Querying Big Data: Bridging Theory and Practice

Big data introduces challenges to query answering, from theory to practice. A number of questions arise. What queries are ＂tractable＂ on big data？ How can we make big data ＂small＂ so that it is feasible to find exact query answers？When exact answers are beyond reach in practice, what approximation theory can help us strike a balance between the quality of approximate query answers and the costs of computing such answers？ To get sensible query answers in big data,what else do we necessarily do in addition to coping with the size of the data？ This position paper aims to provide an overview of recent advances in the study of querying big data. We propose approaches to tackling these challenging issues,and identify open problems for future research.     

基于虚拟仪器的传感器性能测试系统

为检测传感器性能是否符合需求,在傅里叶级数算法原理的基础上,结合虚拟仪器技术,开发设计了传感器性能测试系统。通过实验验证了该测试系统能有效地对传感器性能进行检测,误差约为0.004,同时测试系统还具有一定的可扩展性和通用性,用于实验传感器以外的其他传感器测试。     

基于LabVIEW的弹药库房有害气体检测数据采集系统

通过气体采样分析,确定弹药库房内需要重点检测的有害气体种类,并找到库房内有害气体浓度最高的位置,安装相应的传感器对有害气体进行重点检测。硬件方面,构建了基于传感器、信号调理电路和数据采集卡的硬件系统;软件方面,开发了基于LabVIEW的数据采集软件。最后,通过实验对数据采集系统的性能进行了验证。结果表明,该系统稳定可靠,较好地完成了数据的采集、保存和查询任务。     

粮情智能测控系统中的数据融合技术研究

粮情智能测控系统是保证粮食储藏安全的关键措施之一。针对目前粮情智能测控系统中单一传感器存在测量不足、粮情安全状态难以判断且无法直接检测等问题,研究了一种基于粒子群优化最小二乘支持向量机的粮情安全状态数据融合方法。以粮情数据为研究对象,以粮情安全状态检测为目的,构建基于最小二乘支持向量机的数据融合模型,并采用粒子群优化算法对最小二乘支持向量机的关键参数进行寻优,获取最佳的数据融合结果。根据广西某粮库提供的数据进行实例分析,数据融合结果与实际值误差较小,均方误差为0.06,结果表明,该方法在粮情安全状态的检测上表现出优越的性能,具有科学性和可行性,提高了粮情智能测控系统的准确性和可靠性。     

多传感器数据采集系统中的数据融合研究

针对多传感器数据采集系统的准确性与可靠性的要求,提出了单传感器分批估计融合与模糊理论中的相关性函数与加权自适应算法相结合的数据融合方法。首先,对每一只传感器进行分批估计融合,得到了较为可靠的局部决策值。然后,利用模糊理论中的相关性函数,计算出每只传感器与其它传感器的相关程度,并剔除掉那些相关程度较低的传感器的局部决策值。最后,在权的最优分配原则下,利用加权自适应算法对剩下的局部决策值进行数据融合。该方法能在数据先验知识未知的情况下,客观地反映各个传感器的可靠程度。数据分析结果表明:与同类融合方法相比,该方法具有更高的精度。     

涡轮轴疲劳试验器控制系统设计

在航空发动机研制过程中,对涡轮轴进行模拟加载疲劳试验是一项重要的工作。该试验用于验证涡轮轴设计、加工是否具有足够的强度和在寿命期具有足够的疲劳寿命。试验器电气控制系统采用计算机加数据采集控制多功能卡模式组成核心控制系统。电气控制系统采用NI公司的虚拟仪器软件LabWindows/CVI作为控制和人机界面(HMI)的编程软件。     

基于重叠片排列的流形学习算法

针对线性数据降维算法对处理非线性结构数据的降维效果不是很好,提出一种基于重叠片排列的流形学习算法,该算法根据局部的线性贴片处在非线性流形中的特性,将流形划分为线性互相重叠的局部区域贴片,且利用主成分分析方法得到局部区域贴片的低维表示,然后排列且对齐其低维坐标,以获得整体数据的低维坐标.通过仿真结果证明,基于重叠片排列的流形学习算法在应用于人脸识别和分类问题时以及在识别准确率方面要优于其他经典的流形学习算法.     

OpenMDSP: Extending OpenMP to Program Multi-Core DSPs

Abstract Multi-core digital signal processors （DSPs） are widely used in wireless telecommunication, core network transcoding, industrial control, and audio/video processing technologies, among others. In comparison with general-purpose multi-processors, multi-core DSPs normally have a more complex memory hierarchy, such as on-chip core-local memory and non-cache-coherent shared memory. As a result, efficient multi-core DSP applications are very difficult to write. The current approach used to program multi-core DSPs is based on proprietary vendor software development kits （SDKs）, which only provide low-level, non-portable primitives. While it is acceptable to write coarse-grained task-level parallel code with these SDKs, writing fine-grained data parallel code with SDKs is a very tedious and error-prone approach. We believe that it is desirable to possess a high-level and portable parallel programming model for multi-core DSPs. In this paper, we propose OpenMDSP, an extension of OpenMP designed for multi-core DSPs. The goal of OpenMDSP is to fill the gap between the OpenMP memory model and the memory hierarchy of multi-core DSPs. We propose three classes of directives in OpenMDSP, including 1） data placement directives that allow programmers to control the placement of global variables conveniently, 2） distributed array directives that divide a whole array into sections and promote the sections into core-local memory to improve performance, and 3） stream access directives that promote big arrays into core-local memory section by section during parallel loop processing while hiding the latency of data movement by the direct memory access （DMA） of a DSP. We implement the compiler and runtime system for OpenMDSP on PreeScale MSC8156. The benchmarking results show that seven of nine benchmarks achieve a speedup of more than a factor of 5 when using six threads.     

Efficient Data Access for Location-Dependent Spatial Queries

When the mobile environment consists of light-weight devices, the loss of network connectivity and scarce resources, e.g., low battery power and limited memory, become primary issues of concern in order to efficiently support portable wireless devices. In this paper, we propose an index-based peer-to-peer data access method that uses a new Hierarchical Location-Based Sequential （HLBS） index. We then propose a novel distributed Nearest First Broadcast （NFB） algorithm. Both HLBS and NFB are specifically designed for mobile peer-to-peer service in wireless broadcast environments. The system has a lower response time, because the client only contacts a qualified service provider by accessing the HLBS and quickly retrieves the data to answer the query by using NFB. HLBS and NFB design the index for spatial objects according to the positions of individual clients and transfer the index in the order arranged so that the spatial query can be processed even after the user tunes the partial index. Hence, this design can support rapid and energy-efficient service. A performance evaluation is conducted to compare the proposed algorithms with algorithms based on R-tree and Hilbert-curve air indexes. The results show that the proposed data dissemination algorithm with the HLBS index is scalable and energy efficient in both range queries and nearest neighbor queries.     

一次表面换热器瞬态响应特性的数值模拟

根据一次表面热交换器（PSHE）的结构和流动特点，利用能量守恒定律，导出它的瞬态温度变化物理模型和数学方程式.研究工作流体温度和流量发生阶跃变化时PSHE出口温度的响应特性，分析指出一次表面换热器板片各几何参数以及通道形状对其温度响应特性的影响次序是：板片厚度δ最强，宽度W和数目n次之，波纹通道形状最弱.比较研究表明，由于PSHE的固体壁面时间常数远小于板翅式和管壳式换热器，因此这种轻质结构换热器的响应特性明显优于常规热交换器，非常适用于那些要求工况经常变动、能够提供的场地和空间又十分有限的化工联合装置.