found that using such an additive model is not always feasible because of the dependence and feedback among the criteria to somewhat different degrees. To solve the issue the analytic network process (ANP) method is proposed by Saaty. The general method is easy and useful for solving the above-mentioned problem. However in ANP procedures, using average method (equal cluster-weighted) to obtain the weighted supermatrix seems to be irrational because there are different degrees of influence among the criteria. Therefore, we intended to propose an integrated multiple criteria decision making (MCDM) techniques which combined with the decision making trial and evaluation laboratory (DEMATEL) and a novel cluster-weighted with ANP method in this paper, in which the DEMATEL method is used to visualize the structure of complicated causal relationships between criteria of a system and obtain the influence level of these criteria. And, then adopt these influence level values as the base of normalization supermatrix for calculating ANP weights to obtain the relative importance. Additionally, an empirical study is illustrated to demonstrate that the proposed method is more suitable and reasonable. By the concept of ideal point, some important conclusions drawn from a practical application can be referred by practitioners.