Analysis of sea level changes in the Caspian Sea related to Cosmo-geophysical processes based on satellite and terrestrial data

Analysis results of the average annual sea levels in the Caspian Sea obtained from ground and satellite observations, corresponding to solar activity characteristics, magnetic field data, and length of day are presented. Spectra of the indicated processes were investigated and their approximation models were also built. Previously assumed statistical relationships between space-geophysical processes and Caspian Sea level(CSL) changes were confirmed. A close connection was revealed between the low-frequency models of the solar and geomagnetic activity parameters and the CSL changes. Predictions extending into the next decades showed a high probability of an increase in the CSL and a decrease of the compared space-geophysical parameters.

Multimode Process Monitoring Based on the Density-Based Support Vector Data Description

Complex industry processes often need multiple operation modes to meet the change of production conditions. In the same mode,there are discrete samples belonging to this mode. Therefore,it is important to consider the samples which are sparse in the mode.To solve this issue,a new approach called density-based support vector data description( DBSVDD) is proposed. In this article,an algorithm using Gaussian mixture model( GMM) with the DBSVDD technique is proposed for process monitoring. The GMM method is used to obtain the center of each mode and determine the number of the modes. Considering the complexity of the data distribution and discrete samples in monitoring process,the DBSVDD is utilized for process monitoring. Finally,the validity and effectiveness of the DBSVDD method are illustrated through the Tennessee Eastman( TE) process.

Fast Web - Based Data Transmission

Since web based GIS processes large size spatial geographic information on internet, we should try to improve the efficiency of spatial data query processing and transmission. This paper presents two efficient methods for this purpose: division transmission and progressive transmission methods. In division transmission method, a map can be divided into several parts, called “tiles”, and only tiles can be transmitted at the request of a client. In progressive transmission method, a map can be split into several phase views based on the significance of vertices, and a server produces a target object and then transmits it progressively when this spatial object is requested from a client. In order to achieve these methods, the algorithms, “tile division”, “priority order estimation” and the strategies for data transmission are proposed in this paper, respectively. Compared with such traditional methods as “map total transmission” and “layer transmission”, the web based GIS data transmission, proposed in this paper, is advantageous in the increase of the data transmission efficiency by a great margin.

Image Processing on Geological Data in Vector Format and Multi-Source Spatial Data Fusion

The geological data are constructed in vector format in geographical information system (GIS) while other data such as remote sensing images, geographical data and geochemical data are saved in raster ones. This paper converts the vector data into 8 bit images according to their importance to mineralization each by programming. We can communicate the geological meaning with the raster images by this method. The paper also fuses geographical data and geochemical data with the programmed strata data. The result shows that image fusion can express different intensities effectively and visualize the structure characters in 2 dimensions. Furthermore, it also can produce optimized information from multi-source data and express them more directly.

大数据驱动的决策制定:乐观抑或悲观?

大数据驱动公共决策模式迭代升级,重构了决策制定、执行、监督和反馈全链条中的权力关系与资源配置。对此,学界出现了乐观论与悲观论两种基本的论调:乐观者认为大数据驱动的决策制定具有诸多优势和良好发展前景;悲观者则认为现实中的大数据并不一定会促使决策更加精准、科学和民主,反而可能会因数据本身来源和格式的复杂性、数据互通和共享标准的差异性、多主体利益博弈的政治性以及隐私侵犯和信息泄露的可能性而导致更为复杂的政策失灵。进一步分析发现,乐观论和悲观论之间的分歧主要源于技术与政治、权利与权力、工具理性与价值理性之间孰轻孰重。面向未来,可以推动大数据驱动的决策制定向审慎的乐观主义迈进,建构数字技术、政治过程与制度运作之间的互嵌与互适关系,以此锚定大数据驱动决策制定的基本方向,真正发挥大数据在政府决策和社会治理中的作用。

基于QT的多型号弹载记录仪回读系统设计

弹载记录仪在军事和航天领域发挥着重要作用。然而,不同的弹载记录仪在数据上传方式、编帧结构和回读指令等方面可能存在差异,这导致传统的回读系统无法满足其多样化的需求。为解决这一问题,设计了一种基于QT的多型号多功能数据回读系统。该系统支持多种接口传输方式,用于读取不同型号的弹载记录仪数据。同时,它可以根据不同型号的记录仪设置相应的读取指令,并实时绘制回读过程中的数据曲线。回读完成后,系统能够分离处理不同编帧方式的数据。试验验证表明,该系统能够有效实现针对不同型号记录仪的数据回读、数据绘制和数据分离等功能。该系统的设计显著提高了回读过程的效率和灵活性,具有较强的工程实用价值。

数据手套用柔性传感系统及信号特征分析技术

对数据手套采集信息的各组成部件进行归纳,总结数据手套中的传感系统,重点探讨柔性传感器的制备和传感阵列在手套中的集成。综述数据手套在不同应用场景下对采集信号的处理模式,特别介绍深度学习及神经网络计算方法在手势识别中的研究进展。最后,总结数据手套需突破的问题及未来发展趋势。

5G基站设备数据配置故障分析处理研究

5G基站设备是5G通信网络中的重要组成设备,是连接5G网络用户终端设备与5G核心网的桥梁,直接与网络用户终端设备进行信息发送与接收,给网络用户提升感知,因此5G基站设备运行是否正常显得格外重要。借助5G基站设备数据配置故障分析处理思维导图,依托5GStar软件对真实环境进行仿真实践,对5G基站设备故障或进行数据配置时出现的故障进行分析并作对应处理,可以给网络维护人员提供一定参考。

面向动态路网的移动对象分布式k近邻查询算法

动态路网k近邻(kNN)查询是许多基于位置的服务(LBS)中的一个重要问题。针对该问题,提出一种面向动态路网的移动对象分布式kNN查询算法DkNN(Distributed kNN)。首先,将整个路网划分为部署于集群中不同节点中的多个子图;其次,通过并行地搜索查询范围所涉及的子图得到精确的kNN结果;最后,优化查询的搜索过程,引入查询范围剪枝策略和查询终止策略。在4个道路网络数据集上与3种基线算法进行了充分对比和验证。实验结果显示,与TEN~*-Index(Tree dEcomposition based kNN~*Index)算法相比,DkNN算法的查询时间减少了56.8%,路网更新时间降低了3个数量级。DkNN算法可以快速响应动态路网中的kNN查询请求,且在处理路网更新时具有较低的更新成本。

基于数字基座的高质量教育大数据体系构建

文中探讨了如何打造数字基座,构建高质量的教育大数据体系.首先,阐述了数字基座的重要性及其在大数据体系中的作用.其次,介绍了构建高质量教育大数据体系的关键要素,包括数据采集、数据处理、数据存储、数据安全等.最后,提出了具体的实施方案,分析了该领域的未来发展方向,以期为相关领域的研究提供参考.

级联信道的案例式教学方法

级联信道是“信息论基础”中的重要概念之一,其性质“数据处理定理”极为重要,但相关概念较抽象,传统教学方法的实际效果有待提高。以易懂的“外国人中文传话”游戏切入,将抽象概念具体化,由此引入级联信道定义及性质,在理论推导数据处理定理的基础上,结合该定理的实际应用让学生理解“信息不增”与数据处理的内在关系。此外在教学中植入文化自信、理论与实践结合等思政元素。

Novel region-based image compression method based on spiking cortical model

To get the high compression ratio as well as the high-quality reconstructed image, an effective image compression scheme named irregular segmentation region coding based on spiking cortical model（ISRCS） is presented. This scheme is region-based and mainly focuses on two issues. Firstly, an appropriate segmentation algorithm is developed to partition an image into some irregular regions and tidy contours, where the crucial regions corresponding to objects are retained and a lot of tiny parts are eliminated. The irregular regions and contours are coded using different methods respectively in the next step. The other issue is the coding method of contours where an efficient and novel chain code is employed. This scheme tries to find a compromise between the quality of reconstructed images and the compression ratio. Some principles and experiments are conducted and the results show its higher performance compared with other compression technologies, in terms of higher quality of reconstructed images, higher compression ratio and less time consuming.

基于拟合误差消除的探地雷达图像鲁棒双曲线识别模型

作为一种无损探测工具,探地雷达已广泛应用于各种场景,但从探地雷达B扫描图像中自动提取信息仍然具有挑战性。本文提出了一种从探地雷达B扫描图像中自动识别和拟合双曲线的鲁棒集成模型。首先,实现了由均值对消、基于梯度的自适应阈值算法和开闭操作组成的图像预处理方法,其中,均值对消抑制杂波和噪声,基于梯度的自适应阈值算法可以将B扫描图像转换为二值图像,然后通过开闭操作去除离散的噪声点;接下来,通过下开口扫描聚类算法识别具有向下开口的点集;之后,利用基于代数距离的双曲线拟合算法对这些点集进行直接拟合;最后,根据这些点集的拟合结果,基于拟合误差的剔除方法去除不具有完全双曲特征的下开口点集,从而实现B扫描图像中所有双曲点集的识别和拟合。由上述方法组成的集成模型能够自动、稳健地从探地雷达B扫描图像中提取信息。在合成数据集和实测数据集上的实验表明了所提出模型方法的有效性。

基于复杂事件处理技术的监控信息“事件化”处理机制设计及应用

随着国内智能电网建设的深入推进,电力系统的数字化、信息化、智能化不断发展,电力能量流、信息控制流和管理业务流等数据呈爆炸性增长。在电网出现大面积故障事件时,集中监控变电站无序且杂乱的监控信号,造成电网监控工作质效低下。集中监控系统告警信号和设备数据之间的离散关系给提高劳动效率和实现监控智能化升级带来诸多困难。基于监控信息“事件化”项目,文章提出了基于复杂事件处理(complex event processing,CEP)技术的监控信息“事件化”处理机制的总体设计思路,完成了数据提炼成信息、信息聚合成事件、事件转化成决策的过程研究。据此搭建的监控信息“事件化”分析平台,日平均“事件化”率达到95.3%左右,在夜间实现了“黑屏”监视,并且可以周期性实现数据价值挖掘和推送,促进监控运行业务向智能化转型升级。

基于RAPIDS的无参DBSCAN算法

具有噪声的基于密度的空间聚类(Density‑based spatial clustering of applications with noise,DBSCAN)能够发现不同密度和大小的类簇,对噪声也有很好的鲁棒性,被广泛地应用到数据挖掘的任务中。DBSCAN通常需要调整参数MinPts和Eps以达到更优的聚类效果,但往往在搜索最优参数的过程中会影响DBSCAN的性能。本文从两个方面优化DBSCAN,一方面,提出一种无参的方法优化DBSCAN全局参数选择。无参方法利用自然最近邻获得数据集的自然特征值,并将自然特征值作为参数MinPts值。然后,根据自然特征值计算自然特征集合,利用自然特征集合中的数据分布特性,分别采取统计最小值、平均值和最大值3种方式得到Eps值。另一方面,采用集成数据科学实时加速平台(Real‑time acceleration platform for integrated data science,RAPIDS)的图形处理器(Graphics processing unit,GPU)计算加快DBSCAN算法的收敛速度。实验结果表明,本文提出的方法在优化DBSCAN参数选择的同时,取得了与密度峰值聚类(Density peaks clustering,DPC)相当的聚类结果。

基于数字孪生的交通运输一体化建设探索

针对解决超大城市复杂交通系统治理难题,及时响应瞬息万变复杂问题决策和跨业务协同治理的迫切需求,通过研判新时期交通运输行业面临的风险与挑战,探索基于数字孪生的交通运输数字底座建设,围绕纵向打穿、横向拉通的方式,高度融合交通全行业数据、交通专业算法、共享通用专业技术等交通运输全要素资源,推动交通规划建设、交通综合治理、设施安全管养、运输安全监管、公交资源调控等核心业务流程再造与创新提升,形成基于数据驱动的交通“规划-设计-建设-运营-数据”模式,实现交通治理模式由传统被动响应、粗放管理向主动管控、精准调控转变。

我国水文资料整编和数据库技术发展综述

水文是水利和国民经济建设与发展重要的基础工作。经过整编的水文资料是国家重要的基础信息资源之一, 它被广泛应用于防汛抗旱、水工程规划设计、水资源管理与开发利用、水环境保护、水科学研究及其他国民经济建设。长期以来,水文资料为我国水利和国民经济建设与发展提供了科学决策依据。随着经济社会发展和人民生活水平不断提高,对控制水旱灾害、水环境监测与保护、水土保持与生态、水资源管理等方面要求越来越高,对水文资料分析处理、存储、应用服务要求也相应提高。本文主要从技术角度,对我国水文资料整编主要技术方法和水文年鉴发展进行了总结与分析;对水文数据库有关技术标准制定、水文数据库建设成就进行回顾;同时结合水文信息共享和应用服务需求,对相关技术发展进行了展望。

工艺制造资源建模及其在协同工艺设计中的应用

根据敏捷制造和机械加工工艺设计特征的要求 ,建立面向计算机辅助工艺计划的工艺制造资源模型。研究了工艺制造资源模型的建模方法 ,进一步论述了协同工艺设计的体系结构、协同工艺设计中工艺制造资源中间件的解决方案、服务器端应用程序的开发和实现方法 ,为实现协同工艺设计提供强有力的技术支持。

AbIx： An Approach to Content-Based Approximate Query Processing in Peer-to-Peer Data Systems

In recent years there has been a significant interest in peer-to-peer （P2P） environments in the community of data management. However, almost all work, so far, is focused on exact query processing in current P2P data systems. The autonomy of peers also is not considered enough. In addition, the system cost is very high because the information publishing method of shared data is based on each document instead of document set. In this paper, abstract indices （AbIx） are presented to implement content-based approximate queries in centralized, distributed and structured P2P data systems. It can be used to search as few peers as possible but get as many returns satisfying users＇ queries as possible on the guarantee of high autonomy of peers. Also, abstract indices have low system cost, can improve the query processing speed, and support very frequent updates and the set information publishing method. In order to verify the effectiveness of abstract indices, a simulator of 10,000 peers, over 3 million documents is made, and several metrics are proposed. The experimental results show that abstract indices work well in various P2P data systems.

基于数据仓库的电力决策支持系统的设计研究

数据仓库 (datawarehouse)和联机分析处理 (onlineanalyticalprocessing ,OLAP)是决策支持系统的有机组成部分。介绍了数据仓库和OLAP技术的有关概念和内容 ,以宝钢的电力系统为研究背景 ,研究运用数据仓库和OLAP建立电力决策支持系统 ,为电力系统经济运行的决策支持提供有效手段。