砝码自动检定系统

现有标准砝码检定仍以实验室手工检定为主,检测效率低下、人工成本高.根据JJG99-2006《砝码》国家检定规程要求,系统选用高精度响应特点的传感机构和传感器,设计了方便不同外形砝码取放、具有防划防撞功能、满足精准定位要求的机械定位机构;设计了高效的控制系统,实现实时数据远程传输,完成砝码性能指标全自动检测,大大提高检测效率与管理水平,保证检定质量.     

基于ANN的哈萨克文手写文字识别系统的研究

光学字符识别系统在自动处理,人机交互,办公自动化以及商业领域中有非常广泛的应用。论文主要讨论如何结合结构方法和神经网络的技术,来实现哈萨克语手写文字识别系统的实现。该方法有以下几个优点：方法使用了基于规则（结构）的方法和分类测试;方法更加适合于像哈萨克文字一样具有较大的字符集和字符尺寸不一致的字符集;特征提取的代价较低,运行时间主要由字符尺寸和字体决定。该系统使用一个五层的人工神经网络对字符进行分类,使用10个用户的不同的手写字体进行测试,正确识别率为91%。     

面向资源受限用户的高效动态数据审计方案

物联网(IoT)设备推动着云存储外包数据服务的快速发展,从而使云存储外包数据服务得到越来越多终端用户的青睐,因此如何确保云服务器中用户数据的完整性验证成为一个亟待解决的热点问题.针对资源受限的用户,目前的云数据审计方案存在运算复杂、开销高和效率低等问题.为了解决这些问题,提出一个面向资源受限用户的高效动态数据审计方案....     

Visual Reconstructability as a Quality Metric for Flow Visualization

We present a novel approach for the evaluation of 2D flow visualizations based on the visual reconstructability of the input vector fields. According to this metric, a visualization has high quality if the underlying data can be reliably reconstructed from the image. This approach provides visualization creators with a cost‐effective means to assess the quality of visualization results objectively. We present a vision‐based reconstruction system for the three most commonly‐used visual representations of vector fields, namely streamlines, arrow glyphs, and line integral convolution. To demonstrate the use of visual reconstructability as a quality metric, we consider a selection of vector fields obtained from numerical simulations, containing typical flow features. We apply the three types of visualization to each dataset, and compare the visualization results based on their visual reconstructability of the original vector field.     

支持形状分析的符号执行引擎的设计与实现

目前提高软件可靠性的方法有3种:动态测试、静态分析和程序验证。动态测试的结果依赖于测试集的设计,误报率低,漏报率高,分析结果不稳定。程序验证可以对程序的各种性质进行完备的验证。但目前程序验证通常都需要手动证明,分析成本最高。而程序静态分析可以更早、更全面、较高效和低成本地检测到程序中的缺陷。其中符号执行技术是一种比较有应用前景的静态分析技术,可以很好地控制 精确度。针对符号执行可伸缩性差和容易产生路径爆炸的问题,在符号执行过程中利用形状分析技术实现自动推导循环不变式和构建函数行为规范,实现了一个较为实用的C程序分析工具。     

CFD验证与确认数据库平台数据结构设计与应用

计算流体动力学（CFD,computational fluid dynamics）验证与确认数据库平台用于存储和管理精细风洞试验、飞行试验、数值计算产生的标准算例数据。针对结构复杂、维度较高且参数不固定的CFD验证与确认标准算例数据,设计一种灵活的数据结构,动态存储不同标准算例的来流状态数据与结果数据,减少数据冗余,提高数据可扩展性。基于该数据结构完成标准算例数据质检与元数据管理设计,确保数据库平台能够精准、高效的为CFD软件可信度评价或相关研究提供数据服务。应用证明,验证与确认数据库平台实现了标准算例数据的有效管理和高效应用,为国家数值风洞工程和国内相关CFD软件的验证和确认提供了有力支撑。     

基于DPI-C的脉动阵列模块验证平台

针对卷积神经网络加速器中有关于脉动阵列模块的验证,提出并实现了一种基于直接编程接口C（DPI-C,Direct Programming Interface C）程序的验证平台,采用内嵌DPI-C程序并利用通用验证方法学（UVM,Universal Verification Methodology）满足脉动阵列模块中的浮点数乘加运算的验证需求。实验利用了SystemVerilog中的DPI接口技术,在验证平台中实现对C或C++代码的调用,通过编写C函数来实现复杂的参考模型,浮点数乘加运算便是利用C代码编写的。验证平台的整体结构是根据UVM来设计的,其中包括激励的设计、参考模型的编写、数据校对等组件,整个验证平台高效、简洁。此平台已经应用于人工智能芯片的验证工作中,编写的测试用例可以对脉动阵列进行充分验证,覆盖率达到了100%。验证平台可以保证脉动阵列验证的全面性、高效性并且调试纠错简单方便,同时还实现了UVM环境和测试用例的重用。     

Neural Network Recognition of Hand-printed Characters

Character recognition systems can contribute tremendously to the advancement of the automation process, and can improve the interaction between man and machine in many applications, including office automation, cheque verification and a large variety of banking, business and data entry applications.The main theme of this paper is the automatic recognition of hand-printed Latin characters using artificial neural networks in combination with conventional techniques. This approach has a number of advantages: it combines rule-based (structural) approach for feature extraction and non-linea classification tests for recognition; it is more efficient for large and complex data sets; feature extraction is inexpensive and execution time is independent of handwriting style and size. The technique can be divided into three major steps: The first step is pre-processing in which the original image is transformed into a binary image utilising a 300 dpi scanner and then thinned using a parallel thinning algorithm. Second, the image-skeleton is traced from left to right in order to build a binary tree. Some primitives, such as Straight lines, Curves and Loops, are extracted from the binary tree. Finally, a three layer artificial neural network is used for character classification. The system was tested on a sample of handwritten characters from several individuals whose writing ranged from acceptable to poor in quality and the correct average recognition rate obtained using cross-validation was 86%.     

一种工作用S型热电偶自动检定系统设计与应用

为了提高热电偶检定系统的检定时间和控温精度,基于LabVIEW设计了一种工作用S型热电偶的检定系统.以数据采集卡和可控硅为核心搭建了硬件系统,使用图形化编程语言LabVIEW开发了上位机软件,并对检定炉温度控制算法进行优化,人机界面友好、高效便捷.经过实验性投运,系统性能与检定企业出具结果一致,具有较高的实用价值.     

RISC指令集众核处理器功能验证与实现

众核技术已成为当前处理器体系结构发展的必然趋势,如何对众核处理器设计进行有效而充分的验证,成为当今IC设计验证领域的研究热点之一,也是众核处理器芯片能否成功流片的关键因素之一。目前工业界采用基于仿真的验证作为主要的验证方式,重点介绍了以覆盖率为导向的RISC众核处理器的功能验证环境的整体设计,提出了“被动式”的验证思想,并采用“软硬件协同验证”的策略,最终达到每条指令都比对通过的验证目标,辅以后期阶段所引入的时序验证策略和功耗评估策略,完整地提出了一套芯片验证平台搭建和验证功能实现的方法流程。     

基于遗传算法的全芯片级覆盖率驱动随机验证技术

随机测试生成技术是当今大规模集成电路仿真验证流程中的重要支撑技术.覆盖率驱动的随机测试生成方法是目前该领域研究的热点.遗传算法具有部分优化问题的黑盒特性,不需要了解问题的太多先验知识,适合处理黑盒优化问题.因此,将遗传算法应用在覆盖率反馈驱动随机测试生成时,不需要复杂的领域先验知识,节约了大量的专家时间,提高了验证的自动化程度.分析了各种基于遗传算法的覆盖率驱动的随机测试生成方法,并在此基础上设计和实现了基于遗传算法的全芯片级覆盖率驱动随机验证平台.该平台被实际应用在龙芯处理器的验证中,实验结果表明,平台有效提高了验证效率.     

Courseware abstraction: reducing development costs while producing qualitative improvements in CAL

Abstract Courseware abstraction is an approach to CAL whereby the lesson author creates a general parameterized CAL lesson that is then applied to many concrete examples. This approach has the following advantages over alternative approaches to lesson development: it is cost efficient; it facilitates lesson verification; it encourages the provision of as many examples as are desirable; it simplifies the selection of appropriate examples for presentation to each student; it provides a convenient framework for student evaluation, and it supports the development of factually exhaustive lessons. In short, it provides qualitative improvements, while at the same time reducing lesson development costs. Although widely used, courseware abstraction has not previously been identified as an important CAL technique and its relative merits have never received attention. In particular, there has been a failure to recognize that generative CAL derives most of its power from the use of courseware abstraction.     

基于OBB树的无网格几何数据处理

提出一种新的基于有向包围盒树(Oriented Boundmg Box,OBB树)的处理无网格几何数据方案.与最常用的八叉树比较,它具有三方面优点:首先,OBB树反映了统计意义上的几何模型空间分布,它不仅提供了辅助的层次结构,其本身还可以用于生成原始几何模型的形状逼近;其次,OBB树的节点数目和所需内存比八叉树少,且更贴近几何模型;其三,遍历OBB树的代价略高于八叉树,收敛速度却更快.针对点云模型,作者将OBB树结构应用于点云模型的自适应绘制.实验结果验证了OBB树的上述优点.     

分布式海量矢量地理数据共享研究

地理空间数据的应用应用范围迅速扩大,实现空间数据的共享,充分有效利用已有数据,可节约用户成本,栅格数据的共享方式在多媒体领域有较多研究,而矢量数据研究得不多,本文讨论了分布式海量矢量地理空间数据共享的几个问题－海量空间数据的管理,传输,可视化及空间数据共享的安全问题。     

Secure service composition with information flow control in service clouds

Service clouds built on cloud infrastructures and service-oriented architecture provide users with a novel pattern of composing basic services to achieve complicated tasks. However, in multiple clouds environment, outsourcing data and applications pose a great challenge to information flow security for the composite services, since sensitive data may be leaked to unauthorized attackers during service composition. Although model checking has been considered as a promising approach to enforce information flow security precisely, its high complexity on modeling and the heavy cost on verification cause great burdens to the process of service composition. In this paper, we propose a distributed approach to composing services securely with information flow control. In our approach, each service component is first verified through model checking, and then a compositional verification procedure is executed to ensure the information flow security along with the composition of these services. The experimental results indicate that our approach can reduce the cost of verification compared with the global verification approach.     

Automatic processing of handwritten bank cheque images: a survey

Bank cheques (checks) are still widely used all over the world for financial transactions. Huge volumes of handwritten bank cheques are processed manually every day in developing countries. In such a manual verification, user written information including date, signature, legal and courtesy amounts present on each cheque has to be visually verified. As many countries use cheque truncation systems (CTS) nowadays, much time, effort and money can be saved if this entire process of recognition, verification and data entry is done automatically using images of cheques. An attempt is made in this paper to present the state of the art in automatic processing of handwritten cheque images. It discusses the important results reported so far in preprocessing, extraction, recognition and verification of handwritten fields on bank cheques and highlights the positive directions of research till date. The paper has a comprehensive bibliography of many references as a support for researchers working in the field of automatic bank cheque processing. The paper also contains some information about the products available in the market for automatic cheque processing. To the best of our knowledge, there is no survey in the area of automatic cheque processing, and there is a need of such a survey to know the state of the art.     

通用SPI Flash控制器的设计与验证

为提高X处理器的可靠性、节省其芯片管脚及功耗,以串行外设接口(SPI)Flash作为程序加载存储器,设计一款通用的SPI Flash控制器,给出其组成结构及具体实现方法。采用基于属性描述语言(PSL)的断言检查对该控制器进行功能验证,以降低验证复杂度、提高验证速度和质量。实验结果证明,其功能覆盖率达到了100%。     

一种监管友好的可编辑区块链方案

现有区块链内容监管方案均采用事后治理方式,缺乏事前审计,且存在签名失效和多版本区块验证效率低的问题。针对这些问题,首先,设计了一种可动态调整可追责的数据审计方法,实现了对区块链交易数据的事前审计;其次,设计了一种编辑可控的数字签名方案RCDSS（redaction-controlled digital signature scheme）,解决了因编辑操作造成的签名失效问题;最后,设计了一种区块链数据一致性验证协议,实现了对查询结果的高效验证。安全分析和性能测试结果表明了其安全性和有效性。该方案在实现监管可控的情况下,仍然保持了较高的区块生成和验证效率,为区块链内容监管提供了一种新的解决思路。     

Recursive hiding of biometrics-based secret sharing scheme using adversary structure

This paper first investigates the applications of recursive hiding of secret, which was originally proposed for visual cryptography to space efficient secret sharing, and then provides a novel recursive hiding of biometrics-based secret sharing scheme using adversary structure. The proposed scheme may find applications for sharing secrets with excess bits, especially in the scenarios where resources are strictly limited and the requirement of verification is demanding. Existing ways of combiner verification always just rely on exponentiation or only by hiring one-way hash function, which cannot thwart the stolen share attack, spoofing attack or discriminate an imposter who fraudulently obtains the access privileges from the genuine participant. Nonetheless, these problems can be tackled by the unique property of biometrics in our paper. Most importantly, unlike most counterpart schemes, no other random numbers are used to protect the secret pieces, hence, our scheme is simpler and more efficient, and the computation cost is relatively low.     

Selection of optimized features for fusion of palm print and finger knuckle‐based person authentication

The impact of digital technology in biometrics is much more efficient at interpreting data than humans, which results in completely replacement of manual identification procedures in forensic science. Because the single modality‐based biometric frameworks limit performance in terms of accuracy and anti‐spoofing capabilities due to the presence of low quality data, therefore, information fusion of more than one biometric characteristic in pursuit of high recognition results can be beneficial. In this article, we present a multimodal biometric system based on information fusion of palm print and finger knuckle traits, which are least associated to any criminal investigation as evidence yet. The proposed multimodal biometric system might be useful to identify the suspects in case of physical beating or kidnapping and establish supportive scientific evidences, when no fingerprint or face information is present in photographs. The first step in our work is data preprocessing, in which region of interest of palm and finger knuckle images have been extracted. To minimize nonuniform illumination effects, we first normalize the detected circular palm or finger knuckle and then apply line ordinal pattern (LOP)‐based encoding scheme for texture enrichment. The nondecimated quaternion wavelet provides denser feature representation at multiple scales and orientations when extracted over proposed LOP encoding and increases the discrimination power of line and ridge features. To best of our knowledge, this first attempt is a combination of backtracking search algorithm and 2D²LDA has been employed to select the dominant palm and knuckle features for classification. The classifiers output for two modalities are combined at unsupervised rank level fusion rule through Borda count method, which shows an increase in performance in terms of recognition and verification, that is, 100% (correct recognition rate), 0.26% (equal error rate), 3.52 (discriminative index), and 1,262 m (speed).