CAD/CAM技术及应用对我国机械制造业的影响

分析了我国机械制造业和CAD/CAM技术的现状,预测了它们未来的发展趋势,指出了CAD/CAM软件开发应遵循的原则,阐述了CAD/CAM技术及应用的发展对我国机械制造业的巨大影响和深远意义.     

An error-based micro-sensor capture system for real-time motion estimation

A wearable micro-sensor motion capture system with 16 IMUs and an error-compensatory complementary filter algorithm for real-time motion estimation has been developed to acquire accurate 3D orientation and displacement in real life activities. In the proposed filter algorithm, the gyroscope bias error, orientation error and magnetic disturbance error are estimated and compensated, significantly reducing the orientation estimation error due to sensor noise and drift. Displacement estimation, especially for activities such as jumping, has been the challenge in micro-sensor motion capture. An adaptive gait phase detection algorithm has been developed to accommodate accurate displacement estimation in different types of activities. The performance of this system is benchmarked with respect to the results of VICON optical capture system. The experimental results have demonstrated effectiveness of the system in daily activities tracking, with estimation error 0.16 ±0.06 m for normal walking and 0.13 ±0.11 m for jumping motions.     

基于循环谱包络的BPSK信号码元速率改进估计算法

采用频域平滑周期图法估计循环谱，分析了循环谱包络的谱特征，推导出了谱峰幅度和位置值，提出了一种基于循环谱包络BPSK信号的码元速率估计的改进算法，给出了信号估计的具体步骤，分析了估计算法的性能．进行了计算机仿真实验。仿真结果表明该估计算法可适用于较低信噪比情况，无需多维搜索。     

移动自组网中基于渗流理论的概率可靠分发协议

提出了基于渗流理论的概率可靠分发协议(PLPD).与其他概率可靠分发协议不同,PLPD协议感知节点的地理信息并进行有向分发,不需要泛洪控制信息来进行组成员管理.在PLPD协议中,每个组成员只需维护其邻近区域中部分其他组成员视图,并以一定的概率向视图中的成员转发消息.采用渗流理论对PLPD协议的分发过程建模,从理论上证明了当分发概率参数大于某个阈值时,PLPD使每个消息被分发到所有组成员的概率为1.模拟实验表明,PLPD协议在获得高可靠性的同时有效地减少了网络负载,并在大规模移动自组网络中有较好的可扩展性.     

西南铝工业用水的污染控制

铝加工工业最大的环境问题是工业废水问题.作者对西南铝工业用水污染治理及监测状况进行了简要的归纳与总结,在对近4年的工业废水监测数据进行统计分析与污染源综合评价的基础上,探讨了主要污染因子污染程度的动态变化过程和各个污染源对区域水质污染的贡献程度,分析了该企业工业用水管理中可能存在的问题并提出相应建议.     

复合材料机翼结构热校形工艺实验及数值模拟

纤维增强树脂基复合材料机翼结构复杂,往往存在明显的固化变形现象,严重影响机翼的装配和气动特性。本研究目的在于建立大型复合材料复杂结构的热校形工艺方法,解决复合材料机翼制造的变形控制问题。针对复合材料机翼的固化变形特点,设计了新的热校形夹具工装。在评价复合材料应力松弛特性的基础上,建立了大型复合材料机翼结构热校形工艺的有限元模拟方法,实现了对热校形后机翼结构残余变形的有效预报,分析了校形载荷、校形温度等关键工艺参数对校形效果的影响规律,形成优化的热校形工艺方案。模拟及实验结果表明,复合材料热校形工艺可以适用于大型复杂结构,复合材料机翼89.5%的固化变形被热校形工艺的残余变形抵消,达到机翼的装配和气动外形要求。      

虚拟现实技术在动漫设计中的应用

随着科学技术的不断创新与发展,虚拟现实技术在中国动漫设计行业中的应用越来越普遍,其已经成为当前动漫设计行业发展的关键技术之一。在动漫设计工作中,要创作出更丰富和精彩的动漫作品,设计者必须凭借现代化信息技术,在动漫设计中融入虚拟现实技术,实现我国动漫设计行业的改革创新。文中主要阐述了虚拟现实技术在动漫设计工作中的主要呈现方法,并探究了在动漫设计工作中应用虚拟现实技术的对策。     

一种新的结构化对等网负载均衡算法

研究结构化对等网(P2P)中的负载均衡问题,P2P网络的节点、延迟和处理能力差异性很大,当前负载均衡算法忽略节点差异性,造成网络负载极不平衡,容易出现"热点"问题,使负载变化大。为了更好的均衡P2P负载,提出一种新的网络负载均衡算法。算法充分考虑节点之间的差异性,对物理节点的地址空间进行动态分配,对于热点资源下载采用局部搜索算法找到邻居节点,并自动把负载转移到轻载节点上,保证节点间负载均衡。仿真结果表明,新网络负载均衡算法加快了负载均衡速度,使P2P网络负载均衡更加均衡,能够很好保持系统稳定性。     

基于FPGA和ARM的AES算法设计和实现

针对于高级加密标准(AES,advanced encryption standard)硬件实现的可重构与效率问题,提出了一种基于现场可编程逻辑器件(FPGA,field programmable gate array)和微处理器ARM(advanced RISC machines)的AES设计方法。基于电子密码本(ECB,electronic code book)操作模式,可完成AES所有标准的加密和解密,并进行了工程实现与验证,可作为IP(intellectualproperty)核使用。为实现理想的数据吞吐率/面积比,结合AES和FPGA的特点,对字节替换和密钥扩展采用查表的优化算法,并提出了列混合的优化结构,在保证运算速度下节约了器件资源。利用FPGA内部自带的双端口可配置随机存取存储器(RAM,random access memory)作为信息与密钥的缓存,解决存储和ARM与FPGA时序问题。在进行资源与速度的分析和与3种典型设计比较后的结果表明,具有最好的吞吐率/面积比。     

Artificial intelligence based ensemble approach for intrusion detection systems

Internet attacks pose a severe threat to most of the online resources and are a prime concern of security administrators these days. In spite of many efforts, the security techniques are unable to detect the intrusions accurately. Most of the methods suffer from the limitations of a high false positive rate, low detection rate and provide one solution which lacks the classification trade-offs. In this work, an effective two-stage method is proposed to produce a pool of non-dominating solutions or Pareto optimal solutions as base models and their ensembles for detecting the intrusions accurately. It generates Pareto optimal solutions to a chromosome structure in stage 1 formulating Pareto front. Whereas, another approximation to the Pareto front of optimal solutions is made to obtain non-dominating ensembles in the second stage. The final prediction ensemble solutions are computed from individual predictions using majority voting approach. Applicability of the suggested method is validated using benchmark dataset NSL-KDD dataset. The experimental results show that the recommended method provides better results than conventional ensemble techniques. The recommended method is also adequate to generate Pareto optimal solutions that address the issue of improving detection accuracy for minority as well as majority attack classes along with handling classification tradeoff problem. The proposed method resulted detection accuracy of 97% with FPR of 2% for KDD dataset respectively. The most attractive feature of the proposed method is that both generation of base classifier and their ensemble thereof are multi-objective in nature addressing the issue of low detection accuracy and classification tradeoffs.