CAD与CAPP集成研究回转体类零件特征识别

本文研究了回转体轴类,轴套类零件的特征识别。对这类零件常用的特征单元进行了定义,描述了这类零件的特征模型:介绍了它的识别方法和特征参数定义方法。     

软件组件技术在欧特克产品中的应用

软件组件技术是一些可执行单元,可以通过独立的开发和配置,然后整合到各个独立的软件系统中去,是软件系统内被标识、符合某种标准要求的组成部分。针对欧特克用户对软件使用的新需求,通过对用户工作流程以及产业发展的分析,提出了使用组件技术的解决方案,论述了以软件组件技术为核心的解决方案,在欧特克产品实施中的设计、实现过程。     

磁性材料产业现状与展望

介绍磁性材料的主要品种，如永磁体、软磁体和磁记录介质材料的行业现状及技术进步。     

光催化剂SrTiO3的制备及其性能的研究

论述用化学液相共沉淀法制备SrTiO_3的最佳条件,及在不同的活化条件下对SrTiO_3光催化性能的影响。此外还研究了掺入过渡金属氧化物对SrTiO_3催化性能的改善。     

水下拖曳体多源信息监控系统设计与实现

基于海洋电法探测系统中水下拖曳体对多源信息实时监控的需求,设计了一种准实时监测拖曳体的运动状态与环境信息的监控系统。该系统可与水面监控器保持命令与数据沟通,并在监控器的指令下启动水下电法仪执行参数设置、数据采集等操作。经系统样机的海上测试结果表明,系统性能稳定可靠,能够在其他水下信息采集作业中得到推广应用。     

Tri-pyramid Robot: Design and kinematic analysis of a 3-DOF translational parallel manipulator

3-DOF translational parallel manipulators have been developed in many different forms, but they still have respective disadvantages in different applications. To overcome their disadvantages, the structure and constraint design of a 3-DOF translational parallel manipulator is presented and named the Tri-pyramid Robot. In the constraint design of the presented manipulator, a conical displacement subset is defined based on displacement group theory. A triangular pyramidal constraint is presented and applied in the constraint designs between the manipulator?s subchains. The structural properties including the decoupled motions, overconstraint elimination, singularity free workspace, fixed actuators and isotropic configuration are analyzed and compared to existing structures. The Tri-pyramid Robot is constrained and realized by a minimal number of 1-DOF joints. The kinematic position solutions, workspace with variation of structural parameters, Jacobian matrix, isotropic and dexterity analysis are performed and evaluated in the numerical simulations.     

Surface morphology and nodule formation mechanism of cellulose acetate membranes by atomic force microscopy

By the use of atomic force microscopy (AFM), formation mechanism of nodular structure in cellulose acetate membranes was systematically investigated. Elementary factors affecting the nodule formation were delineated on the basis of both kinetic and thermodynamic considerations. It was shown that (1) the exact nature of nodular structure is thermodynamic equilibrium glassy state; nodular structure will vanish in the rubbery state; (2) the thermodynamic factor affecting nodule formation is the membrane formation temperature; with the membrane formation temperature decreasing, more chain segments are able to form nodular structures; (3) nodule formation is dependent on the segment rearrangement; variation of the solvent environment is the major kinetic factor affecting the segment rearrangement and nodule formation. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 1328–1335, 2003     

Security-aware intermediate data placement strategy in scientific cloud workflows

Massive computation power and storage capacity of cloud computing systems allow scientists to deploy data-intensive applications without the infrastructure investment, where large application datasets can be stored in the cloud. Based on the pay-as-you-go model, data placement strategies have been developed to cost-effectively store large volumes of generated datasets in the scientific cloud workflows. As promising as it is, this paradigm also introduces many new challenges for data security when the users outsource sensitive data for sharing on the cloud servers, which are not within the same trusted domain as the data owners. This challenge is further complicated by the security constraints on the potential sensitive data for the scientific workflows in the cloud. To effectively address this problem, we propose a security-aware intermediate data placement strategy. First, we build a security overhead model to reasonably measure the security overheads incurred by the sensitive data. Second, we develop a data placement strategy to dynamically place the intermediate data for the scientific workflows. Finally, our experimental results show that our strategy can effectively improve the intermediate data security while ensuring the data transfer time during the execution of scientific workflows.     

Increasing recommended effectiveness with markov chains and purchase intervals

Recommendation system is an important component of many websites and has brought huge economic benefits and challenges for online shoppers and e-commerce companies. Existing recommendation systems focus on producing a list of products which users may be interested to purchase, while overlooking the purchase chain and temporal diversity which may increase the likelihood of a purchase decision. In this paper, we propose to utilize the Markov chain to track the chain of users’ purchase behaviors and utilize the purchase intervals to improve the temporal diversity for e-commerce recommender. We design and implement several algorithms and integrate these into our recommendation model. We evaluate our system on a real-world e-commerce dataset. Experimental results demonstrate that our approach significantly improves the accuracy, conversion rate and temporal diversity compared to the state-of-the-art algorithms.