Embedded medical big data network and nursing intervention of aspiration pneumonia

In this work, doctors can find useful tips to discover semantic similarities to diagnostic tasks, natural biomedical language, and writing to obtain effective simulations. It proposes a concrete analytical framework for a considerable collection. It does some preliminary analysis using datasets extracted from the entire graduate entrance exam library. It has developed a web front end to demonstrate this method's practicality in the real-world context. The quickly extending field of enormous information examination is starting to assume a basic function in creating clinical practice and exploration. It gives a device to amass and retain a lot of organized and unstructured information created by the board, investigation, and current medical services frameworks. As of late, big data information examination has been applied to measures that help clinical administrations and illness investigation. The appropriation and R and D in this space are hampered by some key issues intrinsic in the huge information worldview. Basic Analysis of Images, Signals, and Genomics: In this article focus on these key challenges and discusses some of the three promising medical research areas. It targets large amounts of medical data, and the use of multimodal data from different sources has also been discussed in recent studies. Research Areas with the potential and significant impact in providing medical services are also being considered.     

Human health big data evaluation based on FPGA processor and big data decision algorithm

At present, the development of health care industry is also very vigorous and prosperous, and has become one of the most widely developed industries in the world. Medical centers and service centers in various regions have begun to transform from medical model to health care model. This field programmable gate array has great advantages in this respect, and it is also one of the principles of patient-centered nursing. With the vigorous development of machine learning, its application scope is more and more extensive, and its application in medicine is also very common. People use machine learning to process big data in the medical field. In order to better manage patient data and realize patient-centered, we must analyze a large number of health data. The traditional management tools are not enough to support the analysis of modern data. Therefore, we should use advanced big data processing technology for relevant data processing, and use updated tools to meet the current medical needs. The signal processing based big data evaluation is to be done through FPGA. The proposed system contains three process these process are executed through the machine learning based. The first process preprocessing is used eliminate the noise of the image or irrelevant data avoided. The second process feature selection based decision tree technique used and then after the final process classification stage based machine learning technique is used to analysis of the big data accuracy level. FPGA based machine technique used to achieve the better result of the proposed system.     

基于概率的大数据查询系统——Probery

针对大数据环境下完整性查询时间代价消耗过高的问题,提出了一种采用近似完整性查询方法的系统——Probery。Probery所采用的近似完整性查询方法不同于传统的近似查询,其近似性主要体现为数据查全的可能性,是一种新型的数据查询方法。Probery首先将存入系统的数据划分为多个数据分段;然后,根据概率放置模型将各个数据分段的数据存储在分布式文件系统中;最后,对于给定的查询条件,Probery采用一种启发式查询方法进行概率查询。通过与其他主流的非关系型数据管理系统的查询性能进行比较,对Probery进行验证,Probery在损失8%查询完整性的情形下,查询时间较HBase相比节约了51%,较Cassandra相比节约了23%,较MongoDB相比节约了12%,较Hive相比节约了3%。实验结果表明,Probery可以适当地损失查询完整性来提高数据的查询性能,具有较好的通用性、适应性和可扩展性。     

医疗大数据平台数据高并发方案设计与关键技术分析

结合近几年在医疗大数据平台开发领域的工作实践和对现阶段主流开源开发技术的应用,在对医疗大数据平台的数据和业务特点深入理解和分析的基础上,从开源技术角度对端到端的业务系统的高并发问题详细描述了总体方案设计和关键技术分析。     

大数据环境下医疗数据隐私保护对策研究

随着大数据技术和"互联网+医疗健康"应用的蓬勃发展,个人医疗数据信息在全生命周期各阶段均面临着越来越多的隐私泄漏挑战,安全问题频发。在对北京市部分医院和患者进行个人医疗数据信息隐私保护问题调研分析基础上,面向医疗大数据环境分析了个人医疗数据全面生命周期存在的隐私信息泄漏风险模式,进而从法规规范层面、技术措施层面和应用实施层面提出了一个个人医疗数据隐私保护框架,并分别从隐私保护意识提升和安全技术措施层面提出个人医疗数据隐私保护对策与建议。     

轻量级大数据运算系统Helius

针对Spark数据集不可变,以及Java虚拟机（JVM）依赖环境引起的代码执行、内存管理、数据序列化/反序列化等开销过多的不足,采用C/C++语言,设计并实现了一种轻量级的大数据运算系统--Helius。Helius支持Spark的基本操作,同时允许数据集整体修改;同时,Helius利用C/C++优化内存管理和网络传输,并采用stateless worker机制简化分布式计算平台的容错恢复过程。实验结果显示：5次迭代中,Helius运行PageRank算法的时间仅为Spark的25.12%~53.14%,运行TPCH Q6的时间仅为Spark的57.37%;在PageRank迭代1次的基础上,运行在Helius系统下时,master节点IP接收和发送数据量约为运行于Spark系统的40%和15%,而且200 s的运行过程中,Helius占用的总内存约为Spark的25%。实验结果与分析表明,与Spark相比,Helius具有节约内存、不需要序列化和反序列化、减少网络交互以及容错简单等优点。     

基于大数据的掌上医疗器械检索平台研究

为了提高掌上医疗器械的信息化检索和管理能力,提出基于大数据的掌上医疗器械检索方法,构建掌上医疗器械检索的大数据分布模型,采用有向图模型构建掌上医疗器械信息库的检索节点分布结构模型,在掌上医疗器械信息库库中进行语义关联规则分析,采用字符串的匹配技术,建立掌上医疗器械信息库检索的模糊决策模型,采用大数据融合方法实现掌上医疗器械检索的算法设计,结合自相关特征匹配方法实现掌上医疗器械信息库的语义特征提取,实现掌上医疗器械检索平台的优化设计。仿真结果表明,采用该方法进行掌上医疗器械检索的智能性较好,检索的查准性较高,时延较低。     

基于FPGA的数据采集系统的设计

介绍了一种用于汽车姿态测量的数据采集系统的设计,该系统基于FPGA+USB架构,采用FPGA控制整个系统的采集时序,USB芯片作为数据采集通道,上位机完成姿态解算和数据显示功能.     

一种基于快递大数据的异常检测系统

随着信息时代的到来，快递行业迅速发展起来，推动着流通方式的转型和消费升级。人们在享受快递业发展带来巨大便捷的同时，也伴随着难以控制的流动性风险，给公共安全带来严峻的挑战。例如，偷窃的赃物通过快递方式进行销赃，利用快递方式运输毒品、爆炸物等危险物品。基于以上考虑，通过分析真实的历史快递记录，着力于研究利用快递方式进行销赃这一类犯罪行为，进而以识别该类嫌疑人为研究目标，从统计、时间和地理3方面特征进行了详细的分析。另外，提出了一种Two Step异常检测方法用于嫌疑人的识别。该方法分为2步，第1步是过滤正常用户，第2步是识别嫌疑人。实验结果表明，通过该方法能够准确地识别出嫌疑对象，相比较传统方法，该方法能够有效地解决正负类数据不平衡问题，降低误检率，因此具有较高的实用价值。     

基于大数据的智慧灌溉系统构建研究

针对传统农作物灌溉方式容易造成严重的水资源浪费,缺乏科学有效的灌溉方式,提出一种基于大数据的智慧灌溉系统.首先,搭建了以STM32F103作为核心处理器硬件平台;通过对无线传感器终端、数据汇集终端、灌溉执行终端和上机位软件功能模块4个部分的设计,完成对系统软件的设计.然后,构建了基于LSTM的智慧灌溉预测模型.最后,根...     

基于大数据的企业信息化互补系统设计

为解决当前企业中存在的企业信息化特征不明显、变量因素不确定、无法确保企业是否盈利等问题,设计了大数据环境下企业信息化互补系统。该系统根据企业信息化互补机制的阶段性特征,改进互补系统硬件部分;利用企业信息化资本调查方式设定互补变量,提高企业信息化资本的调查速率,对互补函数进行设定与分析,分析中小企业和大企业之间互补机制差异,完成系统软件部分的优化,实现大数据环境下企业信息化互补系统设计。将传统互补系统与改进互补系统进行对比,验证大数据环境下企业信息化互补系统的实行对企业的运营效益。实验结果表明,该系统能确保企业运营长期处于盈利状态,并可获得良好收益。本系统的设计也为内外资企业的互补提供良好的外部环境。     

基于FPGA的USB接口数据采集系统设计

介绍了一种高速实时数据采集系统的设计.该系统以FPGA作为逻辑控制的核心,以USB2.0作为与上位机数据传输的接口,能同时支持单端16路和差分8路模拟信号输入,最大采样率为200kHz,12位的转换精度.描述了系统的主要组成和FPGA模块化设计的实现方法,并给出了其核心模块的时序仿真波形图.     

基于FPGA的数据采集分析系统设计

FPGA是一种高密度逻辑器件。与通用的MCU相比,FPGA具有并行数据处理特性。利用该特性,能够实现对高速A/D的采样控制;同样,使用FPGA对采样数据进行频谱分析,能够达到比DSP芯片更高的数据处理速度。     

基于FPGA和USB的数据采集系统的设计

介绍了一种用于炮口冲击波精确测量的数据采集系统设计.该系统是一种基于通用串行总线(USB)接口和FPGA技术的多通道同步数据采集系统,采用FPGA控制系统的采集时序,USB芯片作为数据采集通道,上位机完成数据显示功能,最后对电路进行了环境测试,并分析了测试结果.     

基于FPGA的遥感数据采集与快视系统

提出了一种基于现场可编程门阵列（FPGA）的实时遥感卫星数据采集与快视系统的设计方案,该方案充分利用FPGA的硬件资源简化逻辑设计,并采用总线复用技术和内存映射文件的方法实现了采集和快视的实时并行处理以及海量数据的高速存取。     

Business big data analysis based on microprocessor system and mathematical modeling

Big data analysis requires examining large amounts of data. This is, so discover the hidden patterns, and give the insight to make decisions on the correct business. Companies, because it uses the power of data and technology be a more objective data-driven. Big data of human resources, faced with various problems from big data storage security problems. These issues have been discussed in the next four categories based on the Contextual Data Analyzing Technique (CDAT) using FPGA tool. Data were collected and finally to analysts that are eligible to determine the problems caused by direct analysis, on security issues, and to find the problem. Companies that big data is presented to improve the company's strategy, to the best of time, various opportunities to make the right decisions. Human resources are one of the substantive departments of any company that needs big data benefits in a different process. The main purpose is to describe the big human data analysis method to improve company performance. Also, the problem is, all of the human resources department is that it is facing using big data.     

基于空间大数据的院前急救非均匀相对稳定模型

将一块区域等分网格化或等分蜂窝格化通常是院前急救资源(如急救站点、急救车辆)分布分配的模型基础,即院前均匀化模型。迄今为止,依据均匀化模型实现急救资源覆盖仍是对院前问题认识的基本思想基础。主要以深圳市宝安人民医院院前科为观察对象,通过院前急救空间大数据分析,提出了院前急救3个空间数据特征,即:非均匀特征、相对稳定特征、个体差异特征,为重新认识院前急救、更好地把握院前急救提供了新方法和新的决策依据。重点基于院前非均匀相对稳定特征提出了一种院前非均匀相对稳定模型的建模方法,并应用规划数学探讨了院前医院站点优化计算分布。     

A MRI image segmentation method based on medical semaphore calculating in medical multimedia big data environment

Multimedia Tools and Applications - In this paper, we calculate global signal distribution of medical images, including intensity distribution and direction of the signal. We can get a global...     

Robotic hand system design for mirror therapy rehabilitation after stroke

Microsystem Technologies - This paper developed a robotics-assisted device for the stroke patients to perform the hand rehabilitation. Not only the system can perform passive range of motion...