结合断言与覆盖率为导向的验证方法

伴随着半导体工艺的不断发展,可以将更多的功能集成到单系统芯片上.这对传统的验证方法和验证途径提出了种种挑战.以覆盖率为导向的验证方法中,覆盖率模型是在外部通过DUT执行的功能来统计覆盖率,很难侦测到DUT内部的工作状态,存在对功能"遗漏点"的侦测.基于断言的验证方法可以将断言加入到DUT内部,通过断言覆盖加强覆盖率检测.阐述了将断言和覆盖率为导向相结合的验证方法,并用此种方法对USB2.0系统进行了验证.讨论了如何将两种验证方法有效地结合,并且通过比较覆盖率为导向的验证方法与结合断言与覆盖率为导向的验证方法的结果,说明结合断言与覆盖率为导向的验证方法提高了验证过程中的观测性,减少了验证周期.     

数据挖掘中分类方法的研究

分类是数据挖掘中的最重要的技术之一。目前实现分类的方法有统计方法、机器学习方法和人工智能方法等，常用的技术有决策树分类、贝叶斯分类、神经网络分类等。通过对当前具有代表性的分类算法原理进行分析、比较，总结出每种算法的性能特征，既便于使用者了解掌握各种分类算法、更好地选择合适的算法，又便于研究者对算法进行研究改进，提出性能更好的分类算法。     

面向大规模日志数据的聚类算法研究

针对大规模日志数据的聚类问题,提出了DBk-means算法.该算法使用Hadoop对原始日志数据进行预处理,并结合了k-means和DBSCAN聚类算法各自的优势.实验结果表明,相比k-means算法进行聚类分析,文中使用DBk-means算法进行聚类,能够取得更好的聚类效果,正确率可以达到83％以上.     

基于数据挖掘技术的提高公路路面质量的模型研究

由于我国建设高速公路的历史不长,对高速公路路面寿命的客观规律的了解还不太全面、深入。因此需要对现有的试验数据进行研究分析,从中寻找提高高速公路路面质量的改进方案以延长高速公路路面的寿命。根据实践中获得的海量数据,利用数据挖掘等计算机技术进行处理,建立数学模型。还进一步挖掘出如何选择和配置原材料,才能提高高速公路路面质量。     

基于大数据挖掘技术的机动车驾驶人智能培训系统的研究

文章以LBS技术、RIDF物联网技术、基于可视化分析的大数据技术等为基础,建立一套机动车驾驶人智能预约培训监管系统。系统基于RFID识别距离探测、大功率远距离WIFI数据传输、LBS智能跟踪定位等技术对教练车,教练员,学员进行实时定位跟踪,智能监管,可以有效杜绝驾考行业偷减学时,教练擅自离岗等乱象,避免学车过程中的安全事故。同时,采集机动车驾驶人培训各项相关数据,根据可视化技术及大数据挖掘技术进行分析,构建一个科学,合理,高效的智能学车推荐模型。     

Data Mining for Hierarchical Model Creation

In this paper, we examine the problem of learning inhabitant behavioral models in intelligent environments. We maintain that inhabitant interactions in smart environments can be automated using a data-driven approach to generate hierarchical inhabitant models and learn decision policies. To validate this hypothesis, we have designed the ProPHeT decision-learning algorithm that learns a strategy for controlling a smart environment based on sensor observation, power line control, and the generated hierarchical model. The performance of the algorithm is evaluated using real data collected from our MavHome smart home and smart office environments.     

数据开采若干新方法研究

决策离不开知识，从数据库中采掘知识、是解决信息爆炸和知识贫乏的有效途径。文中就当前数据开采的几种新方法，即粗集、语气理论和云模型等方法的研究现状进行了评述，指出其存在的问题，最后指出数据开采方法面临的挑战。     

Distributed PIN Verification Scheme for Improving Security of Mobile Devices

The main driving force for the rapid acceptance rate of small sized mobile devices is the capability to perform e-commerce transactions at any time and at any place, especially while on the move. There are, however, also weaknesses of this type of e-commerce, often called mobile e-commerce, or m-commerce. Due to their small size and easy portability mobile devices can easily be lost or stolen. Whereas the economic values and privacy threats protected with Personal Identification Numbers (PIN) are not particularly high for normal voice-enabled mobile phones, this is not true any more when phones have developed to Personal Trusted Devices (PTDs). Still, PINs are used also in this new context for authorization and identification purposes. PINs are currently used both for protection of the devices and for authentication, as well as authorization of the users. It is commonly recognized that not many techniques of storing the PINs into the memory of the device or on the SIM card are safe. Even less sophisticated thieves might uncover the PIN inside the stolen mobile devices and for sophisticated thieves uncovering the PIN stored safely might be possible. In this paper we propose a new scheme to cope with the problem of uncovering the PIN that reduces the risks of m-commerce. The basic idea is that instead of storing the entire PIN digits (or some hash value) in the mobile device, we store part of the PIN in a remote machine in the network. The PIN verification then involves both the mobile device and the remote machine, which must verify their respective parts of the PIN. Also, the improvements of the security over the existing schemes are shown using a probabilistic model. In the best case, where the probability of discovering the PIN irrespective of the storage scheme is negligible in relation to directly uncovering it, the increase in security is over 1000%.     

并行数据挖掘算法综述

数据挖掘在工业和商业领域中发挥着越来越重要的作用.随着数据量的增加,挖掘算法处理海量数据的能力问题日益突出.研究并行算法,是解决这一问题的有效途径.该文对常用的数据挖掘算法C4.5,SLIQ,SPRINT,关联规则,K-平均值,K-最近邻,贝叶斯网络,人工神经网络,遗传算法及并行性进行了研究探讨,为数据挖掘研究者提供借鉴.     

在线签名识别的数据采集与通信

笔迹信息的数据采集是在线签名识别算法的基础。设计由四线电阻式触摸屏,触摸屏控制器ADS7846,单片机AT89S52构成的采集系统实现在线签名识别的数据采集。采用USB接口芯片PDIUSBD12实现与PC机的通信。实现了对签名笔迹的坐标、速度及压力信息的采集与传输,并对采集的数据进行预处理。实验结果表明签名采集系统采集精度高,稳定可靠,抗干扰能力强。     

采用数据挖掘技术的数据库审计系统

针对传统数据库审计系统分析预警能力不强的状况,本文设计了一个新型的基于数据挖掘技术的数据库审计系统.系统利用数据挖掘技术中的关联和聚类算法,完成用户行为模式的规则总结,实现了对用户异常行为的自适应入侵检测.     

数据仓库和数据挖掘语言初探

着重阐述了数据仓库的基本概念、特征和体系结构，并介绍了使DW作用得以发挥的决策支持工具。还介绍了几种数据挖掘语言及其标准化方面的研究进展，提出了数据挖掘语言分类的方法，在此基础上，对数据挖掘语言的结构和组成进行了探讨和研究，最后指出了数据挖掘语言的发展趋势，以及若干待解决的问题。     

数据挖掘助力精细化流量经营

移动互联网时代,移动数据流量正以前所未有的速度在增长,电信运营商面临着增量不增收、流量套餐渗透率不高、自有移动互联网业务推广难等问题.本文结合电信运营商的实际案例,介绍运用协同式过滤、社交网络分析、决策树等数据挖掘技术在流量套餐精确营销、移动互联网业务个性化推荐等流量经营重点工作中的应用和效果.     

Data Replication for Improving Data Accessibility in Ad Hoc Networks

In ad hoc networks, due to frequent network partition, data accessibility is lower than that in conventional fixed networks. In this paper, we solve this problem by replicating data items on mobile hosts. First, we propose three replica allocation methods assuming that each data item is not updated. In these three methods, we take into account the access frequency from mobile hosts to each data item and the status of the network connection. Then, we extend the proposed methods by considering aperiodic updates and integrating user profiles consisting of mobile users' schedules, access behavior, and read/write patterns. We also show the results of simulation experiments regarding the performance evaluation of our proposed methods     

Web数据挖掘技术研究

Web数据挖掘就是利用数据挖掘技术从网络文档和服务中发现和提取信息。Web数据挖掘是一种新兴的边缘科学技术,他涉及到机器学习、数据挖掘、信息检索、自然语言处理、数据库以及人工智能等技术,可用于网络检索、网站建设以及电子商务等方面。根据数据挖掘对象的不同可以将Web数据挖掘分为3类:Web内容挖掘、Web结构挖掘和Web访问信息挖掘。     

关联规则的挖掘

数据挖掘是在数据库中对数据进行一定的处理 ,获得其中隐含的 ,事先未知的 ,却又可能极为有用的信息。介绍了数据挖掘的概念和技术 ,应用Apriori算法进行关联规则的挖掘 ,应用于实例中 ,取得了良好的结果。     

Parametric Evaluation of Video Motion Tracking Data Sets

Video tracking is a complex problem because the environment, in which video motion needs to be tracked, is widely varied based on the application and poses several constraints on the design and performance of the tracking system. Current datasets that are used to evaluate and compare video motion tracking algorithms use a cumulative performance measure without thoroughly analyzing the effect of these different constraints imposed by the environment. But it needs to analyze these constraints as parameters. The objective of this paper is to identify these parameters and define quantitative measures for these parameters to compare video datasets for motion tracking.     

Signature Verification and Bloom Hashing Technique for Efficient Cloud Data Storage

Wireless Personal Communications - In transform based image denoising methods, how to modify the transform coefficients is an important problem. In wavelet image denoising, two-dimensional tensor...     

现场核查中的数据认证协议

现场核查中,各种核查数据通常需要在公开信道中进行远程传输才能到达核查方,因此,数据很容易被篡改．为保证数据的真实性和完整性,本文首先建立了一种多重数据认证协议,其中采用的关键技术是数字签名和验证技术[1～2]．最后,对协议进行了全面的评估．