Data acquisition system based on LabVIEW for array sensors

本文介绍了以单片机进行数据采集,LabVIEW为开发平台,两者之间通过串口进行通信的多通道数据采集系统。该系统可对低频传感器信号进行采集、显示和存储。文中详细介绍了软、硬件设计方案和测试结果。This paper describes a data acquisition and display system based on LabVIEW platform and AT89S51 Microcontroller, which communicate with each other via RS232 interface, using user-defined communication protocol to ensure communication efficiency and stability. The system adopts MAX197 A/D converter, which acquires 0～+ 10V voltage signals through 6 analog input channels with 12-bit resolution. And the MCU is programmed with Assembly Language. LabVIEW carries out the management tasks, including the data acquisition control, Serial Port Communication control, display and storage of available data. The system, which has low cost and good performance, has been tested and reflects easy operation, good stability and reliability

The Analysis and Assessment of Groundwater Quality of Qinhuangdao

针对秦皇岛市地下水位下降,环境污染日益严重的现实,开展了以海水入侵区为主的地下水质综合评价与分析。在全市境内布设76眼监测井,用单因子法和综合法对地下水质量进行了评价,并对地下水水质变化趋势进行了分析。研究结果表明:Ⅰ类水只占5.3%,Ⅱ、Ⅲ水占14.5%,Ⅳ类及超Ⅳ类水占到80%以上,其中Ⅴ类水占40%。主要污染物有Fe、Mn、NO3-N、Cl、总硬度等。地下水质监测动态变化显示:总硬度、Cl-、矿化度、F-等呈上升趋势,其中总硬度和Cl-上升达75%,说明海水入侵的影响很大。To conter the situation of increasingly declining groundwater level and environmental pollution,the water quality assessment and analysis of sea water invasion district was studied.76 monitoring wells were laid,a single index method and the method of the comprehensive evaluation were used and the groundwater trends was analyzed.The results showed that the shallow groundwater of Qinhuangdao City meeting the Ⅰcategory water standard accounted for only 5.3%,Ⅱ,Ⅲcategories 14.5%,Ⅳ,Ⅴcategories more than 80%,40% of which wasⅤcategories and that Fe,Mn,NO3-N,Cl,total hardness were the major chemical components.The dynamics monitoring of underground water indicated that total hardness,chlorine,degree of mineralization,fluorine are becoming upward trend,especially total hardness and chlorine increased by over 75%, which means salt water intrusion on the larger impact.河北省自然基金项目(301165

Treatment of PEG wastewater by batch-fed hydrolytic- aerobic recycling process

A novel batch-fed hydrolytic-aerobic recycling process was used in the treatment of PEG-containing waste water and the performance of the process was studied.When the concentration of PEG6000 and COD_ Cr were 1.0 g·L~ -1 and 2300 mg·L~~ -1 respectively,the hydrolytic-aerobic recycling process could better degrade PEG than the single hydrolytic or aerobic sequencing batch reactor(SBR)process.The recycling rate and volume ratio of hydrolytic and aerobic system were two important parameters,which influenced the treatment capacity of the recycling process.国家自然科学基金项目(20076037).~

Small fixed-wing unmanned aerial vehicle recovery system

本发明涉及无人机回收领域，具体地说是一种小型固定翼无人机回收系统，包括无人船、滑轨台、拦阻索、回收网系统、无人机和相对设置的机械臂，滑轨台设置于无人船上，在所述滑轨台上设有滑轨，且所述相对设置的机械臂分别可移动地设置于不同的滑轨上，所述相对设置的机械臂动力输出端通过拦阻索相连，所述回收网系统包括主架体和设置于主架体之间的回收网，且回收网两侧的主架体分别可移动地设置于不同的滑轨上，在所述无人机上设有连接钩，且所述无人机降落时，所述连接钩先钩住所述拦阻索，然后无人机落入所述回收网中。本发明将无人船与无人机结合，能够实现在无人船上对小型固定翼无人机有效拦截回收

Robot flexible controller for complex CPS (Cyber Physical System) and implementation method thereof

本发明涉及了一种用于复杂CPS的机器人柔性控制器及其实现方法，属于智能制造控制领域。本发明的控制器包括机器人模型模块，控制算法模块，传感器模块，观测器模块和动态连接模块。方法包括：任务描述与解析；由动态连接模块描述机器人模型模块、控制算法模块、传感器模块之间的连接规则，并根据需求定义性能指标；动态连接模块根据自定义规则生成动态连接表，通过仿真对比，在控制算法模块中选取符合性能指标的控制算法；生成可执行的实时仿真代码，下载到控制机中并实时运行。本发明的控制器不针对某一个别型号的机器人，其标准化、模块化的设计理念适用于多种机型的机器人控制应用。</p

Frequent Sequential Pattern Mining under Differential Privacy

频繁序列模式挖掘是数据挖掘领域的1个基本问题,然而模式本身及其支持度计数都有可能泄露用户隐私信息.差分隐私(differential privacy, DP)作为一种新出现的隐私保护技术,定义了一个相当严格的攻击模型,通过添加噪音使数据失真达到隐私保护的目的.由于序列数据内在序列性和高维度的特点 ,给差分隐私应用于频繁序列模式挖掘带来了挑战.对此提出了一种基于交互式差分隐私保护框架的频繁序列模式挖掘算法Diff-FSPM(differen tial-privacy frequent sequential pattern mining).该算法利用指数机制获取最优序列长度,并采用一种维规约策略获得原始序列数据集的规约表示,有效降低序列维度的影响;应用前缀树压缩频繁 序列模式,利用拉普拉斯机制产生的噪音扰动频繁模式的真实支持度计数,同时采用闭频繁序列模式和Markov假设,有效分配隐私预算,并利用一致性约束后 置处理,增强输出模式的可用性.理论角度证明算法满足epsilon-差分隐私,实验结果验证算法具有较好的可用性.Frequent sequential pattern mining is an exploratory problem in the field of data mining. However, directly releasing the discovered frequent patterns and the corresponding true supports may reveal the individuals' privacy. The state-of-the-art solution for this problem is differential privacy, which offers a strong degree of privacy protection by adding noise. Due to the inherent sequentiality and high-dimensionality in sequences, it is challenging to apply differential privacy to frequent sequential pattern mining. To address those problems, this paper presents a differentially private method called Diff-FSPM that uses an interactive way to find frequent patterns. To reduce the impact of dimensionality, Diff-FSPM first employs the exponential mechanism to obtain the optimal sequential length for truncating each sequence in the original dataset. After that, Diff-FSPM relies on a prefix-tree to compress all the frequent patterns, and then utilizes the Laplace mechanism to perturb the true support of the frequent patterns. To efficiently allocate the privacy budget, Diff-FSPM uses the closet frequent pattern and Markov assumption to guide the mining process. Finally, Diff-FSPM adopts a post-processing technique with consistency constraint to boost the accuracy of the returned noisy support counts. We theoretically prove that Diff-FSPM satisfies epsilon-differential privacy, and the experimental results show that it outperforms the existing methods in terms of utility