Vertical handoff algorithm in heterogeneous networks to maximize system benefit

A new vertical handoff decision algorithm is proposed to maximize the system benefit in heterogeneous wireless networks which comprise cellular networks and wireless local area networks (WLANs). Firstly the block probability, the drop probability and the number of users in the heterogeneous networks are calculated in the channel-guard call admission method, and a function of the system benefit which is based on the new call arrival rate and the handoff call arrival rate is proposed. Then the optimal radius of WLAN is obtained by using simulation annealing (SA) method to maximize the benefit. All the nodes should handoff from cellular network to WLAN if they enter WLAN’s scope and handoff fromWLAN to cellular network if they leave the scope. Finally, the algorithm in different new call arrival rates and handoff call arrival rates is analyzed and results show that it can achieve good effects.     

Automatic patent document summarization for collaborative knowledge systems and services

Engineering and research teams often develop new products and technologies by referring to inventions described in patent databases. Efficient patent analysis builds R&D knowledge, reduces new product development time, increases market success, and reduces potential patent infringement. Thus, it is beneficial to automatically and systematically extract information from patent documents in order to improve knowledge sharing and collaboration among R&D team members. In this research, patents are summarized using a combined ontology based and TF-IDF concept clustering approach. The ontology captures the general knowledge and core meaning of patents in a given domain. Then, the proposed methodology extracts, clusters, and integrates the content of a patent to derive a summary and a cluster tree diagram of key terms. Patents from the International Patent Classification (IPC) codes B25C, B25D, B25F (categories for power hand tools) and B24B, C09G and H011 (categories for chemical mechanical polishing) are used as case studies to evaluate the compression ratio, retention ratio, and classification accuracy of the summarization results. The evaluation uses statistics to represent the summary generation and its compression ratio, the ontology based keyword extraction retention ratio, and the summary classification accuracy. The results show that the ontology based approach yields about the same compression ratio as previous non-ontology based research but yields on average an 11% improvement for the retention ratio and a 14% improvement for classification accuracy.     

有关最低工资标准确定若干问题的系统思考

最低工资制度是社会保障制度的重要组成部分。论文在对国内外有关最低工资制度的研究现状进行综述的基础之上,归纳出最低工资制度与标准的发展脉络及趋势,进而指出研究最低工资标准的基本思路与主要内容,最后提出了确定最低工资标准的建议。     

山东省奶业发展战略研究

研究了山东省奶业发展中存在的问题,并通过战略研究寻找解决问题的办法。提出了山东省奶业发展10项战略措施,可供政府部门、加工企业和饲养业决策参考。图1,表1,参2。     

水泥窑协同处置生活垃圾的燃烧特性分析优化

针对传统方法难以分析掺烧生活垃圾后的水泥窑复杂燃烧特性的问题,引入数据挖掘技术,以国内某水泥厂为对象,采集相关参数数据,使用稳定性选择算法分析各参数对煤耗与NO_x排量的影响系数,通过随机森林算法建立煤耗与NO_x排量的数学模型,结合K-means聚类算法得出关键优化参数及其最优值。结果表明,该方法能够建立精确的煤耗与NO_x排量模型,挖掘出节能减排的关键优化参数及其最优目标值。通过改善关键优化参数至最优值,能够大大降低煤耗与NO_x排量,可指导水泥厂优化窑内燃烧特性。     

基于VR运动模拟器的体感模拟算法的研究

针对VR(Virtual Reality)运动模拟器使用的经典体感模拟控制算法存在相位延迟、虚假暗示的缺点导致虚实运动一致性不够,引发VR晕动症的问题,提出了一种改进体感模拟算法。改进体感模拟算法在经典模拟算法的基础上加入了前庭感知系统,对算法的输出误差进行反馈,采用模糊控制算法对输入加速度和角速度进行修正和预测,并且对虚拟现实中地形的起伏变化进行模拟。在MATLAB/Simulink中对改进体感模拟算法进行建模仿真,仿真结果表明改进体感模拟算法降低了相位延迟和虚假暗示,提高了虚实运动的一致性。     

可重构视频阵列处理器测试平台设计与实现

针对可重构视频阵列处理器的设计要求及传统测试方法测试视频编解码系统时速度慢、精度低和可观测性不强的问题。开发了基于Qt的用户界面,设计实现了以现场可编程门阵列(Field programmable gate-array,FPGA)为核心的软硬件协同测试平台。在PC端实现以软件仿真为基础的数据传输与图像重现,在FPGA端实现以可重构视频阵列处理器为基础的视频编解码算法并行映射。实验结果表明,在工作频率为100 MHz时,FPGA与PC之间可正确传输数据并满足算法测试时不同测试用例的更换需求,具有较好的可观测性。     

作战仿真模型组合流程动态可编辑方法研究

针对作战仿真系统灵活性差、交互性低、可操作性难等问题,结合国内外仿真系统设计模式现状,在深入研究作战模型动态组合技术、作战模型动态编辑技术和可视化编程技术的基础上,提出了一种基于脚本语言的支持可视化编程、模型组合可动态修改的作战模型仿真技术,在模型设计上采用面向接口与切面设计方式,从而实现灵活高效作战行为建模与仿真。通过舰艇平台仿真系统开展攻防对抗作战仿真,对方法的可行性与有效性进行了验证。试验结果表明,该方法提高了作战仿真开发效率与灵活性,具有较好的应用前景。     

多精英采样与个体差分学习的分布估计算法

提出了基于多精英采样和差分搜索的分布估计算法EDA-M/D (Estimation distribution algorithm based on multiple elites sampling and individuals differential search)。EDA-M/D利用多精英个体独立采样生成子代来提升算法全局搜索能力,利用精英群体分布的σ²约束采样半径,实现种群从全局搜索逐步过度到局部搜索。当精英群体停滞时,劣势个体借助精英群体的μ和种群历史最优解进行差分搜索,帮助种群跳出局部最优解。通过多精英采样与差分搜索的自适应协同实现种群宏观信息与个体微观信息的有机融合。实验结果表明EDA-M/D在稳定性和搜索能力方面均表现出明显的优势。