某型探空火箭组合导航系统设计

为解决某型探宅火箭由于无控制系统造成的毪行弹道偏差及落点散布较大的问题,提出由MIMU/GPS组合导航设备、液体姿控发动机、飞控计算机等组成的低成本简控系统方案;组合导航算法采用速度位置间接匹配、反馈校正的Kalman滤波组合法;组合导航设备选用TMS32C67完成导航算法实时解算及信息融合,CPLD完成MIMU及温度传感器的数据采集,MCS51单片机完成GPS板的串口通信;数学仿真结果表明:在475s飞行时间内,火箭姿态控制精度不大于1°,飞行轨迹与理想弹道基本重合,相比原无控火箭有很大改善.     

一种支持大规模多种精度地形的实时绘制算法

为加强大规模地形数据的表现能力,通常采用地形叠加或地形编辑等方法在局部地形数据上构建更高精度的细节模型.因而如何将大规模地形数据与具有高精度的细节数据进行实时融合与绘制成为一个迫切需要解决的问题.基于Geometry Clipmap方法对这一问题开展研究,给出了一种支持大规模多种精度地形的实时绘制算法.在预处理阶段,对大规模地形数据采用clipmap结构进行组织,对细节数据使用mipmap结构进行组织;在运行阶段,重点针对clipmap更新所引起的不同种精度数据间特有的"F"形空洞进行分析和处理,使用过渡带结构对空洞区域进行修补,并对修补后的顶点进行了平滑处理.实验结果表明,该方法有效解决了"F"形空洞并支持大规模地形及细节数据的实时绘制.     

基于ARM7的油罐区测控系统的研究与设计

针对油罐区测控系统实时动态监控的需要,介绍了一种基于ARM7嵌入式微处理器的油罐区测控系统。以LPC2119为核心,采用罐区分布式结构,并用压力变送器和温度传感器分别对油罐的液位和温度进行实时在线检测和控制。软件设计中移植了μC/OS-Ⅱ操作系统,采用多任务设计方法,缩短了软件的开发进程,并有效地将LPC2119强大的管理功能和CAN总线的优点结合起来,使得通信部分能有效地将数据发送到上位机。该系统已应用于作业现场,运行可靠,取得良好的效果。     

基于服务的Agent社会组织研究

Web Service应用上的人工架构模式成为了其被高度重用的瓶颈。通过Agent对Web Service的封装能极大地改善WebService资源在应用上的主动性及智能性。针对Web Service封装后所形成的Agent服务,给出了基于服务本体及Agent服务描述语言(ASDL)的服务发现方法,并在此基础上给出了基于服务的Agent社会组织机制。实际应用证明方法可行有效。     

Data-intensive document clustering on graphics processing unit (GPU) clusters

Document clustering is a central method to mine massive amounts of data. Due to the explosion of raw documents generated on the Internet and the necessity to analyze them efficiently in various intelligent information systems, clustering techniques have reached their limitations on single processors. Instead of single processors, general-purpose multi-core chips are increasingly deployed in response to diminishing returns in single-processor speedup due to the frequency wall, but multi-core benefits only provide linear speedups while the number of documents in the Internet is growing exponentially. Accelerating hardware devices represent a novel promise for improving the performance for data-intensive problems such as document clustering. They offer more radical designs with a higher level of parallelism but adaptation to novel programming environments.In this paper, we assess the benefits of exploiting the computational power of graphics processing units (GPUs) to study two fundamental problems in document mining, namely to calculate the term frequency-inverse document frequency (TF-IDF) and cluster a large set of documents. We transform traditional algorithms into accelerated parallel counterparts that can be efficiently executed on many-core GPU architectures. We assess our implementations on various platforms, ranging from stand-alone GPU desktops to Beowulf-like clusters equipped with contemporary GPU cards. We observe at least one order of magnitude speedups over CPU-only desktops and clusters. This demonstrates the potential of exploiting GPU clusters to efficiently solve massive document mining problems. Such speedups combined with the scalability potential and accelerator-based parallelization are unique in the domain of document-based data mining, to the best of our knowledge.     

Mining Object Similarity for Predicting Next Locations

Next location prediction is of great importance for many location-based applications. With the virtue of solid theoretical foundations, Markov-based approaches have gained success along this direction. In this paper, we seek to enhance the prediction performance by understanding the similarity between objects. In particular, we propose a novel method, called weighted Markov model (weighted-MM), which exploits both the sequence of just-passed locations and the object similarity in mining the mobility patterns. To this end, we first train a Markov model for each object with its own trajectory records, and then quantify the similarities between different objects from two aspects: spatial locality similarity and trajectory similarity. Finally, we incorporate the object similarity into the Markov model by considering the similarity as the weight of the probability of reaching each possible next location, and return the top-rankings as results. We have conducted extensive experiments on a real dataset, and the results demonstrate significant improvements in prediction accuracy over existing solutions.     

基于概率交易模型的线下百货推荐

该文提出了一种新颖的概率交易模型PTM,针对线下百货进行个性化的推荐。传统的推荐模型,如K-近邻算法、矩阵分解等,或者仅利用局部的数据,使得模型面临线下数据极大的稀疏性挑战,或者忽略百货数据中的交易维度,使得模型损失了同一交易中多商品共现的强相关信息,最终导致它们在面对线下百货推荐问题时性能低下。针对以上的问题,本模型从交易的维度出发,建模交易记录中的共现模式,并利用全局的交易数据来学习商品的相关分量,在此基础上推断出用户的兴趣分布,实现个性化的推荐。在真实的线下百货交易数据上的实验结果表明,该模型能够极大地提高线下百货领域个性化推荐的准确性。
     

高校就业服务信息门户系统的设计

就业是社会及其关注的问题,也是高校一项重要的工作。本文设计的高校就业服务信息门户系统的目的是完善高校就业服务工作,将学生、用人单位、就业政策和高校的信息有效的进行结合和对接。本文从技术支持、功能设计、数据库设计和用户界面几方面对系统的设计进行了详细的阐述。     

能耗最优的水下滑翔机采样路径规划

研究了以能耗为优化准则的水下滑翔机海洋环境参数采样路径规划方法.首先,根据水下滑翔机的运动特点,建立了水下滑翔机采样作业过程的能耗模型;其次,基于能耗模型提出了一种能耗最小的滑翔运动参数优化方法,该方法避免了求解复杂的混合整数非线性规划问题;之后,在能耗最优的滑翔运动参数优化基础上,提出了一种基于两步链式Lin-Ker...     

一种支持多重循环软件流水的寄存器结构

寄存器结构及其分配是软件流水算法的关键之一.为支持多重循环的软件流水,该文提出一种新颖的寄存器结构：半共享跳跃式流水寄存器堆.它可以有效地解决多重循环软件流水下的特殊问题,即：同层次和跨层次的寄存器重命名问题以及断流问题;有效地消除外层循环的体间读写相关,提高程序的指令级并行度.它有3种分配方式可供灵活使用：单个寄存器、流水寄存器和寄存器组方式.流水寄存器方式对生存期确定的、局限于一个循环层次的寄存器重命名问题提供简单而有效的支持.寄存器组分配方式解决了多重循环软件流水时变量生存期不确定的情况.跳跃操作为