计算机数据安全存储技术及应用

数据安全是计算机安全问题的核心,对于很多具有高度保密要求的单位,安全地存储重要数据,并且在不需要这些数据时作彻底销毁不被他人恢复是至关重要的。本文详细介绍了数据安全存储技术的发展现状,并结合典型的企业信息安全防护体系设计进一步阐述了如何为具有一定保密要求的部门建立可靠的数据安全防护系统。此外,本文从数据存储和销毁的原理上进行了详细分析,并给出了应用软件及案例的测试说明,提出了安全销毁数据的详细解决方法。     

A robust critical path in an environment with hybrid uncertainty

In this article, we consider the project critical path problem in an environment with hybrid uncertainty. In this environment, the duration of activities are considered as random fuzzy variables that have probability and fuzzy natures, simultaneously. To obtain a robust critical path with this kind of uncertainty a chance constraints programming model is used. This model is converted to a deterministic model in two stages. In the first stage, the uncertain model is converted to a model with interval parameters by alpha-cut method and distribution function concepts. In the second stage, the interval model is converted to a deterministic model by robust optimization and min-max regret criterion and ultimately a genetic algorithm with a proposed exact algorithm are applied to solve the final model. Finally, some numerical examples are given to show the efficiency of the solution procedure.     

基于内容的静态语义概念视频检索方法研究

本文针对互联网视频检索技术的发展,阐述了目前主流视频搜索引擎的技术现状,分析了互联网视频检索的关键技术,特别是对于视频特征的提取技术。本文的创新点是提出了一种通用的基于内容的静态语义视频检索方法,该方法可以弥补基于文本视频检索的有关不足,并且在TRECVID的视频概念检索数据的静态语义概念中得到验证,运行稳定。     

一种简化的三维模糊制器

针对三维模糊控制器规则多,结构复杂,难以实现的问题,提出了一种简化的三维模糊控制器。该方法是把三个输入量分别为偏差、偏差变化、偏差的偏差变化的一维模糊控制器加权融合实现简化的三维模糊控制器。并提出了根据不同类型的被控对象设置三个加权系数。加权系数具有粗调、细调和微调的作用,类似于传统PID调节器的比例、积分和微分,实现对系统静差的消除。     

面向多商户的第三方电子券系统设计与实现

电子券正成为商家促销的一种新技术手段.在一个已有的定制化电子券系统的基础上,针对服务于多商户的应用背景,对系统的需求进行了重新梳理和流程优化,给出了改造后的系统架构.同时,还对新系统的权限管理与访问控制问题进行了重点分析和设计,引入基于角色的访问控制模型,使之能支持面向多商户的管理.     

软件单元测试应用研究及案例分析

单元测试是软件测试过程的第一站,高质量的单元测试是软件质量保证的必要条件,本文就单元测试的概念、测试类型及规程作了简单的阐述,同时就单元测试进行了案例分析。     

检验标准管理系统的设计与实现

检验标准管理系统从工作实际出发,采用VisualBasic来制作交互介面,MicrosoftAccess作为后台支持的数据库来管理数据信息,从而实现产品质量检验机构的检验标准管理自动化。该系统是从服务客户和检验人员的角度出发,本着为客户提供准确、快捷、方便服务和更好管理本单位检验标准、方便检验人员使用的原则,可使检验机构大量的检验标准信息得以快捷管理,缩短了客户办理检验业务的时间,以及检验人员检验过程中快速查询使用检验标准的相关信息。本管理系统主要完成:对检验标准中数据的增加、数据的删除、数据的查询和数据的浏览。     

Estimation in Random Coefficient Autoregressive Models

Abstract. We propose the quasi‐maximum likelihood method to estimate the parameters of an RCA(1) process, i.e. a random coefficient autoregressive time series of order 1. The strong consistency and the asymptotic normality of the estimators are derived under optimal conditions.     

PRAND: GPU accelerated parallel random number generation library: Using most reliable algorithms and applying parallelism of modern GPUs and CPUs

The library PRAND for pseudorandom number generation for modern CPUs and GPUs is presented. It contains both single-threaded and multi-threaded realizations of a number of modern and most reliable generators recently proposed and studied in Barash (2011), Matsumoto and Tishimura (1998), L’Ecuyer (1999,1999), Barash and Shchur (2006) and the efficient SIMD realizations proposed in Barash and Shchur (2011). One of the useful features for using PRAND in parallel simulations is the ability to initialize up to 10¹⁹${10}^{19}$ independent streams. Using massive parallelism of modern GPUs and SIMD parallelism of modern CPUs substantially improves performance of the generators.     

A hybrid intelligent system for medical data classification

In this paper, a hybrid intelligent system that consists of the Fuzzy Min–Max neural network, the Classification and Regression Tree, and the Random Forest model is proposed, and its efficacy as a decision support tool for medical data classification is examined. The hybrid intelligent system aims to exploit the advantages of the constituent models and, at the same time, alleviate their limitations. It is able to learn incrementally from data samples (owing to Fuzzy Min–Max neural network), explain its predicted outputs (owing to the Classification and Regression Tree), and achieve high classification performances (owing to Random Forest). To evaluate the effectiveness of the hybrid intelligent system, three benchmark medical data sets, viz., Breast Cancer Wisconsin, Pima Indians Diabetes, and Liver Disorders from the UCI Repository of Machine Learning, are used for evaluation. A number of useful performance metrics in medical applications which include accuracy, sensitivity, specificity, as well as the area under the Receiver Operating Characteristic curve are computed. The results are analyzed and compared with those from other methods published in the literature. The experimental outcomes positively demonstrate that the hybrid intelligent system is effective in undertaking medical data classification tasks. More importantly, the hybrid intelligent system not only is able to produce good results but also to elucidate its knowledge base with a decision tree. As a result, domain users (i.e., medical practitioners) are able to comprehend the prediction given by the hybrid intelligent system; hence accepting its role as a useful medical decision support tool.