基于图像的信息隐秘检测系统的设计

传统的网络访问控制机制大多与身份认证机制分开设计,针对其安全性差、效率低等问题,受人体免疫系统能自动识别并排斥非自体物质原理启发,该文提出了一种基于家族基因的网络访问控制模型(FBAC),给出了模型中网络家族、家族基因、基因证书等定义,建立了基因指派、制定族规、基因签名等用于生成基因证书的机制,描述了网络家族构造和基于家族基因的访问控制等算法.解决了入侵者绕过身份认证机制而存取网络资源的安全问题,克服了X.509数字证书认证效率低、证书主体信息不明确的缺陷,具有安全、高效等特点,是保障网络安全的一种有效新途径.     

基于家族基因的网络访问控制模型

传统的网络访问控制机制大多与身份认证机制分开设计，针对其安全性差、效率低等问题，受人体免疫系统能自动识别并排斥非自体物质原理启发，该文提出了一种基于家族基因的网络访问控制模型(FBAC)，给出了模型中网络家族、家族基因、基因证书等定义，建立了基因指派、制定族规、基因签名等用于生成基因证书的机制，描述了网络家族构造和基于家族基因的访问控制等算法。解决了入侵者绕过身份认证机制而存取网络资源的安全问题，克服了X.509数字证书认证效率低、证书主体信息不明确的缺陷，具有安全、高效等特点，是保障网络安全的一种有效新途径。     

基于组合阶双线性群的组签名方案

利用Lewko等人于2010年提出的三素数组合阶双线性群理论,构建了一个基于BMW模型的高效组签名方案,并通过引进Groth-Sahai等人提出的非交互式零知识证明理论,解决了传统组签名方案通信效率低、不能抵抗选择密文攻击等问题.方案中签名的大小是一个常量而非依赖于其它系统参数.作者同时给出了严格的安全性证明,并将文中方案分别与已有的典型方案在效率和安全性方面进行了比较,结果表明该方案在这两方面均具有一定优势.     

基于MicroWindows的多设备支持智能中文输入系统

针对现有嵌入式中文输入系统输入设备种类支持单一、中文输入引擎效率低、用户体验差等问题,提出一种基于MicroWindows的智能中文输入系统。系统首先在前端的设备输入实现层模块式完成了不同类型的设备消息封装投递,然后在消息处理中心对各种输入设备的投递信息进行集中处理,通过统一分发处理的方式编码为输入法处理的消息类型,最后结合改进N元文法模型与用户模型实现中文输入引擎。MIPS等硬件平台的实际应用结果表明,该系统运行状态良好,汉字输入流畅快捷,比以往的中文输入方式提高了35%的输入效率。     

连锁业务中远程数据传输的研究与实现

远程数据传输是连锁业务系统的关键技术之一.为实现企业总部和各门店之间高效、稳定、可靠的远程数据传输,通过比较研究远程数据传输方法,并结合连锁业务系统的特点,提出一种兼顾经济性、效率性和安全性的远程数据传输方案,应用断点续传技术实现数据传输的可靠性,应用身份认证和加密技术保证数据的安全性,应用多线程技术满足实时高效的数据传输要求.该方案能较好地应用于连锁业务系统.     

基于超椭圆曲线密码的共享验证签名方案

分析了已有共享验证数字签名协议，针对已有方案运算开销大、执行效率低、安全性差的缺陷，提出了一类基于超椭圆曲线密码的共享验证数字签名方案；方案中的协议与算法安全、简洁、高效，降低了软硬件实现的系统开销，可广泛应用于计算机与无线通信等网络环境。     

基于区块链的铁路电子提单系统

提单是国际物流中的重要单证, 应用于铁路运输时将提高货物和资金流转效率. 现存的电子提单系统存在安全性低、公信力不足等问题, 难以保障各个参与方的权益. 本文在满足提单主要功能的基础上, 利用区块链去中心化、可溯源、可编程的特性, 确定了基于区块链的电子提单系统框架. 采用超级账本技术, 本文设计并实现了在区块链网络中多机构、多角色参与的电子提单发布、审核、质押等业务逻辑, 保证了电子提单安全、高效地流转. 经过区块链系统打包的交易数据, 凭借共识机制被锚定在链上, 实现了交易信息实时共享与查询, 有效地解决了物权争议与货物追踪问题.     

一种通用高效的重叠网格"挖洞"算法

研究了建立重叠包络面和中空(非计算区域)包络面的鲁棒性方法,并提出了迷路算法应用于确定重叠包络面内外点,为重叠网格提供了高效、可靠、通用的"挖洞"算法,该算法复杂度低、实现简单、健壮性较好.实验结果表明,对于大网格量的复杂计算区域问题,该算法仍能得到较理想的效率.     

云计算在网络综合设计教学中应用初探

针对通用实验机房面临的实验环境安全性问题和维护效率低下问题,根据云计算的优势,探索将云计算平台应用于具体实践课程中。云计算平台在网络综合设计课程中的实践应用表明,云计算可使实验环境维护变得轻松、实验过程变得安全高效、实验组织变得更加灵活。     

绑定式近场通信3GCOS安全性研究

分析近场通信技术在应用上的安全问题和3GCOS系统的安全属性,针对卡的安全性问题提出解决方案。以3G的USIM卡为载体,采用近场通信技术把非接触的应用绑定在USIM卡上,在USIM卡中共存非接触应用的系统,并通过不同的接口实现方式与外界接触,实现不同的应用功能,制造出集成非接触应用的USIM卡。     

Proteomics analysis of cellular components in lentiviral vector production using Gel-LC-MS/MS

Among the gene therapy vectors developed to date, lentiviral vectors persist in the host and are therefore best suited for long-term gene transfer and gene-replacement therapies. Human immunodeficiency virus (HIV)-1-based lentiviral vector products are currently produced by transient transfection, filtration and ultracentrifugation, and the quality of the resultant vector product is variable. We reason that by identifying host proteins co-produced with viral vectors we may better understand the mechanism of viral vector production, and improve the safety and quality of the resultant products. Our LC-MS/MS studies identified both viral vector proteins and host proteins, including nuclear proteins, elongation factors and chaperone and heat shock proteins (HSP), and confirmed the presence of known HIV-incorporated proteins, e.g. elongation factor-1α, HSP70 and Histone 2A, demonstrating the capability and viability of LC-MS/MS methods for the proteomic analysis of highly complex samples. Evaluation of the functions of the identified components is in progress to understand their implication for product quality and safety. These studies support the development of improved production and characterisation methods and advance the clinical application of lentiviral vector-based products.     

Field, force and transport analysis for magnetic particle-based gene delivery

Magnetic particles are used to deliver gene vectors to target cells for uptake in a process known as magnetofection. Magnetic particle-based gene delivery has been successfully demonstrated for all types of nucleic acids and across a broad range of cell lines. It is well suited for multiwell culture plate systems wherein magnetic particles with surface-bound gene vectors are introduced into culture wells, and a magnetic force provided by rare-earth magnets beneath and aligned with the wells attracts the particles to the cells for uptake. In this paper, models are presented for analyzing and optimizing this process. These include closed-form equations for predicting the magnetic field and force and a drift–diffusion equation for predicting the transport and accumulation of particles in a well. The closed-form equations enable rapid parametric analysis of the spatial distribution of the field and force in a well as a function of key parameters including its dimensions, the magnet-to-well spacing, the strength of the magnet, the influence of neighboring magnets and the properties of the particles. The particle transport equation accounts for the field-induced drift of particles as well as fluidic drag and Brownian diffusion. It is solved numerically using the finite volume method. The theory is demonstrated via application to a multiwall plate magnetofection system and the impact of various factors that govern gene delivery is assessed. The models provide insight into gene delivery and are well suited for parametric analysis of particle accumulation in the wells. They enable the rational design of novel magnetofection systems.     

Overview of microneedle system: a third generation transdermal drug delivery approach

Transdermal drug delivery has given cardinal contribution to medical practices. First-generation transdermal delivery of small, lipophilic, low-dose drugs and second-generation delivery systems using chemical enhancers, non-cavitational ultrasound and iontophoresis have also resulted in various clinical products provides added functionality. Third-generation delivery systems using microneedles, thermal ablation, microdermabrasion, electroporation and cavitational ultrasound targeting skin’s barrier layer of stratum corneum. Microneedles acquire pronounced intrigue in recent days. Currently, microneedles are advancing through clinical trials for delivery of macromolecules and vaccines, such as insulin, parathyroid hormone and influenza vaccine. The review explains about the concept of transdermal drug microneedle system comprising of microreservoir, micropumps, flow sensors, types of microneedles. Various researches carried out on these components of microneedle system is elaborately discussed in this review.     

Experimental evaluation of software development tools for safety-critical real-time systems

Since the early years of computing, programmers, systems analysts, and software engineers have sought ways to improve development process efficiency. Software development tools are programs that help developers create other programs and automate mundane operations while bringing the level of abstraction closer to the application engineer. In practice, software development tools have been in wide use among safety-critical system developers. Typical application areas include space, aviation, automotive, nuclear, railroad, medical, and military. While their use is widespread in safety-critical systems, the tools do not always assure the safe behavior of their respective products. This study examines the assumptions, practices, and criteria for assessing software development tools for building safety-critical real-time systems. Experiments were designed for an avionics testbed and conducted on six industry-strength tools to assess their functionality, usability, efficiency, and traceability. The results some light on possible improvements in the tool evaluation process that can lead to potential tool qualification for safety-critical real-time systems.     

An adaptive updating protocol for reducing moving object database workload

In the last decade, spatio-temporal database research focuses on the design of effective and efficient indexing structures in support of location-based queries such as predictive range queries and nearest neighbor queries. While a variety of indexing techniques have been proposed to accelerate the processing of updates and queries, not much attention has been paid to the updating protocol, which is another important factor affecting the system performance. In this paper, we propose a generic and adaptive updating protocol for moving object databases with less number of updates between objects and the database server, thereby reducing the overall workload of the system. In contrast to the approach adopted by most conventional moving object database systems where the exact locations and velocities last disclosed are used to predict their motions, we propose the concept of Spatio-temporal safe region to approximate possible future locations. Spatio-temporal safe regions provide larger space of tolerance for moving objects, freeing them from location and velocity updates as long as the errors remain predictable in the database. To answer predictive queries accurately, the server is allowed to probe the latest status of objects when their safe regions are inadequate in returning the exact query results. Spatio-temporal safe regions are calculated and optimized by the database server with two contradictory objectives: reducing update workload while guaranteeing query accuracy and efficiency. To achieve this, we propose a cost model that estimates the composition of active and passive updates based on historical motion records and query distribution. More system performance improvements can be obtained by cutting more updates from the clients, when the users of system are comfortable with incomplete but accuracy bounded query results. We have conducted extensive experiments to evaluate our proposal on a variety of popular indexing structures. The results confirm the viability, robustness, accuracy and efficiency of our proposed protocol.     

Reservoir-based polymer drug delivery systems

The importance of drug delivery has increased over the past decades, and significant advances have been made in the development of novel technologies. This review focuses on the use of different polymer drug delivery systems and their advancement toward clinical applications.     

SVM在基因表达数据分类中的研究和应用

介绍了一种使用基因芯片实验产生的基因表达数据对功能基因进行分类的方法,该方法是以支持向量机(SVM)理论为基础的。文中描述了径向基函数SVM,与其它SVM相比,径向基函数SVM在基因分类中有更好的性能。SVM的理论基础是统计学习理论,它不仅结构简单,而且技术性能高,泛化能力强,在基因表达式分类中表现出有很多优点,成为热点研究方向。     

Application of iot medical image detection and prenatal genetic testing in obstetric clinic

The use of new techniques and methods can be significantly improved during prenatal examination and screening of fetal genetic abnormalities. Expanding the number of vectors in screening and screening for single-cell gene diseases in fetal DNA will increase the probability of success of the whole screening test.Recently, sub chromosomal abnormalities have been introduced into prenatal care. The lack of suitable tools makes it very difficult to obtain information about collection, management, and prenatal genetic testing. The purpose of this study is to improve the accessibility of nutritional information by using the advantages of advanced medical image detection and integrating the IoT (Internet of Things) and prenatal genetic testing platforms in obstetric outpatient clinics. Records are kept that the platform will allow IoT to interact with sensor practitioners and provide immediate access to medical images prior to delivery. This proposed system provides an IoT application for managing obstetric outpatient information and prenatal genetic testing requirements. The requirement for establishment is the realization of the development of an IoT platform for complete medical image detection information management with IoT input required for integration with existing medical information systems. In response, the purpose of the study is to use integrated IoT applications to help nutrition professionals, researchers, patients, and especially mothers, to enhance their collection of medical imaging and prenatal genetic testing IoT sensor based information transfer.     

Cancer classification using ensemble of neural networks with multiple significant gene subsets

Molecular level diagnostics based on microarray technologies can offer the methodology of precise, objective, and systematic cancer classification. Genome-wide expression patterns generally consist of thousands of genes. It is desirable to extract some significant genes for accurate diagnosis of cancer because not all genes are associated with a cancer. In this paper, we have used representative gene vectors that are highly discriminatory for cancer classes and extracted multiple significant gene subsets based on those representative vectors respectively. Also, an ensemble of neural networks learned from the multiple significant gene subsets is proposed to classify a sample into one of several cancer classes. The performance of the proposed method is systematically evaluated using three different cancer types: Leukemia, colon, and B-cell lymphoma.     

基因表达谱数据分析技术

人类基因组计划的研究已进入后基因组时代,后基因组时代研究的焦点已经从测序转向功能研究,主要采用无监督和有监督技术来分析基因表达谱和识别基因功能,通过基因转录调控网络分析细胞内基因之间的相互作用关系的整体表示,说明生命功能在基因表达层面的展现,对目前基因表达谱数据分析技术及它们的发展,进行了综述性的研究,分析了它们的优缺点,提出了解决问题的思路和方法,为基因表达谱的进一步研究提供了新的途径。