基于re3data的中英科学数据仓储平台对比研究

以re3data为数据获取源,选取中英两国406个科学数据仓储为研究对象,从分布特征、责任类型、仓储许可、技术标准及质量标准等5个方面、11个指标对两国科学数据仓储的建设情况进行对比分析,试图为我国数据仓储的可持续发展提出建议:广泛联结国内外异质机构,推进多学科领域的交流与合作,有效扩充仓储许可权限与类型,优化技术标准的应用现况,提高元数据使用的灵活性。

History and evaluation of national-scale geochemical data sets for the United States

Six national-scale,or near national-scale,geochemical data sets for soils or stream sediments exist for the United States.The earliest of these,here termed the ＇Shacklette＇ data set,was generated by a U.S. Geological Survey（USGS） project conducted from 1961 to 1975.This project used soil collected from a depth of about 20 cm as the sampling medium at 1323 sites throughout the conterminous U.S.The National Uranium Resource Evaluation Hydrogeochemical and Stream Sediment Reconnaissance（NUREHSSR） Program of the U.S.Department of Energy was conducted from 1975 to 1984 and collected either stream sediments,lake sediments,or soils at more than 378,000 sites in both the conterminous U.S.and Alaska.The sampled area represented about 65%of the nation.The Natural Resources Conservation Service（NRCS）,from 1978 to 1982,collected samples from multiple soil horizons at sites within the major crop-growing regions of the conterminous U.S.This data set contains analyses of more than 3000 samples.The National Geochemical Survey,a USGS project conducted from 1997 to 2009,used a subset of the NURE-HSSR archival samples as its starting point and then collected primarily stream sediments, with occasional soils,in the parts of the U.S.not covered by the NURE-HSSR Program.This data set contains chemical analyses for more than 70,000 samples.The USGS,in collaboration with the Mexican Geological Survey and the Geological Survey of Canada,initiated soil sampling for the North American Soil Geochemical Landscapes Project in 2007.Sampling of three horizons or depths at more than 4800 sites in the U.S.was completed in 2010,and chemical analyses are currently ongoing.The NRCS initiated a project in the 1990s to analyze the various soil horizons from selected pedons throughout the U.S.This data set currently contains data from more than 1400 sites.This paper（1） discusses each data set in terms of its purpose,sample collection protocols,and analytical methods;and（2） evaluates each data set in terms of its appropriateness as a national-scale geochemical database and its usefulness for nationalscale geochemical mapping.

Fuzzy data envelopment analysis approach based on sample decision making units

The conventional data envelopment analysis （DEA） measures the relative efficiencies of a set of decision making units with exact values of inputs and outputs. In real-world prob- lems, however, inputs and outputs typically have some levels of fuzziness. To analyze a decision making unit （DMU） with fuzzy input/output data, previous studies provided the fuzzy DEA model and proposed an associated evaluating approach. Nonetheless, numerous deficiencies must still be improved, including the α- cut approaches, types of fuzzy numbers, and ranking techniques. Moreover, a fuzzy sample DMU still cannot be evaluated for the Fuzzy DEA model. Therefore, this paper proposes a fuzzy DEA model based on sample decision making unit （FSDEA）. Five eval- uation approaches and the related algorithm and ranking methods are provided to test the fuzzy sample DMU of the FSDEA model. A numerical experiment is used to demonstrate and compare the results with those obtained using alternative approaches.

The Design and Implementation of the Data Buffer Unit in an Artificial intelligence Computer ITM-1

This paper describes the function,structure and working status of the data buffer unitDBU,one of the most important functional units on ITM-1.It also discusses DBU’s supportto the multiprocessor system and Prolog language.

Reconfigurable-System-on-Chip Implementation of Data Processing Units for Space Applications

Application-specific data processing units (DPUs) are commonly adopted for operational control and data processing in space missions. To overcome the limitations of traditional radiation-hardened or fully commercial design approaches, a reconfigurable-system-on-chip (RSoC) solution based on state-of-the-art FPGA is introduced. The flexibility and reliability of this approach are outlined, and the requirements for an enhanced RSoC design with in-flight reconfigurability for space applications are presented. This design has been demonstrated as an on-board computer prototype, providing an in-flight reconfigurable DPU design approach using integrated hardwired processors.

Using Genetic Algorithm as Test Data Generator for Stored PL/SQL Program Units

PL/SQL is the most common language for ORACLE database application. It allows the developer to create stored program units (Procedures, Functions, and Packages) to improve software reusability and hide the complexity of the execution of a specific operation behind a name. Also, it acts as an interface between SQL database and DEVELOPER. Therefore, it is important to test these modules that consist of procedures and functions. In this paper, a new genetic algorithm (GA), as search technique, is used in order to find the required test data according to branch criteria to test stored PL/SQL program units. The experimental results show that this was not fully achieved, such that the test target in some branches is not reached and the coverage percentage is 98%. A problem rises when target branch is depending on data retrieved from tables;in this case, GA is not able to generate test cases for this branch.

新型电力系统数据跨域流通泛安全边界防护技术

新型电力系统建设涉及多业务系统、多部门、多方主体间进行海量、异构数据的交互和共享,电力数据的内外部网络环境与安全形势日趋复杂化,数据流通的脆弱性风险加剧。首先,分析新型电力系统下数据流的类型与特性,概括电力数据流通安全防护面临的新形势;其次,基于专用数据处理器(DPU)的高性能流量编排和多功能安全网关能力,构建面向电力数据跨域流通安全增强的泛安全边界,凭借数据面可编程技术沟通网络安全与数据安全双维度安全能力,提出基于DPU的数据跨域流通协同防护技术应用方案;最后,阐释DPU在不同电力通信网络层次的部署方式、价值与关键技术,分析现阶段DPU在电力领域应用存在的挑战。

An Integrated Method of Data Mining and Flow Unit Identification for Typical Low Permeability Reservoir Prediction

With the development of oilfield exploration and mining, the research on continental oil and gas reservoirs has been gradually refined, and the exploration target of offshore reservoir has also entered the hot studystage of small sand bodies, small fault blocks, complex structures, low permeability and various heterogeneous geological bodies. Thus, the marine oil and gas development will inevitably enter thecomplicated reservoir stage;meanwhile the corresponding assessment technologies, engineering measures andexploration method should be designed delicately. Studying on hydraulic flow unit of low permeability reservoir of offshore oilfield has practical significance for connectivity degree and remaining oil distribution. An integrated method which contains the data mining and flow unit identification part was used on the flow unit prediction of low permeability reservoir;the predicted results?were compared with mature commercial system results for verifying its application. This strategy is successfully applied to increase the accuracy by choosing the outstanding prediction result. Excellent computing system could provide more accurate geological information for reservoir characterization.

Clastic compaction unit classification based on clay content and integrated compaction recovery using well and seismic data

Compaction correction is a key part of paleogeomorphic recovery methods. Yet, the influence of lithology on the porosity evolution is not usually taken into account. Present methods merely classify the lithologies as sandstone and mudstone to undertake separate porositydepth compaction modeling. However, using just two lithologies is an oversimplification that cannot represent the compaction history. In such schemes, the precision of the compaction recovery is inadequate. To improve the precision of compaction recovery, a depth compaction model has been proposed that involves both porosity and clay content. A clastic lithological compaction unit classification method, based on clay content, has been designed to identify lithological boundaries and establish sets of compaction units. Also, on the basis of the clastic compaction unit classification, two methods of compaction recovery that integrate well and seismic data are employed to extrapolate well-based compaction information outward along seismic lines and recover the paleo-topography of the clastic strata in the region. The examples presented here show that a better understanding of paleo-geomorphology can be gained by applying the proposed compaction recovery technology.

多源地理产品数据的元数据统一设计与采集管理技术

面向多源地理产品数据管理应用的需求,明确了本文讨论的地理产品数据的范畴,分析了地理产品数据的存储组织及应用特点。基于存储组织需求,统一设计了数据大类小类两级分类目录及类别编码,设计了地理数据产品的元数据采集规范。提出了数据集-数据单元两级元数据的设计理念以便满足不同数据粒度的管理需求,分别设计了数据集元数据和数据单元元数据的详细组成,统一设计了空间地理产品数据与非空间地理产品数据的元数据,明确了数据集目录和数据单元的命名原则。设计并实现了能够自动采集多源地理产品元数据的软件,实现了基于统一元数据设计的数据管理软件。结果表明,这种方法能够满足用户对多源地理产品数据的统一存储组织、多粒度管理、高效便捷检索等需求。

基于门控循环单元网络的钻井井漏智能监测方法

井漏是钻井过程中常见的钻井风险,若对该风险发现、处理不及时,极易导致井塌事故,轻则延长施工周期,重则危害现场人员人身安全。为了提高油气井钻井过程中井漏风险识别的准确性,降低风险识别对人为经验的依赖,结合钻井参数的非线性以及长时依赖特征,提出了一种基于门控循环单元(Gated Recurrent Unit,GRU)网络的井漏风险智能识别方法。该模型以池体积、出口流量和立管压力作为监测参数构建GRU网络,能够提取监测参数的时间序列特征,以实现对井漏风险的准确识别。利用现场实测钻井数据对模型进行了实验测试,结果表明,该方法对井漏风险的识别准确率达到了90.1%,优于长短期记忆网络的识别结果。

基于HSA技术的IEC104协议安全设计方案

以电力行业广泛使用的IEC104协议为研究对象,对该协议的报文结构进行分析并找出其存在的安全隐患和漏洞;提出增加安全信息控制字段,对核心数据进行加密处理,形成安全通信协议APDUSec;在不改变原有传输模式下,采用了RSA加密算法和HMAC认证算法,确保了协议的保密性、完整性和不可否认性;为解决电力通信系统中存在的通信链路故障,借助HSA技术来解决环路检测和分片安全问题.仿真测试结果表明:APDUSec在一定程度上能有效满足信息保密与身份认证的需要,HSA技术在检测环路、传输效率等方面具有一定的优势.本文结果对IEC104协议运行的安全性和可靠性研究具有一定的参考价值.

定点形变数据中暂态短持时异常信号的检测方法研究

分别将线性叠加及零延迟相乘算法用于人工合成数据中的暂态信号检测实验,对比2种算法在暂态信号识别中的效果。结果表明,将同台多道、多台多道数据进行零延时相乘能够更有效地压制数据中的干扰和噪声,使准同步暂态信号得到放大凸显,实现暂态异常信号的初步检测与识别。在此基础上,利用零延时相乘算法处理2002~2022年云南定点形变观测数据,从中识别出11组暂态短持时信号,并进一步分析信号与云南境内M_(S)5.0以上地震的时空关联性。

基于Mogrifier-BiGRU的飞行器轨迹预测

针对当前飞行器轨迹预测准确性低的问题,引入双向传播机制和Mogrifier数据耦合模块,改进传统门控循环单元网络,提出基于Mogrifier-BiGRU的飞行器轨迹预测算法,加强网络对历史数据的学习与记忆,使得输入信息与隐藏层数据的充分耦合,提高预测准确度。仿真结果表明,所提方法对飞行器轨迹预测的准确度可达到96.26%,满足我方作战指挥人员对战场态势趋势准确预测的实际需求。

贫数据中基于模型自训练的空气处理设备故障诊断

针对空气处理设备(AHU)故障贫数据,基于深度置信网络(DBN)模型对4种特征选择算法进行对比研究,结果表明最大相关最小冗余算法的特征子集在诊断准确率及子集元素稳定性上表现最优。提出将DBN嵌入自训练框架的故障诊断模型,发现DBN自训练的诊断准确率较单纯DBN最高可提升19.5%。提出均匀抽样及按比例抽样2种自训练伪标签抽样策略,二者的诊断准确率均随抽样数减小而增大,在不同抽样数中的最大差异为3.42%;在所有贫数据样本中,均匀抽样策略始终优于按比例抽样,诊断准确率最大相差1.39%,表明在故障标签匮乏时,采用均匀抽样策略及较小的抽样数有利于提升DBN自训练的诊断性能。

基于多模态数据融合的改进中尺度涡检测模型

提出一种基于多模态数据融合的改进中尺度涡检测模型。该模型以海平面高度数据为基础,首次将融合表层海温数据扩展为融合多深度层海温数据;将海温数据的深度层作为通道,嵌入通道注意力机制,使得模型能够关注于海水温度数据中最具有区分度的深度层;模型在编码及解码过程中采用残差学习单元,在加深网络深度的同时,更好地拟合激活函数,缓解训练问题,以提高模型的检测准确率。以中国南海部分海域为例开展实验验证,结果表明该中尺度涡检测模型准确率达到93.62%,模型具备有效性和可靠性。

基于数字孪生的工业机器人建模及监测方法

针对工业机器人数据不透明、监测存在死角等问题,通过对实体工业机器人分析和研究,构建数字孪生机器人监测系统。首先从几何、物理、逻辑3个维度完成虚拟机器人的建模;其次基于开放平台通信联合架构(open platform communications united architecture,OPC UA),实现机器人的数据采集和通信,设计用户显示界面,达到数据实时可视化的效果;最后,通过机器人仿真实验得出机器人末端执行器X、Y、Z坐标的相对位置误差分别为0.48%、0.32%、0.27%,通过数字孪生机器人监测同步实验验证机器人关节角度误差最大值为0.31°。实验结果表明:该方法能够实现数字孪生工业机器人的运动数据监测,减少工业机器人在生产过程中发生意外和故障的风险,为智能工业机器人的发展提供思路和方向。

个人通信数据的敏感性识别与隐私计量研究

[目的/意义]相关法律法规和通信数据行业标准中,将个人通信数据划分为四个等级,但缺失定量研究支撑,本文定量测度通信隐私值,解决该问题。[研究设计/方法][研究设计/方法]首先归纳通信隐私文本类型并建立通信隐私文本库,其次构建通信敏感词表,进行通信数据的敏感性识别,最后通过设计隐私计量模型,对通信隐私进行计量。[结论/发现][结论/发现]隐私性从高到低依次为:通信内容数据、统计分析数据、个人相关数据、通信衍生数据、通信地址数据。[创新/价值][创新/价值]基于通信隐私文本,识别通信敏感数据,计量通信隐私值,对基于主观的隐私主体敏感性认知测度方法进行补充,为个人通信数据分级保护提供定量依据。

基于机器学习的随机信号缺失数据功率谱估计

为了解决随机信号在传递接收过程中可能出现的数据不规则、不完整的问题,提出了一种极值梯度提升树-支持向量回归(XGBoost-SVR)与门控循环单元神经网络结合的预测方法,用于稀疏随机信号的缺失数据填补。先使用极值梯度提升树和支持向量回归结合对原始数据集填补,再使用门控循环单元模型进行训练并预测出缺失的数据,最后通过傅里叶变换和小波变换,实现功率谱估计。数值分析结果表明:在含有噪声干扰的情况下,即使数据缺失高达70%,该预测方法仍然可以很好地还原目标功率谱。该方法处理的缺失数据可以更好地还原随机信号的特征,为信号预测和灾害预防提供有力支持。

基于改进机器学习的无人机中继通信数据调度控制研究

为解决无人机通信网络中数据调度行为中断概率过大的问题,实现对通信资源的合理分配,提出基于改进机器学习的无人机中继通信数据调度控制方法;设计基本网络架构,联合BMRC协议,设置URLLC数据链路单元,联合相关通信数据样本,求解通信中断概率的具体数值,实现对无人机中继通信网络资源的联合优化处理;分别计算时隙分配参量与带宽分配参量,并以此为基础,确定无人机中继位置,实现对中继通信资源的调度;按照机器学习算法标准,定义PCA改进特征,从而完善改进机器学习算法,再联合最优控制器闭环,实现对通信数据调度行为的控制;实验结果表明,改进机器学习算法作用下,随着中继数据累积量的增大,无人机通信网络中数据调度行为中断概率的最大值只能达到7.3%,有效降低了中断概率,符合合理分配通信资源的实际应用需求。