Godson-3: A Scalable Multicore RISC Processor with x86 Emulation

The Godson-3 microprocessor aims at high-throughput server applications, high-performance scientific computing, and high-end embedded applications. It offers a scalable network on chip, hardware support for x86 emulation, and a reconfigurable architecture. The four-core Godson-3 chip is fabricated with 65-nm CMOS technology. Eight- and 16-core Godson-3 chips are in development.     

数字签名技术在移动商务中的应用

移动商务作为一种全新的商务和服务方式,在给用户带来低成本和便捷的同时,也带了诸多安全问题。解决这些问题的手段有很多,数字签名是比较常用且非常有效的一种方法。它提供了不可抵赖、数据源认证、身份识别等特性。本文工作主要针对移动商务中的安全问题,重点研究其中的数字签名问题。通过开发设计手机银行数字签名系统和基于SMS服务的手机数字签名系统,在保障移动商务安全性的同时,为用户提供了安全的信息传递途径,特别是为移动商务的发展提供了技术支持。     

A two-phase framework for quality-aware Web service selection

Service-oriented computing is gaining momentum as the next technological tool to leverage the huge investments in Web application development. The expected large number of Web services poses a set of new challenges for efficiently accessing these services. We propose an integrated service query framework that facilitates users in accessing their desired services. The framework incorporates a service query model and a two-phase optimization strategy. The query model defines service communities that are used to organize the large and heterogeneous service space. The service communities allow users to use declarative queries to retrieve their desired services without worrying about the underlying technical details. The two-phase optimization strategy automatically generates feasible service execution plans and selects the plan with the best user-desired quality. In particular, we present an evolutionary algorithm that is able to “co-evolve” multiple feasible execution plans simultaneously and allows them to compete with each other to generate the best plan. We conduct a set of experiments to assess the performance of the proposed algorithms.     

Two-Dimensional Multilabel Active Learning with an Efficient Online Adaptation Model for Image Classification

Conventional active learning dynamically constructs the training set only along the sample dimension. While this is the right strategy in binary classification, it is suboptimal for multilabel image classification. We argue that for each selected sample, only some effective labels need to be annotated while others can be inferred by exploring the label correlations. The reason is that the contributions of different labels to minimizing the classification error are different due to the inherent label correlations. To this end, we propose to select sample-label pairs, rather than only samples, to minimize a multilabel Bayesian classification error bound. We call it two-dimensional active learning because it considers both the sample dimension and the label dimension. Furthermore, as the number of training samples increases rapidly over time due to active learning, it becomes intractable for the offline learner to retrain a new model on the whole training set. So we develop an efficient online learner to adapt the existing model with the new one by minimizing their model distance under a set of multilabel constraints. The effectiveness and efficiency of the proposed method are evaluated on two benchmark data sets and a realistic image collection from a real-world image sharing Web site—Corbis.     

Micromachining of passive planar micromixer on poly (methyl methacrylate) substrate with excimer laser ablation

Excimer laser ablation technique was introduced into this work to fabricate a passive planar micromixer on the PMMA substrate. T-junction shaped and width-changed S-shaped microchannels were both designed in this micromixer to enhance mixing effect. The mixing experiment of distilled water and Rhodamine B with injection flow rate of 500 and 1,500 μm/s validates the mixing effectivity of this micromixer, and indicates the feasibility of excimer laser ablation in the microfabrication of μ-TAS device.     

关于公平交换协议中使用正交验证理论的安全性分析及改进

所谓公平交换协议是指,一个电子商务协议能保证交易双方在执行协议的过程中,任何一方通过欺诈行为、误传消息或者提前终止协议这些不公平方式,都不可能从另一方获取利益.要么任何一方都可以得到对方的信息,要么双方都得不到对方的信息.Ray等学者自2000年先后提出了一系列基于正交验证理论的公平交换协议.这类协议的重要贡献之一在于,基于正交验证理论,通过使用一对相容密钥分别对同一商品加密,使得在不泄露所购买商品的情况下,用户在付款之前能够对所购买商品的正确性进行验证,实现了使用离线TTP的优化公平交换协议.然而,通过对Ray协议进行安全性分析发现,恶意商家可以任意传送错误商品的信息也能轻易通过用户的验证,导致用户为之付款,即该验证过程是不安全的,最终导致该类协议退化为一个使用在线TTP的公平交换协议.另外,给出了改进方案,以避免上述攻击.     

深层网查询接口的自动集成

深层网数据库的访问方式主要是通过查询接口,所以查询接口是外部访问深层网数据库的门户.为了能够同时访问同一领域多个Web数据库,需要对多个Web数据库的查询接口进行集成.因此,提出基于本体的深层网查询接口集成方法.首先构建领域核心本体,在模式匹配过程中,不断完善核心本体;然后,以本体作为媒介,在不同查询接口模式间建立属性映射关系,发现属性间的语义关联;最后,根据本体概念出现的频数生成集成接口.实验表明提出的深层网查询接口自动集成方法是可行的和高效的.     

基于使用控制模型的防恶意下载系统

为了对恶意下载行为实施有效控制,研究通用访问控制框架和使用控制模型(UCON),提出基于流量的UCON。设计并实现基于UCON的防恶意下载系统,阐述其关键技术和实现方法。实验结果表明,该模型能有效控制用户下载行为,具有高安全性和较强的操作灵活性。     

求解昂贵区间多目标优化问题的高斯代理模型

本文将数据挖掘(高斯过程回归建模)和智能进化算法(GA,NSGA-Ⅱ)进行结合,用于解决优化函数未知的昂贵区间多目标优化问题.首先利用高斯过程对采用中点和不确定度表示的未知目标函数和约束函数进行建模,由于相关性和准确性是区间函数模型的两个必备条件,故提出一种融合多属性决策的双层种群筛选策略,并将其嵌入到遗传算法求解高斯模型参数的过程中,第1层根据相关性属性排除候选解集中部分劣解,第2层根据准确性属性排除候选解集中其余超出种群规模的劣解,两属性的权重系数决定两层排除劣解的比例.然后将所建模型作为优化对象的代理模型引导区间NSGA-II算法优化求解,从而获得所需的Pareto前沿.     

基于周期信号的迭代学习控制在逆变器中的应用

提出一种基于周期信号的迭代学习控制方法,并将其应用于电力逆变器,分析了跟踪误差沿迭代方向的收敛条件,给出了控制律的时域表达形式以及参数的确定方法.由于该方法理论上可实现跟踪误差收敛到零,因而使逆变器输出电压跟踪精度大幅提高.通过MATLAB/Simulink仿真,该方法的有效性得到验证;此外,与传统PID控制相比,仿真结果显示出该方法具有较好的负载适应能力以及优越的跟踪性能.